Designing an optimum protected areas system for Sri Lanka's natural forests. Volume 1

ENVIRONMENTAL MANAGEMENT IN FORESTRY DEVELOPMENT PROJECT

DESIGNING AN OPTIMUM PROTECTED AREAS
SYSTEM FOR SRI LANKA’S NATURAL FORESTS

Volume 1

PROTECTED
AREAS UNIT

Reference Copy

A Project of the Environmental Management Division, Forest Department
Ministry of Lands, Agriculture and Forestry

Prepared by

IUCN-The World Conservation Union

and the

World Conservation Monitoring Centre

for the

Food and Agriculture Organization (FAO) of the United Nations

March 1997

The Environmental Management Component of the Environmental
Management in Forestry Development Project has been implemented by the
Forest Department with technical assistance from IUCN-The World
Conservation Union under Contract No. DP/SRL/89/012-001/FODO to the
Food and Agriculture Organisation of the United Nations. It has been funded
by the United Nations Development Programme in accordance with the
Project Document: Environmental Management in Forestry Developments
(December 1989).

This report has been prepared by Dr M. J. B. Green, World Conservation
Monitoring Centre, Cambridge and Dr E. R. N. Gunawardena, Department
of Agricultural Engineering, University of Peradeniya with input from other
members of the National Conservation Review Team.

NATIONAL CONSERVATION REVIEW TEAMS
Environmental Management Division, Forest Department

S.D. Abayawardana, National Counterpart: Database Management and Conservation Review
Anusha Edirisinghe, Database Assistant

IUCN-The World Conservation Union

Wet zone survey team: Dr A.H. Magdon Jayasuriya, National Consultant, Flora
(Wet zone districts B.W. Martin Wijesinghe, Field Assistant, Flora
and Hambantota District) Upali Weerasekera, Field Labourer, Flora

A. Christie M. Fernando, Herbarium Assistant

G.P.B. Karunaratne, National Consultant, Fauna
Samanth Suranjan Fernando, Field Assistant, Fauna
Laksiri Karunaratne, Field Assistant, Fauna
Roshan Perera, Field Assistant, Fauna

G.T. Mahesh Priyadashana, Field Assistant, Fauna
Jagath Premathilake, Field Assistant, Fauna

Dry zone survey team 1: Dr Tissa Herath, National Consultant, Flora
(Anuradhapura, Matale districts) Udhayani R. Weerasinghe, Graduate Assistant, Flora
W.M. Ratnayake, Field Labourer, Flora
Saman Weediyabandara, Herbarium Assistant, Flora

Upali B. Ekanayake, National Consultant, Fauna
G.P.B. Karunaratne, National Consultant, Fauna
Dr Sriyani Miththapala, National Consultant, Fauna
Dr U.K.G.K. Padmalal, National Consultant, Fauna
Samanth Suranjan Fernando, Field Assistant, Fauna
Laksiri Karunaratne, Field Assistant, Fauna

Wajira Kempitiya, Field Assistant, Fauna

G.T. Mahesh Priyadashana, Field Assistant, Fauna

Dry zone survey team 2: Don Bhathiya Sumithraarachchi, National Consultant, Flora

(Kurunegala, Monaragala, Udhayani R. Weerasinghe, Graduate Assistant, Flora
Polonnaruwa, Puttalam W.M. Ratnayake, Field Labourer, Flora
districts) Saman Weediyabandara, Herbarium Assistant, Flora

Upali B. Ekanayake, National Consultant, Fauna
G.P.B. Karunaratne, National Consultant, Fauna
Samanth Suranjan Fernando, Field Assistant, Fauna
G.T. Mahesh Priyadashana, Field Assistant, Fauna

Dr E.R. Nimal Gunawardena, National Consultant, Forest Hydrology

Dr Michael J.B. Green, International Consultant, Conservation Review
David A. Hughell, International Consultant, Database Analyst

ACKNOWLEDGEMENTS
SL aT, Ny ET ER 1c Sek a

This National Conservation Review has proved to be a very successful initiative, due to the
tremendous enthusiasm and commitment of its team members (listed on the previous page),
and the invaluable support received from a wide range of organisations and individuals.
Although too numerous to acknowledge individually, it is entirely appropriate to single out
the many staff from the Forest Department and Department of Wildlife Conservation, as well
as the numerous villagers, who assisted the teams in the field. Their local knowledge was
vital to the success of the project in so many different ways, not least the safety of team
members.

The project has benefitted throughout its course from the personal involvement of Mr H.M.
Bandaratillake, who originally set up the Environmental Management Division prior to being
appointed Conservator of Forests. His current successor, Mr Sunil Liyanage, has continued
to ably support the project. Technical assistance was provided by several branches within the
Forest Department, in particular the Forest Inventory and Management Branch under Mr
W.R.M.S. Wickramasinghe who made available its National Forest Geographic Information
System. Special thanks are due to Mr C.A. Legg, Miss N. Palihawadana and Mr M.
Warnapriya for their GIS expertise.

Support and technical expertise from a number of other individuals have been key to the
successful execution of this project. They include the late Dr S. Balasubramanian, Professor
I.A.U.N. Gunatilleke, University of Peradeniya, Mr T. Hewage, Director, Forestry Planning
Unit, Mr M. Jansen, World Bank, Dr S. Kotagama, Open University and Dr N. Pallewatta,
University of Colombo.

The NCR teams acknowledge the excellent administrative and logistic support provided by
IUCN-Sri Lanka, in particular Mr Kapila Fernando, Projects. Director. Mr Leslie Wijesinghe,
Country Representative, and his predecessor, Mr M.S. Ranatunga, have maintained a keen
interest in the project. Mr Vitus Fernando, formerly of IUCN-The World Conservation
Union, also played a major role in securing and initiating the project.

Several individuals at the World Conservation Monitoring Centre have contributed their GIS
expertise to this project, notably Mr Simon Blyth and Dr Alejandro Sandoval. Mrs Victoria
Freeman provided secretarial assistance.

Finally, we wish to pay a special tribute to Karu, Mr G.P.B. Karunaratne, our colleague and
close friend who died from cancer shortly after completing five years of fieldwork. He will
be remembered, especially by the many young naturalists whom he trained in the field during
the course of the NCR.

National Conservation Review teams

EXECUTIVE SUMMARY

Sri Lanka is a small but biologically diverse country that is recognized as a biodiversity
hotspot of global importance for plants. Many plants and animals are endemic to the island,
26% in the case of flowering plants and from 45% to 76% for certain taxonomic groups of
animals. Much of this diversity is found in the south-west wet zone which occupies one-third
of the country. Closed canopy natural forest covers 24% of the country but it is least
extensive in the wet zone where human population pressures are highest.

The over-riding objective of this National Conservation Review (NCR) of remaining natural
forest in Sri Lanka is to define a national system of conservation forests in which watersheds
important for soil conservation and hydrology are protected, forest biodiversity is fully
represented and cultural, economic and social needs are met.

The NCR focused on assessing the importance of forests for soil, water and biodiversity
conservation. All natural forests of 200 ha or more were included in the NCR, except those
in the north and east of the island which were politically inaccessible. The biodiversity
_ assessment was restricted to woody plants, vertebrates, molluscs and butterflies. Despite such
limitations, the NCR is among the most detailed, comprehensive and innovative
evaluations of its kind carried out in any tropical country. Between April 1991 and
September 1996, a total of 1,725 plots (100 m x 5 m) were inventoried along 310 gradient-
directed transects in 204 forests. Analyses are based on approximately 69,400 records of
1,153 woody plant species and 24,000 records of 410 species of selected animal groups. A
total of 281 forests were evaluated with respect to their importance for soil and water
conservation.

Sri Lanka has an extensive system of protected areas covering over 14% of total land area.
However, this system is least extensive in the wet zone, where watershed protection is of
paramount importance and biodiversity is highest. The results from the NCR show that many
of the most important forests for soil and water conservation are not protected. Furthermore,
certain floristic regions and forest types are poorly represented within the existing protected
areas system. It has also been shown by this study that up to 15% of species diversity may
be absent from the present system.

It is reassuring to find that 46% of the highest category of wilderness lies within protected
areas, indicating their integrity and the relative absence of infrastructural developments, such
as settlements and roads. A further 20% of high quality wilderness is found in forest and
proposed reserves.

Of the 281 forests assessed for watershed protection, 85 were identified as being extremely
important for soil protection and flood control, or interception of fog in the case of those
located above 1,500 m. In general, wet zone forests are a top priority for soil and water
conservation, particularly the largest units of contiguous forest (Central Highlands, KDN,
Knuckles and Sinharaja) which protect the headwaters of the country’s major rivers.

ili

Of the 204 forests assessed for biodiversity conservation, minimum sets of 108 and 49 were
identified for representation of woody plant and endemic woody plant species, respectively.
Woody plant and animal diversity is represented within a total of 133 forests, but it should
be noted that some woody plant inventories were inadequate and that all animal inventories
were incomplete. Some 80% or more of woody plant and animal species are represented
within eight units of contiguous forest, namely: Bambarabotuwa, Central Highlands,
Gilimale-Eratne, KDN, Knuckles/Wasgomuwa, Pedro, Ruhuna/Yala and Sinharaja.

There is considerable commonality between forests important for soil and water conservation
and those rich in species. An integrated analysis shows that a minimum set of 104 of 224
units of contiguous forest are necessary to meet watershed protection and biodiversity
conservation priorities. Such an optimum system of conservation forests covers 516,795 ha,
or 7.8% of total land area. With the exception of a few small fragments, all forests within
the wet zone are included in this optimum system, together with the extensive forests of
Ruhuna/Yala in the south-east and several small units to the north. If one of the criteria is
changed from representation of all species to endemic species only, the minimum set of
contiguous forests falls to 70 but the system extends over almost as large an area (490,193
ha, or 7.4% of total land area).

Given that there is very little redundancy in the wet zone, forests being important for either
biodiversity conservation or for protection of watersheds, the current ban on logging should
be maintained for the foreseeable future. As it is unlikely that such measures will be adequate
to safeguard the entire spectrum of forest biodiversity, it will be necessary to conserve
biodiversity though other measures, including private stewardship of natural forests. In the
meantime, much can be achieved by upgrading the conservation status of existing forest and
proposed reserves in the wet zone.

The Forest Department, in collaboration with other sectors, is encouraged to consider
pragmatic ways of addressing the conservation priorities emanating from this study, taking
into proper account their cultural, economic and social implications. Importantly, its
Environmental Management Division now has the necessary skills and tools to optimise this
system of conservation forests further in response to socio-economic and other constraints
that might arise during the planning process. The Environmental Information Management
System, held by the Division, provides a powerful tool for generating optimum systems of
conservation forest according to predefined criteria and quantifying their potential benefits
and costs.

In order to further optimise the system of conservation forests, it will be necessary to carry
out additional surveys of forests overlooked by the NCR, as well as those inadequately
inventoried for species. Moreover, any plans to release forest lands for other forms of use
should be preceded by more detailed biodiversity surveys in order to fully evaluate their
potential impact. This should be considered mandatory for any forest either not surveyed or
inadequately surveyed by the NCR, particularly if it lies in the wet zone.

Despite the wealth of data generated by the NCR, they are preliminary and provide a basis
for systems planning. Much more detailed and wide-ranging surveys will be required to plan
and monitor the management of individual conservation forests once they are established.
Given the continual need to survey and monitor biodiversity, it should be noted that there are
more rapid, less costly alternatives of inventorying plant taxa at the level of genera without
significantly jeopardising representation of species within minimum forest systems.

iV

CONTENTS

Volume 1

INDRODUCTIONM citRTae oe e e a e R e pac eae 1
1.1 BACKGROUND TO THE NATIONAL CONSERVATION REVIEW ..... 1
1.2 VALUE OF FORESTS FOR SOIL AND WATER CONSERVATION ..... 2
1.2.1 Tropical forests and soil conservation..................... 3
1.2.2 Hydrological importance of tropical forests ................. 4

1.3 VALUE OF FORESTS FOR BIODIVERSITY CONSERVATION ....... 6
1-3 ll- Whatsisibiodiversity?..o = 6 0% ie cop ec) ee 6
R322) Wihyaconsenvewbiodiversity;?,). 45-1 ee eee ee 8
1.3.3 Why are forests important for biodiversity? ................. 11

14 SEORESTMEONSERVATION, 52252 22500 aca ee een eee oe 11
Hea Me Protécteduareasiens ofa Gb ele el & a I 11
1.4.2 Criteria for selecting protected areas to conserve biodiversity ...... 12
SRIBMANKACSIEORESIS ee 0hes eee codeine fans ee eee od 16
2.1 GEOGRAPHICAL SETTING .¢ «ceil dt dos 5 5 ae: 1 16
2 el Vintluenceyof climate) 2.02.4 .6.4 & oo eon: Sloe 16
2.1.2) Rivernibasinysystemys. 44 tees ees aura oR ae: 19
Desi Waterresources; @ Eas ee A PL Oe Ae Pee ee! 19

2:2 BIODIVERSITY 2.5% » 62 YER Se Eee ee. Se 19
De sles ROrest COversand (Giversityea eat 6 ee ee eee) er 21
DMDEDCSpECieSidiversity: ) 2 hia .+2e aos. >. eG AE pees. Se. oe 22
2°2).3' (Genetic: diversity, aver ae orl ct eee. 2 Fae 22,
22). 4» ossiot biodiversity is (31) 722 2 ee Re a ee 23

23, PROTECTION OF EORESTS 22a n eer ee ae een eran 25
23M, . Barly JMiStOny ie jes ce Bede kee wi eke oe RU ee ee ee 25
2.3.2 Evolving conservation policies and legislation. ............... 25
2:33: Nationall:context 0.405. ae ee wo be Oo ee Se 31
2)3)45 Internationalicontext) 4 | -eariey aoe eis eee cnet eee 32
2).3-5; _Protectedtareas*systemine eM Wey A SOMME TV. & 32
METHODS - SOIL AND WATER CONSERVATION ASSESSMENT ......... 40
3.1 VINTRODUCTION: «2.5 one eats & os. er eee? pater: Sb 2 40
322 -SOIL- EROSION... ..4 . Riese th obras ine eversentiels cease AAR = 40
3.2.1 Assessment of the importance of forests for soil conservation ...... 40
3.2.2 Ranking forests for soil erosion ........................ 43

3.3 HEADWATERS PROTEGHION Sa> 425 555-- 545 cnet) Oe ee ae 43
3 4gRROODIHAZARD: h.a. Ge eee ae eae es oe MOR FOe: 4 44
3.4.1 Estimating flood hazard from catchment characteristics .......... 44

3.5 FOG INTERCEPTION AT HIGHER ALTITUDES ................ 45
3)-5al) *Fieldtexperimentstin’ Sr Wankae ee Fe a ee sa cones 46

BOVE VALUATION tne fhe fon he GR or eh s5 toce Gy enero rangers 47
Si6ale Preliminanyerankin Sen eset eee re ee eee ee gece 47
36-2) winalrankin geese: Macrame: kane gle Wea Se les Lo: <r Re 47
3.6.3 Selection of forests for soil and water conservation ............ 47

3:7 CONSTRAINTS ars Seis Arey, CEPTS eee SOE, CR SEE Ee 48
3 folk WSOUVCrOSION 2 «dec. Sees Pea a. ene. tee eee ee 48

3 ied) Headwaters protectonyy sicecmete is Paice eee) cir outset FP osprey a 48
31/53) eloodthazard =.) sects cu kateb Senn Menards ti. atta REN eee 49

378i WORKEDFEXAMPEE R22 Ain hieie Sm tye eek ney SO ee. ee 49
3/8: SSoilkerosion™ Sites ee oe ee els Sees ed ee 49
3¥8-2) sHeadwaterssproteciOniemee ie eee ore ny eset ae) SPS en oe 54
3283) wb ood snazat dy. chen, ete ge Sueur inn 7s eee rc det. LAR A 55
32874 MROPMNIETCEPOM ys vn. Gat itews ctf rae sie, ee ome ate IONS 2. eae 56
METHODS - BIODIVERSITY ASSESSMENT .....................0.. 60
ANI INGRO DW CRIO NW seer eee ete feat er STEER Tel Genes ea 60
Al MESUGVEVECeSIOMs cof teieiry fh ealcsetiss Sickest te Me Peek a A Mae NS era 60
AMID mGradsectysamplin Oise ress eae teen) ausccbe Me tal i eet NED coches 61
AnlesaConsenvationvevaluationmer ars cae ae eee enn nent cnn ane 62
4.2 CRITERIA USED TO IDENTIFY FORESTS .................... 62
4.3 INVENTORYING SPECIES DIVERSITY ...................... 63
Aes Ay GTAGSCCtS pak gle we abe cokes eM etee RATS SAF eD ate TONE Be ae eas ae 63
Al3 (2 eSamplinguwithiny Ota aweeusuact oie.) Mana nen een: Ah OY 66
Arse Ses Samipleysize: gm rien eres ieee ee ca see eee ea ob Jeane, Oe hee 2 69
Aes dye Observations betweensplotsmesm =e a) seeeene nie -een te ean one 70

AL Sno) LMAO OF IENOMy GE a5 vc o ot ob ob 008 oo dle Gidlelo A bie’ 71

Ana GAP SAINTE YASS meee eta aye we oy Sere ca oa tary MEER MR RTO Dig ta yes 71
AVA UR OTEStsty PES!) aanete ome: aie eke ae Mer Ot Stee RE. LR ee 72
APACS Wilderness) aaeteepcs ce coeur ces Ca elk MERE eae EI. Ee ae 72
4.4.3 Floristic regions and edaphic zones ...................... 73

4.5 ENVIRONMENT INFORMATION MANAGEMENT SYSTEM ........ da
Ano ONS TERAMIN Stats eget ed ara th SMR RO erg hee ea are One T cn ci jhe sa. hl re 78
Aone Samplingstloralidiversitye sata eee aun ne icine nei sean 78
AxGe2eeSamplinostaunalediversityay-etee ee eae iene eae Se eee 78
4.6.3 Taxonomic distinctness and genetic diversity ................ 79
RESULTS - SOIL AND WATER CONSERVATION ASSESSMENT .......... 80
Ss lGINTRODUCTION capa cee ee yeaah tauae eae seems te Zeke tea 80
5: 2ySOM, EROSION ae ee ee AERA ee ee 80
553) HEADWATERS PROMPECTION HAH sent ee en ee ee ne 82

vi

4 SEL OODIHAZARD Ie, of COS eee Mees UC AE, LP, oa) er 83

SSE OGHNRERGEPMION 22.00 8 4..545 55 22g 6 ko eo oe eee 83
SIG CONSERVATION: PRIORITIES a ae eee SR ee 85
SHoMenIndividuallorestsi 49 sews Ae. Eee) eens Sere ke ener: 85
5-6-2 Contiguousorests ) cha: 26, © SAO eSeC EN: ieee eae aie 90

5.7 CONCLUSIONS AND RECOMMENDATIONS .................. 92
RESULTS - BIODIVERSITY ASSESSMENT .....................005. 93
CACINTRODWCRONim, roe siees wre goleeri seven cnedertales). 65 oe 93
Gul Rorestsi-s een ee 2. WE a, SY AE, eR fh UA ey 93
Gule2eiGradsectsvand!plotsimens!.i rete Cee a werent ee) ier tenner 93
Gules MEloratandsfaunatly ee: reales, SD Os cree 93
62eSPECIES DIVERSITWiMwinSs SUS) 2c) STS. SEE (oS ee 96
GPL oralwwCnnNieisey ooo god ocosbasacocgoeeeeenecuogeac 96
G2 (COnirnOws WETS oo og po kabbhsooradcssoctcstodooccs 96
6.2.3 Optimum networks for species diversity ................... 97
6.2.4 Species represented in existing protected forests .............. 98
63KGAPR: ANALYSIS aN. 2. 0. SE Se oe SPe. aos 103
Goll VCMT YES co aaepoocs ceases oubuucononoos minds ogac 103
626% 2imWildemessnely, Genet. 2 Re Ree eee Ce, OF 104
6.3.3 Floristic regions and soil-edaphic units .................-.. 110

6.4 CONCLUSIONS AND RECOMMENDATIONS ................. 112
WATERSHED PROTECTION AND BIODIVERSITY CONSERVATION ...... 114
Al SINDRODUCTION 24 Sasenee See ee. AOR 79 Te: PSII «kt 114
7.1.1 Datasets used to compare watershed and biodiversity values ...... 114

7.2 AN INTEGRATED APPROACH TO CONSERVATION ............ 115

7.2.2 Priorities for watershed protection and species diversity conservation 115

REFERENCES ase ani fens Sean. ey eke. 7 Pe 8o. e est eer ce ie 130

Vil

Figures

Figure 2.1 Rainfall isohyets and climatic zones of Sri Lanka superimposed on the
distribution of closed canopy forest in 1992, based on the 1:50,000-scale forest map

Of Sriliankal(esovandwewellasl995) 2 2 ee 4 aiers eee Seok. a eemeee yc 17
Figure 2.2 Discharge from Sri Lanka’s main rivers (Source: National Atlas of Sri

TE ATIK a) eer Ora eRe gee re RM SEM arth Ser nero ose ccaldn Pe dcr vem cle cee 18
Figure 2.3 Surface water potential of districts in Sri Lanka ................ 20
Figure 2.4 Relationship between increasing human population and declining forest cover

(Source: sBPWA 1995) eis ar acu pees eo otiucdd Mensa tra eIsasie dene. 2! CARAFE Gece 24
Figure 2.5 Growth of protected areas system in forestry and wildlife subsectors ... 34

Figure 2.6 Map of designated areas administered by the Forest Department and
Department of Wildlife Conservation

Bs AE Cee OV a2" J” SSR Ee ea a ee CE aT eT Oo od ee SORTER EMEPE GES, Jot 35
Figure 2.7 Distribution of size of protected areas administered by Forest Department and
Department of Wildlife Conservation .................-.-.5.2-0-. 38
Figure 3.1 Increase in net rainfall from fog interception at Horton Plains between
INovembersl993sandi@ctober 1995 ee nares eee a hs = eon ee CRN ee 46
Figure 3.2 Mean annual rainfall isohyets for Dellawa.................... 50
Figure 3.3 Overlaying a 10x10 mm grid onto a contour map to estimate mean slope in
IDIOT EN CI e eo uget coat nl bea oh a) Ach Phot t La. oa. a ere e ee emReR a gs Re Le Mem PR 52
Figure 4.1 Schematic diagram showing alignment of transects in relation to (a)
altitudinal gradient, (b) access routes, (c) riverine and (d) coastal vegetation. [Not to
Scaling sane eee ee OR Renee too: ae en et PAE Ee Pe Seer 64
Figure 4.2 Schematic diagram of plots aligned along transects at regular intervals in (a)
wet zone forests and (b) dry zone forests. [Not to scale] ................ 65
Figure 4.3 Accumulative number of woody plant species recorded in consecutive plots
in Sinharaja. Sampling is discontinued once the number of new species inventoried
in at least two consecutive plots falls below the 5% threshold.............. 70
Figure 4.4 Floristic regions of Sri Lanka (Source: Ashton and Gunatilleke, 1987) .. 75
Figure 4.5 Soil-edaphic units of Sri Lanka (Source: Survey Department) ........ 76

Figure 4.6 Relationship between endemic plant and animal species diversity in natural
forests. Each data point represents a forest adequately surveyed during the NCR. . 79
Figure 5.1 Distribution of units of contiguous forest identified as highest importance for

watershed protection (i.e. soil and water conservation) ................. 91
Figure 6.1 Distribution of plots (100 m x 5 m) sampled during the NCR. ....... 94
Figure 6.2 Minimum network of contiguous forests in which all 1,153 species of woody

plantsyare represented en mweee wae one ty er) eh cy aks Acs lee eae ee 99
Figure 6.3 Minimum network of contiguous forests in which all 410 species of animals

ATE sTEPLESCHtcd ea meee we wade area erred cue Sern coe esncaeculeews, mea Oe 100
Figure 6.4 Minimum network of contiguous forests in which all 455 endemic species of

woody, plantstaresrepresented sua-pem-ecte. amin er A sess se we ee 101

Figure 6.5 Minimum network of contiguous forests in which all 138 endemic species of

fallimial Seale snepresem ted suse een tania ee teen ews 102
Figure 6.6 Designated areas superimposed on the 1:50,000-scale forest map of Sri Lanka
(lgeco¢and Jewell, 1995) 0. oo. ee ee. an A Dearie tt 105
Figure 6.7 Designated areas superimposed on a wilderness map of Sri Lanka... . . 106
Figure 6.8 Designated areas superimposed on floristic regions. The dry and arid
lowlands region is further classified into edaphic zones. ............... 111
Figure 7.1 Relationship between total soil erosion and woody plant diversity for 118
IMitSKOh CONT SUOUSMTOFESt =. eh eee eee ae ees Se 116
Figure 7.2 Relationship between flood hazard and woody plant diversity for 118 units
OMCONtZUOUSITOTES Hae LSI ara ee ee ee ae 116
Figure 7.3 Relationships between total soil erosion, flood hazard and woody plant
diversity for 118 units of contiguous forest ....................0.. 117

Figure 7.4 Minimum network of contiguous forests of highest importance for watershed
protection and representation of all 1,153 woody plant species and 410 animal species
recordedhinsthesNCRe . anaes 46 above. oat hoe ie ea ee 120

Figure 7.5 Minimum network of contiguous forests of top priority for watershed
protection and representation of all 455 endemic woody plant species and 138
endemic animal species recorded inthe NCR. ..................... 121

Figure 7.6 Distribution of elements of biodiversity and socio-economic land use
requirements within a forest, as a prerequisite to planning an integrated approach to

management (Source: Howard, 1995) ........................... 127
Figure 7.7 Zonation of a forest to meet biodiversity conservation, community and timber
production requirements (Source: Howard, 1995) ................... 128

Figure

Annex 1
Annex 2
Annex 3
Annex 4
Annex 5
Annex 6
Annex 7
Annex 8

Annex 1
Annex 2
’ Annex 3
Annex 4
Annex 5
Annex 6
Annex 7
Annex 8
Annex 9
Annex 10
Annex 11
Annex 12
Annex 13

Annex 14

Volume 1 - Annexes

Designated Areas of Sri Lanka .............-.---+-+---- 137
istioteDesignated@Areasma 4 sus tiem nema nenees teu) Uc oicmet- weno Suen 141
Importance of Natural Forests for Controlling Soil Erosion ...... 149
Importance of Natural Forests for Protection of Headwaters ..... 153
Importance of Natural Forests for Flood Control ............ 157
List of Forests Inventoried for Species ..........----+---- 161
Summary of Woody Plant Diversity Within Individual Forests .... 166
Summary of Faunal Diversity Within Individual Forests ........ 170
Soil/Water Conservation and Biodiversity Assessments ......... 195

Volume 2 - Annexes

Distribution of Woody Plant Species in Forests ............. 202
Distribution of Animal Species in Forests ................. 318
_Minimum Forest Network for Woody Plants ............... 360
Minimum Forest Network for Animals .................. 364
Minimum Forest Network for Endemic Plants .............. 368
Minimum Forest Network for Endemic Animals ............ 372
Minimum Network of Contiguous Forests for Woody Plants ..... 376
Minimum Network of Contiguous Forests ror Animals ......... 379
Minimum Network of Contiguous Forests for Endemic Plants .... 382
Minimum Network of Contiguous Forests for Endemic Animals ... 385
Forest Network for Woody Plants, Based on Existing Protected Areas 388
Forest Network for Animals, Based on Existing Protected Areas ... 391
Forest Network for Endemic Woody Plants, Based on Existing Protected
JENTEENG 3. oy “towchec acdc gehen Spe Oy Gc Ri OAR oh ce a) 394
Forest Network for Endemic Animals, Based on Existing Protected Areas
Bp ba ea SEU aE Sell, ae 1 ne oo 397

Chapter 1
INTRODUCTION

1.1 BACKGROUND TO THE NATIONAL CONSERVATION REVIEW

A major criticism of the first Forestry Master Plan for Sri Lanka (1986) was its failure to
address the environmental aspects of forestry, particularly with respect to conserving the
country’s rapidly dwindling natural forests in the wet zone (FPU, 1995). As a result of this
criticism and following the preparation of the Forestry Sector Development Project (FSDP)
in 1986, IUCN-The World Conservation Union was invited by the Government of Sri Lanka
in 1988 to assess the environmental implications of the FSDP and, subsequently, in April
1989 to formulate an Environmental Management Component to strengthen environmental
safeguards within the FSDP. This formulation led to the present Environmental Management
in Forestry Development Project (EMFDP), which has run from April 1991 to September
1996! (UNDP/FAO/GOSL, 1989).

A principle recommendation arising from the IUCN (1988) assessment was to introduce a
moratorium on all logging within the wet zone, pending a conservation evaluation of the
country’s remaining rain forests. This ban was introduced in 1990 and awaits the outcome
of the conservation evaluation, which has since been carried out as part of the EMFDP and
is the subject of this report.

Commonly referred to as the National Conservation Review (NCR), this component of the
EMEDP is concerned with evaluating all remaining natural forests (including mangrove) with
respect to their importance for biodiversity, in terms of ecosystem and species diversity, and
their value for soil and water conservation. Its over-riding objective is:

to define a national system of conservation forests in which watersheds important
for soil conservation and hydrology are protected, forest biodiversity is fully
represented and cultural, economic and social needs are met.

This objective nests within the wider framework of strengthening the institutional capabilities
of the Environmental Management Division, set up within the Forest Department in 1990 to
address forest conservation and management issues (UNDP/FAO/GOSL, 1989). The project
has been implemented by the Forest Department, with technical assistance from IUCN-The
World Conservation Union under contract to the Food and Agriculture Organization of the
United Nations, and with funds from the United Nations Development Programme. In order
to meet its objective, the project includes natural forests administered by the Forest
Department and other government agencies, such as the Department of Wildlife
Conservation.

The NCR follows on from an Accelerated Conservation Review (ACR) of 30 lowland rain
forests, managed as 13 units and covering some 480 km* (TEAMS, 1991). Scientific

' This includes a six-month extension to the original schedule.

1

information on their conservation importance was urgently needed ahead of the NCR because
these forests had been earmarked for logging.

During the course of the NCR, a new Forestry Sector Master Plan (FPU, 1995) has been
formulated for the period 1995-2020 which is based on a new National Forestry Policy,
1995. Together, they mark the turning point from focusing on exploitation of natural forests
to an over-riding priority for conservation of biodiversity and protection of watersheds. Also
significant is the policy shift towards people’s participation in the protection and management
of natural forests through appropriate partnership and tenurial arrangements. The NCR has
been fully incorporated within the new Forestry Sector Master Plan.

Another relevant initiative is the preparation of a Biodiversity Conservation Action Plan for
Sri Lanka, which commenced in 1996 following a planning phase in 1995. The biodiversity
component of the Forestry Sector Master Plan, hence the NCR, will fall within the
framework of this Action Plan.

The NCR has run for the entire duration of the EMFDP. Field work commenced in earnest
in September 1991 and continued until March 1996. During this time remaining natural
forests were surveyed, with the exception of those inaccessible in the north and east due to
ongoing activities of the LTTE, the Tamil separatist movement. Thereafter, time was spent
identifying herbarium and museum specimens, validating field data entered into the
Environmental Information Management System (EIMS), analysing and reviewing the results
in consultation with other government agencies, scientific institutions and non-government
organisations at workshops, and producing this report.

The purpose of this report is to provide a comprehensive account of the results of the NCR,
particularly tn so far as they can be used to design an optimum system of forests for soil,
water and biodiversity conservation purposes.

The report comprises seven chapters. Chapter 1 and 2, respectively, focus on the importance
of forests for watershed protection (i.e. soil and water conservation) and biodiversity
conservation in general, and with specific reference to Sri Lanka. The methodology is
outlined in Chapters 3 and 4 for watershed protection and biodiversity, respectively. A
worked example of the assessment of the importance of forests for soil and water
conservation is provided in Section 3.8. The results of the soil and water conservation and
biodiversity assessments are presented in Chapters 5 and 6, respectively. Results from these
two assessments are integrated in Chapter 7 in order to better define an optimum system of
conservation forests. Chapter 7 concludes with a review of how the findings from this study
can be translated into effective conservation action.

1.2 VALUE OF FORESTS FOR SOIL AND WATER CONSERVATION

Natural forests play an important role in the conservation of soil and water resources. They
contribute to the stability of watersheds by protecting the soil surface from the direct impact
of intensive tropical rain storms, by stabilizing ground water levels and stream flows, and
by recycling some rainfall as part of the hydrological cycle.

Rainfall is intercepted by the forest canopy and the rest falls on the forest floor where
additional protection from splash erosion is provided by the covering of leaf litter. Organic

matter incorporated into the soil from the leaf litter improves the surface soil properties by
increasing infiltration of rainfall, thereby reducing surface run-off and the effects of rill and
gully erosion. Water rapidly percolates vertically into the subsoil and drains laterally into the
streams.

The removal of forest cover exposes the soil to erosion and compaction. Reduced vegetation
cover allows more water to reach the soil more rapidly. Less infiltration, caused by surface
sealing and compaction, increases surface run-off and, hence, erosion. This quickly reduces
the depth of the soil and its capacity to store water. For example, an average of 300 mm of
soil has been lost from Sri Lanka’s upper Mahaweli watershed during the last 100 years
(Krishnarajah, 1982), thereby reducing the capacity of the soil profile to store water by about
60 mm. With increasing surface run-off, the ground water table is progressively lowered and
processes of desertification set in. Steep hill sides become more prone to landslides as tree
roots rot, perennial streams become intermittent, and floods more frequent with increased
surface run-off and accumulating sediment in the river beds. Inevitably, the repercussions of
increased sediment loads and higher flood peaks are experienced further downstream from
the deforested headwaters. In the long term, sedimentation of reservoirs may substantially
reduce their capacity to store water for hydropower and irrigation, jeopardizing the ago-
industrial base of the economy.

1.2.1 Tropical forests and soil conservation

Deforestation is a major cause of soil erosion in many tropical countries. The popular view
that trees check soil erosion, particularly when planted in stands, is scientifically proven.
Besides erosion, deforestation can lead to various problems downstream, such as reservoir
siltation, sedimentation of irrigation works, and higher flood peaks.

It is necessary to distinguish between surface erosion, gully erosion and landslides because
the ability of forests to control these various types of erosion differs considerably. In a
review of 80 studies of surface erosion in tropical forests and tree crop systems, Wiersum
(1984) concluded that surface erosion is negligible in those systems where the soil surface
is adequately protected from the impact of raindrops by a well-developed litter and herb
layer. Erosion is slightly higher if the understorey is removed, but rises dramatically with
the removal of the litter layer. Studies in India have shown by that sediment loads are about
five times higher in deforested than forested catchments (Haigh et al., 1990). In Kanneliya,
which lies in Sri Lanka’s wet zone, it has been shown Ponnadurai et al. (1977) that sediment
loads are lower (0.15 t ha! yr") for natural forest than selectively logged forest (0.27 t ha”
yr‘). Sediment loads for pines (0.49 t ha yr‘) and grasslands (3.3 t ha"! yr') are still higher
(Gunawardena, 1989a), but nowhere near the high loads of 100 t ha! yr! recorded from
formerly forested, badly managed agricultural land (Stocking, 1984).

Accelerated soil erosion on hill sides shortens the effective life span of reservoirs. A study
of 17 major reservoirs in India, for example, shows that they are filling at about three times
the expected rate because of the vast areas deforested (Tejwani, 1977). Similarly, high rates
of siltation (13,500 m? km” yr’) have been recorded from deforestation in Tanzania (Kunkle
and Dye, 1981). In Sri Lanka, serious concern was expressed in 1873 about soil erosion
caused by indiscriminate conversion of forest for plantation agriculture. A recent study shows
that 15 millions tons of sediment passed through the Peradeniya gauging station in the upper
Mahaweli watershed during the period 1952-1982 (NEDECO, 1984). Almost 44% of the
capacity of the Polgolla Barrage, sited about 4 km downstream from this station, was silted

by 1988, only 13 years after its commissioning (Perera, 1989). There is every indication that
the reservoirs built under the Accelerated Mahaweli Development Project are silting up at
a much faster rate than predicted at the feasibility stage.

Hill roads cause many landslides and are a major source of sediment. It has been estimated
that roads in the Central Himalaya produce 430-550 m* km’ yr of sediment (Haigh er al.,
1990). Similarly, studies carried out in Sri Lanka have identified landslides as a major source
of sediment (Gunawardena, 1987).

1.2.2 Hydrological importance of tropical forests

The influence of forests on the hydrological cycle has been studied for a long time, but many
contradictory views persist. While there is general agreement about the beneficial effect of
forest on microclimate, air and water purification processes, and control of run-off and
erosion, the influence of forest and forest reclamation on the water balance within a region
remains the subject of much controversy. The way in which forest influences rainfall, water
yield and flooding is discussed in the following three sub-sections.

Rainfall

Opinions differ regarding the effect of forest on rainfall. Some authorities maintain that forest
has a marginal effect on rainfall, while others consider that the removal of forest results in
desertification. The consensus among hydrologists is that changes in land use have no effect
on rainfall, except in extensive areas such as the tropical watersheds of the Congo and
Amazon (Bruijnzeel, 1986; Meher-Homji, 1988; Pereira, 1989).

Although the impact of deforestation on rainfall is contentious and difficult to quantify at
present, there is rather more agreement about its repercussions on storm intensity and
associated soil erosion (Meher-Homji, 1988). Dickenson (1980) reviewed a number of studies
and concluded that deforestation could increase the intensity and reduce the duration of
tropical rainfall, enhancing run-off without necessarily changing the total amount of rain
falling during a given period. Long-term observations of private rubber plantations in
Malaysia provide circumstantial evidence of profound and lasting changes arising from forest
clearance (Unesco, 1978). Total rainfall remained unchanged following large-scale forest
clearance: rainfall frequency decreased but its intensity increased. Similarly, Meher-Homji
(1980) has shown that large-scale deforestation tends to reduce the number of rainy days
rather than the total volume of the rainfall. The result is enhanced soil erosion and,
consequently, a higher incidence of major disasters. If rainfall remains unchanged in total
amount but becomes sporadic, with a higher incidence of torrential downpours, the
consequences are more flooding and greater siltation of river beds and reservoirs. Greater
erosion reduces the capacity of soils to store water, with the result that streams dry up more
quickly if drought conditions persist.

Water yield

A common misconception is that the complex of forest soils, roots and litter behaves like a
sponge, soaking up water during rainy spells and releasing it gradually during dry periods.
Although forest soils generally have higher infiltration and storage capacities than soils with
less organic matter, most of this water sustains the forest rather than stream flow. Moreover,
appreciable quantities of rainfall (20%) are intercepted by the canopies of tropical forests,

30% in the case of wet zone forests in Sri Lanka (Ponnadurai et al., 1977), and released
back into the atmosphere.

Hibbert (1967) was the first to review the effect of forest clearance on water yield. On the
basis of 39 studies, he concluded that:

e reduction of forest cover increases water yield,
e establishment of forest cover on sparsely vegetated land decreases water yield, and
¢ response to treatment is highly variable and, for the most part, unpredictable.

Subsequent work by Bosch and Hewlett (1982), however, has shown that water yield can be
predicted. They examined 94 case studies, including those reviewed by Hibbert, and
concluded that coniferous forest, deciduous hardwood forest, brush and grass cover, in that
order, have decreasingly less influence on water yield from the source area compared to bare
ground which has none. Other work by Hamilton and King (1983) and by Oyabande (1988)
supports these findings.

Such findings, however, do not necessarily apply in the tropics where intense rainfall is
experienced over short intervals. For example, about 75% of the annual rainfall occurs
during two weeks in some parts of Sri lanka’s dry zone. Most of this water travels rapidly
through the river basin system if the land is devoid of dense forest. Such forest may hold
‘much of this rain water, increasing the opportunity for infiltration and thereby diverting more
water to the reservoir of ground water than would be the case in the absence of forest. This
replenishment of ground water may increase water yield during the dry season. As yet, there
have been no experimental studies to support this theory.

The only undisputed case of forests having a positive influence on water yield is along coastal
belts and at high elevations where the incidence of cloud or fog is high. Such cloud forests,
which comprise almost 5% of the total area of closed moist tropical forest (Bruijzneel, 1986),
intercept significant quantities of horizontal precipitation from cloud or fog. Typically, in the
humid tropics, this represents from 7-18% of normal, vertical precipitation recorded during
rainy seasons to over 100% during dry seasons. Preliminary studies conducted at 2100 m in
Sri Lanka have shown that cloud forests contribute an additional 17% of normal precipitation
(Mowjood and Gunawardena, 1992). Thus, conversion of cloud forest to agricultural land
in the humid tropics will cause a marked and usually irreversible reduction in stream flow
and ground water storage. This, and the fact that they often constitute unique ecosystems,
provides a strong case for their conservation.

Flooding

Forest clearance in tropical uplands has often been considered to be the major cause of severe
flooding, particularly in Asian countries such as northern India, China and the Philippines
(Bruijzeel, 1986), and it is widely believed that upland afforestation provides the solution to
this pressing problem. On the other hand, Bosch and Hewlett (1982) concluded from their
review of mainly North American research that deforestation does not significantly increase
the volume of water flowing in large streams, although significant increases in stream flow
usually occur in small streams and these are related to the proportion of the catchment area
that is cleared.

It has been shown that the presence or absence of forest has little effect on the magnitude of
flooding, which is mainly the result of too much rain in too short a period. The degree of
flooding is also a function of basin and channel geometry.

Recent studies in the tropics still suggest, however, that afforestation greatly reduces flood
peaks by reducing surface flow. Studies conducted at Kanneliya, in Sri Lanka’s low-country
wet zone, show that the ratio of run-off/rainfall was increased by 29% in a logged catchment
(Ponnadurai et al., 1977). Comparative studies conducted at Wewelthalawa in the mid-
country wet zone show that pine plantations produce 48% less surface run-off compared to
grasslands (Gunawardena, 1989b). Similarly, in India, deforestation may account for the
increase in extent of flood prone land from 20 to 40 million ha in the ten years up to 1989
(Haigh et al., 1988).

1.3. VALUE OF FORESTS FOR BIODIVERSITY CONSERVATION
1.3.1 What is biodiversity?

Biodiversity, a contraction of the term biological diversity, is most commonly used to refer
to the number, variety and variability of living organisms. In its widest sense, biodiversity
is synonymous with life on Earth, being the product of millions of years of evolution and
thousands of years of cultivation of plants and domestication of animals.

It has become customary to define biodiversity in terms of genes, species and ecosystems,
corresponding to three fundamental and hierarchically-related levels of biological organisation
(WCMC, 1992):

e genetic diversity is about the range of genetic material in the world’s living
organisms. It is a concept concerning the variability within a species, upon which
depend the breeding programmes necessary to protect and improve cultivated plants
and domesticated animals as well as much scientific advance and innovation. It is
measured by the variation in genes, the chemical units of hereditary information that
may be passed from one generation to the next.

e species diversity is about the variety of living organisms on Earth (Box 1.1). It is
measured by the total number of species within a given area under study. The species
level is generally regarded as the most natural one at which to consider whole-
organism diversity, being the primary focus of evolutionary mechanisms.

e ecosystem diversity is about the variety of ecological complexes (habitats) within
which species occur. Their health and conservation are crucial for the well-being and
survival of the species which they support, as well as for human welfare. Quantitative
evaluation of ecosystem diversity is problematic. While genes and species define
themselves through replication, and communities may be defined and classified
relatively unambiguously, ecosystems tend not to exist as discrete units, but represent
parts of a highly variable natural continuum within which any perception of change
is heavily scale-dependent. Moreover, unlike genes and species, ecosystems explicitly
include abiotic components, being partly determined by soil parent material and
climate.

The number of species present in a given area, species richness, is the most straightforward
and in many ways the most useful measure of biodiversity. Species richness tends to vary
geographically according to a series of general rules, of which the most important are:

warmer areas support more species than colder ones;

wetter areas support more species than drier ones;

less seasonal areas support more species than seasonal ones;

areas with varied topography and climate support more species than uniform ones;
and

e larger areas support more species than smaller ones.

Box 1.1 How many species are there?

A species is a group of actually or potentially interbreeding living organisms reproductively isolated from
other such groups (Mayr, 1969).

The number of species on Earth is very high but not known to within even an order of magnitude because
the majority are thought to remain undescribed. An estimated 1.7 million species have been described to
date, of which some 250,000 are flowering plants, over 1 million are invertebrates (insects are the largest
group with 950,000 species) and about 45,000 are vertebrates (WCMC, 1992). Estimates of the total
number of species that might exist in the world range from five million to nearly 100 million, with insects
and micro-organisms constituting most of the species thought to exist but not yet discovered and
described.

Thus, most species are concentrated in the tropics where conditions are hot and wet. Lowland
tropical terrestrial ecosystems tend to have the highest diversity, with diversity declining with
precipitation and latitude (or altitude). Similar generalisations apply to aquatic ecosystems.
Coral reefs, lakes and wetlands in the tropics exhibit a higher diversity than temperate
systems. Apart from precipitation and temperature gradients, species richness is also
governed by nutrient and salinity levels in terrestrial and aquatic ecosystems, respectively
(McNeely, 1988; WCMC, 1992; OECD, 1996).

Despite its usefulness, species richness is an incomplete measure of diversity and has
particular limitations when comparing the diversity of two different areas. One factor is
species endemism - i.e. whether or not a species is restricted (endemic) to an area under
consideration. Any given area contributes to global diversity in terms of its complement of
species and the proportion which are unique to that area. For example, islands, such as Sri
Lanka, typically have fewer species than equivalent-sized continental areas but a higher
proportion which are found nowhere else. In other words, they have lower species diversity
and higher species endemism.

Another important factor is taxonomic diversity. Species that are very different from each
other, by virtue of being distantly related, contribute more to overall diversity that closely
related species. Thus, there is a case for measuring diversity at taxonomic levels higher than
species (e.g. genera or families), given that an area with ten species in the same genus, for
example, is less diverse than an area with ten species from ten different genera.

While species diversity may be strongly correlated with ecosystem diversity, it is usually not
possible to maximise both species diversity and genetic diversity. Genetic diversity increases
with the size of a population, but a population increase in some species may lead to a decline
in genetic diversity in others, or even to a reduction in species diversity. Thus, strategies to

7

conserve biodiversity must be directed towards maintaining the diversity of species and their
associated habitats, while ensuring that no species falls below the minimum population level
at which its future viability is severely at risk due to the loss of genetic diversity. Thus, from
a management perspective, it is essential to identify objectives precisely in order to plan
appropriate biodiversity conservation strategies.

1.3.2 Why conserve biodiversity?

Biodiversity has been slowly and naturally evolving since the beginning of life. Human
activities also shape biodiversity. Pressures on biodiversity from increasing human
populations and associated environmentally-unsound development have risen dramatically in
the last century or more, resulting in the loss of much diversity, particularly at genetic and
species levels. While the rate at which species are becoming extinct is uncertain, because so
many species are unknown (Box 1.1), it has been estimated for various taxonomic groups of
species in tropical forests that from 2% to 25% of species might become extinct over the next
25 years (UNEP, 1995). This represents 1,000-10,000 times the historic rate of extinction.

The loss of the world’s biodiversity, and its ecological and economic consequences, is now
widely recognised as a matter of urgent global concern. The increasing importance given to
conserving biodiversity is evident from the rapid ratification of the Convention on Biological
Diversity, one of three international environmental treaties signed by 157 countries at the
United Nations Conference on Environment and Development, or Earth Summit, in 1992.
Its principle objectives are the conservation of biodiversity, the sustainable use of its
components, and the equitable sharing of the benefits arising from the use of genetic
resources. The Convention entered into force in December 1993 and has now been ratified
by over 130 countries, including Sri Lanka in 1994.

It is important to interpret the word conservation in terms of the management of human use
of the Earth’s resources so that it may yield the greatest sustainable benefit to present
generations while maintaining its potential to meet the needs and aspirations of future
generations (IUCN, 1980). Thus, conservation is not focused solely on preservation, rather
the emphasis is on wise use, thereby contributing to sustainable development. Sustainability
is the basic principle of all social and economic development, optimizing the social and
economic benefits available in the present without jeopardising the likely potential for similar
benefits in the future (McNeely ef al., 1990).

Preserving biodiversity ensures that present and future options for its wise use are
maintained, and that the planet is kept in a state supportive of human life (WCMC, 1992).
Among the many reasons why biodiversity is important to human society are the following
principle values:

¢ biodiversity facilitates ecosystem functions that are vital for continued habitability of
the planet (e.g. carbon exchange, watershed flows of surface and ground water,
protection and enrichment of soils, regulation of surface temperature and local
climate);

e biodiversity offers aesthetic, scientific, cultural and other values which are intangible
and non-monetary but are nonetheless almost universally recognised;

¢ biodiversity is the source of most of the world’s products, including foodstuffs,
fibres, pharmaceuticals and chemicals, and it provides the basis of biotechnology;

e biodiversity forms the basis for breeding new and improved varieties of crops and
livestock; and

e the uniqueness and beauty of diverse ecological systems has value for ecotourism and
a wide range of recreational uses (OECD, 1996).

These and other values can be classified in terms of their direct and indirect benefits, as
shown in Box 1.2. Indirect benefits are seldom accounted for in cost-benefit analyses, but
they may far outweigh direct benefits. Values are perceived in different ways according to
needs. At the local level, for example, consumptive use value is often the most relevant,
while national governments tend to be most interested in productive use value, often in terms
of revenue from foreign exchange earnings. Although many products of biodiversity are
traded internationally, the world community is also likely to be interested in non-consumptive
use and existence values, particularly as it grapples with global issues such as climate change
and rising sea level.

Assessing the values of biodiversity is an essential first step towards sound, sustainable
development, enabling planners and resource managers to address conservation needs. The
second step is to develop optimum strategies to conserve biodiversity.

Box 1.2 Values of biodiversity

Direct Values

e@ Consumptive use value is the non-market value of natural products, such as
firewood, game and fodder, that are consumed directly, without passing through a
market.

Productive use value is the value of natural products harvested commercially, such
as fish, medicinal plants and timber.

Indirect Values

@ Non-consumptive use value is concerned primarily with nature’s services rather than
her goods through the proper functioning of ecosystems, such as watershed protection,
photosynthetic fixation of solar energy, regulation of climate and soil production. It
also includes recreational, aesthetic, spiritual, cultural, scientific and educational
values.

Option value is concerned with maintaining as many gene pools as possible,
particularly for those wild species which are economically important or potentially so,
in anticipation of unpredictable biological and socio-economic events. It is the value
of keeping options open for the future.

Existence value is the value of ethical feelings towards the very existence of wildlife.

(Source: McNeely, 1988)

Box 1.3 Some values of forest

WATER
The importance of forests in the hydrological cycle is well known, although far from
properly understood (see Section 1.2.2). Both agriculture and industry depend on good
quality water provided by forested watersheds. In relation to biodiversity, tropical forests
provide spawning and feeding grounds for freshwater fishes during times of flood.

CLIMATE
Forests are closely linked to climate change, notably in their capacity to mitigate global
warming through their role as carbon sinks. They sequester 90% of the world’s terrestrial
carbon, storing 20-100 times more carbon than agricultural land.

AMENITY
Tourism is the world’s leading industry (worth US $350 billion per year), much of it being
based on nature. Forests attract increasing numbers of national and foreign visitors.

TIMBER
The international trade in timber amounts to some US $103 billion per year, most of which
comes from temperate forests. In the tropics, 80% of the estimated 1 billion cubic metres
removed annually is used for fuel, providing a significant proportion of energy in rural
areas.

MEDICINES
Forests are the source of many medicinal plants, one estimate suggesting that 28% of all
plants have been used for medicinal purposes.

NON-WOOD FOREST PRODUCTS
Other than medicinal plants, this category includes products such as game, fish, nuts,
fruits, mushrooms, resins and honey. Studies have shown that such products may be worth
more than the timber within the same area.

AESTHETICS
Many people benefit from forests indirectly through a variety of media, without ever
visiting them. This is particularly true of the biodiversity within forests. Documentary films
on wildlife, for example, feature increasingly during prime viewing times, providing
benefits worth millions of dollars.

RESEARCH
Many scientists are involved in forest-based research, indicating the value of forests and
their associated species for elucidating a wide range of issues of importance to society.

EDUCATION
Forests provide an educational resource for students to learn about ecology, forest
management, anthropology, philosophy, aesthetics and other subjects.

(Source: McNeely, 1996)

10

1.3.3 Why are forests important for biodiversity?

Forests cover 27% of the Earth’s terrestrial surface (FAO, 1995). They are the major source
of living, three-dimensional structural complexity on land, providing a rich and diverse
source of habitats, from their canopies to root systems, for other species. In the words of
Fernside (1990):

forests are the great biotic flywheel that keeps the biosphere functioning more or less
predictably. They are the major biotic component of the global carbon cycle, contain
about three times as much carbon as the atmosphere, and their destruction contributes
directly to the warming of the earth over large areas, energy balance, water balance,
nutrient fluxes, and air and water flows. They are, moreover, the major reservoir of
biotic diversity on land: there is no habitat richer in species, none more promising
as a source of succour for a swelling, grasping human population uncertain as to
where its great hopes lie.

In so far as biodiversity is concerned, forests are the main home of the Earth’s species. Rain
forests are particularly rich in species: covering less than 6% of the Earth’s land surface,
they contain at least 50% of the world’s species (Collins, 1990). This reservoir of genetic
resources is vital for human welfare, as a source of raw material for drugs, biological control
- of crop pests, and improving cultivated plants and domesticated animals through breeding or
genetic engineering. Forest diversity also provides for the vast array of timber and non-wood
forest used commercially and by local or indigenous communities. Forests provide many
other benefits, although not all of these are necessarily a direct function of their diversity
(Box 1.3).

1.4 FOREST CONSERVATION
1.4.1 Protected areas

One of the best-known and most effective ways of conserving biodiversity in order to better
meet the material and cultural needs of mankind now and in the future is through the
establishment and management of protected areas (MacKinnon et al., 1986; McNeely, 1988).
Such views are echoed by The World Bank in a strategy paper for conserving biodiversity
in the Asia-Pacific region: "setting up comprehensive and well-managed protected area
systems is likely to be the most practical way to preserve the greatest amount of the world’s
biological diversity and the ecological processes that define and mould it" (Braatz, 1992).

As defined at the IV World Congress on National Parks and Protected Areas, Caracas, 10-22
February 1992,

a protected area is an area of land (and/or sea) especially dedicated to the
protection and maintenance of biological diversity, and of natural and
cultural resources, and managed through legal or other effective means
(IUCN, 1994a).

In practice, protected areas are managed for a wide variety of purposes which may include:

e scientific research,
e wilderness protection,

11

preservation of species and ecosystems,

maintenance of environmental services,

protection of specific natural and cultural features,
tourism and recreation,

education,

sustainable use of resources from natural ecosystems, and
maintenance of cultural and traditional attributes.

Six distinct categories of protected area are recognized by IUCN, definitions of which are
provided in Box 1.4. One or more of the above management objectives may be encompassed
to a greater or lesser extent within a particular category. Very often it is necessary to zone
a protected area to provide for a range of management objectives and multiplicity of uses.
Zonation can also be used to buffer ecologically sensitive core areas from external pressures.

Such integration of strict protection with sustainable use forms the basis of the biosphere
reserve concept, first launched in 1971 under the UNESCO Man and the Biosphere
Programme and now being widely applied to resolve the often conflicting interests of
conservation and development. The concept concerns the zonation of a biosphere reserve into
areas of different use, with a strictly protected core area of high biological value buffered
by concentric zones under progressively more intensive but sustainable forms of development
towards its periphery (Batisse, 1986). It has been applied widely to other types of protected
area.

The maintenance of biodiversity on land outside protected areas is also essential, particularly
in South Asia and Mainland South-East Asia where protected areas cover only 3.6% of these
regions ((Green et al., 1996). Some of the more innovative and cross-sectoral approaches to
conserving biodiversity are reviewed by McNeely et al. (1990).

1.4.2 Criteria for selecting protected areas to conserve biodiversity

To ensure that protected areas function with maximum effect, they should be selected in
accordance with principles of conservation biology. The following criteria provide a basis
for the selection of protected areas.

Size

Protected areas should be as large as possible in order to (a) minimise risks of species’
extinctions and (b) maximise representation of ecological communities and their constituent
species.

(a) Given that protected areas are effectively islands of natural or near-natural habitat
in a sea of humanity, they should be as large as possible to maximise the degree to
which their contents retain their integrity and to minimise extinction rates. The
larger a protected area is, the better it is buffered from outside pressures (Soule,
1983).

While many of the human pressures on species and their habitats can be reduced or
removed through more effective management, chance demographic and genetic
events are more difficult to overcome. Since genetic variability is rapidly lost in
small populations due to genetic drift (random changes in gene frequencies) and

12

Box 1.4 Definitions of the IUCN protected area management categories

CATEGORY I

CATEGORY Ia

Definition:

CATEGORY Ib

Definition:

CATEGORY II

Definition:

CATEGORY III

Definition:

CATEGORY IV

Definition:

CATEGORY V

Definition:

CATEGORY VI

Definition:

Strict Nature Reserve / Wilderness Area: protected area managed mainly for
science or wilderness protection

Strict Nature Reserve: protected area managed mainly for science

Area of land and/or sea possessing some outstanding or representative ecosystems,
geological or physiological features and/or species, available primarily for scientific
research and/or environmental monitoring.

Wilderness Area: protected area managed mainly for wilderness protection

Large area of unmodified or slightly modified land, and/or sea, retaining its natural
character and influence, without permanent or significant habitation, which is
protected and managed so as to preserve its natural condition.

National Park: protected area managed mainly for ecosystem protection and
recreation

Natural area of land and/or sea, designated to (a) protect the ecological integrity of
one or more ecosystems for present and future generations, (b) exclude exploitation
or occupation inimical to the purposes of designation of the area and (c) provide a
foundation for spiritual, scientific, educational, recreational and visitor opportunities,
all of which must be environmentally and culturally compatible.

Natural Monument: protected area managed mainly for conservation of specific
natural features

Area containing one, or more, specific natural or natural/cultural feature which is of
outstanding or unique value because of its inherent rarity, representative or aesthetic
qualities or cultural significance.

Habitat/Species Management Area: protected area managed mainly for
conservation through management intervention :

Area of land and/or sea subject to active intervention for management purposes so
as to ensure the maintenance of habitats and/or to meet the requirements of specific
species.

Protected Landscape/Seascape: protected area managed mainly for
landscape/seascape conservation and recreation

Area of land, with coast and sea as appropriate, where the interaction of people and
nature over time has produced an area of distinct character with significant aesthetic,
ecological and/or cultural value, and often with high biological diversity.
Safeguarding the integrity of this traditional interaction is vital to the protection,
maintenance and evolution of such an area.

Managed Resource Protected Area: protected area managed mainly for the
sustainable use of natural ecosystems

Area containing predominantly unmodified natural systems, managed to ensure long
term protection and maintenance of biological diversity, while providing at the same
time a sustainable flow of natural products and services to meet community needs.

(Source: IUCN, 1994a)

13

(b)

Shape

inbreeding (breeding among close relatives), populations should be maintained as
large and diverse as possible (Wilcox, 1984).

Thus, protected areas need to be large enough to support minimum viable
populations of key species. Good candidates are umbrella species, whose
conservation will provide a protective umbrella for other associated species, and
ecologically significant species which occupy central positions in the food webs of
communities (Wilcox, 1984). Populations of key species should consist of at least
500 genetically effective individuals, or a total population of about 1,000 individuals
including juveniles and other non-breeders, in order to maintain sufficient variability
for adaptation to long-term changing environmental conditions (Frankel, 1983;
Soule, 1987)’.

Protected areas should encompass as wide a contiguous range of ecological
communities as possible because few species are confined to a single community and
few communities are independent from those adjacent to them (MacKinnon et al.,
1986). The more communitiés represented, the greater the number of species and the
greater the complexity of ecological interactions. Maximum representation of
communities is best achieved by ensuring that the entire range of an environmental
gradient, such as altitude or soil type, is included.

There is a relationship between the number of species within a relatively uniform
area and the size of that area. As a general rule, for every 10-fold decrease in the
size of an area, 30% fewer species are present (Wilcox, 1984). The relationship has

been described by a variety of equations (see Nicholls, 1991), of which the most
usually used are: species richness (S) as a power function of area (A),

S = kA*(1+e)
and its logarithmic transformation,
In(S) = In(k) + zIn(A) + In(1+e)

where k and z are constants (or parameters) and e is the stochastic or random
component of the model.

Protected areas should be of a compact shape in order to minimise ‘edge effects’, and their
boundaries should be biogeographically meaningful.

Edge effects, such as colonisation by invasive species from adjacent disturbed habitats or
human encroachment, can be minimised by selecting compact shapes, preferably circular.
Boundaries should follow natural topographic features, but watersheds are preferable to rivers
because the latter often bisect essential terrestrial habitats of a range of species (MacKinnon
et al., 1986).

> For short-term survival of serious inbreeding and its deleterious effects, the minimum viable population is estimated to be 50 breeding
individuals (Soule and Wilcox, 1980).

14

Corridors and clusters

Protected areas should be linked to each other by corridors of natural or semi-natural habitat
or located in clusters to prevent them from becoming completely isolated from each other.

Corridors and clustering of protected areas enable animals to move between adjacent sites,
thereby maximising the exchange of genetic material between neighbouring populations. They
also increase the effective size of protected areas.

Representativeness

The full complement of biodiversity within a region should be represented within a system of
protected areas.

Given that it is seldom possible to protect entire geopolitical units in their natural state,
systems of geographically scattered protected areas need to be established which are
representative of every ecological community within a region.

Systems should be optimal in terms of the amount and uniqueness of biodiversity protected
per unit area to make most efficient use of scarce land resources for conservation. This is
best achieved by giving priority to centres of high species diversity.

Pragmatism

Pragmatic considerations should be incorporated in the selection and design of protected
areas.

For example, an area should only be protected for conservation purposes if there is a good
chance of its ecological integrity being maintained. Thus, protected areas should only be
established in areas where they can be afforded adequate protection (MacKinnon ef al.,
1986).

Other important considerations are the desirability to locate protected areas in areas where
they can provide a variety of goods (e.g. firewood, minor forest products) and services (e.g.
research, tourism, watershed protection), and to avoid establishing them in areas of high
timber or agricultural production potential unless there are no suitable alternatives
(Howard, 1991).

15

Chapter 2
SRI LANKA’S FORESTS
ETS RT SRP 7 aR ON A SC

2.1 GEOGRAPHICAL SETTING

Sri Lanka is an island, 65,610 km’ in area, lying off the south-eastern corner of the Indian
subcontinent from which it has been separated since the late Miocene. Originally part of
Gondwanaland in the distant geological-past, it was never fully submerged by the sea, with
the result that sedimentary deposits of Miocene limestone are confined to the north-west,
including the Jaffna Peninsula. The rest of the island, nearly 90%, comprises pre-Cambrian
crystalline rocks.

Approximately 75% of the island is coastal plain, sometimes referred to as the first
peneplain. It is most extensive in the north and east where the landscape features isolated
hills, remnants of erosion, that rise up 600 m or more. Here also occur many hundreds of
reservoirs, legacies from the 12th century or earlier of the highly advanced irrigation systems
built by the Rajarata civilization to water vast areas of paddy (Baldwin, 1991).

Inland from the first peneplain, a second peneplain rises to about 500 m. Further inland is
a third peneplain comprising a south-central massif which rises to just over 2,500 m. The
massif is a compact physiographic unit, somewhat anchor-shaped, with the Central Highlands
bounded by a high mountain wall to the south and the Knuckles Range forming the extremity
of the northern arm. The headwaters of all major rivers originate from this massif.

2.1.1 Influence of climate

The south-central massif has a major influence on the climate, intercepting the moisture-laden
winds of the south-west monsoon from May to September when high rainfall is experienced
in the south-western lowlands and windward slopes of the Central Highlands. During this
Yala season the rest of the country in the north, east and south-east remains dry,
experiencing the south-west monsoon as a dry, desiccating wind. The northern, eastern and
southern parts of the country are much drier, averaging 1000-2000 mm per year as compared
to 2000-5000 mm in the south-west, and receive most rainfall from the north-east monsoon
during the Maha season (October-January).

On the basis of this climatic regime, the island is conventionally divided into wer,
intermediate and dry zones (Figure 2.1). It should be appreciated, however, that the
boundaries of these zones are imprecise and subject to academic debate. For example, the
intermediate zone is not always distinguished and sometimes a fourth, arid zone is recognised
for the north-west and south-east coastal areas, which receive less than 1250 mm of rainfall
per year.

Climate is main determinant of natural forest distribution. As described more fully in
Section 2.2.1, tropical rain forest is the climax vegetation of the south-west wet zone, with
wet evergreen montane forest present at higher altitudes. The intermediate zone of the
seasonally dry northern and eastern plains has tropical semi-evergreen forest, which gives

16

Climatic Zones of Sri Lanka
+

FORESTS
CLOSED CANOPY FORESTS *

RAINFALL ISOHYETS

/\/ 1800mm
NN 2500mm

* includes mangrove and
riverine dry forests.

DRY ZONE ©

WET ZONE

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

Figure 2.1 Rainfall isohyets and climatic zones of Sri Lanka superimposed on the
distribution of closed canopy forest in 1992, based on the 1:50,000-scale forest map of Sri
Lanka (Legg and Jewell, 1995)

17

Climatic Zone Boundary
Isohyets inmm.

Mean Annual Discharge
in millions of M>

Source: National Atlas of Sri Lanka

Batticaloa

4

(eee lee

aa murnegele
_-->>. Mana Oke

500
~ 200

x (S
Watawala ©
Rotnopura

Figure 2.2 Discharge from Sri Lanka’s main rivers (Source: National Atlas of Sri Lanka)

18

way to tropical dry mixed evergreen forest in the dry zone. The arid zone of the north-
western and south-eastern extremities of the island are covered with tropical thorn forest
(Baldwin, 1991).

2.1.2 River basin system

Surface water, which is essentially the surplus run-off from rainfall after evaporation and
infiltration have occurred, drains radially from the high watersheds in the central hills. There
are 103 natural river basins which cover 90% of the island. The remaining 94 coastal basins
are small, contributing little to water resources. River basins in the wetter parts of the hill
country are perennial, while many of those in the dry zone are seasonal. Only a few river
basins carry water from the wet to the dry zone, such as the Mahaweli Ganga which drains
16% of the island. The relative importance of the main rivers is shown in Figure 2.2 in
terms of their mean annual discharge.

The south-western part of the central hills comprises the critical upper catchments of the
country’s largest rivers. Over 65% of wet zone catchment rainfall is discharged into rivers,
with the Kalu Ganga having the maximum discharge of 77%. Rivers rising in the drier
eastern half of the hill country discharge 20-40% of rainfall.

2.1.3. Water resources

The surface water potential is summarised for each district in Figure 2.3. Values exceed
2.4 m for Colombo, Galle, Kalutara, Kegalle and Ratnapura districts, while most districts
in the Dry Zone have less than 0.03 m water depth. Hence, the most luxuriant vegetation
(rain forest) occurs in the wet zone, while the thorn forest characteristic of the dry zone
reflects the high water deficit. However, surface water levels provide only an indirect
indication of the availability of water for vegetation, the critical limiting factor being its
monthly distribution.

2.2 BIODIVERSITY

Sri Lanka is one of the smallest but biologically most diverse countries in Asia. It is
recognized as a biodiversity hotspot of global importance, being one of 250 sites of prime
importance for the conservation of the world’s floristic diversity (Davis and Heywood, 1994).
Its diverse topography and varied tropical climate have given rise to extremely high levels
of species diversity, higher than in most other tropical Asian countries when measured per
unit area. Much of this diversity is endemic, a reflection of the island’s separation from the
Indian subcontinent since the late Miocene.

The various types of ecosystems have been relatively well studied and defined, but species
diversity in many taxonomic groups remains poorly recorded and little is known about the
genetic diversity within species. Recent reviews of Sri Lanka’s biodiversity can be found in
Baldwin (1991) and Wijesinghe ef al. (1993).

Much of this diversity is found in Sri Lanka’s forests, particularly those in the wet and
intermediate zones of the south-west of the island where conditions are wettest and
temperature (dependent on altitude) most varied. Diversity tends to be lower in the seasonally
dry plains of the dry zone to the north and east.

19

WATER DEPTH (m)

Kilinochchi 0-05
VALE 0.5- 1.0

1.0-1.5.
1.5 -2.0
2.0 -2.5
2.5 >

Anuradhapura
0.29

Puttalam
2 0.34

Polonnaruwa
°
0.46

Batticaloa
0.21

+ Kurunegala.°
*-0.62!5°

Figure 2.3 Surface water potential of districts in Sri Lanka

20

2.2.1 Forest cover and diversity

Closed-canopy forest covers nearly 24% of the island and open canopy a further 7%
(Table 2.1). Its distribution, based on interpretation of 1992 Landsat imagery by Legg and
Jewell (1995), is shown in Figure 2.1. An estimated 4,055 ha of degraded natural forests
have been enriched with mahogany (Legg and Jewell, 1995). Most remaining forest is of the
dry monsoon type, which is most extensive in the north and south-east of the island. Only
fragments of tropical rain forest, few larger than 10,000 ha, remain in the south-west wet
zone, where species diversity is highest. Although the total area of mangrove forest is very
small, its importance as an ecosystem is considerable. It stabilizes the shoreline of estuaries
and lagoons, and provides essential spawning and nursery grounds for many species of fish,
as well as habitat for a variety of crustaceans and other marine life.

Table 2.1 Extent of remaining natural forest in 1992 (Source: Legg and Jewell, 1995)

Total area (ha) % total land area”

Closed-canopy:

Montane
Sub-montane
Lowland
Moist monsoon
Dry monsoon
Riverine
Mangrove
Sub-total
Open canopy:
Sparse
TOTAL

3,108
68,838
141,549
243,877
1,094 287
22,411
8,687
1,582,757

463,842
2,046,599

* Percentages are based on a total land area of 6,616,628 ha.

Table 2.2 Main types of natural forest, their dominant communities or species and their bio-climatic
distribution (Source: Wijesinghe ef al., 1993)

Forest type Dominant communities or species

Wet evergreen forest
(tropical rain forest)

Tropical montane forest

Intermediate evergreen
forest

Dry mixed evergreen
forest

Semi-evergreen thorn
forest

Dipterocarpus (low/mid altitudes)

Mesua-Doona-Shorea (mid altitudes)

Campnosperma zeylanica (Adam's Peak range)
Vitex-Wormia-Chaetocarpus-Anisophyllea (low altitudes)

Syzygium-Calophyllum-Gordonia-Michelia (widespread)
Stemonoporus (Adam’s Peak range)

Intermediate between wet evergreen and dry mixed
evergreen forest

Manilkara-Drypetes-Chloroxylon (widespread)
Alseodaphne-Berrya-Diospyros (more humid conditions)

Manilkara hexandra, Salvadora persica, Dichrostachys
cinerea, Acacia spp.

21

Bio-climatic zone

Low/mid-country wet

Montane wet

Low/mid-country
intermediate
Montane intermediate

Dry

Arid

The major types of natural forest ecosystem and their distribution are shown in Table 2.2.
In general, tropical rain forest occurs in the lowlands of the wet zone up to about 900 m. Its
dominant trees form a closed canopy at 25-30 m, with emergents rising to 45 m. The
undergrowth is relatively sparse but rich in epiphytes and lianas. Lower montane (900-1350)
and upper montane (> 1350 m) forests have a lower canopy and denser undergrowth. The
intermediate evergreen forest of the transition zone, between the wet and dry zones, has its
own characteristic species e.g. Lunumidella (Melia dubia), Pihimbiya (Filicium decipiens),
Katu imbul (Bombax ceiba), and Murutha (Lagerstroemia speciosa) as well as some in
common with the adjacent zones. The dry mixed evergreen forests of the dry zone are often
without a closed canopy and seldom exceed 20 m in height. In the extreme north-west and
south-east of the island, which have very long dry seasons, they give way to semi-evergreen
thorn forest of lower stature and with an undergrowth of thorny shrubs.

2.2.2 Species diversity

Much of Sri Lanka’s flora and fauna has been collected and described since the early
nineteenth century, although lower forms of plants and animals remain poorly known. Even
among the vertebrates and flowering plants, however, it appears that many species remain
undiscovered. Intensive surveys in recent years in Hiniduma, Ritigala and Sinharaja have led
to the discovery of many new species. It is likely that more species await discovery in
biologically diverse places such as the Knuckles, Horton Plains and Peak Wilderness, which
have yet to be systematically inventoried.

The number of species of vascular plants, vertebrates, and some invertebrate groups
described to date is summarised in Table 2.3, together with their status. Many of these
species are endemic to Sri Lanka, for example 26% of flowering plants, 76% of land snails,
60% of amphibians, and 49% of reptiles. Prior to the NCR, little was known about the
distribution and status of many of these species. Based on such information as does exist,
numerous species are threatened with extinction according to either national or international
criteria’.

2.2.3 Genetic diversity

Genetic diversity is the least well studied component of biodiversity. Most of the research
on it has been related to economically important crops. For example, germ plasm from some
native spices of commercial importance has been collected from the wild, such as cinnamon
(Cinnamomum verum), cardamom (Elettaria cardamomum), betel (Piper betle), and pepper
(Piper nigrum). A large number of wild fruits that are consumed mostly by villagers have
yet to be studied and their genetic diversity preserved. Likewise the gene pool of many
medicinal plants and wild relatives of cultivated plants is still found only in the wild, where
it is threatened by continuing deforestation and unsustainable exploitation.

Regarding the fauna, there have recently been a few studies of large vertebrates, notably
elephant and leopard, which indicate a decrease in genetic diversity as a consequence of
geographic isolation from the Indian subcontinent. However, there has been no further study

3 It should be noted that many endemic species are listed in Table 2.3 as threatened at national but not global level. In principle, any
endemic which the host country considers to be threatened should be classified as threatened by IUCN by virtue of it endemicity. In
practice, criteria need to be applied more consistently at national and international levels to avoid such anomalies.

22

to assess whether or not this diversity has been further eroded as a result of the decline of
populations due to habitat fragmentation.

Table 2.3 Numbers of species of vascular plants, vertebrates and selected invertebrate groups and
levels of endemism and threat, based on Bandaranaike and Sultanbawa (1991) for angiosperms,
Ratnapala and Arudpragasam (n.d.) for land snails, Kotagama (n.d.) for vertebrates and WCMC
(1994) for other plant and animal groups. National threatened status is based on Wijesinghe er al.
(1993), and global threatened status on the 1994 IUCN Red List of Threatened Animals and the
WCMC Plants Database (23 December 1994).

Number Number

National Global National Global
criteria criteria criteria criteria

Pteridophytes 90 (29%) 36 (11%) 57 (18%) 30 (53%) 35 (61%)
Gymnosperms 1 (100%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Angiosperms 487 (14%) 413 (12%) 879 (26%) 227 (26%) 399 (45%)
Butterflies 81 (33%) 3 (1%) 14 (6%) 11 (79%) 3 (21%)
Spiders 14 (4%) 0 0%) 0 0%) 0 (0%) 0 (0%)
Land molluscs 152 (57%) 0 0%) 201 (76%) 152 (76%) 0 (0%)
Freshwater fishes 30 (46%) 19 (29%) 29 (45%) 28 (97%) 19 (66%)
Amphibians 29 (60%) 0 (0%) 29 (60%) 29 (100%) 0 (0%)
Reptiles 113 (70%) 9 (6%) 79 (49%) 78 (99%) 1 (1%)
Birds 56 (13%) 8 (2%) 24 (6%) 17 (71%) 6 (25%)

Mammals 39 (44%) 9 (10%) 12 (13%) 11 (92%) 0(0%)

“ Excludes the newly described toad Bufo kotagami (Fernando et al., 1994).

2.2.4 Loss of biodiversity

Sri Lanka has one of the densest human populations in Asia, with the result that much of its
original forest has been cleared for settlement, cultivation, and production of timber. Changes
in land-use practices began with the onset of the colonial period. Until the early 19th century,
most of the hill country and low country dry zone were forested; large tracts of forest
remained in the north, east, and south-east; only the extreme south and south-west were
generally cultivated, paddy fields and coconut plantations being common (Holdsworth, 1872).
From 1830, vast tracts of forest at middle altitudes were cleared for coffee, to be replaced
by tea from 1850 after the coffee plantations were devastated by a leaf-blight. Forest
clearance in the dry zone began around 1869, accelerating towards the turn of the century
with the introduction of large colonization schemes. Shifting cultivation or chena also became
more widely practised, contributing significantly to the destruction of forest cover (Perera,
1977).

The emphasis on timber production continued long after independence in 1948. The result
of this policy, combined with the demands of an increasing human population, has been the
rapid reduction of forest cover. The human population has risen from 0.9 million in 1822
(the first census) to nearly 18 million inhabitants in 1994; the forest cover has declined from
about 84% of the total land area in 1881, to 23.9% in 1992 (Figure 2.4). Loss of natural
forest cover has been most pronounced in the wet zone, where it has become extremely
fragmented (Figure 1.1) due to the much higher human population density. Here, in
approximately one-third of the island, reside 55% of the human population.

23

Human population

=>
ro)
E
uo}
3
8s
~—
w
Oo
>
lo}
is)
o
n
o
=
°
oy

Figure 2.4 Relationship between increasing human population and declining forest cover
(Source: FPU, 1995)

In general, however, the impact of loss of forest on species diversity cannot be quantified
because of the lack of historical baseline information. There is evidence to suggest that some
forest species may already have become extinct. Of the 58 dipterocarps, for example, all of
which are endemic and 11 of which have been described during only the last 25 years, one
species is thought to have become extinct.* There are many more documented examples of
forest species that have become rare, very often because of over-exploitation. Satinwood
(Chloroxylon swietenia), ebony (Diospyros ebenum), calamander (Diospyros quaesita), and
nedum (Pericopsis mooniana) are now rare, having been selectively removed for their
valuable timber. Madara (Cleistanthus collinus) seems to have been exploited to extinction’.
Medicinal and ornamental species, such as orchids, are also at risk from exploitation. Of the
170 species of orchid found mostly in forest, 13 species are thought likely to become extinct.
They include Dendrobium maccarthiae, D. heterocarpum, Ipsea speciosa, and Rhynchostylis
retusa. Further details of plant species in decline can be found in Sumithraarachchi (1986),
Baldwin (1991) and IUCN Wijesinghe er al. (1994).

Among forest vertebrates, the elephant has declined from more than 10,000 at the beginning
of this century to 2500-3000 in 1993 due to hunting and destruction of habitat, particularly
wet montane forests. This decline may have been confined to the British colonial period,
when the population is reported to have decreased from 10,000 to 2,000 elephants, but there
is a paucity of post-independence census data (Santiapillai and de Silva, 1994). The
remaining population is now restricted to the dry zone, but even here its natural habitat has
become increasingly fragmented and isolated, disrupting movements and dispersal patterns.
In the case of reptiles, 14 species of endemic snakes have not been recorded since 1950 or

+ This information is based on a 1994 review of the herbarium collection at the Royal Botanic Gardens, Peradeniya (A.H.M.
Jayasuriya, pers. comm.).

> The absence of any records of this species from the NCR provides further evidence of its extreme rarity or possible extinction.

24

earlier, 13 of which are forest inhabitants, albeit mostly rather inconspicuous due to their
burrowing habits (G.P.B. Karunaratne, pers. comm., 1994).°

The full impact of this reduction in forest cover on biodiversity, in terms of loss of species,
will never be known, but threats to the future survival of species will rise as their habitats
diminish. Currently, threats are greatest in the more densely populated wet zone, where
levels of species richness and endemism are highest.

2.3 PROTECTION OF FORESTS
2.3.1 Early history

Sri Lanka has a strong tradition in nature protection Sri Lanka which dates back to the
introduction of Buddhism in 246 BC. Prior to that, it is likely that hunting was enjoyed by
at least the elite of society, but this practice changed under the Buddhist philosophy of
reverence for all forms of life - killing was forbidden. One of the world’s first wildlife
sanctuaries was established by King Devenampiyatissa in the 3rd century BC. Succeeding
kings continued to uphold Buddhist precepts: forests were protected by royal edicts, tree
felling and collection of forest products were controlled and the fragile ecosystem of the wet
zone forests were left practically undisturbed. Kings appointed kele koralas (forest officers),
whose duties included prevention of poaching and protection of royal trees. In the 12th
century AD, King Kirti-Nissanka-Mala proclaimed that no animals should be killed within
a radius of seven gav (35.7 km) of the city of Anuradhapura (Abeywickrema, 1987; IUCN,
1990).

2.3.2 Evolving conservation policies and legislation
Forest policy and legislation

Evolving policies and legislation concerned with forest and biodiversity conservation are
summarised in Table 2.4. Forestry legislation was introduced principally to protect national
and community interests in forest resources through reservation of state lands as reserved
forests and village forests, respectively. The Forest Ordinance, with its emphasis on timber
production, has become greener through various amendments. For example, activities such
as bark stripping, tapping, quarrying, burning lime or charcoal, collecting forest produce and
pasturing cattle were added to the list of activities prohibited within reserved forests under
the Amendment Act No. 13 of 1966. The Ordinance, last amended by Act No.84 of 1988, is
presently undergoing further revision to strengthen its provisions for conservation, as well
as to improve enforcement measures and raise penalties for forest offenses. Provision is made
in the draft amendment for the establishment of conservation forests.

© The 14 species of snake, known only from their type specimens in the case of the endemic species, are as follows: Typhlops
lankaensis Taylor 1947, T. violaceus Taylor 1947, T. malcomi Taylor 1947, T. tenebrarum Taylor 1947 and T. veddae Taylor 1947, all
five of which are thought by some authorities to be conspecific with a living species (Ramphotyphlops braminus), T. ceylonicus Smith 1943,
Uropeltis rubunae Deraniyagala 1954, Rhinophis tricolorata Deraniyagala 1975, R. punctata Muller 1832, R. porrectus Wall 1921, R.
dorsimaculatus Deraniyagala 1941, Colubes fasciolatus Shaw 1802, Dendrelaphis oliveri Taylor 1950 and Gerarda prevostiana Eydoux
& Gervais 1832-1837.

25

Table 2.4 Chronology of key policies and laws concerning conservation of forests and associated

biodiversity
Policy/law [Competent authority] Provisions for biodiversity conservation

1848 Timber Ordinance No.24 Reservation of forests, largely for timber production.

Forest Ordinance No.10
[Conservator of Forests]

Hooker advocates protection of natural forests above
5,000 ft as climatic reserves.

Protection of forests and their products within reserved
forests (including stream reservations) and village forests,
primarily for sustained production. Also, protection of
wildlife in sanctuaries.

Forest Ordinance No.16
[Conservator of Forests]

Protection of forests and their products within reserved
forests and village forests, primarily to provide for
controlled exploitation of timber.

First authoritative Forest Policy Preservation of indigenous flora and fauna

Amended © Clearing of forests prohibited above 5,000 ft.

Plantations to be converted to indigenous species.

Protection of wildlife in national reserves (i.e. strict
natural reserves, national parks, and intermediate zones
embodying only crown land) and sanctuaries (comprising
both crown and private land) and outside such protected
areas. Total protection afforded to wildlife in national
reserves and sanctuaries, but in sanctuaries habitat
protected only on state land while traditional human
activities may continue on privately-owned land.

Fauna and Flora Protection Ordinance
No.2
[Director of Wildlife]

© Amendment Act No.44 © Nature reserve and jungle corridor incorporated as

categories of national reserve.

Amendment Act No.1 © Intermediate zone, envisaged as a buffer zone to
provide for controlled hunting, removed from

Ordinance.

Amendment Act No.49 © Refuge, marine reserve and buffer zone incorporated

as categories of national reserve.

Emphasis on conserving forests to preserve and ameliorate
the environment, and to protect flora and fauna for
aesthetic, scientific, historical and socio-economic reasons.

National Forest Policy

Re-stated in 1972 and 1980

Unesco Biological Programme Arboreta, representative of the main bio-climatic zones,
Unesco Man and Biosphere Programme demarcated within forest and proposed reserves.

Mahaweli Environment Project Network of protected areas established to mitigate impact
of Mahaweli Development Project on wildlife and to

protect catchments in upper reaches of Mahaweli Ganga.

National Heritage Wilderness Areas Act
No.3
[Conservator of Forests]

Protection of state land having unique ecosystems, genetic
resources or outstanding natural features within national
heritage wilderness areas.

National Policy for Wildlife Conservation
(approved by Cabinet)

Objectives include the maintenance of ecological processes
and preservation of genetic diversity. Ex situ conservation
is recognized as important for threatened species.

Forestry Sector Development Programme:
Environmental Management in Forestry
Development Project

1995 National Forestry Policy
(approved by Cabinet)

Logging of natural forests banned in wet zone, pending
review of their watershed protection and biodiversity
conservation values.

Over-riding priority given to conservation of biodiversity
and protection of watersheds.

26

Concern about the complete denudation of forests for coffee and tea plantations was
expressed in 1873 by the eminent botanists Hooker and Thwaites, and by Gregory, the then
Governor of Ceylon. That same year Joseph Hooker warned against the replacement of
natural forests with plantations in view of its serious impact on the climate, and advocated
the complete protection of all natural forests above 5,000 ft (about 1,500 m) as climatic
reserves (Jansen, 1989). This was eventually incorporated within an amendment to the Forest
Policy in 1938.

Preservation of native flora and fauna has featured consistently in forest policy, beginning
with the country’s first Forest Policy introduced in 1929 by the British Governor, Sir Herbert
Stanley, and including the subsequent National Forest Policy of 1953. The National Forest
Policy was reformulated in 1980 to give more emphasis to preserving the environment and
to include a new objective, specifically to involve local people in forestry activities through
a programme of social forestry. However, this policy was not officially adopted, having
never been approved by the Cabinet, and has since been superseded by the new National
Forestry Policy of 1995.

A turning point was reached in 1972 when public outcry against tree felling in Sinharaja
Forest Reserve prompted the Cabinet to appoint a Sub-Committee to examine the problem.
Then in the mid-1980s, during the formulation of the first Forestry Master Plan of 1986, it
was recognized, after intense lobbying by the NGO community, that provisions for forest
conservation were totally inadequate, particularly in the wet zone. An environmental impact
assessment of the Forestry Master Plan was carried out by IUCN-The World Conservation
Union, to which the Government responded positively by:

e introducing a moratorium on logging in the wet zone until the conservation value of
remaining natural forests had been assessed; and

© incorporating an environmental component within the Forestry Sector Development
Programme.

In order to overcome the weaknesses inherent in the Forest Ordinance, the National Heritage
Wilderness Areas Act No.3 was passed in 1988 to provide for the protection of unique or
outstanding natural areas. Entry is by permit and activities are restricted to scientific research
and observation of flora and fauna. Other conditions include the over-riding of anything
contradictory in the provisions of any other written law apart from the Constitution. The Act
was introduced principally to safeguard biodiversity within Sinharaja, the largest tract of rain
forest remaining in the country which had been nominated the previous year for inscription
on the World Heritage List as a natural property. Sinharaja was declared a national heritage
wilderness area in 1988 and that same year it was also designated a World Heritage site.

The new National Forestry Policy gives overriding priority to the conservation of biodiversity
and protection of watersheds within forest ecosystems (Box 2.1). Among the various
strategies identified for implementing this policy are a number that relate to the establishment
of a permanent forest estate for conservation. These are cited in Box 2.2.

Adoption of many of the new forestry policies will need to be reinforced by changes to the
existing legislation, notably the Forest Ordinance which is presently under revision. The
Forest Ordinance will need to give priority to the conservation of biodiversity within forests
and make adequate provisions for its protection, particularly in conservation forests.
Boundary demarcation and notification of the many reserves proposed over several decades
is also an outstanding priority. This will need to be rationalized as part of a review of the
protected areas system in the forestry subsector (FPU, 1995).

Di

Box 2.1 National Forestry Policy of 1995

Parts of the National Forestry Policy which focus specifically on forest and biodiversity conservation are
as follows:

National Forestry Policy objectives

To conserve forests for posterity, with particular regard to biodiversity, soils, water, and historical,
cultural, religious and aesthetic values.

Policy on management of state forest resources

All state forest resources will be brought under sustainable management both in terms of continued
existence of important ecosystems and flow of forest products and services.

The natural forests will be allocated firstly for conservation, and secondly for regulated multiple-use
production forestry.

For the management and protection of the natural forests and forest plantations, the state will, where
appropriate, form partnerships with local people, rural communities and other stakeholders, and

introduce appropriate tenurial arrangements.

Planned conversion of forests into other land uses can take place only in accordance with procedures
defined in legislation and with accepted conservation and scientific norms.

Policy on management of private forest and tree resources

The state will promote tree growing by local people, rural communities, NGOs and other non-state
sector bodies for the protection of environmentally sensitive areas.

Policy on wood and non-wood forest products, industries and marketing

Effective measures to protect the forests and prevent illegal trade in wood, non-wood forest products
and in endangered species of flora and fauna will be instituted.

Policy on institutional support for forestry development
Legislation will be amended or revised, as necessary, to support implementation of the policy.
The state will provide full support to the various resource managers for sustainable forestry

development, and its institutions will be reoriented and strengthened to enable them to accomplish
their role.

Policy on intersectoral linkages

Nature-based tourism will be promoted to the extent that it does not damage the ecosystems and
insofar as it provides benefits to the local population.

The general public and industries will be educated about the importance of forestry, and of
conserving biodiversity and protecting watersheds.

28

Box

PUD Strategies for National Forestry Policy Implementation

The following strategies identified in the National Forestry Policy of 1995 are directly concerned with
the allocation of state forest land for conservation and protection purposes:

1

1.10

Strategies to promote sustainable land use for forestry

Allocation and zoning of state forest land for conservation, agroforestry and forest plantation
development, in order to establish a Permanent Forest Estate.

All forests will be brought under management by allowing for combinations of managers, including
state agencies, and managers outside the state sector such as local people, user groups, rural
communities, NGOs, the estate sector, and local industries. However, natural forests should be
managed only by the state agencies together with the local people and communities, possibly assisted
by NGOs. Various partnership approaches to forest management and conservation will be developed,
including joint forest management and leasehold forestry. The new approaches have to be adopted
first on a pilot basis before any comprehensive schemes are implemented.

State forest land will be allocated for management ‘in the following categories:

(i) Class I forests. These forests should be strictly conserved or preserved to protect biodiversity,

soils, and water, and historical, cultural, religious and aesthetic values. Research is allowed
in these areas.
Class II forests. Non-extractive uses (such as scientific research, protection of watersheds and
habitats of wildlife, and regulated nature-based tourism) should be allowed, as well as
controlled collection of NWFPs and dead fuelwood by local people living adjacent to the
forest. Al] the activities have to be in accordance with the management plans that are to be
developed jointly with the rural communities. This category would include all other protected
areas not in Class I. Zoning of such forests should be adopted, wherever feasible, to assign
different parts of the forest for protection, collection of traditional forest products, conserving
religious and cultural values, etc. The broad management objectives would be the same as in
Class I.

State forest land for conservation

The existing Protected Area System (PAS) will be rationalized and consolidated into an
integrated PAS (Class I and II forests), covering biodiversity related to both flora and fauna,
critical watersheds, and forests with special cultural, religious, historic, and aesthetic values.
The ministries responsible will take measures to ensure that the protected areas will be of a
size necessary to conserve biodiversity.

The PAS will be demarcated on the basis of biodiversity surveys, other scientific studies and
approved criteria.

® Macro-level criteria will be developed for establishing a protected area system whose
boundaries will be established on maps and in a Geographic Information System.

© At the operational level, the implementing agencies, with the participation of the local
people and NGOs, will develop criteria and demarcate the areas to be managed as protected
areas.

The PAS will be managed by the state, in co-operation with local people and NGOs.

@ Strict conservation areas (Class 1) will be zoned and managed by authorized officers only
for conservation and research. Other protected areas will be zoned and managed jointly by
the state and local people, with assistance from NGOs, as multiple-use conservation forests,
where only those activities that are defined in the management plans are allowed.

29

Wildlife policy and legislation

Various legislation was introduced from 1890 onwards to control the reckless slaughter of
wildlife, all of which was subsequently integrated under the Act No.1 of 1908. Proponents
of the new restrictions formed the Game Protection Society in 1894 - today the Wildlife and
Nature Protection Society - and employed watchers to protect areas reserved for game
hunting. Similar initiatives were taken by the then Conservator of Forests and two vast,
uninhabited forests were declared as sanctuaries for the protection of wildlife under the
Forest Ordinance No. 10 of 1885, namely Yala (Block II) in 1900 and Wilpattu in 1905
(Kotagama, 1992).

In 1930 administration of forests was placed under the Ministry of Agriculture and Lands.
One of its first initiatives was to set up a Fauna and Flora Protection Committee to advise
on the reservation of additional areas for the protection of flora and fauna. The Committee's
recommendations were accepted in 1935, and provided the basis to the Fauna and Flora
Protection Ordinance enacted in 1937 (Kotagama, 1992). This legislation has since been
amended on several occasions. A significant provision in Amendment Act No.1 of 1970 is the
recognition of indigenous rights (i.e. rights acquired prior to the establishment of a national
reserve or sanctuary), but such rights are deemed to have lapsed if not exercised for a
continuous period of two years. The most recent Amendment Act No.49 of 1993 provides for
the establishment of several new categories of reserve (Table 2.4) and raises penalties for
infringements of the Ordinance which had become grossly inadequate.

The need for a wildlife conservation policy was long recognized as a high priority but only
relatively recently adopted in the form of a National Policy for Wildlife Conservation,
following its approval by the Cabinet of Ministers in June 1990. The policy was formulated
in response to the Sri Lanka National Conservation Strategy (CEA, 1988), approved by
Parliament in 1988, and its objectives are based on those of the World Conservation Strategy
(IUCN/UNEP/WWFE, 1980). Salient features of the policy are summarised in Box 2.3.

Box 2.3 National Policy for Wildlife Conservation, 1990

The fundamental objectives of the National Policy for Wildlife Conservation in Sri Lanka are:
to maintain ecological processes ...
to preserve genetic diversity, especially the biodiversity and endemic biota.

to ensure the sustainable utilization of species and ecosystems ... which are of immediate and
potential importance to support the people.

In the introduction to the National Policy for Wildlife Conservation, attention is drawn to the
crucial importance of the wet zone for biodiversity and endemism and the urgent need to
redress the drastic imbalance of protected areas, most of which are located in the dry zone.
Although implicit in the objectives, none of the policy statements makes specific reference
to biodiversity conservation, other than one concerning the importance of ex situ conservation
in protecting threatened species. Rather more attention is given to clearly defining
management objectives specific to each protected area designation, and to providing for a
multiplicity of sustainable uses for the benefit of local people and visitors. The policy also

30

advocates a decentralized administration to enhance the flow of benefits from protected areas
to those living in their vicinity. Very little of this policy has been implemented as yet
(FPU, 1995).

2.3.3 National context

The strong conservation tradition and affinity of Sri Lankan culture towards nature is
enshrined within the second Republican Constitution (1978) which includes the following
clauses:

e The State shall protect, preserve and improve the environment for the benefit of the
community. [Article 27.14]

e The exercise and enjoyment of rights and freedom is inseparable from the performance
of duties and obligations, and accordingly it is the duty of every person in Sri Lanka
to protect nature and conserve its riches. [Article 28F]

This has provided the foundation of a series of cross-sectoral conservation initiatives to
address the ever-increasing demands on and threats to Sri Lanka’s natural resources. The first
attempt to address environmental conservation issues in a coherent, holistic manner was the
preparation of a National Conservation Strategy by the Central Environmental Authority
(1988), closely followed by an Action Plan in which specific activities were identified. The
Strategy includes directions for the establishment of a comprehensive system of protected
areas and, in the forestry subsector, for the identification of forests for legal protection.

This initiative was followed by a review of Sri Lanka’s natural resources (Baldwin, 1991)
funded by USAID, and the preparation of a National Report to UNCED. With support from
the World Bank, the newly established Ministry of Environment and Parliamentary Affairs
prepared a National Environmental Action Plan for 1992-1996. This 1994 update of the
Action Plan includes a chapter on Forests and Bio-diversity, in which the prerequisites to
effectively conserving what remains in Sri Lanka’s forests are identified as:

e high-level political commitment to establish an appropriate legal, institutional and
policy framework; and

¢ improved political and public understanding of the economic and environmental
benefits (MEPA, 1994).

The 1994 update emphasizes the urgent need for fundamental policy and institutional reforms
within the forestry and wildlife subsectors, but any attempt to propose specific policy reforms
is considered premature in view of the ongoing Forestry Master Plan.

Within the forestry subsector, the release of the first Forestry Master Plan, 1985-2020
(Jaakko Poyry International Oy, 1986) marked the turning point of forest policy from one
of exploitation to conservation of natural forests. While much forest has since been secured
for conservation, and more will be allocated, the need to effectively manage protected areas
and ensure that the benefits of doing so flow to local communities is emerging as the over-
riding priority for this and the next decade. These and other issues are addressed in the
present Forestry Sector Master Plan (FPU, 1995), the biodiversity chapter of which will be
incorporated as the forestry sector component of the Biodiversity Action Plan for Sri Lanka.
This plan is now in the process of being prepared, following the formulation of a strategy
to guide its preparation (MTEWA, 1994).

31

2.3.4 International context

Sri Lanka has entered into a number of international agreements relating to the conservation
of biodiversity, details of which are summarized in Table 2.5. The MAB Programme,
Ramsar Convention and World Heritage Convention are concerned specifically with
protecting internationally important properties for conservation, but also include more general
measures for the wise use of all wetlands (Ramsar Convention) or protection of all cultural
and natural heritage (World Heritage Convention). The Convention on Biological Diversity
provides inter alia for the conservation of biodiversity both within and outside protected
areas, and the maintenance of viable populations of species within their natural surroundings.
Under the Forest Principles, which are not legally binding, the importance of forests as
storehouses of biodiversity is recognized and the State is encouraged to protect ecologically
viable representative or unique examples of its forests.

2.3.5 Protected areas system

Growth

The growth in Sri Lanka’s protected areas system is shown in Figure 2.5. Within the forestry
subsector, forest reserves were gazetted from 1850 onwards, but none was demarcated until
1885 and none notified with boundaries until 1890. The bulk of the forest reserves network
was established in the 1920s, although a-large number of smaller reserves were notified in
the subsequent two decades. Many more reserves were proposed during this period but never
actually notified.

Table 2.5 Obligations under international biodiversity conservation agreements to which Sri Lanka
is party

International agreements Obligations

UNESCO Man and Biosphere Objective of programme is to establish a global system of
Programme biosphere reserves representative of natural ecosystems to
conserve genetic diversity and to promote conservation
activities such as monitoring, research and training. Emphasis
is on:
restoration of degraded ecosystems
integration of traditional land use practices within a
conservation framework
involvement of local people in conservation planning

Convention on International Trade in The Convention aims to protect wildlife from over-

Endangered Species of Wild Fauna exploitation and to prevent international trade from

and Flora, 1973 threatening species with extinction. Trade in species listed

(CITES) under Appendix I is prohibited. Appendix II species may be
traded in accordance with a permit system, provided export is
not detrimental to the survival of the species.

Convention Concerning the Protection | The Convention provides for the protection of cultural and
of the World Cultural and Natural natural properties deemed to be of outstanding universal
Heritage, 1972 value. Obligations of State parties include:
(World Heritage Convention) © identify sites of outstanding universal value and
nominate them for inscription on the World Heritage
List
protect all cultural and natural heritage (not just World
Heritage sites)

32

International agreements Obligations

Convention on Wetlands of The Convention aims to stem the loss of wetlands and ensure
International Importance especially as their conservation for fauna and flora and for ecological
Waterfowl Habitat, 1971 processes. Obligations of State parties include:
(Ramsar Wetland Convention) © designate one or more wetlands for inclusion in the List
of Wetlands of International Importance
promote wise use of all wetlands (includes marine waters
to a depth of 10 m - hence mangroves)
promote the conservation of wetlands through the
establishment of nature reserves on wetlands,
irrespective of their inclusion or not in the List of
Wetlands of International Importance, and manage
wetlands for the benefit of waterfowl.
promote training in the fields of wetland research,
management and wardening.
consult with other Contracting Parties about
implementation of the Convention, especially with
regard to transfrontier wetlands, shared water systems,
shared species and development aid for wetland projects.

Non-legally binding authoritative The guiding objective of these Principles is to contribute to
statement of principles for a global the management, conservation and sustainable development of
consensus on the management, forests and to provide for their multiple and complementary
conservation and sustainable functions and uses. Principles to be pursued by each State
development of all types of forests, include:
UNCED 1992 © recognize the role of forests ... as rich storehouses of
(Forest Principles) biodiversity
protect ecologically viable representative or unique
examples of forests
carry out EIAs where actions are likely to have
significant adverse impacts of important forest resources
control pollutants that are harmful to the health of forest
ecosystems

Convention on Biological Diversity, Objectives of the Convention are conservation of
1992 biodiversity, sustainable use of its components and equitable

sharing of benefits arising from utilization of genetic

resources. Obligations of State parties include:

© develop national plans for the conservation of
biodiversity

© identify and monitor components of biodiversity
important for its conservation
establish a system of protected areas for biodiversity
conservation
conserve biodiversity within and outside protected areas
promote the protection of ecosystems, natural habitats
and maintenance of viable populations of species in
natural surroundings
promote environmentally sound and sustainable
development in areas adjacent to protected areas
restore degraded ecosystems, promote recovery of
threatened species and control alien species
adopt measures for ex situ conservation of biodiversity
to complement in situ measures
protect and encourage customary use of biological
resources in accordance with traditional practices that
are compatible with conservation requirements
adopt economically and socially sound incentives for
biodiversity conservation
introduce EIA procedures for proposed projects likely to
adversely affect biodiversity, with provision for public
participation

33

rc)
fs
jo}
jo)
o
=
tas
©
®
—
o
o
fa
FS
Ay
3
E
=|
rs)
°
<x

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960
10 year period beginning ...

Protected Areas: “Protected Areas Forest Reserves
(DWLC) g (FD) (FD)

Figure 2.5 Growth of protected areas system in forestry and wildlife subsectors

While there has been no appreciative growth in the forest reserve network since the 1950s,
there has been a significant shift in the function of forest and proposed reserves from
production to conservation. This began in the mid-70s with establishment of a network of 36
Man and Biosphere reserves within which timber extraction was not permitted.’ In the last
few years the network of forest protected areas has expanded considerably, with the addition
of 31 conservation forests in the wet zone and the Knuckles Conservation Forest in the
intermediate Zone (Figure 2.5).

Within the wildlife subsector, the network of protected areas has grown progressively since
the enactment of the Fauna and Flora Protection Ordinance (Figure 2.5). The beginnings of
this network are masked by the fact that game sanctuaries established from 1900 onwards
were subsequently abolished under the new Ordinance and declared as national reserves or
sanctuaries. The network expanded considerably during the 1980s, mostly in the basin and
adjacent areas of the Mahaweli Ganga to protect water catchments and to provide refuge to
animals displaced by the Accelerated Mahaweli Development Programme.

A complete list of nationally designated areas is provided in Annex 1, together with maps
showing their boundaries. It should be noted that many of these areas designated under
national legislation or, as in the case of proposed reserves, intended for notification are not
protected areas sensu IUCN (see Box 1.4).

’ The original network of 36 Man and Biosphere reserves covered 298,317 acres, or 120,724.8 ha (Bharathie, 1979). It included
Hurulu and Sinharaja, which were designated international biosphere reserves in 1977 and 1978, respectively. The present network appears
to be less extensive but further checking of existing records is necessary in order to clarify its precise extent.

34

Designated Areas of Sri Lanka KEY

FOREST SECTOR

SS Proposed Reserve

(2 Forest Reserve

Hl Conservation Forest *

WILDLIFE SECTOR

(0) National Park

== Nature Reserve
Sanctuary

WM Strict Natural Reserve

* includes Sinharaja NHWA

:
i i ‘

Ss

Projection
CM 81 degrees, Lat of Contre Proj 8 degrees

Figure 2.6 Map of designated areas administered by the Forest Department and Department
of Wildlife Conservation

35

Subsector comparisons

Designated areas administered by the Forest Department tend to be small and confined
mostly to the wet zone, whereas those under the authority of the Department of Wildlife
Conservation tend to be larger and occur mainly in the dry zone. This is shown clearly by
the distribution map of designated areas in Figure 2.6.

Over 28% of the total land area of Sri Lanka® is reserved and administered by either the
Forest Department or Department of Wildlife Conservation: 16.1% and 12.4%, respectively,
after correction for land released by the Forest Department subsequent to being reserved
(Table 2.6). This is an overestimate, however, because Forest Department records do not
account for reserves transferred to the Department of Wildlife Conservation and designated
as national reserves or sanctuaries. Correction for this double counting, using statistics
generated from the National Forest Geographic Information System (Table 2.7), produces
an estimate of 15.1% of total land area under the Forest Department. However, the actual
percentage of total land area under the Forest Department is between 15.1% and 16.1% for
reasons given in the footnote to Table 2.7.

Table 2.6 Extent of designated areas administered by Forest Department and Department of Wildlife
Conservation.

National designation No.
| ectared | resent |

Forest Department

[Propesedreeve | zi | catute7| 9.4] seve | 89)
[National Heritage Witemes area | [nie] 02] nae | 2
6.

Department of Wildlife Conservation
Jungle Corridor
National Park

Nature Reserve

1
12
3
52
3
n

” Corrected, in the case of Forest Department, for land released subsequent to being reserved or proposed for
reservation.

BA figure of 6,616,618 ha for the total land area in Sri Lanka is used for statistical analyses throughout this report, this being
consistent with that used by Legg and Jewell (1995) to estimate forest cover.

36

Table 2.7 Overlap of forest and proposed reserves with protected areas administered by the
Department of Wildlife Conservation.!

" Statistics were generated from the National Forest GIS maintained by the Forest Department. Reserves managed by the Department of Wildlife
Conservation and Forest Department were overlaid to calculate the extent of overlap between respective categories of reserve. The two GIS datasets are
not completely comprehensive. For example, maps of forest and proposed reserves under the Forest Department do not take into account changes in
boundary due to lands released subsequent to the designation of these reserves. Such mapped information is not readily available. Thus, total overlap may
overestimate double counting by including some released lands.

Currently, the Forest Department manages 148,512 ha for conservation or 2.2% of total land
area (Table 2.8). Thus, the national system of protected areas covers over 14% of total land
area, which is higher than in many other South and South-East Asian countries (McNeely et

al., 1994).

Table 2.8 Extent of protected areas administered by the Forest Department

Description
- Name

International biosphere reserves
- Hurulu Forest Reserve
- Sinharaja Forest Reserve/Proposed Reserve!

National biosphere reserves”

Conservation forests (wet zone)

- Knuckles Conservation Forest 1 16,000

- Sinharaja National Heritage Wilderness Area 1 11,187

- other conservation forests 31 60,525
14 160,472

Total - corrected’

Sinharaja Forest Reserve and Proposed Reserve were included within Sinharaja National Heritage Wilderness Area, subsequent to their designation as
an international biosphere reserve.

2 Statistics for the total number and area of national biosphere reserves are conflicting. According to the Environmental Information System maintained
by the Forest Department, there are 40 national biosphere reserves covering a total area of 93,222 ha, plus an additional two international biosphere reserves
(Hurulu and Sinharaja) with a combined area of 9,376 ha. These records are based on the Forest Department Register and UNESCO, respectively.
However, records on file in the Forest Department indicate a total of 41 biosphere reserves, including the two internationally designated biosphere reserves,
covering an area of 72,760 ha. It is quite likely that neither dataset is entirely accurate (up-to-date) as there are statistical discrepancies between a number
of individual sites. The latter dataset is used in this study because it provides a more conservative estimate of the protected areas system. Sinharaja is also
a World Heritage site, but the area of this property is included within the statistics for international and national biosphere reserves.

} Corrected for seven national biosphere reserves (Diyadawa, Gilimale-Eratne, Haycock, Kaneliya, Kombala-Kottawa, Oliyagankele and Rammalakanda),
with a total area of 1,477 ha, which are located within wet zone conservation forests, Dotalugala national biosphere reserve (1,619 ha) in the Knuckles
Conservation Forest and Sinharaja Biosphere Reserve which lies within Sinharaja National Heritage Wilderness Area.

37

However, many of Sri Lanka’s protected areas are small and isolated, reflecting the
fragmented nature of much of the remaining natural habitat. As shown in Figure 2.7, 30%
of protected areas are less than 100 ha and 54% are less than 1,000 ha in size. Whereas most
protected areas of the Forest Department are less than 1,000 ha, most of those of the
Department of Wildlife Conservation are larger than 1,000 ha. However, many of the Forest
Department’s small protected areas are biosphere reserves (61% are less than 100 ha), which
are core areas of much larger forest or proposed reserves. Nevertheless, opportunities to
protect large blocks of forest are becoming fewer. For example, approximately half of the
31 other conservation forests in the wet zone (Table 2.8) are less than 1,000 ha.

7)
2
o
7)
@
—_

-
fo)
°

2

SSR ace
SL SSR

2
Q

101-999 1,000-9,999 10,000-99,999 > 100,000
Protected area size classes (ha)

Figure 2.7 Distribution of size of protected areas administered by Forest Department and
Department of Wildlife Conservation

The single largest protected area is Wilpattu National Park (133,571.4 ha) in the north-west
arid zone. Slightly larger is the 144,512.8 ha complex of contiguous protected areas in the
south-east, dry zone, comprising Ruhuna National Park, Yala East National Park and Yala
Strict Natural Reserve. Protected areas tend to be smaller in the intermediate and wet zones,
much more of the original forest having been converted to other forms of land use. Here,
the largest and most important protected areas are Peak Wilderness Sanctuary and adjacent
Horton Plains National Park (with a combined area of 25,539 ha), Knuckles Conservation
Forest (16,000 ha) and Sinharaja National Heritage Wilderness Area (11,187 ha).

Internationally designated protected areas

Sri Lanka participates in all three international initiations concerned with protected areas (see
Table 2.5), and has sites listed under each of them (Table 2.9). Arguably the most important
site for biodiversity conservation is Sinharaja, the country’s largest remnant of rain forest
which has been declared a biosphere reserve under the UNESCO MAB Programme and
subsequently inscribed on the World Heritage List of Natural Properties.

38

Table 2.9 Natural sites designated for conservation under international initiatives

International initiative Protected area Year Area (ha)
Ramsar Wetland Convention

UNESCO MAB Programme

World Heritage Convention

39

Chapter 3
METHODS - SOIL AND WATER CONSERVATION ASSESSMENT
cS ae Bas BM a |

3.1 INTRODUCTION

The importance of forests for soil and water conservation is assessed on the basis of the
following four criteria, as reviewed in Section 1.2:

e Soil Conservation
- soil erosion

e Water Conservation
- flood hazard
- protection of headwaters
- fog interception

Similar criteria have been identified by MacKinnon et al. (1986) for the selection of areas
in need of protection for their hydrological functions.

Whereas forest is entirely beneficial for the prevention of erosion, its presence has both
positive and negative impacts on the hydrological cycle as discussed in Section 1.3.2. Thus,
the importance of forest for soil conservation is given priority weighting over its water
conservation value in the methodology.

The methodology is described below and a worked example is provided in Section 3.8.

3.2. SOIL EROSION

Two approaches to assess erosion at the reconnaissance level have been identified by Morgan
(1980). The first is based on regional variations of various erosion indices, such as gully
density and drainage density. The second uses rainfall to calculate an erosivity index based
on kinetic energy. The latter, physically-based method has been universally accepted as a
standard technique. It was used in a case study to assess the erosion risk of Peninsular
Malaysia (Morgan, 1980). A similar procedure has been adopted in the present study to
determine rainfall erosivity. In addition, some of the parameters usually considered in more
detailed erosion assessment procedures are also incorporated in the methodology.

3.2.1 Assessment of the importance of forests for soil conservation

Soil erosion by water is influenced most by the amount of rainfall. In regions of very low
mean annual rainfall, little erosion is caused by the rain running off the land because most
of it is absorbed by the soil and vegetation. In other regions of very high rainfall (> 1000
mm yr’), as in Sri Lanka, dense forest typically develops which protects the soil from
erosion by water. Removal of this natural forest cover usually results in severe erosion.

40

However, it is not only the amount of rainfall that affects soil erosion but also its intensity.
The intense downpours characteristic of the tropics have a very much greater impact than the
gentler rains of temperate climates. The zone of intensive or ‘destructive’ rain lies between
approximately 40° North and 40° South, within which Sri Lanka is situated.

The severity of soil erosion also depends on the susceptibility of a given soil to erosion. This
attribute of soil is influenced mostly by its physical characteristics, such as texture, structure,
infiltration capacity and permeability. Soil structure is largely determined by the organic
matter content of the soil: the higher the level of organic matter, the less susceptible the soil
is to erosion.

Thus, the amount of erosion depends upon a combination of the power of the rain to cause
erosion and the ability of the soil to withstand erosion (Hudson, 1981). In mathematical
terms, soil erosion is a function of the erosivity of the rain and the erodibility of the soil, or

Erosion = f(Erosivity)(Erodibility).
This relationship is expressed by the Universal Soil Loss Equation (USLE), developed by

Wischmeir and Smith (1965) and widely accepted as a predictive equation to estimate the
mean annual soil erosion. In its basic form, USLE is:

A = EK. (1)
where A = mean annual soil loss (t ha! yr’),
E = erosivity, and

K = erodibility.

Erosivity can be defined as the potential ability of the rain to cause erosion. For given soil
conditions, one storm can be compared quantitatively with another based on a numerical scale
of values of erosivity. Erodibility is defined as the vulnerability of the soil to erosion and,
for given rainfall conditions, one soil condition can be compared quantitatively with another,
based on a numerical scale of values of erodibility.

Erodibility has three components: first the fundamental or inherent characteristics of the soil,
such as texture, structure and organic matter content, which can be measured in the
laboratory; secondly, topographic features, especially the slope of the land; and thirdly, the
way in which the soil is treated or managed. In the present study, the third factor is assumed
to be a constant because the only type of land use under consideration is natural forest. Thus,
the following equation is used to predict soil loss from natural forest:

As ELKS. (2)

where S = slope factor.
Estimating rainfall erosivity

Rainfall erosivity is a function of the size and velocity of the rain drops. It can be predicted
from its proven relationship with rainstorm intensity (Wischmeier and Smith, 1958; Hudson,
1981; Lal, 1976; Morgan et al., 1982). But rainfall intensity data are not available in many
countries, including Sri Lanka, due to a lack of recording rain gauge stations’. This problem

ea recording rain gauge automatically records the amount of rainfall with time.

41

can be overcome by developing models to predict rainfall erosivity from meteorological
parameters, such as total annual rainfall and the Fournier Index, which are commonly
available from non-recording rain gauge stations (Arnoldus, 1980).

A similar approach has been used in Sri Lanka (Premalal, 1986). Ten meteorological stations
with recording rain gauges were selected to sample the mid- and up-country zone (i.e. above
300 m) and 12 for the low-country zone (i.e. below 300 m). An erosivity index was
calculated using the procedure described by Hudson (1981). A regression equation was
derived for the mid- and up-country to predict erosivity from mean annual rainfall, modified
Fournier Index and altitude. For the low-country, it was found that mean annual rainfall
alone is strongly correlated with erosivity.

However, these two equations for the mid/up-country and low-country zones can only be
used to estimate erosivity for a given forest if it has a single value for altitude and lies within
one zone. Consequently, the original data for mid-, up- and low-country were pooled and a
multiple step-wise regression performed on erosivity with a variety of independent variables,
including mean annual rainfall, modified Fournier Index and altitude. This showed that mean
annual rainfall alone accounts for about 75% of the variation. The resultant regression
equation is given below:

E = 972.75 + 9.95 MAR, (R* = 0.75) (3)

where E = Erosivity (J m? Yr’), and
MAR = Mean annual rainfall (mm).

Two hundred and twenty station-years of rainfall data were used to derive the above
equation. This is a considered to be an adequate sample size, being very much larger than
the 11 station-years of data used to derive a similar erosivity index for Peninsular Malaysia
(Morgan, 1980). It should be emphasized that the above Equation (3) is valid only for Sri
Lanka.

An estimate of mean annual rainfall is a prerequisite to calculating erosivity for a given forest
using Equation (3). The isohyetal method (Linsley er al., 1982) was used to estimate mean
annual rainfall (Section 3.8.1) in preference to Theissen’s polygon method of weighting,
which is not suitable, particularly in the case of smaller forests.

Estimating soil erodibility

The erodibility of the major soil types in Sri Lanka is given by Joshuwa (1977). Erodibility
values are obtained from the soil map which is superimposed on the forest map in order to
assign the respective erodibility value to each forest. This is necessarily crude because more
detailed soil maps are not available.

The alternative of surveying soils within individual forests to obtain a more detailed
information on soil type was not warranted in view of the time involved in obtaining
adequate sample sizes. Furthermore, since there is only a twofold difference between the
highest and lowest erodibility values of the major soils in Sri Lanka, more precise estimates
would not make a significant difference to the overall assessment of the hydrological value
of forests.

42

Determining slope factor

The mean slope is determined using the procedure described by Fleming (1975). Each forest
is located on the 1:63,360 series of topographic maps and overlaid by a grid, effectively
dividing it into smaller units. The perpendicular distance is measured from the contour at
each grid point to the nearest stream (or paddy field when there is no stream in the vicinity).
This value is divided by the altitudinal difference to derive the slope from which an
arithmetic mean is obtained. The procedure, described in Section 3.8.1, is modified in the
case of dry zone forests where stream density is lower due to the reduced rainfall and to the
terrain being less steep. In such cases, slope is estimated by dividing the difference in altitude
between two points by the distance for a range of different aspects and calculating a mean
value.

The slope factor in Equation (2) has a value of 1.0 when the slope is 9%. Soil erosion
increases exponentially with the slope. It has been widely accepted that in the tropics the
exponential term for the slope is equal to 2 (Hudson, 1981). Thus, the slope factor in the
USLE should be substituted by mean slope as follows:

S = (s/9) (4)

where S slope factor, and
Ss = mean percentage slope.

3.2.2 Ranking forests for soil erosion

Substitution of the erosivity, erodibility and slope factor into Equation (2) enables the mean
annual soil loss to be estimated for a given forest under standard conditions, which are as
follows:

e slope length is 22.6 m,
- @ jand use is bare cultivated fallow, and
e land is ploughed up and down the slope.

In other words, the value of the mean annual soil loss represents the worst-case scenario
when the forest is removed and the land is badly managed. These erosion values can be
reduced substantially by introducing conservation practices and covering the bare soil with
vegetation. Forests with very high soil erosion rates are those most important for soil
conservation; they rank high in priority for protection measures.

3.3 HEADWATERS PROTECTION

Policy within the Sri Lanka’s Commission on Land Use demands that

e stream sources and headwaters of river systems,
e water divides, and
e stream reservations and riparian land

be protected for soil and water conservation purposes.
The importance of a forest for protecting stream sources is evaluated by counting the number
of streamlets originating from within a forest using the 1:63,360 topographic series of maps.

A second criterion used is the number of major river catchments protected by the forest,

43

based on the standard system of river catchments defined by the Irrigation Department
(Navaratne, 1985). Assessing the importance of a forest in terms of its proximity to the
headwaters of a river and for protecting stream reservations and riparian land is based on the
distance from the forest to the outlet of the river. Distance was selected as the criterion
because water originating from a given forest will sustain flora and fauna throughout its
course to the sea. It is measured from the headwaters stream closest to the centre of the
forest, along its course to the outlet, using the 1:63,360 maps.

In summary, the assessment is based on:

e the number of streamlets originating from the forest,
the number of river catchments protected by the forest, and

e the distance (km) from the headwaters stream nearest the centre of the forest to the
outlet.

3.4 FLOOD HAZARD

In the absence of flow records for a forest, a preliminary estimate of the mean annual flood
or other flood statistics may be obtained from the relationship between floods and catchment
characteristics using maps (NERC, 1975). However, this indirect method is generally less
reliable than any direct analysis of flood statistics. Research in the UK has provided a set of
equations relating mean annual flood to catchment area alone, with provision for regional
variations. Other investigations have taken into account climate and slope (NERC, 1975).

The use of multiple regression techniques to study the relationship between mean annual
flood and its coefficient of variation and catchment characteristics is widely accepted. One
reason why such techniques have been so useful in assessing flood hazard is the strong
relationship between mean annual flood and other variables, such as slope and channel
network (i.e. number of streams per unit area), which can be estimated easily from
topographic maps.

3.4.1 Estimating flood hazard from catchment characteristics

In the absence of any previous research on estimating flood hazard from catchment
characteristics for Sri Lankan conditions, a mode! developed in the UK has been adopted for
the present study. This is justified because the behaviour of most of the variables concerned
with the flooding component of the hydrological cycle appear to be the same. Details of the
analysis and the flood prediction equations are given in a Flood Studies Report
(NERC, 1975).

In the UK study, catchment characteristics were obtained from 1:63360 and 1:25000
topographic maps. Climatic variables were also used. Of these variables, only those which
can be measured or estimated accurately were selected for this study, namely mean annual
rainfall, catchment area (or forest area for the purposes of this study) and stream frequency.
These three variables account for 86% of the variation of mean annual flood.

Most of the rainfall stations in Sri Lanka have more than 30 years of rainfall data from which
mean annual rainfall can be calculated. Area can be measured using a planimeter. Stream
frequency is measured by counting the number of channel junctions within a forest, using the
1:63,360 topographic series, and dividing by its area. A stream without any junctions is

44

given a value of one, as if it had a single junction. It is best to work progressively up along
each tributary; the running total is noted at each major junction. This value is then divided
by the area and presented as stream junctions km? (adapted from NERC, 1975).

Stream frequency was selected in preference to drainage density, which cannot be reliably
sampled by grid or other methods (NERC, 1975). It is simpler to measure and it is strongly
correlated with drainage density (Melton, 1958). Moreover, 1:63,360 maps are sufficiently
detailed for measuring stream frequency. In the UK study, there was a very high correlation
(0.89) between stream frequency measurements from 1:63,360 and 1:25,000 maps for 55
catchments.

The predictive equation for mean annual flood is given below:
BESMAF = 4.53*10° AREA®™ STMFRQ°*! SAAR!** — (5)

where BESMAF = mean annual flood (m? s°),

AREA = area (km’),
STMFRQ = stream frequency (stream junctions km”), and
SAAR = mean annual rainfall (mm)

It should be noted that the values estimated from the equation will not provide absolute
values of mean annual flood since the regression equation was derived from a different set
of data. However, the values indicate the flood response of each forest and should be used
for ranking purposes only.

3.5 FOG INTERCEPTION AT HIGHER ALTITUDES

Altitude has been identified as a criterion for identifying forests for conservation in the past
mainly because the headwaters of major rivers originate from higher elevations. However,
the importance of forests for protecting stream sources and headwaters of river systems is
assessed using measures other than altitude, as described in earlier in this chapter (3.3).

Recent research has shown that altitude has a direct effect on the hydrological cycle through
the contribution of additional moisture from cloud forests (Juvik and Ekern, 1978;
Gunawardena, 1991; Mowjood and Gunawardena 1992). Since a given forest may extend
over a range of altitudes, altitude needs to be adjusted accordingly, using a procedure similar
to the isohyetal method (Linsley et al., 1982). Calculation of the mean altitude enables the
percentage of additional moisture contributed through fog interception to be calculated using
the following equation, which was derived from experimental studies conducted in Hawaii:

Y = -38.5 + 0.04 X (6)
where Y = additional percentage moisture contributed by fog, and
X = altitude (m).

Mean annual rainfall for a given forest is multiplied by Y (Equation 6) to estimate the annual
fog contribution (mm). This is converted to a volumetric value by multiplying by the area
of the forest. Since fog interception increases with altitude, Y should be calculated at 500 ft
(167 m) intervals and multiplied by the respective area. The equation is valid for forests
above 1,500 m, there being no significant fog interception at lower altitudes.

45

Application of this equation, derived from fog studies in Hawaii, to conditions in Sri Lanka
is justified elsewhere (Gunawardena, 1991). As described in the next section, similar studies
are underway in Sri Lanka. Once completed, these will enable the coefficients in
Equation (6) to be modified.

3.5.1 Field experiments in Sri Lanka

A field study to determine the significance of fog interception to the hydrology of catchment
systems was begun at Horton Plains in 1993. An automatic weather station with a fog
collector was installed at the top of a 20 m high tower, which stands 5 m above the forest
canopy. The net rainfall beneath the forest canopy is also measured. A detailed description
of the experiment is given elsewhere (Bastable and Gunawardena, 1994).

Preliminary results, based on two years of data, show that interception of horizontally driven
fog by the forest canopy may account for over 50% increase in net rainfall for certain
months, usually during the south-west monsoon (Figure 3.1). On average, such horizontal
interception of fog accounts for 3.6% of annual rainfall (Gunawardena, 1996). Assuming that
the vertical interception of fog is about 30% of annual rainfall, which is a reasonable value
for tropical forest, the total contribution from fog to the hydrological cycle is about 33.6%
of annual rainfall.

|
#
s
&
~
7)
a
=|
o
a
Ba
2
3}
J
BR

Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
month

441993 & <= Ss 1914 SSeS

Figure 3.1 Increase in net rainfall from fog interception at Horton Plains between November
1993 and October 1995

It will be necessary to obtain several years of data from additional locations in order to
determine the coefficients of Equation (6). Meanwhile, these preliminary results suggest that
the value of Y (moisture contributed by fog) in Equation (6) is somewhat inflated. Such an
overestimate does not directly affect the results of the present study because they are based
on ranks rather than absolute values of the fog contribution.

46

3.6 EVALUATION

The following evaluation is applied to all natural forests except those which have already
been designated for strict protection by the government because they lie in the immediate
catchment of hydroelectric and water supply reservoirs.

3.6.1 Preliminary ranking

Forests are ranked according to four main criteria as a measure of their importance for soil
and water conservation. The four criteria are: i

i soil erosion,
il importance as headwaters of rivers,
ill flood hazard, and
iv additional moisture from fog interception.

Soil erosion is measured for each forest as mean annual soil loss (t ha! yr') using Equation
(1) which treats erosivity, erodibility and slope as independent variables.

The importance of a forest for protecting headwaters of rivers is measured in terms of a)
the number of streamlets originating from the forest, b) the number of river catchment areas
protected by the forest, and c) the length along the river from the centre of the forest to the
river outlet. Each forest is ranked in descending order for criterion a, b, and c, separately.
The values of the three columns of ranks are added horizontally, and the lowest value is
assigned the highest rank. If two values are equal, priority is given in the following
order: a), b), c).

Mean annual flood, which is used as an index of flood hazard, is estimated for each forest
by substituting mean annual rainfall, area and stream frequency in the predictive
Equation (5).

Fog interception is measured as the additional moisture (mm yr’) contributed by a forest
(above 1,500 m).

3.6.2 Final ranking

The four main criteria (Section 3.6.1) are classified into two groups, namely:

e soil conservation importance (criterion i), and
e hydrological importance (criteria 11, 111, and iv).

Importance for soil conservation is based on ranking soil erosion (criterion i). Hydrological
importance is based on ranking the summation of the rank values of criteria ii, iii, and iv.
The lowest value is ranked highest. If there are two equal values, priority is given in the
following order: criteria ii, iii, iv. Ranks for soil conservation and hydrological importance
are added and their values ranked,the lowest value being ranked highest. If two values are
equal, priority is given to soil conservation.

3.6.3 Selection of forests for soil and water conservation

In order to prioritise forests for soil and water conservation, threshold values of 300 t ha!
yr! for soil erosion and 10 m? s? for mean annual flood were identified on the basis of a

47

preliminary analysis of results for the wet zone (Green and Gunawardena, 1993). Forests
with values exceeding both these thresholds are considered to be of highest importance for
conservation; those with values exceeding one or other threshold are considered important
to conserve; and those with values below both thresholds are ranked as lowest importance.

In addition, any forest above 1,500 m was automatically considered to be a top priority for
conservation because of its significant contribution to fog interception.

The importance of a forest for protecting headwaters of rivers was not used in this final
selection procedure because it was derived from a series of ranking procedures, rather than
being based on absolute values as for erosion and flood control, and fog interception.

3.7 CONSTRAINTS

The methodology developed for this study is adequate for a rapid assessment of the
importance of forests for soil conservation and hydrology. Although some field checking was
carried out to validate the results, subjectively interpreting them as necessary, more detailed,
quantitative studies of soil and hydrological conditions in Sri Lanka are required in order to
refine the methodology. Plans are underway to examine soil erosion and hydrology in the
upper catchment areas of the country using a GIS. Once the relevant data have been
digitised, they can be used to improve on the estimates derived from the present study.

Given that the headwaters of all major rivers in Sri Lanka lie in the wet and intermediate
zones (Figure 2.2), not surprisingly none of the forests in the dry zone is shown to be
important for soil or water conservation using the methodology developed for this study. The
major hydrological role of forests in the dry zone concerns the recharge of the ground water
reservoir during the north-east monsoon. Unfortunately, however, there has been very little
study of the significance of this role of forests. Thus, caution must be exercised in evaluating
dry zone forests until such time as this role can be measured quantitatively.

3.7.1 Soil erosion

Estimates of soil erosion potential are influenced principally by values for rainfall and slope,
the erodibilty value having little effect. The most sensitive variable in determining soil
erosion is slope because the slope factor increases exponentially with slope. Forests with rock
outcrops and lower stream density tend to have higher values of slope. Thus, any inaccuracy
in estimating slope will result in exaggerated soil erosion values.

Although not available for this study, GIS software can be used to measure slope much more
accurately, resulting in more reliable estimates of soil erosion.

3.7.2 Headwaters protection

Importance for headwaters protection is based on summing the rank orders of forests for their
number of streams, distance to river outlet and the number of catchments they encompass.
Whereas there are several hundred rank values for the first two criteria, there are only five
values for the number of catchments. Thus, catchment number has very little influence on
the final rank.

48

3.7.3, Flood hazard
Determination of flood hazard is based on the assumption that the entire catchment area
above the point at which mean annual flood is estimated is forested. This may not always be
the case.
3.8 WORKED EXAMPLE
This section provides a worked example for nine forests selected from Galle and Matara
districts. It is based on preliminary data obtained at the outset of the NCR (Green and
Gunawardena, 1993).
3.8.1 Soil erosion
Estimating rainfall erosivity
Rainfall erosivity is estimated from the following equation:

E = 972.75 + 9.95 MAR, (R* = 0.75) (1)

’ where E = Erosivity (J m® Yr’), and
MAR = Mean annual rainfall (mm).

The isohyetal method is used to estimate mean annual rainfall. This is illustrated in
Figure 3.2 for Dellawa using mean annual rainfall data from nearby rain gauge stations
(Table 3.1).

Table 3.1 Data from rain gauge stations in the vicinity of Dellawa

Rain gauge station Mean annua

Rainfall (mm)

49

Data for each station are plotted on a 1:63,360 map, enabling contours of equal rainfall
(isohyets) to be drawn. Mean annual rainfall is estimated for each area between adjacent
isohyets, weighted by its percentage area. Summation of the mean values for each area
provides an estimate of mean annual area for the entire forest, as follows:

A (Ra + Rg)/2 + B (Rg + Ro)/2 + C (Ro + Rp) + -..

MAR = (2)
100

where MAR = Mean annual rainfall,
R,, Rg, Re, and Rp are the rainfall isohyets, and
A, B, and C are the areas enclosed within isohyets R, - Rg, Rg - Rc, and Re - Rp, respectively.

Substituting values from Figure 3.2, the mean annual rainfall for Dellawa is calculated as
follows:

3.1(4050) + 14.2(3950) + 20.8(3850) + 23.5(3750) + 34.8(3650) + 3.4(3550)
MAR =

100
MAR = 3759 mm

The value for mean annual rainfall is substituted in Equation (1) in order to calculate an
erosivity value for Dellawa as follows:

E = 972.75 + (9.95 x 3759)
E = 38375 J ma yr)

Figure 3.2 Mean annual rainfall isohyets for Dellawa

The erosivity index (383.75) is obtained by dividing the erosivity value by 100. It indicates
the ability of the rainfall to cause soil erosion. Mean annual rainfall and the respective
erosivity values are given in Table 3.2 for each forest.

50

Table 3.2 Mean annual rainfall and erosivity index for selected forests in Galle and Matara districts

rainfall (mm)
1. Beraliya (Akuressa)
2, Dellawa
c
4, Kalubowitivana
| 3
6, Kekanadure

7. Masmullakele 2076 216.29
8. Oliyagankele 2465 254.99
9. Rammalakanda 2837 292.01

Estimating soil erodibility

The major soil type(s) within a forest can be determined by superimposing the forest
boundary onto the soil map (published by the Survey Department of Sri Lanka). Erodibility
values of the major soil types are given by Joshuwa (1977). If there is more than one type
within a forest, the erodibility value should be weighted according to the area covered by the
different soils.

All forests selected in this example have red yellow podzolic soils, for which the erodibility
value is 0.22.

Determining slope factor

Forest boundaries are marked onto 1:63,360 maps and a 10 mm x 10 mm grid drawn over
each forest, as shown in Figure 3.3 for Dellawa. The perpendicular distance is measured
from the contour at each grid point to the nearest stream. This distance is divided by the
altitudinal difference between the contours at the grid point and the stream in order to
calculate the slope. Slope values are summed and divided by the number of grids in order
to obtain a mean value.

The slope at each grid point is given in Table 3.3 for Dellawa. Summation of the slopes
(14.38) and division by the total number of grid points (52) gives a mean value of 0.28, or
28%. The slope factor is calculated as follows:

S = (s/9)?
S = (28/9)
S = 9.68
where S = slope factor, and

Ss = mean percentage slope.

Mean slope and the slope factor are given for each forest in Table 3.4.

51

SE PR
ae = Sie

Figure 3.3 Overlaying a 10x10 mm grid onto a contour map to estimate mean slope in
Dellawa

Table 3.3 Slopes at grid points in Dellawa

BESS ea ee eee
fe oe oi A | | ee
BR eee ee eee
ll a ies ie a ee a
Page oh Thnellc [soll theese a ae
ee ee | ee
ere lee ae ee eee
Ee ee Se

ee

i a al ae
ee eee
js | P| | | ose} oer] ona] orol or] oss] o.se] 0.20
fr al ol EE ko.
Ee Lo Ee eee

52

Table 3.4 Mean slope and slope factor for selected forests in Galle and Matara districts

|

Calculating soil erosion

The mean annual soil loss is calculated by substitution of the values of the erosivity index,
erodibility, and slope factor into Equation (4).

A =E.K:S. (4)
A = mean annual soil loss (t ha’ yr’),

E = erosivity index,

K = erodibility, and

S = slope factor.

where

Substituting the respective values for Dellawa forest,
A = 383.75 x 0.22 x 9.68
eS eae vite

Values of the erosivity index, erodibility, slope factor and erosion hazard are given in
Table 3.5 for each forest. These results show that Kalubowitiyana has the highest erosion
hazard. This forest has the highest erosivity index as well as the highest slope factor, making
it most prone to erosion.

Table 3.5 Erosion for selected forests in Galle and Matara districts, together with values of erosivity

index, erodibility and slope factor

9 Ramat 292.01

53

3.8.2 Headwaters protection
Streamlets originating from a forest

The number of streamlets originating from a forest is counted, using the 1:63,360 series of
maps. The value for Dellawa is 77.

Number of river catchments protected by a forest

Streamlets originating from a forest are traced to major rivers, identified as such by the
Irrigation Department (see Chapter 3.3). The number of major rivers into which flow the
streamlets of a forest is counted. Dellawa contributes water to two major rivers, namely
Nilwala and Gin Ganga.

Distance from headwaters of centralmost stream to its outlet

The stream closest to the centre of a forest is selected and the distance measured from its
headwaters to its mouth, using a thread laid along its course. If there are two river
catchments, the values of the respective distances are summed. Values for Dellawa are as
follows:

Distance along Nilwala River = 58
Distance along Ginganga = 87
Total distance = 145 km

The number of streamlets and river catchments, and the total distance between headwaters
and outlets are given in Table 3.6 for each forest.

Table 3.6 Distance of stream headwaters from river mouths for selected forests in Galle and Matara
districts, together with the number of streamlets and major rivers

Forest Streams | Major Headwaters distance (km)*
Rivers

1 Beraiya(akuresy | 37 | 2 | oa | | oo || | ow |
Pe EaiG |
3. Diyadawa 4 58

3
5)

43

“Nil = Nilwala; Gin = Ginganga; Pol = Polwatta Ganga; Kir = Kirama Oya

54

3.8.3 Flood hazard

Mean annual flood for a given forest is used as an index of its response to floods, and hence
provides a measure of its role in reducing flood hazard. It is estimated using the following
predictive equation:

BESMAF = 4.53*10° AREA®?* STMFRQ°*! SAAR!34 (5)
where BESMAF = Mean annual flood (m? s°),

AREA = Area (km’),
STMFRQ = Steam frequency (stream junctions km”), and
SAAR = Mean annual rainfall (mm)

Area

This information is available for most forests that have been notified as forest reserves under
the Forest Ordinance or as national reserves and sanctuaries under the Fauna and Flora
Protection Ordinance. It is also available for proposed reserves. For other state forests, for
which such information may not be available, the area is measured directly from 1:63,360
maps using a planimeter. The area of Dellawa is 22.36 km’.

Stream frequency

Using 1:63360 maps on which forest boundaries have been marked, the number of stream
junctions within each boundary is counted. Streams without any tributaries are considered as
one junction. The total number of stream junctions within the 22.36 km’ Dellawa is 65.
Thus, its stream frequency is:

STRFRQ = 65/22.36
STRFRQ = 2.9

Mean annual rainfall

Determination of mean annual rainfall is described in Section 3.1.1. The mean annual rainfall
(SAAR) for Dellawa is 3759 mm.

Calculating flood hazard
Substituting values of area, stream frequency and mean annual rainfall into Equation (5), the

mean annual flood for Dellawa is:

BESMAR =4.53*107 22.37° 9 2199753759"
BESMAF = 65.47 (m’ s")

If a forest does not have a stream originating from it, the mean annual flood is considered
to be equal to zero. The values of area, stream frequency, mean annual rainfall and mean
annual flood are given in Table 3.7.

55

Table 3.7 Flood hazard for selected forests in Galle and Matara districts, together with values of
area, stream frequency and mean annual rainfall

t ha'yr'

km?
1. Beraliya (Akuressa) 16.46 2671
3. Diyadawa 24.48 3410 57.72

Mean Annual Rainfall

10.23

26.55

3.8.4 Fog interception

Assessment of fog interception applies only to forests above 1,500 m. All forests selected
from Matara and Galle districts for purposes of this worked example lie below this altitude.
Hence, the additional moisture contributed by fog interception is zero.

For illustrative purposes, the procedure for estimating fog interception for a selected forest,
Hakgala, is given below using Equation (6).
Y = -38.5 + 0.04 K (6)

where Y = additional percentage moisture contributed by fog, and
X = altitude (m).

The value of Y is multiplied by the mean annual rainfall to estimate the additional moisture
contributed by fog in mm per annum. The volume is estimated by multiplying the depth of
the additional moisture by the area of the forest. The procedure for estimating total fog
interception for Hakgala is given below.

An estimated 26.6 ha of Hakgala forest lies within an altitudinal range of 5,000-5,500 ft
(1,667-1,833 m). The mean altitude is 5,250 ft or 1,750 m. Substituting this mean altitude
in Equation (6),

Y = -38.5 + (0.4 x 1750)
Y = 31.5%

The mean annual rainfall for Hakgala is 2176 mm. Thus,

depth of fog interception = 2176 x 31.5/100
depth of fog interception = 685.4 mm per annum

and volume of fog interception = 685.4*10° x 26.6*10* per annum.

The total volume of fog intercepted by the entire forest of Hakgala is shown in Table 3.8.

56

Table 3.8 Annual volume of fog intercepted by Hakgala forest

(m) (m) (ha) (m**1000)
1, 883-2,000 sealiateial aaa L882.
20002167 7145.9
21612,38 1716.3
2,3332,500 a3
a aT ETT

3.8.5 Evaluation
Preliminary ranking

Forests are ranked according to a single criterion, soil erosion, as a measure of their
importance for soil conservation, and according to three criteria for assessing their water
conservation value, namely importance as headwaters of rivers, flood hazard and additional
moisture contributed by fog interception.

The importance of a forest for protecting headwaters of rivers is assessed in terms of three
sub-criteria: the number of streamlets originating from it, the number of river catchments
protected by it, and the distance from the headwaters to the river mouth. Each of these sub-
criteria is ranked separately and the values of the three columns of ranks are added
horizontally to derive an overall headwaters value which is then ranked. If values are equal,
priority is given in the order: streams, major rivers and distance. The results of this ranking
procedure are given in Table 3.9.

Table 3.9 Selected forests in Matara and Galle districts ranked for their importance as headwaters

catchments
Streams Major Distance Headwaters Headwaters
Rank Rivers rank total rank
rank

[i Beata cAtuessd) | 4 | ot | os |. w | os |
i ie ae as es
Breed | ee
faxawniis [3 [os [os Ts [oa
ee ae a | a a
ee a a
2 ae ee ee ee
[aes OT ee a ae ee
(a | |

Nn

Dy

Hydrological importance is determined by adding the rank values of headwaters importance,
flood hazard and fog interception and assigning the highest rank for the lowest total. If two
or more values of the total are equal, priority is given to the value of the headwaters rank.
The results of this ranking procedure are given in Table 3.10. It should be noted that rank
values of forests for headwaters importance and flood hazard are very similar (see
Section 3.8.3).

Table 3.10 Selected forests in Matara and Galle districts ranked for their hydrological importance

Se i De
Ste a
Doe Ue ee |
banner b= Sie [RSE le | otal

Danes ee eee | 2
cae woe Lae
hides Fils |freeiatpel| x soo) om oi eel
i ike
ere et ee eee

Final ranking

The rank values of erosion and hydrology are summed for each forest and the total ranked
to obtain an overall ranking for soil and water conservation. If two or more totals are equal,
priority is given to erosion hazard. The results of the final ranking are given in Table 3.11.

Table 3.11 Final ranking of selected forests in Galle and Matara districts for their importance in
soil and water conservation

Erosion rank Hydrology Erosion + hydrology
rank

eee a ee a

3. Diyadawa

4. Kalubowitiyana

5. Kanumuldeniya

6. Kekanadur tie is 7)

9. Rammalakanda

58

This worked example shows that Diyadawa is overall the most important of the selected
forests for its role in conserving soil and maintaining the hydrological regime. Dellawa is
hydrologically the most important forest, mainly due to its dense stream network.
Kalubowitiyana ranks highest for soil conservation alone, a reflection of its high rainfall and
steep terrain, but it is relatively less important for hydrology due to its small size. The
extremely high erosion value, more than double that of any other forest (Table 3.5), was
checked in the field and seen to be high, as evidenced by a recent landslide.

Selection of forests for soil and water conservation

Forests are prioritised according to their importance for soil and water conservation in
Table 3.12, based on absolute measures of soil erosion and mean annual flood, respectively.
The importance of forests for protecting the headwaters of rivers is not used in this final
selection procedure because it closely mirrors mean annual flood (Table 3.10). In addition,
any forest above 1,500 m is automatically considered to be a top priority for conservation
because of its significant contribution to the hydrological cycle through fog interception. In
the case of this particular example, none of the forests lies above 1,500 m.

Table 3.12 Importance of selected forests in Matara and Galle districts for soil and water
conservation

j HIGHEST IMPORTANCE IMPORTANT FOR CONSERVATION LOWEST IMPORTANCE
FOR CONSERVATION FOR CONSERVATION
Soil erosion >300 tha! yr’ Soil erosion >300 t ha yr! Mean annual flood >10 m? s' Soil erosion <300 t ha! yr’!
Mean annual flood >10 m? s" - Mean annual flood <10 ms!
Beriliya (Akuressa) Kanumuldeniya
Otiyagankele

59

Chapter 4
METHODS - BIODIVERSITY ASSESSMENT
PLE PSH TMT SERIA Tir IESE FREE ROE Te

4.1 INTRODUCTION

Biodiversity surveys are necessary for rational land use planning and decision-making, and
they are required to resolve land use conflicts. Much of the conflict between logging and
forest conservation, for example, is concerned with which species and how many are present
in a particular area. If that information is present the issue can be simplified. The conflict
remains but it can be resolved on the basis of facts, not guesses or unsound extrapolations.
Very often, however, the information is not available and the first step towards resolving the
conflict is to conduct a biodiversity survey to determine what species are present, where they
are and how many. This is the prevailing situation in Sri Lanka, as already outlined in
Section 2.2.2.

Financial resources for surveying biota are diminishing relative to planning needs, hence it
is essential that surveys are cost-effective (Burbidge, 1991). To help ensure that costs are
kept to a minimum, only relevant data should be collected and they should be available for
re-use as required.

It is necessary, therefore, to develop a method of surveying biodiversity that is both
comprehensive and cost-effective (i.e. rapid) in order to meet one of the objectives of the
NCR component of the Environmental Management in Forestry Development Project,
namely:

to assess the conservation value of Sri Lanka’s remaining natural forests, including
mangroves.

This will enable decisions concerning future uses of these natural resources to be based on
sound, scientific principles.

4.1.1 Survey design

The most widely used scientific criteria for assessing conservation value are diversity, rarity,
naturalness, size and representativeness (Margules and Usher, 1981; Usher, 1986; Margules
et al., 1988). Indeed, these criteria are used to identify natural properties under the World
Heritage Convention. All refer, either wholly or in part, to a common underlying theme: the
maintenance of biodiversity in perpetuity.

Conservation planning in the past has usually be focused on ensuring adequate representation
of communities or habitats, but many species cannot necessarily be perpetuated by the
reservation of communities because of their dependence on disturbance, their ranging
behaviour or their occurrence in community interfaces. Thus, the best conservation planning
should encompass both species and communities, with priority, if any, being given to species
(Kirkpatrick and Brown, 1991). In practice, the number of species has become the simplest
and most commonly used measure of biodiversity (Bond, 1989).

60

Hunter et al. (1988) consider, however, that the selection of protected areas should be more
strongly influenced by the distribution of physical environments than by that of communities,
which are transitory assemblages or co-occurrences among taxa that have changed in
distribution, abundance and association in response to past climatic changes. Ideally,
protected areas should encompass a sufficiently broad range of physical environments to
allow organisms to adjust their local distribution in response to long-term environmental
changes. Given that landscapes also change, albeit over a longer time span, protected areas
should be connected by corridors to allow species to modify their geographic distribution.

There is also a growing awareness that conservation planning must also take into account the
human dimension, given that most biodiversity is lost directly as a result of human activities.
Thus, it is important for socio-economic and political factors to be considered in the design
of protected area systems (Forester et al., 1996).

Four complimentary approaches were adopted for the NCR. First, species’ distribution
patterns were used to define a national network of conservation forests in which species
diversity is fully represented. Secondly, to avoid any gross oversights in planning at the
ecosystem level, forest types and floristic regions were examined to ensure that they were
well represented within the optimum set of conservation forests identified from species’
distribution patterns. Thirdly, in the interests of the long-term preservation of Sri Lanka’s
biodiversity, particularly with respect to changes in global climate anticipated over the next
century, edaphic (soil) zones were examined to ensure that the full range of the island’s
physical environments were represented within the optimum set of conservation forests. In
practice, it was necessary to combine the floristic and edaphic analyses due to current
limitations with the available classifications. Finally, potential threat from human
development pressures was considered by assessing the wilderness value of forests and
maximising the protection of relatively undisturbed forests.

4.1.2 Gradsect sampling

In order to define a national network of conservation forests in which species diversity is
fully represented, it is necessary first to determine the distributions of species, and then to
identify an optimum set of forests which encompasses all species through some form of
pattern analysis. Surveys intended to provide data for defining a representative protected
forests network require a procedure which ensures that the full range of biodiversity is
sampled. Such surveys are concerned with gathering information about species’ distribution
patterns, rather than obtaining unbiased estimates of the abundance of individual species
using standard, statistical, sampling techniques. Stratification is essential but practical
problems of travel costs and accessibility must be incorporated into any cost-effective survey.

Gradient-directed transect (gradsect) sampling is the deliberate selection of transects which
contain the steepest environmental gradients with maximum access present in an area (Austin
and Heyligers, 1991). It was selected for the NCR as being the most appropriate technique
for rapidly assessing species diversity within natural forests.

Gradsect sampling is designed to provide a description of the full range of biodiversity within
a region, overcoming problems of inadequate representative sampling and accessibility, while
minimising survey costs. Gradsects are deliberately selected to contain the strongest
environmental gradients within a region to optimise the amount of information gained relative
to expenditure of time and effort. Sampling along a gradsect maximises variation between

61

plots, and accessibility can be enhanced by choosing localities with an adequate road network
to reduce travel time. It has been shown statistically that gradsects capture more information
than randomly placed transects of similar length (Gillison and Brewer, 1985; Austin and
Heyligers, 1989).

4.1.3 Conservation evaluation

Historically, the selection of protected areas has tended to be ad hoc, often depending on the
availability of land unsuitable for other forms of land use and influenced strongly by
perceived threat (Leader-Williams et al., 1990). This is unsatisfactory because it results in
a bias of the range of species protected.

A widely-used, more systematic alternative is to rank candidate sites according to various
criteria of conservation value, such as diversity, rarity, naturalness, size and
representativeness as mentioned above. Combining ranks for different criteria to derive an
index of conservation value, however, inevitably involves weighting of the criteria according
to a subjective assessment of their relative importance (Margules, 1989). Moreover, a major
draw back in ranking sites for their conservation value on the basis of a single application
of a formula is that sites of lower conservation priority may duplicate species represented in
sites of higher conservation priority (Kirkpatrick, 1983). Other problems associated with
combining ranks to derive a conservation value index are reviewed by Margules et al.
(1991). ;

An alternative approach is to use patterns of species’ distributions to identify a set of sites
which encompasses all species (Margules et al., 1988, 1991). This minimum set of sites in
which all species (or other units of diversity) are represented at least once is the bottom line:
the bare minimum. Anything less would constitute an inadequate representation of
biodiversity.

Algorithms can be employed to identify minimum networks of sites in which biodiversity is
adequately represented. Two approaches are commonly used, both of which use
complementarity as a criterion for site selection. The greedy or richness heuristic algorithm
identifies sites which contribute most new species to the network, beginning with the most
species rich site. The other, rarity algorithm is slightly more efficient in terms of minimising
the number of sites necessary for all species to be represented. The site with the rarest
species is selected first; thereafter the site with the next rarest species and greatest
complement of species to the network is selected (Csuti and Kiester, 1996). Such algorithms
can be constrained in various ways: for example, to ensure that each species is represented
in at least two sites. The large area of land required to represent biodiversity, even when the
number of sites is minimised, makes it unlikely that all, or even most, species will be
represented in a protected areas network. However, the minimum set approach identifies
explicitly which sites are needed to maximise biodiversity and, therefore. which species will
not be represented in a proposed system that does not include all of those sites
(Margules, 1989).

62

4.2 CRITERIA USED TO IDENTIFY FORESTS

Natural forests were identified from the New 1:500,000 Scale Forest Map of Sri Lanka (Legg
and Jewell, 1992)'°. However, as this map was not available at the beginning of the NCR.
forests in Galle, Matara and Hambantota districts were identified from the 1:100,000 Land
Use series. Forests were selected for inclusion in the NCR on the basis of the following
criteria:

e any legally designated reserve'’ containing closed canopy natural forest, as defined
in the New 1:500,000 Scale Forest Map of Sri Lanka, irrespective of its size; and

¢ any proposed reserve or other state forest with at least 200 ha!’ of closed canopy
natural forest, or any other smaller forest known to be of particular biological
importance.

The 30 forests previously surveyed under the Accelerated Conservation Review (TEAMS,
1991) were also included to ensure that a consistent, systematic approach was applied to all
forests.

The distribution of natural, closed canopy forest, based on the new 1:50,000-scale forest map
(Legg and Jewell, 1995), is shown previously at a greatly reduced scale in Figure 2.1
(Section 2.2.1). For purposes of the NCR, the wet zone is delimited by the 2500 mm isohyet
and includes montane forest, sub-montane forest and lowland rain forest. The boundary
between the intermediate and dry zones is defined by the 1800 mm isohyet.

4.3 INVENTORYING SPECIES DIVERSITY
4.3.1 Gradsects

Previous studies have shown that rock type, precipitation and temperature have a strong
influence on the distribution of plant species (Austin 1978, Austin et al., 1984). Altitude,
which is closely correlated with temperature, was chosen as the main environmental variable
for the NCR because of the ready availability of such information from topographical maps
(1:63,360 series). Aspect was also taken into consideration.

Transects were oriented along altitudinal gradients in order to sample the full range of
biodiversity within a forest. Reference to the 1:63,630 series of topographic maps enabled
transects to be positioned at right angles to contours, ensuring that the full range of altitudes
and aspects was covered by one or more transects within each forest. Schematic diagrams
in Figure 4.1 show how transects were aligned along altitudinal gradients (a), changing
direction to maximise variability and taking advantage of available access routes (b). Narrow

'0 This was later revised and the final version published in a Special Issue of the Sri Lanka Forester on remote sensing (A 1:50,000-
scale forest map of Sri Lanka: the basis for a national forest geographic information system, Legg, C. and Jewell, N, 1995).

'! The term legally designated denotes any forest reserve or national heritage wilderness area administered by the Forest Department,
and any national reserve (i.e. strict natural reserve or national park) or sanctuary administered by the Department of Wildlife Conservation.

i2 Originally, a threshold of 50 ha was applied to Galle, Matara and Hambantota districts at the outset of the NCR, but this was later
raised to 100 ha to expedite the survey. On 19 May 1993 a decision was taken to raise the threshold again to 200 ha to further expedite
the survey.

63

TRANSECT

Figure 4.1 Schematic diagram showing alignment of transects in relation to (a) altitudinal
gradient, (b) access routes, (c) riverine and (d) coastal vegetation. [Not to scale]

64

forest —

€ coastal

FOREST EDGE

Figure 4.2 Schematic diagram of plots aligned along transects at regular intervals in (a) wet
zone forests and (b) dry zone forests. [Not to scale]

65

belts of vegetation, such as riverine forest, were sampled in a zigzag direction along the
width of the forest, crossing between banks as conditions permitted (c, d).). In the case of
extensive forests, Landsat Thematic Mapper false-colour images (scale 1:50,000) were used
to differentiate between community types and ensure that each was sampled. While large-
scale maps of the soil and vegetation would have helped in deciding where to align transects,
such information was not available for the majority of forests.

A single gradsect with at least five plots was considered to be a minimum for sampling small
forests of about 200 ha, but at least four or five gradsects were required for those of about
10,000 ha, particularly in the case of forests in the wet zone where species diversity is
higher.

Forests were reached in the field via the most readily accessible routes to keep time spent
travelling to a minimum. Gradsects were walked along fixed bearings, using a compass, and
sampled at regular intervals within plots of 100 m x 5 m.

The first plot was positioned at the beginning of the gradsect when starting on the coast, in
a valley or on a ridge, but otherwise it was placed 100 m inside the perimeter of the forest
to avoid peripheral, disturbed areas. Plots were spaced 150 m apart (i.e. 4 plots per km of
gradsect), the distance between plots being paced. This was generally adequate in rain forest
and/or steep terrain, where species composition tended to be fairly heterogeneous
(Figure 4.2a). In the dry zone, where the topography is fairly uniform (i.e. level terrain) and
there are extensive patches of relatively homogenous forest, plots were spaced up to 400 m
apart (i.e. 2 plots per km), as illustrated in Figure 4.2b. Spacing of plots did not exceed
400 m because of the high investment in time and energy required to walk the gradsect.
Occasionally, it was necessary to space plots as close together as 100 m, as in the case of
narrow bands of coastal vegetation (Figure 4.2b).

Gradsects and plots were permanently marked so that they could be revisited for checking
data or carrying out further fieldwork. Trees were marked with yellow paint at 10-20 m
intervals. Plots were distinguished by means of coloured nylon rope tied out of reach round
a branch of the first and last tree in each plot.

4.3.2 Sampling within plots

Plots were 100 m long, aligned along the length of the gradsect, and 5 m wide (Figure 4.2).
They were measured along the centre-line using a brightly-coloured nylon rope, which
changed from one colour to another at its mid-point (50 m) to facilitate sampling (see below).

The exact location of each plot was determined with a Global Positioning System (GPS)'?.
Interference from dense canopy cover was overcome by climbing a tree in order to obtain
an unobstructed fix from the satellites. Various physical parameters were measured at O m,
50 m and 100 m intervals along the plot, and the condition of the vegetation was also
assessed. The data were recorded on the Plot Description Form (Box 4.1) and subsequently
entered into the Environmental Information Management System (EIMS).

'3 As the GPS was not available at the start of the NCR, plots in Galle, Matara and Hambantota districts were marked on topographic
maps (1:63,630) to obtain the geographic coordinates.

66

Box 4.1 Plot Description Form

DATE:
NAME OF SITE: NO. OF SITE: LEGAL DESIGNATION:
BRIEF DESCRIPTION OF SITE CONDITION:

TRANSECT/PLOT NO.

GEOG. COORD. - LATITUDE
- LONGITUDE

TIME

WEATHER - CLOUD COVER'
- CONDITIONS?

ALTITUDE (M) - MIN.
- MAX.

MEAN we el

ASPECT

ee a a
Pe ee ee eee
fetormertoTOn! es | | la] ee el eesti hep e |
Peioriarea aii) ial ae ae
Pree eee

1/8, 2/8 etc.
1 = dry
2 = moist
3 = wet

. Mainly with respect
to direct observation
of mammals & birds

undisturbed

slight disturbance (a few tree stumps evident)
disturbed (canopy intact but numerous tree stumps)
semi-degraded (up to 50% canopy removed)
degraded (>50% canopy removed)

rocks 5
exposed = 1-5%
leaf litter = 6-25%

. 0 = zero
1
2
herbs 3 = 26-50%
4
5

AURwWNe
iodo toned

= 51-75%
= 76-100%

Date of database entry:
Signed:

67

Box 4.2 Species Inventory Form

DATE:
NAME OF SITE: NO. OF SITE: LEGAL DESIGNATION:

PLANTS'/ANIMALS? (delete as appropriate)

For plants, the number of individuals exceeding 10cm DBH is recorded for each species. A plus indicates the
presence of a species but with no individual exceeding 10cm DBH.

For animals, the number of individuals of all vertebrate groups except fishes (i.e. mammals, birds, reptiles and
amphibians) and certain invertebrate groups (i.e. butterflies, molluscs and termites which build mounds)
directly observed or heard is recorded. A plus sign indicates that a species is present. In the case of indirect
observations the following code is used:

B = burrow D = defecation F = feeding sign H = heard
L = lying site R = rubbing site T = tracks

Species identified in the field are recorded by their scientific name or species code. Unidentified species are
collected for subsequent classification and recorded by their accession or herbarium number.

Date of database entry:
Signed:

The fauna and flora were observed within each plot and recorded on the Species Inventory
Form (Box 4.2). The time required to inventory the species within a plot ranged from less
than one hour in dry monsoon forest to two or even three hours in rain forest. Inventory
forms with a check-list of species and their codes were automatically generated from EIMS,
based on inventories of one or more forests previously surveyed in the vicinity. This reduced

time spent writing species’ names in the field and hastened data entry by using the species’
codes.

68

Fauna

The plot was first walked by the zoologist who recorded any animals (vertebrates, molluscs
and butterflies) seen or heard within the range of visibility - this usually took up to 30
minutes. The zoologist was followed by his assistant carrying the 100 m length of rope, and
by a painter who marked the trunks of trees at 10-20 m intervals along the centre-line. The
zoologist and his assistant then retraced their footsteps either side of the fixed rope,
disturbing the leaf litter and undergrowth as necessary to record the more cryptic and often
smaller animals, their tracks and signs within a 5 m belt (i.e. up to 2.5 m either side of the
fixed rope). The edge of the plot was determined using a 2.5 m long stick held at right
angles either side of the fixed rope.

The faunal survey was restricted to mammals, birds, reptiles, amphibians and two
representative invertebrate groups (molluscs and butterflies). Molluscs were chosen because
their presence can be readily detected from their shell remains, and butterflies because they
tend to be highly visible and are best known among insects. Freshwater fishes were recorded
opportunistically, as time and conditions permitted. Species were recorded on a presence or
absence basis from their tracks and other signs, but the number of individuals was recorded
in the case of direct observations (Box 4.2).

Flora

Once the centre-line of the plot was fixed by the rope, the botanist proceeded to walk along
the length of the plot recording all woody plant species within a 5 m width (i.e. up to 2.5 m
either side of the fixed rope, measured with a stick). Specimens of unidentified species were
collected and numbered for subsequent identification at the National Herbarium, Peradeniya.
The number of individuals exceeding 10 cm DBH was recorded for each species, but species
with no individuals exceeding 10 cm DBH were recorded only on a presence/absence basis
(Box 4.2). The botanist was assisted by one person who checked the width of the plot using
a 2.5 m-long stick and a second who collected, labelled and pressed specimens for the
herbarium. Sometimes it was necessary to climb trees to collect suitable herbarium material.

The floral survey was restricted to woody plants because of time constraints. It was not
possible to revisit plots in different seasons in order to comprehensively inventory herbs. The
floral survey was similar in duration to the faunal survey, but tended to take less time in dry
forest and longer in rain forest. In order to maximise efficiency, the first of either the floral
or faunal survey parties to complete a plot proceeded to locate the next plot.

4.3.3 Sample size

The adequacy of sample size was routinely assessed in the field by regular reference to the
relationship between the accumulative number of woody plant species recorded and the total
area (denoted by total number of plots) sampled. Once the asymptote was reached (i.e. the
majority of species had been recorded) sampling was discontinued for that particular forest.
In practice, sampling continued until the number of new species of woody plants recorded
within at least two successive plots did not exceed 5% of the total number of recorded
species.

An example is shown in Figure 4.3 for Sinharaja National Heritage Wilderness Area, part
of the largest remaining block of rain forest in the country. In this particular example,

69

% new species

g
z
z
z
3
3
:
i)
<

” No. plots F

—4&— Accumulative no. species —@— (No. new species/Accum. no. species) x 100

5% threshold for new species

NOTE: Transect numbers are marked for the first plot only.

Figure 4.3 Accumulative number of woody plant species recorded in consecutive plots in
Sinharaja. Sampling is discontinued once the number of new species inventoried in at least
two consecutive plots falls below the 5% threshold.

because of the large size of Sinharaja, it was necessary to stratify the forest and sample the
full range of community types along a number of different gradsects. As shown in
Figure 4.3, the number of new species recorded within each plot declined along each
gradsect, often dropping below the 5% threshold, but then rose at the beginning of a new
gradsect. In such cases, with large forests, it was necessary to continue sampling until the
5% threshold was not exceeded even with the establishment of a new gradsect in a different
part of the forest.

It is instructive to note that the total of 276 woody plant species recorded within plots 1-29
(gradsects 4, 27, 33 and 61 in Figure 4.3), representing a total sample area of 1.45 ha, is
well in excess of the 184 woody species recorded within a total sample area of 15 ha by
Gunatillake and Gunatillake (1981). Although their research objectives were different to those
of this study, they found that a minimum area of 3.75 ha was required to sample woody
plants in the rain forests of Sinharaja. Such comparisons provide an indication of the cost-
effectiveness of gradsect sampling.

4.3.4 Observations between plots
Noteworthy fauna and flora observed along a gradsect while walking between plots were
recorded, and specimens collected if their identity was uncertain. Such data were entered into

EIMS, but not used in any of the analytical procedures because this would have biased the
results.

70

4.3.5 Analysis of inventory data

An iterative method (after Kirkpatrick, 1983) was used to define a minimum set of sites
necessary to conserve the species diversity contained within Sri Lanka’s natural forests. A
greedy heuristic algorithm was developed to select a set of forests in which all species occur
at least once. It consisted of the following steps (adapted from Margules et al., 1988):

(i) The forest containing the most species was selected.

(ii) From the remaining forests, the forest which had the highest complement of
species not already represented in the previously selected forest was selected next.

(iii) Where two or more forests contributed an equal number of additional species, the
first forest encountered was selected.

(iv) The previous step (ii) was repeated until all species were represented in one or
more forests.

Both woody plant and animal datasets were submitted to this iterative procedure which was
programmed within EIMS. The analyses were also restricted to endemic forest species of
woody plants and animals.

- An alternative rarity algorithm was also programmed within EIMS. This weights for rarity
by selecting forests in order of their contribution of unique species to the network, a unique
species being one recorded within only one particular forest. Both procedures produced
identical or almost identical minimum sets of forests. This was due to the large number of
forests containing one or more unique species - by the time all unique species had been
selected, so had most other species. For the sake of brevity, therefore, only the results of the
first greedy algorithm are presented in this report.

The algorithms developed for EIMS can be constrained to determine the minimum set of
forests needed to represent all species twice, three or more times. While it would be highly
desirable to ensure that all species are conserved within at least two forests, in practice this
was not an option due to the many species recorded from only a single forest.

Individual and contiguous forests

Legally designated forests and other state forests (OSFs) having closed canopies and
contiguous with each other were treated as single units, referred to as contiguous forests.
Treatment as single units ensures that conservation forests are as large as possible, in line
with this main tenet of conservation biology theory. It also enabled data from adjacent forests
to be combined, thereby increasing the incidence of adequately surveyed forests due to the
larger sample sizes.

4.4 GAP ANALYSIS
Gap analysis is a method of conservation risk assessment that evaluates the protection status
of biodiversity, often at the ecosystem level, by overlaying its distribution on a map of

existing protected areas. It can be readily undertaken using a Geographic Information System
(GIS).

71

Gap analysis techniques were used to assess the representativeness of Sri Lanka’s existing
designated areas network at the ecosystem level, as well as to consider its wilderness quality.
Each gap analysis is described in the subsequent sections below.

The GIS coverage used for designated areas was that held within the Forest Department’s
National Forest Geographic Information System. It is reasonably comprehensive, covering
both forest and wildlife sectors, but not all the boundaries of forest reserves or proposed
reserves have been digitised due to a lack of mapped information. Thus, there are a few
discrepancies between this coverage and the list of designated areas provided in Annex 1. In
addition, it was not possible to include the seven conservation forests with OSF status
because their boundaries have yet to be defined, mapped and digitised. Omission of these
seven OSF conservation forests makes only a relatively small difference to the analyses
because their total area is only approximately 7,500 ha.

The designated areas coverage was corrected for overlapping designations, arising from
reserves transferred from the Forest Department to the Department of Wildlife Conservation
and designated as national reserves or sanctuaries. Double counting amounted to a total of
934.31 km’, a breakdown of which is provided in Table 4.1.

Table 4.1 Area of overlap (km’) between designated areas within the forestry and wildlife sectors

Department of Wildlife Conservation

Park Reserve Reserve
ereerraon core) ee ee eae

4.4.1 Forest types

Designation:

Forest Department

Spatial datasets of existing designated areas and closed canopy natural forest cover types,
from the 1:50,000-scale forest map of Sri Lanka (Legg and Jewell, 1995), were
superimposed using an ARC.INFO-based GIS. The extent to which each forest type is
represented within each type of designated area was computed using GIS techniques.

4.4.2 Wilderness

The World Conservation Monitoring Centre has developed a wilderness map for Sri Lanka,
using GIS techniques, as part of a separate study of forest condition. The concept of
wilderness can be defined in terms of the extent to which nature is changed or disturbed due
to the influence of modern society on its attributes, remoteness and primitiveness (Lesslie and
Taylor, 1985). As wilderness cannot be measured in absolute terms, it is best conceptualized
as a continuum from non-wilderness to wilderness, or low wilderness quality to high
wilderness quality as in this study.

72

The method was based on the approach developed by the Australian Heritage Commission
(Lesslie et al., 1988), using the following indicators to derive a wilderness index:

¢ remoteness from settlements (i.e. permanently occupied buildings, cleared
agricultural land, plantation forests)

¢ remoteness from access (e.g. roads, railways, aircraft runways)

¢ aesthetic naturalness - the degree to which the landscape is free from the presence
of permanent structures of modern technological society (e.g. all man-made
structures, ruins, quarries)

Primary data on these three indicators were derived from the Digital Chart of the World
(DCW), a GIS that is based on the Operational Navigation Charts and Jet Navigation Charts
(ESRI, 1992). DCW has 16 thematic layers, ranging from settlements to drainage networks.
In order to derive values for each wilderness indicator, a grid was computer-generated and
overlaid on the appropriate thematic layer. Indicator values were determined for each grid
point by measuring the distance from the grid point to the nearest appropriate feature.

The 1:50,000-scale forest map of Sri Lanka (Legg and Jewell, 1995) was used in conjunction
with DCW to derive the aesthetic naturalness indicator. Each grid point was evaluated with
respect to its proximity to non-closed canopy forest. The three indicators were then to derive
a wilderness index for each grid point. This index provides a measure of socio-economic
influences and threats to remaining closed canopy natural forests.

The designated areas coverage was superimposed on the wilderness map of Sri Lanka and
the extent of protection of each wilderness zone was computed using GIS techniques. Four
wilderness zones were defined approximately as follows:

e¢ Category 1 Low wilderness (Wilderness index < 5)
¢ Category 2 Medium-low wilderness (Wilderness index 5- 9)
e Category 3 Medium-high wilderness (Wilderness index 9-13)
e Category 4 High wilderness (Wilderness index 13-20)

4.4.3 Floristic regions and edaphic zones

As yet, there is no biogeographic or vegetation map of Sri Lanka that is sufficiently detailed
to be useful for gap analysis purposes. Ashton and Gunatilleke (1987) have defined 15
floristic regions for the country, but the dry zone is treated as a single region (Figure 4.4 and
Table 4.2). The Department of Wildlife Conservation is currently working on a
biogeographic map of the country, in collaboration with the Survey Department, but so far
has only mapped soil-edaphic units for the intermediate and dry zones (Figure 4.5 and
Table 4.3), corresponding almost exactly with Floristic Region II (dry and arid lowlands).
Given that the two classifications are complementary, Floristic Region II was subjected to
a more detailed gap analysis by using the soil-edaphic classification.

The two maps were digitised and combined into a single coverage for gap analysis purposes.

The combined coverage was overlaid with the designated areas coverage and
representativeness computed, as in the case of the previous gap analyses.

73

Table 4.2 Floristic regions, with their principal natural vegetation types and dominant plant
communities (Source: Ashton and Gunatilleke, 1987)

No. Floristic Region Characteristic natural vegetation types (dominant plant
communities)
Coastal and marine belt Marine, mangroves, salt marsh, sand dunes, and strand
vegetation

Dry and arid lowlands Tropical dry mixed evergreen forests

Manilkara community

Mixed community (Chloroxylon-Vitex-Berrya-Schleichdera
series)

Tropical thorn forests (Manilkara-Chloroxylon-Salvadora-
Randia series)

Damana and Villu grasslands

Flood-plain wetlands
Riverine and gallery forests

Northern intermediate Tropical moist semi-evergreen forests

lowlands (Filicium-Euphoria-Artocarpus-Myristica series)
IV Eastern intermediate Tropical moist semi-evergreen forests

lowlands Savannah forests

Northern wet lowlands Tropical wet evergreen forests

VI
Tropical wet evergreen forests

VII Southern lowland hills
(Dipterocarpus community, Mesua-Doona community)

VII Wet zone freshwater bodies Streams, rivers, and other freshwater bodies

Ix Foothills of Adam’s Peak and | Tropical wet evergreen forests
Ambagamuwa

Submontane forests (Shorea-Calophyllum-Syzgium series)
XI Kandy and Upper Mahaweli Tropical wet evergreen forests
humid zone dry, pathana grasslands
XII Knuckles
community)
Tropical montane forests (Calophyllum zone)
XIII | Central Mountains, Tropical montane forests (Calophyllum-Walkeri-Syzgium
Ramboda, Nuwara-Eliya community, wet pathana grasslands)
XIV | Adam’s Peak Tropical montane forests
Tropical submontane evergreen forests
XV Horton Plains Tropical montane forests
upper wet pathana grasslands

Sinharaja and Ratnapura Tropical wet evergreen forests
(lowland hill Dipterocarp forests - Mesua-Doona community,
Talawa-grasslands, fernlands)

Tropical submontane forests (Myristica-Cullenia-Aglaia-Litsea

74

Floristic Regions of SriLanka | | ae
| ll_ DRY AND ARID LOWLANDS
gv | aN Ill NORTHERN INTERMEDIATE
¢! < LOWLANDS
wy 9 SS ES |v EASTERN INTERMEDIATE
& “en Seah LOWLANDS
aaah A :. El v NORTHERN WET LOWLANDS
| MI Vi SINHARAJA AND RATNAPURA
Vil SOUTHERN LOWLAND HILLS

Wl |X FOOTHILLS OF ADAM‘S PEAK
AND AMBAGAMUWA

MM Xx! KANDY AND UPPER MAHAWEL!
E33 X11 KNUCKLES

MB X11 CENTRAL MOUNTAINS,
RAMBODA, NUWARA ELIYA

L_]XIV ADAM'S PEAK
MB XV HORTON PLAINS
El SALT AND BRACKISH WATER

\ : SS ee gs pee Be Not mapped:-
S i j : 2 a eee a Z = \\ | COASTAL AND MARINE BELT
ly ee re Sa Vill WET ZONE FRESHWATER BODIES

X MIDMOUNTAINS

hy
KX <
is

f

laa
="

\

0

WORLD CONSERVATION
MONITORING CENTRE

100km

9) 50
Projection Lambert Azimuthal, a ———
CM 81 degrees, Lat of Centre Proj 8 degrees February 1997

Figure 4.4 Floristic regions of Sri Lanka (Source: Ashton and Gunatilleke, 1987)

75

Soils of Sri Lanka ay

1. VERY DEEP LATOSOLS

2. SODIC, SALINE, ALKALI
SOILS

E@l 3. SANDY REGOSOLS
Hs 4. GRUMUSOLS

5. RBE-LHG GRAVELLY AND
LITHIC PHASE

6. RBE-LHG MODAL PHASE
7. DEEP ALLUVIAL SOILS

8. SOILS ON OLD ALLUVIUM
AND SODIC LOWLAND
SOILS
I 9. SHALLOW, GRAVELLY
AND LITHIC NCB SOILS

10. SHALLOW, LITHIC RYP
SOILS

Ml 11. NCB MODAL SOILS

12. GRAVELLY RBE -
SOLODIZED SOLONETZ

Bi 13. w.z.

[=] 14. UNDEFINED

WB SALT AND BRACKISH WATER

| @
80
WORLD CONSERVATION
MONITORING CENTRE

100km

50
Projection Lambert Azimuthal, _—___—/ |

CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 4.5 Soil-edaphic units of Sri Lanka (Source: Survey Department)

76

Table 4.3 Soil edaphic units of the dry and intermediate zones of Sri Lanka

ik a aosubinii soit
Very deep latosols (DL3) Dry and very dry fasciation - dry mixed
ee a forest

Sodic, saline, alkali soils | Sodic, saline, alkali soils (DL4) | tropical thom forest, = thorn forest
= Sandy regosols (DL3, DL4, DL2) sparse, stunted - dry mixed evergreen forest

Grumusols - black clayey sticky soils (DL3, severely stunted - dry mixed evergreen forest
DLA) and thorn scrub

Reddish brown earths - low humic gley soils, | Dry and very dry fasciation of dry mixed
gravelly and lithic phase (DL3) evergreen forest

Reddish brown earths - low humic gley soils, | Dry and moist fasciation of dry mixed
modal phase (DL1) evergreen forest

Deep alluvial soils (DL1, DL2) Riparian, riverine forest and villu grassland
Soils and old alluvium and sodic lowland Damana parkland, grassland and stunted -
soils (DL2) dry mixed evergreen forest
Shallow, gravely and lithic reddish brown Savannah forest - grassland
earths ERNE cia |

Shallow, lithic reddish | Shallow, lithic reddish yellow podsols (13) _| podsols (IU3) | Dry patana grassland patana grassland

Non-calcic brown soils, modal phase (DL2) Dry and moist fasciation - dry mixed
evergreen forest
12 Gravelly reddish brown earths - solodized Very dry fasciation - dry mixed evergreen
solonetz (DL5) forest

4.5 ENVIRONMENT INFORMATION MANAGEMENT SYSTEM

q

All field data were entered into the Environmental Information Management System (EIMS).
This database management system was developed specifically for the Environmental
Management in Forestry Development Project using dBase software. It is fully documented
elsewhere (Hughell, 1993).

It was subsequently necessary to upgrade the software to Microsoft FoxPro (Version 2.6 for
Windows) in order to be able to accommodate large datasets and analyse them relatively
quickly. Following the upgrade in 1996, computing time for some of the iterative procedures
described in Section 4.3.5, for example, was reduced from about 6 hours to 30 minutes.

The NCR component of EIMS comprises the following database files:

¢ Ca.dbf which holds records of all nationally designated conservation areas, as well
as OSFs included in the NCR.
¢ CrPlot.dbf which holds records of all plots inventoried in the NCR.

e PltSp.dbf which holds taxonomic records of woody plant species included in the
NCR.
e AniSp.dbf which holds taxonomic records of animal species included in the NCR.

Wl

e PltDat.dbf which holds records of all woody plant species recorded within each plot
surveyed in the NCR.

e AniSp.dbf which holds records of all animal species recorded within each plot
surveyed in the NCR.

An indication of the size of some of these databases is provided in Section 6.1.3 (Table 6.1).

Field data were first checked, using programmed routines, and then subjected to two types
of analysis. The first produced a summary of biodiversity within each forest and the second
defined a minimum set of forests in which all species were represented, based on iterative
procedures described in Section 4.3.5.

4.6 CONSTRAINTS

The biodiversity component of the NCR represents an extremely important first attempt to
define an optimum system of conservation forests based largely on an assessment of the
status and distribution of Sri Lanka’s flora and fauna. However, it is very much a
preliminary attempt based on rapid survey techniques. It will be necessary to refine this
optimum system as further resources become available to improve the information base and
as tools are developed to undertake more sophisticated analyses. Some of the major
constraints to be addressed in the longer term are identified below.

4.6.1 Sampling floral diversity

In practice, it was not always possible to comprehensively inventory the woody plant flora
within the available time, particularly in the case of the smaller forests in the wet zone where
diversity was highest. It was necessary, therefore, to distinguish between adequately and
inadequately surveyed forests throughout the analyses. This distinction was made on the basis
of the procedure described in Section 4.3.3.

4.6.2 Sampling faunal diversity

It was not possible to comprehensively inventory the selected faunal groups within each plot.
This would have required much more time to repeat surveys at different times of the day and
in different seasons, as well as trap the more cryptic species, all of which was beyond the
resources available to the NCR. By contrast, it was possible to record and, in most cases,
identify all woody plants within a plot, the main challenge being to survey sufficient plots
to adequately sample a forest, as discussed in the next section.

Consequently, in the first instance, forests important for biodiversity were identified on the
basis of their complement of woody plant species. Less emphasis was given to the faunal
inventories due to their incompleteness, although the results of faunal surveys were used to
supplement those of the floral surveys.

For purposes of this study, it is assumed that plant and animal diversity are closely related:
forests rich in woody plant species are also rich in animal species. This is shown in
Figure 4.6 using inventory data for forests considered to have been adequately surveyed, as
defined in Section 4.3.3. Despite the incompleteness of the faunal data, which is assumed to
apply in a consistent manner to all forests surveyed, the relationship between plant and

78

animal diversity is close, particularly for endemics as shown in this example (Figure 4.6).
On the basis of the analytical procedures used to identify optimum systems of conservation
forests, as described in Section 4.3.5, this means that forests rich in animal species can
expect to have been included, but the full range of animal species diversity may not
necessarily be represented.

g
i)
®
i=")
an
-
=|

&
[-")

=
E
o

a=)
£

&

Endemic animal species

Figure 4.6 Relationship between endemic plant and animal species diversity in natural
forests. Each data point represents a forest adequately surveyed during the NCR.

4.6.3 Taxonomic distinctness and genetic diversity

The number of species is not an adequate measure of biodiversity because speciation is not
necessarily correlated with ecological differentiation (Bond, 1989). Thus, the species in a
genus or higher taxonomic unit may be ecologically monotonous. In contrast to large genera
with many ecologically similar species is the case in which extraordinary variability is found
within a single species, perhaps necessitating conservation of individual populations
throughout its entire range. In order to prioritorise the selection of protected areas systems
for biodiversity conservation, taxonomic distinctness should be considered in addition to
species richness and complementarity (Vane-Wright et al., 1991a).

Species richness (number of species) and complementarity (i.e. relative contributions of
individual biotas to the network) are incorporated in the existing conservation evaluation
procedure (Section 4.1.3). Thus, the ideal first choice is the site with the most species (or
rare species); subsequent sites are selected on the basis of their representation of the residual
complement. However, this model does not take into account taxonomic distinctness, the
difference between species in relation to their place in the natural hierarchy. This can be
evaluated by root weighting, whereby species are weighted for distinctness according to their
position in the taxonomic hierarchy (Vane-Wright et al., 1991b). Software systems are being
developed to enable taxic diversity measures to be combined with complementarity for a
range of different organisms, but they were not available during the life of this project.

79

Chapter 5
RESULTS - SOIL AND WATER CONSERVATION ASSESSMENT
TELAT TIGRE DIL Die OO ep VI

5.1 INTRODUCTION

A total of 281 legally designated forests and other state forests (OSFs) were assessed with
respect to their importance for soil and water conservation using the methodology described
in Chapter 3. Natural forests were identified from the New 1:500,000 Scale Forest Map of
Sri Lanka (Legg and Jewell, 1992), as described in Section 4.2 for the biodiversity
assessment.

The assessment was principally a desk exercise, with some checking in the field to validate
the results. In practice, this meant that rather more forests were evaluated for their soil and
water conservation than for their biodiversity importance. Biodiversity surveys took much
longer; moreover, some forests could not be surveyed due to LTTE activities.

A full report of the soil and water conservation assessment is provided elsewhere
(Gunawardena, 1995). The main findings from the study are presented in this chapter, and
they are integrated with the results of the biodiversity assessment in Chapter 7. The results
of the assessment of importance of forest for protection of headwaters are presented in this
chapter, but they were not used in the final identification of forests important for soil and
water conservation for reasons given in Section 3.6.3. It should also be noted that, for the
same reasons, the results of the final ranking procedure described in Section 3.6.2 are not
included in this chapter, but they are presented in the full report by Gunawardena (1995).

5.2 SOIL EROSION

The results of the soil erosion assessment are given in Annex 2, each forest being ranked in
order of its importance for soil protection. Two forests, Kalubowitiyana OSF and Habarakada
Proposed Reserve, exceed a soil erosion potential of 2000 t ha’ yr’. Both are very small
forests, with rock outcrops covered by natural forest and steep slopes on all sides. Landslides
were evident during the field visits, mainly due to the high rainfall, shallow soils and steep
slopes. Three other forests have soil erosion values in excess of 1500 t ha' yr’, namely
Auwegalakanda OSF, Peak Wilderness Sanctuary and Messana Proposed Reserve. They all
occur in high rainfall areas and feature steep terrain.

The results are summarised according to climatic zone and district in Table 5.1. They show
that very few forests are important for soil conservation in the dry zone. Exceptions, which
exceed the conservation threshold value of 300 t ha? yr", are:

e Anuradhapura District Ritigala SNR
¢ Hambantota District Rammalakanda FR
e Monaragala District Dummalahela OSF, Monerakelle OSF, Velihela OSF, Wadinahela OSF
e ~Polonnaruwa District Gunner’s Quoin OSF

Although rainfall is relatively low (<2000 mm), erosion is potentially high due to the steep
terrain.

80

As shown in Table 5.1, Kegalle, in particular, and also Badulla, Galle and Ratnapura
districts have the highest percentage of forests with soil erosion values exceeding the
threshold of 300 t ha” yr’ . Forests in these districts have steep slopes and, in general, are
located on south-western aspects which experience the full impact of the south-west monsoon.
In Kalutara District, forests tend to lie in the coastal plain where the landscape is less
precipitous. Some of the forests in Kandy District, such as Victoria-Randenigala~-Rantambe
Sanctuary, are situated in the rain shadow of the south-west monsoon, hence their lower
potential for soil erosion. Nuwara Eliya District has a relatively low percentage of forests
above the threshold, primarily due to lower rainfall and less steep slopes.

Table 5.1 Soil erosion values of forests summarised by climatic zone and district. Values above the
threshold of 300 t ha! yr’ are shaded.

Total
no.
forests

Soil erosion (t ha™ yr")
% forests

1500- 1000- 500- 300- >300
> 1500 1000 500 300 100 <100

Climatic Zone
District

Dry Zone

Tc
el a
Fe A aS
a a

piace Sc
_= eee eee Ce
aimee [fof of af a{ a] | #0)
Poe ef ep | a] «| ef) sp ao
Pesce or el ee
Pave | ef ef ff =, 7p) as
foome [> op > ap 3s) se) =) =|
[were] sf ef
| vail ie de

81

5.3 HEADWATERS PROTECTION

The results of the headwaters protection assessment are given in Annex 3, each forest being
ranked in order of its importance. Forests in the mid- and up-country districts rank high in
importance.

As summarised in Table 5.2, nine of the 13 forests in Nuwara Eliya District fall within the
25 most important forests. All forests in Nuwara Eliya, Kandy and Badulla districts, with
single exceptions in Badulla and Kandy, lie within the 100 most important forests. These
results clearly demonstrate that forests in the south-central massif, from where all of the
major rivers originate, are important for protecting the headwaters of these rivers.

Table 5.2 Headwaters protection ranks of forests summarised by climatic zone and district

Headwaters rank

1-25 26- 51- 76- 101- 126- 151- 176- 201- | 226-
50 75 100 125 150 175 200 225 251

Climatic Zone
District

Dry Zone

(ce messes coals lee eee el
en ee ee a es
[See al Lae a I
rarer ses
este V0 | ae ae ee a)
eee ee

a
een |e |
Lee ee I AE ee al ee eI
aca ed a
[Ese Sena as ee
(ere) © eo ee
sofia | on
[roan | ost [os [os [oe [os [os | o [is | os | [

82

In the other districts of the wet and intermediate zones, importance for headwaters protection
is much more variable, depending on the individual forest. For example, in Matara District,
Diyadawa Forest Reserve is 18th most important for headwaters protection, while
Kekanadura is tied last in rank (Annex 3). The former encompasses the headwaters of the
Nilwala and Gin Ganga. In contrast, Kekanadura lies close to the coast and no rivers
originate from it. Forests in Kalutara District rank fairly low in importance. Although the
mean annual discharge from the Kalu Ganga is the second highest in the country, its
headwaters lie outside Kalutara in the adjacent districts of Kegalle and Ratnapura.

It should be noted that three forests in Anuradapura District are among the top 10 most
important for headwaters protection. They are Kahalla-Pallekele Sanctuary, which protects
the headwaters of the Deduru Oya, Mi Oya and Kala Oya, and Hurulu Forest Reserve and
Anaolundewa Proposed Reserve, within which lie part of the headwaters of the Mahaweli
Ganga and Yan Oya. Forests in the north-west coastal districts of Gampaha and Puttalam are
among the lower ranks for protection of headwaters.

5.4 FLOOD HAZARD

The results of the flood hazard assessment are given in Annex 4, each forest being ranked
in order of its importance for flood control. Peak Wilderness Sanctuary, Knuckles
Conservation Forest and Sinharaja National Heritage Wilderness Area have a mean annual
flood well in excess of 200 m’s"', due mainly to the high rainfall and their large area.

The distribution of mean annual flood values is shown by climatic zone for each district in
Table 5.3. The pattern is similar to that for soil erosion (Table 5.1), reflecting to some extent
the fact that mean annual rainfall is a variable common to both indices. Also, slope and
stream frequency, which were used in estimating soil erosion and mean annual flood,
respectively, are related: both the number of streams and stream junctions tends to be higher
in steeper terrain. However, the influence of forest area over all of these variables is
predominant, as shown for example by the high mean flood values for Wasgomuwa, Gal Oya
Valley and Uda Walawe national parks (Annex 4).

5.5 FOG INTERCEPTION

Estimates of the total volume of water intercepted from fog are shown in Table 5.4 for
forests above 1,500 m above sea level. Rainfall and altitude provide the basis for estimating
the annual contribution from fog, which is converted to a volumetric value by multiplying
by the area of the forest (Section 3.5).

Peak Wilderness Sanctuary intercepts by far the most fog (Table 5.4). Although its altitude
is lower than many other forests in Nuwara Eliya District, rainfall is high and the forest is
very extensive. Together, with Knuckles Conservation Forest and Pedro Proposed Reserve,
which rank second and third, respectively, these three forests lie in the headwaters of the
island’s major rivers.

83

Table 5.3 Mean annual flood values of forests summarised by climatic zone and district. Forests
with flood values above the threshold of 10 m’s" are shaded.

Climatic Zone Total Mean annual flood (m’s”) %

District no. forests
De ee ea ee
eae olen beeen ee eee ee
Ce ee Se

ee ES ee ee ees)
a eee
a eee
Ee ae
Pee a es eee ee
Pe 2
ees) cl aT
Ee 2 ee |
ee ee ee Se
ES a ee ee
arise ee eee
ee as ee
[ie eo ee
a eS ea ee
ee ee ee |
ae ee ee
Pres | mf sf | ss] «| «| «| x] as)

One of the positive hydrological benefits of forests in the cloud base is their additional
contribution of water intercepted from wind-driven fog, as shown by ongoing studies at
Horton Plains (Section 3.5.1). In the final selection of forests for soil and water conservation
(Section 5.6), this single factor of fog interception is considered to be sufficiently important
to justify protection of all 20 natural forests that lie above the cloud base.

84

Table 5.4 Depth and volume of fog intercepted by forests above 1,500 m

Area Fog
(km?) Hain rank
(mm) (m*)*1000
40 bat | ae acosl laa
140 1,426
172 | Kandepola SitaBlyaFR | 26.16[ is] 23.524] 8 |
2 re i i reel
| Mahakudagala PR | es Se]

EMD | Forest name, designation

248

358
E
52
128

Note: Fog interception is negligible for all other forests located below 1,500 m.-

5.6 CONSERVATION PRIORITIES

5.6.1 Individual Forests

A total of 85 forests, listed in Table 5.5, were identified as highest importance for
conservation on the basis of their value for soil protection and flood control, or fog

interception. Of this total, 75 forests exceed the thresholds of both 300 t ha’ yr’ for soil
erosion and 10 m? s! for mean annual flood. There are an additional 10 forests important for

85

Table 5.5 List of forests of highest importance for soil and water conservation, based on their
importance for soil protection (S), flood control (F) and fog interception (1)

ee eT lala ae meee oe | oe
No. No.

Lit Agra BopalsceR ny 05 | eee] s09 | iknuckiesosrcey Ih 1) eed
| 549 | Aturwelawisahena PR | * | * | | 205 | KobahadunkandaPR {| * | * | |
| 7 | Amanawala-Ampane PR [| * | * [ff 217 | KudumiriyapR | + | * ||
| 528 | AsantanakandaosF | * | * [UL 222 | LabugamaKalatuwanaFr | + | * | |
| 509 | AuwegalakandaosF | * | * | f[ 241 | MagurugoaaFR | = | * ||
[9 | AyagamaPR TT * | 248 | MahakudagaiapR || * | * |
| 28 | BambarabowwaFR(CF) | * | * | [L253 | MatambureFR | = | * ||
[sit | BambarawanaosF | * | * | || 270 | MeepitimanaFR |_|
| 38 | Beraliya Kudagala) PR | * | * [| || 274 | MessanaPRCFH) | * | * ||
| 40 | BogawantalawaPR | * | * [ * | 288 | Morahela ROCF) | * | * ||
[552 | BuawellaosF | * | * [| 289 | Morapitiya-Runakanda | * | * | |
ey ee ee ee Tee a Ea
[57 | DambuluwanaFR | * | * | | 303 | Nakiyadeniyaprcry) {| * | + ||
| 65 | DediyaglaFR | * | * | || 306 | NamunukulapR_ | * | * |
| 515 | Dedugalla-NangalaosF_ | + | * {| || 307 | NanvoyapR || * |
Mahe hse as
Mion Cini Ew Reis een ESS
Lin ie i ne ee aa aa
| scat) Diyadawa ER(CE) eon) S| tals? 8] 5477) Paragala OSE Fae
| 529 | DowwgaiaPR | * | * | i358 | Pattipola-AmbawelaPR_ | | * | * |
IMnTOE Galashiels eT Peak Wilderness S #0) Pec imal
| 571 | GederagaipatanaosF_ | * | * | | Pedro PR EARS
| 112 | Gitimale-Erane PRCF) | * | * | || 383 | RagataPR TT |
| 546 | GongalaosrcF) | * | * | iL 386 | RammalakandapR | * | + |_|
| 544 | GorangalaosrF_ | * [ * [| 388 | Rammatckandarrcr) | * | + |_|
i ern Re aS
(Se ie Cnn mn a aaa Ee
| 545 | Handapan Ella OSKCF) | * | 514 | Sembawate SF | * [| * [|
| 128 | HarasbeddaPR_ | 499
Mimi scene iin ae 414 | SinharajaNHwA | * | * [|
507 | Homadola OSF | + | 426
: 328
| 140 | Horton Plains NP 432 | Tibbutukanda PR | *_|
506
: 551
; 12 | Vellinallure SF |
| 166 | Kalugala PRCF) | * | * 455 | WalankandaFR | * |
456
| 175 | Kanneliya FR(CF) | *
pasa

*

|

*

*

459

468
76 | WewelkanduraPR | * | * |
489 | YakdessakandaPR__| * | * |

*

P<

=
S
p
5
oo
fo)
a
iS)
y
]
|

*

* *

S = Soil erosion >300 t ha! yr'; F = Mean annual flood >10 m’s'; I = Fog interception (altitude > 1,500 m)

86

fog interception, which do not meet both soil erosion and flood control thresholds. It is worth
noting that all three criteria are met by ten forests, namely:

Knuckles Conservation Forest
Ohiya Proposed Reserve
Peak Wilderness Sanctuary
Pedro Proposed Reserve
Welegama Proposed Reserve

Agra-Bopats Proposed Reserve
Bogawantalawa Proposed Reserve
Hakgala Strict Natural Reserve
Kandapola Sita Eliya Forest Reserve
Kikilimana Proposed Reserve

The distribution of these forests of highest importance with respect to the island’s river basin
systems is summarised in Table 5.6. As expected, most of these forests lie within the Kalu
Ganga river basin which receives the highest amount of rainfall and has the highest
runoff/rainfall ratio. Rivers originating from the dry and intermediate zones have fewest of
these forests.

The extent of forests of highest importance for conservation is summarised by climatic zone
and district in Table 5.7. Only one forest in any of the dry zone districts is identified as a
top conservation priority, namely Rammalakanda Forest Reserve in Hambantota District. In
fact, most of this forest lies in the adjacent Matara District and all of it falls within the 2500
mm isohyet that demarcates the wet zone.

Of the 281 forests surveyed for the NCR, all in Nuwara Eliya District and most in Kegalle
District are identified as highest importance for soil and water conservation (Table 5.7). The
findings from this study, that forests in these two districts are the most important for soil and
water conservation, is supported by other data which show that 50% of landslides reported
between 1930 and 1985 occurred in these two districts.

Other wet zone districts (i.e. Colombo, Galle, Kalutara, Matara and Ratnapura) are also
important for soil and water conservation. Reference to column eight of Table 5.7 shows that
the extent of top priority forests in these wet zone districts comprises almost 60% or more
of the total area of forests surveyed for the NCR. It should be noted, however, that the
extent of surveyed forests (column 5) does not necessarily equate to the total area of closed
canopy forests (column 3). This is because the surveyed forests include tracts that are
sparsely covered or even deforested. Thus, the total area of highest importance forests is not
an accurate reflection of the extent of closed canopy forests within them.

The extent of forests of highest importance for soil and water conservation represents 4.3%
of the total area of the districts in which they are located, or 3.0% of the country. Overall,
this is a small percentage, but it is significant for some districts and represents 15-20% for
Galle, Kandy, Kegalle and Nuwara Eliya (Table 5.7).

As shown in Table 5.5, many of these 85 forests of highest importance essentially have no
legal conservation status. A total of six are protected areas, in so far as they have been
designated under the Fauna and Flora Protection Ordinance or, as in the case of Sinharaja,
the National Heritage Wilderness Areas Act. Of the 55 forest and proposed reserves, 20 have
been declared as conservation forests. However, conservation forests do not yet have any
legal basis. The remaining 24 forests are classified as other state forest, for which there are
no conservation provisions.

87

Table 5.6 Distribution of forests of highest importance for soil and water conservation with respect
to river basins

eo we |r a

Table 5.7 Extent of forests of highest importance for soil and water conservation
Climatic Zone District Closed Surveyed forests | Highest importance forests for soil
District (ha)! canopy and water conservation
forest
(ha)! Area (ha) | No. Total
area (ha) | surveyed | district

576,763 | 182,60 i938 | of 0 | oo] 00]
sia.oes | 115,88 sa | o | a | Foo]! ao
315.485 | 62,529 wo] of oo] oo] 00

Wet and Intermediate Zones

Badulla 285,673 26,428 68,184 Le] 6,034 so] aoe

Gama Tes |
Kalua ‘

' Source: Legg and Jewell (1995)

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5.6.2 Contiguous forests

Given the importance of protecting as large expanses of forest as possible for soil and water
conservation purposes, particularly where the terrain is not level, adjacent forests were
treated as single units of contiguous forest and the data re-analysed. The results of the re-
analyses are summarised in Table 5.8 for contiguous forests only, values for other individual
forests having already been presented in Annexes 2, 3, 4 and Table 5.4 for soil erosion,
headwaters protection, flood hazard and fog interception, respectively.

Table 5.9 List of contiguous forests of highest importance for soil and water conservation, based
on their values for soil protection (S), flood control (F) and fog interception (I)

No.

SN Eaihet San We eee
Rabe meee [Slain leone mie |
Bains Io orn ee
ee oe eee
se
BE

* * 489 * *
| 14 | Karavics fe fe | 2st | Magurugota = + [+ | |
| 112 | itimate-zrame | | + cae eon a
[432 | Tibbuukands + |e Horagale-Paragal
cd Dress Ld
| 217 | Kuduminya fe | pe Tate 2 tee
[ie ie ne ES eee
| -522| Kmucktesrwasgomwa | + | + | +] 128 | Harasbeada ||
EA ieee ale earerr es)
ge a
| 392 | Ravamaena tt [=| |

A total of 43 units of contiguous forests were identified as being of highest importance for
conservation on the basis of their importance for soil protection and flood control, or fog
interception (Table 5.9). Of this total, 47 forest units exceed the thresholds of 300 t ha! yr!
for soil erosion and 10 m? s' for mean annual flood. There are an additional 4 forest units

90

Watershed Protection in Sri Lanka KEY

acs Laie ea | ____ CLOSED CANOPY FORESTS *
Bere Coa \ | FORESTS IMPORTANT
0g LRN 9 Ik FOR WATERSHED.
S : PROTECTION

GRADSECT PLOTS

DESIGNATED AREAS
. rel __. WILDLIFE SECTOR
|_| FOREST SECTOR

* includes mangrove and
riverine dry forests.

a

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 5.1 Distribution of units of contiguous forest identified as highest importance for
watershed protection (i.e. soil and water conservation)

91

important for fog interception, which do not meet both soil erosion and flood control
thresholds. It is worth noting that all three criteria are met by five forest units, namely:

Central Highlands
Kikilimana

Ohiya
Knuckles/Wasgomuwa
Pedro

The distribution of these forest units is mapped in Figure 5.1. All of them lie within the wet
zone (compare with Figure 2.1), although the Wasgomuwa part of the Knuckles/Wasgomuwa
complex extends into the intermediate zone. Wasgomuwa, itself, is ranked 36th for
headwaters protection (Annex 3) and it is important for flood control (Annex 4), with a value
of 65.72 m? s7 yr? that is well in excess of the 10 m’ s’ yr’ threshold, but it is not important
for soil erosion (Annex 2). The mapped results also clearly demonstrate that very little forest
remaining in the wet zone is not important for soil and water conservation.

5.7 CONCLUSIONS AND RECOMMENDATIONS

1. Forests remaining in the wet zone, particularly the more extensive units of contiguous
forest, are a top priority for soil and water conservation.

2. All 85 forests of highest importance for soil and water conservation should be

upgraded to an appropriate conservation designation. In particular, the status of those
which are OSFs will need to be upgraded to at least conservation forest status.

92

Chapter 6
RESULTS - BIODIVERSITY ASSESSMENT
fs ee Ne

6.1 INTRODUCTION

In this chapter the importance of forests for biodiversity is assessed in terms of species and
ecosystem diversity. Remaining natural forests having a high wilderness value are also
identified.

Optimum networks of forests for species conservation are identified. Moreover, the extent
to which forest species diversity is represented within the current protected areas system is
examined in order to identify additional species conservation requirements. The sizes of the
datasets used for the analyses of species diversity are considered in the following subsections.

6.1.1 Forests

A total of 204 legally designated forests and other state forests (OSFs) were surveyed for
woody plants and selected animal groups, of which only 81 (40%) were adequately
inventoried according to the criteria described in Section 4.3.3. In the case of the remaining
123 sites (60%), the number of new species recorded in the penultimate or last plot exceeded
the 5% threshold. The 204 surveyed forests are listed in Annex 5, together with an indication
of whether or not they were adequately surveyed. These forests comprised a total of 138
units of contiguous forest, details of which are also given in Annex 5.

6.1.2 Gradsects and plots

A total of 1,725 plots were inventoried along 310 gradsects within the 204 designated forests.
The distribution of these plots is shown superimposed on the new 1:50,000-scale forest map
in Figure 6.1. It should be noted that 44 plots (2.5%) are absent from this map because their
geographic coordinates were not recorded in the field.

6.1.3 Flora and fauna

All analyses were restricted to indigenous, forest species. Thus, exotics were excluded from
the woody plants dataset, and both exotics and species associated with predominantly non-
forest habitats were excluded from the animals dataset. The distribution of indigenous woody
plant and animal species with respect to individual surveyed forests is summarised in
Volume 2 of this report, together with their endemic status, as appropriate.

Species recorded opportunistically outside plots were excluded from all analyses. In the case
of animals, this amounted to 605 records.

The sizes of the plant and animal datasets, including the number of identified records and
species, are given in Table 6.1 according to various criteria. In the case of woody plants, the
76 unidentified records comprise 47 of unknown genera, and 29 of known genera but
unknown species. In the case of animals, the 2,287 unidentified records comprise 63 of

93

Biodiversity Inventory Plots
PAE N

CLOSED CANOPY FORESTS *
GRADSECT PLOTS

* includes mangrove and
riverine dry forests.

CM 81 degrees, Lat of Centre Proj 8 degrees

Figure 6.1 Distribution of plots (100 m x 5 m) sampled during the NCR.

94

unknown genera, and 2,224 of unknown species of known genera. None of these records of
unidentified woody plants or animals was used in analyses.

A breakdown of identified and unidentified records of animals by higher taxa shows that
molluscs accounted for most (86%) of the 2,287 unidentified records (Table 6.2). Molluscs
were the least well identified animal group, with only 48% of records completely identified.
Eleven percent of reptile and 8% of amphibian records were not fully identified. At the
generic level, however, the level of identification was very high (99.8% of all animal
records), with a total of only 63 records unidentified.

Table 6.1 Sizes of plant and animal datasets derived from the NCR. Records used in the analyses
are emboldened. *.dbf refers to the name of the database file within EIMS.

Datasets Plants Animals
PltDat.dbf AniDat.dbf

No. records identified 70,472 30,498
No. records unidentified 76 2,287
Total no. records 70,548 32,785

No. species identified
No. species unidentified

Total no. species

No. records of forest species identified
No. records of forest species unidentified
Total no. records of forest species

No. forest species identified
No. forest species unidentified
Total no. forest species

“The 64 records of indeterminate forest plant species were included in the analyses because they were considered
to be different species from those identified.
* The 24 records of indeterminate forest animal species were included in the analyses because they were considered
to be different species from those identified.

Table 6.2 Unidentified animal records classified by higher taxa

Higher taxon No. records

a a a

Amphibians

95

Of the 19 unidentified animal species, 17 were molluscs, the others being a bird (swift) and
an amphibian. Of the five unidentified forest animal species, all of which were included in
the analysis, three are likely to be new species (two species of the reptile Ceratophora and
a species of the amphibian Bufo). The others are species of Rhacophorus (amphibian) and
Beddomea (mollusc).

6.2 SPECIES DIVERSITY
6.2.1 Individual forests
All species

A total of 1,153 species of woody plants and 410 species of animals (vertebrates, molluscs
and butterflies) were recorded within the 204 surveyed forests. Species recorded within
individual forests are listed in Volume 2 (Annexes 1 and 2, respectively).

The biodiversity within each forest is summarised in Annexes 6 and 7 for woody plants and
animals, respectively. In the case of woody plants, 108 forests are required to conserve all
1,153 species. Of the remaining 96 forests which do not contribute any additional species to
the network of 108 forests, only N=31 were adequately surveyed. Thus, additional surveys
are needed before managing any of the 65 forests for purposes other than conservation, to
avoid the possibility of any negative impact on as yet unrecorded elements of their
biodiversity. Details of this analysis are given in Volume 2 (Annex 3).

The results of a similar analysis for animal species (Volume 2, Annex 4) show that all 410
species are represented within 72 forests. All but 25 of these forests are included in the
minimum network of forests required for woody plant species. In other words, woody plant
and animal diversity is represented within a total of 133 of the 204 forests, but this overlooks
the fact that some forests were inadequately sampled for woody plants and that the faunal
surveys were not comprehensive.

Endemic species

Restriction of the analysis to endemic species shows that 49 forests are necessary for all 455
endemic species of woody plants to be represented (Annex 5, Volume 2) and 35 forests for
all 138 endemic animal species (Annex 6, Volume 2). Endemic woody plant and animal
diversity is represented within a total of 71 of the 204 forests. There is much less
complementarity between minimum forest networks for endemic woody plants and endemic
animals than in the case of all species. This is likely to reflect the larger number of endemic
animal species found in the dry zone compared with endemic woody plant species.

6.2.2 Contiguous forests

Given the principle that conservation areas should be as large as possible, contiguous forests
were grouped and treated as single units for analysis purposes. Of the 138 units of contiguous
forest, the largest are:

Wet zone
¢ Bambarabotuwa (outlier just south of Central Highlands)

96

e Central Highlands (stretching from Peak Wilderness in the west to Horton Plains in
the east and north to Hakgala)

¢ KDN (comprising Kanneliya, Dediyagala and Nakiyadeniya)

e Pedro (north of Nuwara Eliya)

e Sinharaja (comprising 13 forests and including Dellawa and Diyadawa to the south
and Handapan Ella to the east)

Wet/Intermediate zones
e¢ Knuckles/Wasgomuwa (Knuckles Range and adjacent Wasgomuwa)

Intermediate/Dry zones
¢ Puswellagolla (immediately north of Knuckles Range)

Dry zone
e Ruhuna/Yala (Ruhuna, Yala and adjacent forests)

All species

Woody plant diversity (1,153 species) is fully represented within 76 of the 138 contiguous
forests (Volume 2, Annex 7). Of the balance of 62 forests, 42 were inadequately sampled.

_In the case of animals, all 410 species are represented within 48 contiguous forests
(Volume 2, Annex 8). All but 14 of these units are included in the minimum system of
forests required for all woody plant species. In other words, woody plant and animal
diversity is represented within a total of 90 of the 138 contiguous forests.

The distribution of these contiguous forests is shown in Figures 6.2 and 6.3 for woody plants
and animals, respectively.

Endemic species

Restriction of the analysis to endemics shows that 36 of the 138 contiguous forests are
necessary to conserve all 455 endemic species of woody plants (Volume 2, Annex 9) and 23
units for all 138 endemic animal species (Volume 2, Annex 10). Endemic woody plant and
animal diversity is represented within a total of 48 of the 138 contiguous forests (i.e. 12 units
in addition to the 25 units having a full complement of endemic woody plants).

The distribution of these contiguous forests is shown in Figures 6.4 and 6.5 for endemic
woody plants and endemic animals, respectively.

6.2.3 Optimum networks for species diversity

The results of the analyses in the previous section are summarised in Table 6.3. They
indicate the potential cost of conserving biodiversity, in terms of total land area of forest to
be conserved, for a range of options. At the very least, priority must be given to conserving
the full range of Sri Lanka’s endemic forest species, ideally within a system of larger rather
than smaller forests in accordance with principles of conservation biology (Section 1.4.2).
Thus, a network of 36 contiguous forests for endemic woody plants, complemented by an
additional 12 for endemic fauna, should be considered an absolute minimum for conserving
Sri Lanka’s endemic forest species.

97

Table 6.3 Minimum sets of individual forests and contiguous forests necessary for 100%
representation of forest vee

Taxon pa set of forests No. Reference
en unselected (Volume 2)
iu byaarentie! OL | forests
inadequately
eee cn sareyas

Individual forests (N = 204)

frame | ato | 72 | nov avaitabie | at Armes

Much of the species diversity can be represented within a small set of the larger contiguous
forests. For example, the following set of eight units of contiguous forest:

e Bambarabotuwa e Knuckles/Wasgomuwa
e Central Highlands e Pedro

e Gilimale-Eratne e Ruhuna/Yala

e KDN e Sinharaja

account for:

¢ at least 79% of woody plant diversity (see Volume 2, Annex 7),
e at least 88% of endemic woody plant diversity (see Volume 2, Annex 9),

at least 83% of faunal diversity (see Volume 2, Annex 8), and
at least 85% of endemic faunal diversity (see Volume 2, Annex 10).

Essentially, this set of contiguous forests represents KDN, Sinharaja complex and much of
the south-central massif (stretching from the Central Highlands north to Pedro and beyond
to the Knuckles Range) in the wet zone, Wasgomuwa in the intermediate zone and
Ruhuna/ Yala in the south-east dry zone.

6.2.4 Species represented in existing protected forests

Given that any optimum protected areas system will be designed around protected areas that
have already been established, it is instructive to examine the extent to which the present
system is representative of species diversity. Of the 204 designated forests inventoried, 54
are currently protected, 33 being conservation forests in the forestry subsector (see
Table 2.8) and 21 being protected areas in the wildlife subsector. National biosphere reserves
are not taken into consideration, unless they happened to be within conservation forests,

98

Woody Plants of Sri Lanka | | KEY
2S

CLOSED CANOPY FORESTS *

| | | ME FORESTS IMPORTANT
ie FOR WOODY PLANT
SPECIES

GRADSECT PLOTS

DESIGNATED AREAS
___ WILDLIFE SECTOR
"| FOREST SECTOR

* includes mangrove and
riverine dry forests.

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees February 1997

Figure 6.2 Minimum network of contiguous forests in which all 1,153 species of woody
plants are represented.

99

Animals of Sri Lanka | | KEY
a aN | | |

CLOSED CANOPY FORESTS *

| MD FORESTS IMPORTANT
FOR ANIMAL SPECIES

GRADSECT PLOTS

DESIGNATED AREAS
__ WILDLIFE SECTOR
"| FOREST SECTOR

* includes mangrove and
riverine dry forests.

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 6.3 Minimum network of contiguous forests in which all 410 species of animals are
represented.

100

Endemic oe Plants of Sri Lanka | KEY

CLOSED CANOPY FORESTS *

| MI FORESTS IMPORTANT
FOR ENDEMIC WOODY
PLANT SPECIES

GRADSECT PLOTS

DESIGNATED AREAS
_ WILDLIFE SECTOR
|_| FOREST SECTOR

* includes mangrove and
riverine dry forests.

|

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 6.4 Minimum network of contiguous forests in which all 455 endemic species of
woody plants are represented.

101

Endemic Animals of Sri Lanka | | KEY
: |

eo ii CLOSED CANOPY FORESTS *

| MB FORESTS IMPORTANT
FOR ENDEMIC ANIMAL
SPECIES

GRADSECT PLOTS

DESIGNATED AREAS
WILDLIFE SECTOR
|__| FOREST SECTOR

* includes mangrove and
riverine dry forests.

WORLD CONSERVATION
MONITORING CENTRE

100km

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 6.5 Minimum network of contiguous forests in which all 138 endemic species of
animals are represented.

102

because most are small core areas (<1,000 ha) within forest or proposed reserves that were
not necessarily inventoried, per se.

The number and percentage of woody plant and animal species represented within existing
protected forests are summarised in Table 6.4. The analysis shows that existing protected
areas account for nearly 85% or more of forest species diversity, in terms of both endemic
and all species of woody plants and animals. Inevitably, a larger number of forests are
required for all species to be represented than when defining an optimum set of forests
without any preconditions, as shown in Section 6.2.1. However, two important conclusions
can be drawn from a comparison between the two sets of analyses summarised in Tables 6.3
and 6.4:

e Existing protected forests tend to complement each other with respect to both woody
plant and animal species. For example, when selecting protected areas a priori, the
number of forests required for 100% representation of woody plant species is 121
(Table 6.4), only 13 more than the minimum set of 108 forests (Table 6.3).

e Existing protected forests fall far short of endemic species’ requirements. Although
the 54 existing protected areas contain 90% and 85% of endemic woody plant and
animal species, respectively (Table 6.4), this set vastly exceeds the minimum number
required for 100% representation of either endemic woody plants or endemic animals
when selecting protected areas a priori (Table 6.3). For example, it is double the
minimum set of 35 forests necessary for representation of all endemic animal species.

Table 6.4 Number of woody plant and animal species represented within existing protected forests

Total no. Peneceess 2 in 54 No. additional Reference

species Peneceess 2 forests forests required | (Volume 2)
for 100% species

Be % total representation
species

67 | Annex 11
26 | Annex 13

6.3 GAP ANALYSIS
6.3.1 Forest types

The distribution of forest types in relation to the designated areas network is shown in
Figure 6.6. The results of this gap analysis are summarised in Table 6.4. Overall, 31% of
natural forests are represented within protected areas and double this percentage lies within
designated areas. Individual forest types are well represented (nearly 30% or more) within
protected areas, with the exception of mangroves which are limited in extent (8,722 ha) and
poorly represented in both protected and designated areas (8% in either case). Better
representation of mangroves in protected areas can be achieved only by upgrading OSFs to
conservation forest status.

103

Although well represented (49%) in protected areas, montane forests also have a very limited
distribution, covering just 3,121 ha. Given the fragility of montane environments, the
valuable contribution of cloud forests to maintaining hydrological regimes (Section 5.5), and
their rare and often endemic flora and fauna, there is a strong case for strictly protecting all
montane forests. This is readily achievable because the balance lies with proposed reserves,
all of which could be designated as conservation forest or even national heritage wilderness
areas under existing forest policies and/or legislation.

Of the other forest types, riverine dry and sub-montane forest are the least extensive
(<100,000 ha), albeit well represented (>46% and 43%, respectively) in protected areas.
There is considerable opportunity for increasing their representation since, in both cases, one
third lies within forest and proposed reserves.

These results underestimate by about 0.6% (9,100 ha) the extent of closed canopy forest that
is protected for two reasons. First, the designated areas coverage for Sinharaja is based on
the boundaries of the original Sinharaja forest and proposed reserves, totalling 9,581 ha,
rather than the National Heritage Wilderness Area (11,187 ha). Secondly, this coverage does
not include the seven OSFs, covering approximately 7,500 ha, that have been designated
conservation forest.

6.3.2 Wilderness

Designated areas superimposed onto a wilderness map of Sri Lanka are shown in Figure 6.7.
Comparison of this wilderness map with the forest cover map (Figure 6.6) is illuminating on
several accounts:

e The wilderness quality of the extensive closed canopy forest in the north of the island
is not as high as might be anticipated. This reflects the proximity of settlements and
roads to these forests.

e The east-central portion of the island, notably in the vicinity of Madura Oya National
Park and adjacent Nuwaragala Forest Reserve and Baron’s Cap Proposed Reserve,
has a high wilderness value despite its closed canopy forest being less extensive and
fragmented. This reflects the relative absence of settlements and roads in this region.

¢ None of the closed canopy forest in the wet zone comprises high quality wilderness.
The Central Highlands, Knuckles, KDN and Sinharaja forest complexes all fall within
Category 3 (Medium-High). Being hill or mountain ranges, their forested slopes lie
close to settlements and roads in the lower catchment areas.

104

Natural Forests of S

ri Lanka

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

KEY

Hl MANGROVE
RIVERINE DRY FOREST

CLOSED CANOPY FOREST

DRY MONSOON FOREST
LOWLAND RAIN FOREST
Ml MOIST MONSOON FOREST
2 SUB-MONTANE FOREST
@2= MONTANE FOREST

DESIGNATED AREAS
_| WILDLIFE SECTOR
|__| FOREST SECTOR

50

WORLD CONSERVATION
MONITORING CENTRE

100km

February 1997

Figure 6.6 Designated areas superimposed on the 1:50,000-scale forest map of Sri

Lanka (Legg and Jewell, 1995).

105

Wilderness Index of Sri Lanka

KEY

a] High Wilderness
EE

Low Wilderness

DESIGNATED AREAS
___ Wildlife Sector

|_| Forest Sector

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 6.7 Designated areas superimposed on a wilderness map of Sri Lanka.

106

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PAdaSIY
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Aaenjoues aAsasay JINjeN) yaeg jeuonen

uoneAsrasuoD, aasasay pasodoig

PAdISIY SIO NOISY OLLSIHOTA

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The results of a gap analysis are summarised in Table 6.5. High quality wilderness
(Category 4) is most extensive in the eastern parts of the country where large proportions are
represented within:

e Wasgomuwa National Park,

¢ Madura Oya National Park and adjacent Nuwaragala Forest Reserve and Baron’s Cap
Proposed Reserve,

¢ Gal Oya National Park and adjacent Gal Oya Valley North-East Sanctuary and
Nuwaragala Forest Reserve,

e¢ Panama Proposed Reserve,

e Ruhuna National Park and adjacent Yala East National Park and Kumbukkan Forest
Reserve’, and

e Uda Walawe National Park.

The other major tracts of Category 4 wilderness are in the north-west, mostly within Wilpattu
National Park.

Nearly 50% of Category 1 wilderness is represented within protected areas, and there is

considerable potential for ensuring that two-thirds of Category 1 is protected by upgrading
its conservation status within forest and proposed reserves. Priority should also be given to

_ protecting as much as practicable of the remaining Category 1 wilderness that lies outside
designated areas, notably:

e wilderness west of Baron’s Cap Proposed Reserve (sparse forest),

e wilderness north of Gal Oya National Park (closed canopy forest),

e wilderness between Ruhuna (Block IV) National Park and Kumbukkan Forest Reserve
(closed canopy forest), and

e Samanalawewa wilderness north-west of Uda Walawe National Park (little closed
canopy forest but minimal infrastructural development).

Samanalawewa is a particularly interesting area, described in the 1960 Colombo Plan Survey
as wild, rugged, inaccessible and almost uninhabited. Such conditions still prevail except for
the construction of a dam below the confluence of the Walawe Ganga with the Belihul Oya
(Karunaratne, 1992).

Medium-high wilderness (Category 3) is well represented (20%) within protected areas, much
of it providing a buffer to high wilderness areas. There is scope for doubling this level of
representation by upgrading the conservation status of existing forest and proposed reserves
(Table 6.5).

Much of the south-west of the island falls within the medium-low wilderness category,
reflecting the characteristic developed landscapes of coconut, rubber and tea plantations,
intermingled with home gardens and paddy. Albeit low in species biodiversity, such
landscapes are likely to be high in genetic diversity with respect to crop varieties and
remnant specimens of native flora, as well as having important cultural values.

i According to data held in EIMS, which are based on the Forest Department register, Kumbukkan is a proposed reserve, but in the
National Forest GIS it is labelled as a forest reserve in accordance with the Department’s Ordinance Survey records.

109

6.3.3 Floristic regions and soil-edaphic units

The distribution of floristic regions in relation to the designated areas network is shown in
Figure 6.8. The analyses of floristic regions and, in the case of the dry/arid lowlands, soil-
edaphic units show a number of major gaps in the existing protected areas network in terms
of its representativeness (Table 6.6). Nearly half of all regions are poorly represented (i.e.
<10%), as follows:

III Northern intermediate lowlands

V Northern wet lowlands

VII _ Southern lowland hills

VIII Freshwater bodies

XI Kandy and Upper Mahaweli

XIII Central Mountains, Ramboda, Nuwara-Eliya

In the case of Floristic Regions III, V, VII and XI, there is very limited opportunity to
increase representation within protected areas because very little of the original natural forest
remains within these regions. Even if all forest and proposed reserves were upgraded to
conservation forest, protected areas coverage would only exceed 10% for Region VII
(southern lowland hills). The most under-represented region is V: only 0.1% of the northern
wet lowlands of Colombo and adjoining districts lie within protected areas, and a total of
1.4% within designated areas. However, there is considerable scope for increasing
representation of Region XIII (Central Mountains, Ramboda, Nuwara-Eliya), principally by
upgrading some of the proposed reserves (e.g. Kikilimana and Pedro) to conservation forests.

Importantly, the analysis shows that all regions of limited extent (i.e. XII Knuckles, XIV
Adam’s Peak, XV Horton Plains, all of which cover <50,000 ha) are well represented in
protected areas, the exception being VIII (freshwater bodies) in the wet zone (but not the dry
zone - see below). It is not within the scope of this project to consider wetland conservation,
but it has been addressed by a Wetland Conservation Project, ongoing at the time of the NCR
and undertaken by the Central Environmental Authority with support from DGIS, The
Netherlands.

II Dry and arid lowlands

As discussed in Section 4.4.3, the floristic classification defines the dry zone as a single
region (II) which is too coarse for conservation planning purposes. Indeed, reference to
Table 6.6 shows that, as a whole, this region is well represented (17%) within protected
areas.

However, sub-division of this floristic region into soil-edaphic units reveals some significant
gaps in representation, with three units poorly represented (i.e. <10%) as follows:

e 2 Sodic, saline, alkali soils
e 3 Sandy regosols
e 4 Grmmusols

Zones 2 and 4 have a particularly limited distribution, covering some 32,000 ha and 39,000
ha, respectively. Closed canopy forest has largely disappeared from these three units
(Figure 6.6) and wilderness values are low (Figure 6.7), except along the coast of the Jaffna
peninsular where infrastructural development within Zone 3 is less intensive (i.e. Category 3
wilderness).

110

Floristic Regions and Soil Zones

Floristic
Region

DESIGNATED AREAS

(| WILDLIFE SECTOR
[| FOREST SECTOR

(WORLD CONSERVATION

MONITORING CENTRE
100km

Projection Lambert Azimuthal, l ———— —

CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 6.8! Designated areas superimposed on floristic regions. The dry and arid
lowlands region is further classified into edaphic zones.

111

6.4

CONCLUSIONS AND RECOMMENDATIONS

Species diversity

1. Conservation forests should be as large as possible for the long-term maintenance of

genetic and species diversity. Much of Sri Lanka’s biodiversity is represented in the
larger forests, particularly those in the wet zone. Every effort, therefore, should be
made to ensure that the largest remaining forests in the wet zone are designated in
their entirety as conservation forest, notably:

e Bambarabotuwa e Knuckles/Wasgomuwa
e Central Highlands e Pedro

e Gilimale-Eratne e Sinharaja

e KDN

. At the very least, all endemic forest species should be represented within the protected

areas system. Based on known species distributions derived from the NCR, 42 forests
will need to be protected in addition to those already designated as protected areas
(Annexes 13 and 14, Volume 2).

. Ideally, all forest species covered by this study should be represented within the

protected areas system. It is recognised, however, that this priority will need to be
rationalized alongside other conservation priorities, as discussed further in Chapter 7.

Ecosystem diversity

4. On the basis of their limited extent and, in the case of mangroves, low level of

representation within existing protected areas:

¢ protection of mangroves should be maximised by designating as much OSF as
possible as conservation forest.

¢ all montane forest should be strictly protected by upgrading the status of proposed
reserves to conservation forests, or even national heritage wilderness areas.

. High quality wilderness should form the inner core of protected areas, being areas

least likely to be subjected to human impact. Where appropriate and feasible, priorities
are:

© to upgrade forest and proposed reserves containing Category 4 wilderness to
national heritage wilderness areas.

© to protect Category 4 wilderness that presently lies outside designated areas.

¢ to ensure that Category 4 wilderness is buffered by Category 3 wilderness,
preferably within protected areas.

112

6. The existing protected areas system is not sufficiently representative of the main
floristic regions or, in the case of the dry zone, soil-edaphic units. Where
opportunities exist, priorities are:

¢ to increase representation of Floristic Regions III, V, VII and XI within protected
areas.

e to increase representation of Floristic Region XIII (Central Mountains etc) within
protected areas by upgrading the status of reserves such as Kikilimana and Pedro
to conservation forests.

© to increase representation of soil-edaphic units 2, 3 and 4 within protected areas,

particularly in the case of the Category 3 wilderness along the east coast of the
Jaffna peninsular in Zone 3.

ANS)

Chapter 7
WATERSHED PROTECTION AND BIODIVERSITY CONSERVATION
DRL YESS PEAY, SN SATIN 7a ITE A

7.1 INTRODUCTION

In the first part of this final chapter, the relationship between the importance of natural
forests for watershed protection, in terms of soil protection and flood control, and
biodiversity conservation is examined in order to determine the extent to which these
attributes are complementary. Obviously, conservation planning will be more cost effective
with respect to land required for conservation if forests important for watershed protection
are also those rich in biodiversity, including species.

In the second part of this chapter, criteria for designing an optimum system of conservation
forests are considered and applied to the findings from the NCR. Future measures necessary
to establish an optimum system are briefly discussed in the concluding section.

7.1.1 Datasets used to compare watershed and biodiversity values

Although it was intended that all natural forests should be evaluated for their soil and water
conservation importance and their biodiversity value, this was not entirely practicable. The
biodiversity surveys took much longer; moreover, it was not possible to survey biodiversity
within all forests due to ongoing LTTE activities in the north and east of the country. Also,
a number of forests were included in the biodiversity survey after the soil and water
conservation assessment had been completed. The sizes of the datasets are summarised in
Table 7.1.

Table 7.1 Number of forests assessed for soil and water conservation importance and inventoried
for species diversity

Survey Individual forests Contiguous forests

Soi/water conservation survey
Biodiversity survey
r

Note: These summary statistics are derived from data in Table 7.2.

Analyses in this chapter are limited to contiguous forests, given the hydrological and
biological importance of conserving as large fragments of remaining natural forest as
possible, especially with respect to the wet zone where cloud forests are singularly important
for fog interception and moist forests for endemic species of woody (and other) plants and
animals.

114

7.2 AN INTEGRATED APPROACH TO CONSERVATION
7.2.1 Relationship between watershed protection and species diversity

As shown in Figures 7.1 and 7.2, respectively, both total soil erosion and flood control are
closely related to biodiversity, measured in terms of woody plant species. The main
determinants of these close relationships are likely to be rainfall and altitudinal range, both
of which strongly influence species diversity. Thus, forests with steep terrain (i.e. high
altitudinal range) and high rainfall support a greater wealth of species and are more important
for soil protection and flood control than forests with a fairly level terrain and low rainfall.
These findings are consistent with results from other studies which show that species richness
is closely related with climatic and physiographic parameters (Allen, 1992).

It should be possible, therefore, to predict species diversity from importance for watershed
protection (i.e. soil protection and/or flood control), the advantage being that the latter
assessment is much more rapid than the former. Such predictions have limited value,
however, because they are concerned only with total diversity. Species distribution patterns
are not predicted, preventing minimum forest networks from being defined for biodiversity
conservation.

The relative importance of contiguous forests with respect to total soil erosion, flood hazard
and biodiversity is shown in Figure 7.3.. Flood hazard is plotted on the -y axis to facilitate
direct comparison with total erosion (y axis). In general, as woody plant species diversity
diminishes along the x axis, so does importance for soil protection and flood control along
the y and -y axes, respectively. The four most important contiguous forests, as shown left
to right in Figure 7.3, are Central Highlands, Sinharaja, Knuckles and KDN.

7.2.2 Priorities for watershed protection and species diversity conservation

The results of the soil and water conservation assessment and biodiversity survey are
summarised for each unit of contiguous forest in Annex 8 on the basis of their importance
for soil erosion, flood control, fog interception, woody plant species, endemic woody plant
species, animal species and endemic animal species. Of the 224 units of contiguous forest,
203 were assessed for soil and water conservation and 138 were inventoried for species
(Table 7.1).

Units of contiguous forest were prioritised for conservation according to the following
criteria:

e Highest importance
- exceed thresholds for both soil erosion and flood hazard, or
- intercepts water from fog (i.e. located above 1,500 m), or
- included within a minimum network of contiguous forests for woody plant species
or selected groups of animal species.

e Important
- exceed thresholds for either soil erosion or flood hazard

115

=~
a
“
>
=
1
os
£
~
2
S
42)
an
iS)
-
cs)
sg
°
=

No. woody plant species

Figure 7.1 Relationship between total soil erosion and woody plant diversity for 118 units
of contiguous forest

Flood hazard (m3 s-1)

e
; e @ee
e é = @ ry |
0
0 100 200 300 400 500 600
No. woody plant species

Figure 7.2 Relationship between flood hazard and woody plant diversity for 118 units of
contiguous forest

116

LIT

JSAJOJ SNONSIUOS JO syUN gy] JOJ AyssoAp queyd Apoom pue piezey Pooy ‘UOIsOIa |1Os [e}0] UdaMIJaq sdiysuONeaYy ¢*z BNI

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a
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i
a
ik
i}
r=!
=
(=|
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a7)
°
=
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Flood hazard (m3 s-1)

51 61 71 81

Woody plant species rank

e Lowest importance
- below thresholds for both soil erosion and flood hazard, and
- negligible interception of water from fog (i.e. located below 1,500 m), and
- not part of a minimum network of contiguous forests for woody plant species or
selected groups of animal species.

In the case of contiguous forests of highest importance, a further distinction was made to
prioritise those important for endemic species over and above those important for non-
endemic species. Thus, contiguous forests exceeding both soil erosion and flood hazard
thresholds, or intercepting fog or part of a minimum network for endemic species were
considered top priority for conservation.

Units of contiguous forest are listed according to these criteria in Table 7.2. By far the
majority (104) are of highest importance for conservation. The distribution of these
contiguous forests is mapped in Figure 7.4. With the exception of a few small fragments, all
contiguous forests in the wet zone are included within this minimum network, together with
the extensive Ruhuna/Yala unit in the south-east and several small units to the north. This
minimum network covers 516,795 ha, or 7.8% of total land area. Although this equates to
only half of the existing protected areas system, much of it is located within the wet zone
where pressures on land for agriculture and other purposes are enormous.

Options to further reduce this minimum network are limited, particularly if the integrity of
adjacent forests is to be maintained. One option would be to focus on endemic species,
possibly at the risk of some non-endemic species becoming extinct, perhaps within the next
half-century. A network of top priority contiguous forests for watershed protection and
conservation of endemic species comprises a total of 70 contiguous forests (Table 7.2), which
are mapped in Figure 7.5. Although the number of contiguous forests is reduced by about
one-third, the network is still very expansive and covers 490,193 ha, or 7.4% of total land
area. In fact, differences between Figures 7.4 and 7.5 are minor. For example, only a few
of the small forests in the south of the wet zone are not part of the minimum network for
endemic species.

118

Table 7.2 Importance of units of contiguous forest for watershed protection and species
conservation. Top priority forests in the highest importance category are listed in capitals.

Highest importance (N=104)/TOP PRIORITY (N=70)

EMD No./Name EMD No./Name EMD No./Name
7 AMANAWALA-AMPANE -161 KALAHALLA-PALLEKELE (N=2) 327 OHIYA

636 Aruwewa
509 AUWEGALAKANDA
24 BADULLAKELE

-28 BAMBARABOTUWA (N=5)

511 BAMBARAWANA

589 Begahapatana

37 BERALIYA (AKURESSA)
38 BERALIYA (KUDAGALA)
-39 BIBILEHELA (N=2)

44 Bundala
552 BUTAWELLA

-140 CENTRAL HIGHLANDS (N=16)

556 CHILAW LAKE
57 DAMBULUWANA
60 DANDENIYA-APAREKKA
515 DEDUGALLA-NANGALA
575 Dewagiriya
78 DOLUWAKANDA
80 Dunkanda
660 Elagamuwa
96 GAL OYA
101 Galgiriyakanda
534 GALLELETOTA
112 GILIMALE-ERATNE
544 GORANGALA
536 Hapugala
128 HARASBEDDA
539 Hataramune
-129 HAYCOCK (N=2)
136 HINNA
507 HOMADOLA
138 HORAGALA-PARAGALA
146 INDIKADA MUKALANA
147 Ingiriya

Important Forests (N=45)

EMD No./Name

4 Alapalawala

11 Anaolundewa
527 Angamana
605 Balanagala
513 Batahena
568 Beliyakanda
516 Boralugoda

72 Demanagammana
500 Derangala
548 Dumbara
580 Dummalahela
-96 Gal Oya Valley (N =6)
540 Galbokaya
538 Gallegodahinna
566 Gosgahapatana

497 KALUBOWITIYANA
655 KALUDIYAPOKUNA
166 KALUGALA

184 KARAWITA

-175 KDN (N=6)

190 Kekanadura

191 KELANI VALLEY
526 Keulakada Wewa

197 KIKILIMANA

550 KIRIBATGALA

585 Kitulhela

-522 KNUCKLES /WASGOMUWA (N=11)
-208 KOMBALA-KOTTAWA (N=2)

531 KUDAGODA
217 KUDUMIRIYA
535 Kuragala

498 Kurulugala
657 Kurulukele

222 LABUGAMA-KALATUWANA

241 MAGURUGODA

-253 MALAMBURE (N=2)
256 Manapaya

-164 Mangroves (N=3)

263 Masmullekele

502 MEDIRIGIRIYA TULANA
572 Menikdeniya

-281 Mineriya (N=2)

280 Minneriya-Giritale

279 MINNERIYA

525 Miyandagala _

581 MONERAKELLE

293 MULATIYANA

306 NAMUNUKULA

537 NARANGATTAHINNA

EMD No./Name

598 Gunner’s Quoin
519 Guruyalle

543 Handuwelkanda
133 Hidellana-Weralupe
508 Hindeinattu

142 Hurulu

520 Illukkanda

157 Kadawatkele

611 Keeriyagolla

610 Kithedallakanda
169 Kumburugamuwa
221 Kurana Madakada
609 Madigala

239 Maduru Oya Block |
565 Makulussa

Lowest important forests (N=75)

EMD No./Name

10 Ambanmukalana
567 Amsawagama
637 Andarawewa
654 Arangala
554 Aruakalu

17 Attavillu
597 Badanagala

27 Bakinigahawela
630 Bogodayagama
593 Bolhindagala

45 Campbell's Land

62 Darakulkanda

66 Degadaturawa
631 Dematawewa
579 Diggala
586 Diggalahela
642 Galmaduwa
-640 Getamalagamakanda (N =2)
594 Golupitiyahela
584 Guruhela
131 Henegedaralanda
518 Hopewell
-144 Inamaluwa (N=2)
160 Kahalla
170 Kananpella

EMD No./Name

177 Kanugollayaya
178 Kanumuldeniya
639 Katupotakanda
201 Kirinda Mahayayakele
653 Kokkebe

577 Korathalhinna
656 Kosgahakele
596 Kudagala North
601 Kumadiya Tulana
633 Labunoruwa

582 Lolehela

232 Ma Eliya

237 Madunagala

247 Mahakanda

599 Mahamorakanda
249 Mahapitakanda
635 Manawewakanda
272 Marakele

643 Marasinhagama
558 Masawa

517 Matinapatana
646 Medalassa Korale
278 Mihintale

277 Mihintale

285 Miriyagalla

119

329 OLIYAGANKELE

333 Padawiya

-343 PANILKANDA (N=2)
-362 PEDRO (N=3)

376 Potawa

-573 PUSWELLAGOLLA (N=4)
595 Radaliwinnekota

383 RAGALLA

384 Rajawaka

388 RAMMALAKANDA
390 RANWARAGALAKANDA
392 RAVANA ELLA

394 RILAGALA

395 RITIGALA

-398 RUHUNA/YALA (N=8)
407 SELLANKANDAL

514 SEMBAWATTE

-414 SINHARAJA (N=14)
532 Talawegoda

426 TANGAMALAI

432 TIBBUTUKANDA

506 TIBORUWAKOTA

570 Tottawelgola

576 ULGALA

588 Wadinahela

-455 WALANKANDA (N=8)
659 WATHURANA

463 WEDAKANDA

464 Wedasitikanda

471 Welihena

652 Wellamudawa

-487 YAGIRALA (N=3)

489 YAKDESSAKANDA

EMD No./Name

504 Masimbula

269 Meegahatenna

281 Minneriya-Giritale Block |
533 Mulgama

294 Muwagankanda

318 Neugalkanda

389 Ranwala

438 Uda Walawe

443 Ulinduwewa

583 Velihela

452 Victoria~-Randenigala-Rantambe

458 Wanniyagama
465 Weerakulicholai-Elavankulam
521 Wewegalatana
510 Yakdehikanda

EMD No./Name

591 Murutukanda

602 Mutugalla Tulana
-305 Namaneliya (N=2)
638 Pahala Mawatawewa
650 Pallankulama

600 Palliyagodella Tulana
645 Puliyamkulam

634 Puliyankulama

647 Ranawekanda

590 Randeniya

632 Ratmale Kanda

404 Sangappale

-406 Sellandkandal (N=2)
651 Semewa

603 Sinnakallu

592 Sitarama

553 Talpattekanda

644 Tambaragalawewa
629 Tambutakanda

442 Udawattakele

578 Ulgala (old)

453 Viharekele

604 Viyanahela

587 Westminster Abbey
496 Yoda Ela

Watersheds, Plants and Animals KEY
: CLOSED CANOPY FORESTS °

UNSURVEYED

SURVEYED - LOW CONSERVATION
PRIORITY
HB SURVEYED - HIGH CONSERVATIO

PRIORITY FOR WATERSHEDS,
PLANTS AND ANIMALS

DESIGNATED AREAS

___ Wildlife Sector

|_| Forest Sector

* includes mangrove and
riverine dry forests.

WORLD CONSERVATION
MONITORING CENTRE

50 100km

Projection Lambert Azimuthal, |
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 7.4 Minimum network of contiguous forests of highest importance for watershed
protection and representation of all 1,153 woody plant species and 410 animal species
recorded in the NCR.

120

Watersheds, Endemic Plants and Animals KEY
| CLOSED CANOPY FORESTS *

== UNSURVEYED
SURVEYED - LOW CONSERVATION
PRIORITY :

HN SURVEYED - HIGH CONSERVATIO
PRIORITY FOR WATERSHEDS,
ENDEMIC PLANTS AND ANIMALS

DESIGNATED AREAS

"Wildlife Sector

lama
___| Forest Sector

* includes mangrove and
riverine dry forests.

‘WORLD CONSERVATION
MONITORING CENTRE

50 100km

Projection Lambert Azimuthal,
CM 81 degrees, Lat of Centre Proj 8 degrees

February 1997

Figure 7.5 Minimum network of contiguous forests of top priority for watershed protection
and representation of all 455 endemic woody plant species and 138 endemic animal species
recorded in the NCR.

121

7.3. DISCUSSION

There has been extensive dialogue involving both the Forest Department and other
governmental and non-governmental sectors to reach consensus on conservation objectives
and priorities. This has been an ongoing, iterative process as evidenced from:

e the declaration of 13 conservation forests (covering some 24,000 ha) soon after the
NCR commenced, based principally on recommendations from the Accelerated
Conservation Review (TEAMS, 1991); and

e the subsequent declaration of Kanneliya and 17 other conservation forests
(covering a total in excess of 25,000 ha) in the low country wet zone, based on the
preliminary results of the NCR (Green, 1995) which were the subject of a seminar
(Liyanage, 1996).

Following the completion of the field work and prior to the final analysis of the data,
further meetings and seminars were held to reach a degree of consensus on the scientific
criteria for defining an optimum system of conservation forests and their priority. The
outcome of those discussions and their application to the results of the NCR are
considered in the next two subsections, respectively.

7.3.1 Selection criteria for conservation forests
Objectives

The objectives of a national system of conservation forests for Sri Lanka are:

to protect important watersheds,
e to conserve biodiversity, and
e to meet cultural, economic and social needs.

Given that biodiversity is defined in terms of the variability within species (genetic
diversity), the variety of living organisms (species diversity) and the variety of biotic
communities within the biosphere (ecosystem diversity), the most important considerations
in designing a system of forests in which to conserve biodiversity are:

¢ maintenance of evolutionary processes, such as hydrological processes, nutrient
cycles, biotic interactions and disturbance regimes;

¢ representation of all native forest ecosystems and seral stages across their natural
range of variation; maintenance of viable populations of all native forest species in
their natural patterns of abundance and distribution; and

¢ responsiveness to short-term and long-term environmental change (after Noss,
1991, 1992).

While the NCR does not contribute directly to identifying economic and social needs,
particularly with respect to those communities living in and around natural forests, an
attempt has been made to identify those forests likely to be under least pressure from
human activities and, therefore, important in terms of their biological integrity and
wilderness value.

122

Criteria

The following set of criteria should guide the selection of an optimum system of
conservation forests. The order in which they are listed below does not reflect their
relative importance, although the first criterion regarding existing protected areas is a
pragmatic measure.

STATUS QUO

Existing protected areas will provide the foundation upon which to establish a system of
conservation forests.

WATERSHED PROTECTION

Forests important for watershed protection will be selected on the basis of:
e their importance for protection of soil from erosion,
e their importance for control of flooding, and

e their importance for interception of fog.

Priorities for watershed protection, in no particular order, are:

e forests having a soil erosion value > 300 t ha! yr!
e forests having a mean annual flood value > 10 ms".
e forests above 1,500 m because of their role in fog interception.

ECOSYSTEM DIVERSITY

In principle, the best way to represent all ecosystems is to conserve the full array of
physical habitats and environmental gradients, from the highest to the lowest altitudes, the
driest to the wettest sites, and across all types of soils, substrates, and topoclimates
(Hunter et al., 1988; Noss 1991).

In the case of Sri Lanka’s forests, ecosystem diversity will be maximised by:

e ensuring that each floristic region is represented within the conservation forests
system, and

e ensuring that each forest type is represented within the conservation forests
system.
Priorities for ecosystem conservation, in order, are (after WCMC, 1996):

© ecosystems unique to Sri Lanka,
e ecosystems for which Sri Lanka holds a significant part of the world total, and

© species-rich ecosystems.
SPECIES DIVERSITY
Species diversity within Sri Lanka’s forests will be maximised by:

¢ ensuring that all forest species are represented.

123

Priorities for species conservation, in order, are (after WCMC, 1996):

endemic, globally threatened species,
e endemic, nationally threatened species,
endemic, non-threatened species,

e non-endemic, globally threatened species,
(with priority to those for which Sri Lanka holds a significant part of the world population)

e non-endemic, nationally threatened species, and
e non-endemic, non-threatened species.

GENETIC DIVERSITY

Genetic diversity within Sri Lanka’s forests will be maximised by:

e ensuring that conservation forests are as large as possible to maintain viable
populations of plants and animals; and

e linking conservation forests via corridors to provide for genetic exchange between
geographically isolated populations, and for the movement of migratory
populations.

Ideally, forests species, particularly endemics, should be represented within at least two
forests as a safeguard from natural or anthropogenic catastrophes. In practice, this can
only be achieved for some species. Many species, notably endemics, have restricted
ranges that have become further reduced through loss of forest habitat. Thus, large size
and provision of corridors provide all the more important means to counter the potential
loss of genetic diversity.

OTHER CRITERIA

Other important considerations are the desirability, indeed necessity, for conservation
forests to provide a wide range of other cultural and socio-economic goods (e.g.
firewood, non-timber forest products) and services (e.g. research, tourism) in support of
local communities and the public.

7.3.2 Optimum system of conservation forests

The results from this study clearly demonstrates the paramount importance of Sri Lanka’s
natural forests, both in terms of their role in maintaining ecosystem stability and functions
and as a reservoir of high species diversity. It has also been possible to identify those
forests of most importance for watershed protection and for biodiversity conservation at
ecosystem and species levels.

Sufficient information, albeit neither always based on adequate samples with respect to
species inventories nor geographically comprehensive, is now available to identify at least
the most important constituents of an optimum system of conservation forests. These
constituent forests are clearly evident from the results of the watershed and biodiversity
analyses in Chapters 5 and 6, respectively. The close degree of complementarity between
the watershed and biodiversity values of forest, as shown in Section 7.2.1, highlights the
importance of such an integrated approach to conservation.

124

Application of the criteria presented in Section 7.3.1 to the results of this study provides a
sound basis for developing an optimum system of conservation forests. General
guidelines, in order of priority, are provided below.

1. As appropriate, use existing protected areas to provide the basis of a conservation
forests system. A prerequisite is to upgrade the legal conservation status of the
Knuckles and 31 other conservation forests.

Based on NCR records, this will ensure that some 80% or more of species
diversity, (90% in the case of woody plant species) is conserved.

2. Protect top priority contiguous forests, as defined in Table 7.2.

This will ensure that the following are conserved:

- forests of importance for soil and water conservation,
- forests of importance for fog interception, and

- forests of importance for endemic species.

3. Protect any outstanding montane forest that is not covered by the previous
measure.

4. Protect-other contiguous forests of highest importance for non-endemic species, as
defined in Table 7.2.

5. Protect other important contiguous forests, as defined in Table 7.2.
This will ensure that the following are conserved:

- forests of importance for either soil or water conservation.

e Where opportunities exist, and in concert with the above measures, maximise
representation of mangroves, Floristic Regions III, V, VII, XI, XIII and soil zones
2, 3 and 4 of Floristic Region IT within the system of conservation forests.

Other guiding principles are as follows:

e Provide for as large conservation forests as possible, particularly in the wet zone
where the role of forests in watershed protection and biodiversity conservation is
crucial. Key units of contiguous forest which should be conserved in their entirety

include:

¢ Bambarabotuwa e Knuckles/Wasgomuwa
© Central Highlands e Pedro

¢ Gilimale-Eratne e Sinharaja

e KDN

e Incorporate as much wilderness as possible within the conservation forests system.

e Plan for ecological corridors as a link between isolated forest fragments,
particularly in the wet zone.

In conclusion, the results of the NCR show that extensive networks of conservation
forests are necessary for full representation of species diversity, even for endemics.

125

Although there is some redundancy, in terms of forests which do not contribute any
species to the optimum system, it is mostly with respect to forests in the dry zone where
species diversity and levels of endemism are lower. Even small forests in the wet zone
have unique species, such as the 18 ha privately-owned Wathurana forest with its several
endemic and other woody plant species that have not been recorded elsewhere (Annex 6).

Given that there is very little redundancy in the wet zone, forests being important for
either woody plants, animals or for protection of watersheds, every effort should be made
to conserve remaining natural forest and maintain the current ban on logging in the wet
zone for the foreseeable future. It is unlikely, however, that such measures will be
adequate to safeguard the entire spectrum of forest biodiversity. It will be necessary,
therefore, to conserve biodiversity though other measures, including private stewardship
of natural forests.

7.4 FUTURE

Ten years on from the first Forestry Master Plan of 1986, when provisions to safeguard
Sri Lanka’s rapidly dwindling natural forests were totally inadequate, future prospects are
much more promising. The ban on logging in the wet zone, introduced in 1990, has
essentially been enshrined within the National Forestry Policy of 1995, which gives
overriding priority to the conservation of biodiversity and protection of watersheds within
forest ecosystems.

In the meantime, the NCR has been completed and now provides a wealth of reliable data
upon which to implement conservation provisions within the new National Forestry
Policy. The results of the NCR presented in this report provide a sound basis for defining
and establishing an optimum system of conservation forests to meet watershed protection
and biodiversity conservation objectives. However, it is neither possible nor, indeed,
entirely appropriate to precisely identify each conservation forest within this optimum
system for two main reasons:

¢ biodiversity information on some forests is either inadequate or totally lacking; and

e cultural, economic and social considerations need to be taken into account as part
of the decision-making process.

The next step, therefore, is for the Forest Department to consider with other sectors
pragmatic ways of addressing the conservation priorities identified in this report, taking
proper account of any socio-economic implications. Importantly, its Environmental
Management Division now has the necessary skills and tools to elaborate further on the
design of an optimum conservation forests system to meet other criteria that may arise
during the implementation process. As demonstrated for a limited number of scenarios in
this report (Section 6.2), the Environmental Information Management System (EIMS)
provides a very powerful tool with which to explore alternative options for biodiversity
conservation and quantify their potential benefits and costs.

In order to further optimise this system of conservation forests, it will be necessary to
carry out additional surveys of forests overlooked by the NCR, as well as those
inadequately inventoried for species. Moreover, any plans to convert natural forest to
other forms of land use or manage it for purposes other than conservation should be
preceded by more detailed biodiversity surveys in order to fully evaluate their impact.

126

|

LOCATION OF SAMPLE PLOTS

AREAS SUBJECTED TO MECHANISED HARVESTING

127

TREE SPECIES DIVERSITY (NOV PLOT)

COMMUNITY USE REQUIREMENT: WILD COFFEE DISTRIBUTION

fE5] Community use/ouffer zone

[=-] Timber production zone
Hy «Ss Nature Reserve

Figure 7.7 Zonation of a forest to meet biodiversity conservation, community and timber
production requirements (Source: Howard, 1995)

128

This should be considered mandatory for any forest either not surveyed or inadequately
surveyed by the NCR, particularly if it lies in the wet zone.

Despite the wealth of data generated by the NCR, it should be emphasised that they are
preliminary, having been based on rapid assessment techniques. Much more detailed and
wide-ranging surveys will be required to plan the management of individual conservation
forests. An example of an integrated approach to management planning is illustrated in
Figure 7.6. Having surveyed and mapped the distribution of land use patterns and
important elements of biodiversity within a forest, it is then possible to demarcate
management zones to provide a range of services (Figure 7.7). Such an integrated
approach enables conservation and development objectives to be reconciled. It is crucial,
however, to monitor the impact of management measures on SINGS) over the long
term to ensure that they are sustainable.

Inevitably, designing an optimum system of conservation forests is an iterative process,
particularly as more data become available as conservation forests are established and
surveyed for management planning purposes. New data incorporated within EIMS can be
used to refine conservation planning at the system level.

Finally, given the need for further biodiversity surveys, it should be noted that there are
more rapid, less costly alternatives to inventorying plant species. Based on experimental
fieldwork in Sri Lanka, it has been shown that taxa at the level of genera or families are
reliable surrogates for species richness. Inventorying woody plant genera or families
instead of species reduced survey costs by at least 60% and 85%, respectively. In the
case of inventorying at the level of genera, this had little effect on the representation of
the full range of woody plant species within minimum forest systems (Balmford et al.,
1996).

129

REFERENCES
Abeywickrema, B.A. (1987). The threatened plants of Sri Lanka. Unesco MAB National Committee for Sri
Lanka Publication No. 13.

Allen, L. (1992). Plugging the gaps. Nature Conservancy Sept/Oct: 8-9.

Arnoldus, H.M.J. (1980). An approximation of the rainfall factor in the universal soil loss equation.
Assessment of erosion. John Wiley & Sons, Chichester. Pp. 127-132.

Ashton, P.S. and Gunatilleke, C.V.S. (1987). New light on the plant geography of Ceylon. I. Historical
plant geography. Journal of Biogeography 14: 249-285.

Austin, M.P. (1978). Vegetation. In Land use on the south coast of New South Wales, eds Austin, M.P. and
Cocks, K.D. CSIRO, Melbourne. Pp. 44-46.

Austin, M.P. and Heyligers, M.P. (1989). Vegetation survey design for conservation: gradsect sampling of
forests in north-eastern New South Wales. Biological Conservation 50: 13-32.

Austin, M.P. and Heyligers, M.P. (1991). New approaches to vegetation survey design: gradsect sampling.
In Nature conservation: cost effective biological surveys and data analysis, eds C.R. Margules and M.P.
Austin. CSIRO, Australia. Pp. 31-36.

Austin, M.P. Cunningham, R.B. and Fleming, P.M. (1984). New approaches to direct gradient analysis
using environmental scalars and statistical curve-fitting procedures. Vegetatio 55: 11-27.

Baldwin, M.F. (Ed.) (1991). Natural 7eSOUTCeS: of Sri Lanka: conditions and trends. Natural Resources,
Energy and Science Authority of Sri Lanka, Colombo. 280 pp.

Balmford, A., Jayasuriya, A.H.M. and Green, M.J.B. (1996). Using higher-taxon richness as a surrogate
for species richness: II Local applications. Proceedings of the Royal Society of London B 263: 1571-1575.

Banadaranaike, W.M. and M.U.S. Sultanbawa. (1991). A list of the endemic plants of Sri Lanka. Forestry
Information Service, Forest Department, Colombo. 27 pp.

Bastable, H.G. and Gunawardena, E.R.N. (1994). A comparison of climate between two sites at different
elevations in Sri Lanka. In Proceedings of the Phase-1 Review Seminar Workshop of the UP-OFI Link
Project, ed. H.P.M. Gunasena. University of Peradeniya, Sri Lanka. Pp. 205-220.

Batisse, M. (1986). Developing and focusing the biosphere reserve concept. Nature and Resources 12: 2-11.

Bharathie, K.P. (1979). Man and Biosphere reserves in Sri Lanka. Sri Lanka Forester 14 (1&2): 37-40.

Bond, W.J. (1989). Describing and conserving biotic diversity. In Biotic diversity in Southern Africa, ed.
Huntley, B.J. Oxford University Press, Oxford. Pp. 2-18.

Bosch, J.M. and Hewlett, J.D. (1982). A review of catchment experiments to determine the effect of
vegetation changes on water yield and evaporation. Journal of Hydrology 55: 3-23.

Braatz, S. (1992). Conserving biological diversity: a strategy for protected areas in the Asia-Pacific region.
World Bank Technical Paper No. 193. 66 pp.

Bruijnzeel, P.S. (1986). Environmental impact of deforestation in the humid tropics: a watershed
perspective. Wallaceana 46: 3-13.

Burbidge, A.A. (1991). Cost constraints on surveys for nature conservation. In Nature conservation: cost
effective biological surveys and data analysis, eds C.R. Margules and M.P. Austin. CSIRO, Australia.
Pp. 3-6.

130

CEA (1988). The national conservation strategy for Sri Lanka: a synopsis. Central Environmental
Authority, Colombo. 28 pp.

Collins, N.M. (Ed.) (1990). The last rain forests. Mitchell Beazley, London in association with IUCN: The
World Conservation Union. 200 pp.

Csuti B. and Kiester, A.R. (1996). Hierarchical gap analysis for identifying priority areas for conservation.
In Gap analysis: a landscape approach to biodiversity planning, eds Scott, J.M., Tear, T.H. and Davis,
F.W. American Society for Photogrammetry and Remote Sensing, Bethesda, USA. Pp. 25-37.

Davis, S.D. and Heywood, V.H. (1994). Centres of plant diversity: a guide and strategy for their
conservation. Volume II: Asia, Australasia and the Pacific Ocean. The World Conservation Union,
Switzerland and Cambridge, UK.

Dickinson, R.E. (1980). Effects of tropical deforestation on climate. In Browning in the wind: deforestation
and long-range implications. College of William and Mary, Department of Anthropology, Williamsburg,
USA. Pp. 411-441.

ESRI (1992). The digital chart of the world for use with Arc/Info, data dictionary. Environmental Systems
Research Institute, Redlands.

FAO (1995). Forest resources assessment 1990: global synthesis. FAO Forestry Paper 124. 44 pp.

Fernando, P., Dayawansa, N. and Siriwardhane, M. (1994). Bufo kotagamai, a new species of toad
(Bufonidae) from Sri Lanka. Journal of South Asian Natural History 1: 119-124.

Fernside, P.M. (1990). Deforestation in Brazilian Amazonia. In G.M. Woodwell (ed.). Pp. 211-238. (cited
in McNeely, 1996)

Fleming, G. (1975). Computer simulation of hydrology. Elsevier, New York. Pp. 70-78.

Forester, D.J., Machlis, G.E. and McKendry, J.E. (1996). Extending gap analysis to include socioeconomic
factors. In Gap analysis: a landscape approach to biodiversity planning, eds Scott, J.M., Tear, T.H. and
Davis, F.W. American Society for Photogrammetry and Remote Sensing, Bethesda, USA. Pp. 39-53.

Frankel, O.H. (1983). Evolutionary changes in small populations. In Conservation biology: an
evolutionary - ecological perspective, eds Soule, M.E. and Wilcox, B.A. Sinauer, Mass. Pp. 135-149.

Gillison, A.N. and Brewer, K.R.W. (1985). The use of gradient directed transects or gradsects in natural
resources surveys. Journal of Environmental Management 20: 103-127.

Green, M.J.B. (1995). Preliminary analysis of biodiversity within Sri Lanka’s wet zone forests.
Environmental Management in Forestry Development Project, Forest Department. IUCN - The World
Conservation Union, Colombo. 10 pp.

Green, M.J.B. and E.R.N. Gunawardena (1993). Conservation review of some natural forests in Sri Lanka.
Environmental Management in Forestry Development Project, Forest Department. IUCN - The World
Conservation Union, Colombo. 163 pp.

Green, M.J.B., Murray, M.G., Bunting G.C. and Paine, J.R. (1996). Priorities for biodiversity
conservation in the tropics. WCMC Biodiversity Bulletin No. 1. 20pp.

Gunatilleke, C.V.S. and Gunatilleke, I.A.U.N. (1981). The floristic composition of Sinharaja - a rain forest
in Sri Lanka with special reference to endemics and dipterocarps. Malaysian Forester 44: 386-396.

Gunawardena, E.R.N. (1987). Computer simulation of runoff and soil erosion from small agricultural
catchments in Sri Lanka. Ph.D. thesis. Silsoe College, Silsoe, UK. Pp. 147-155.

131

Gunawardena, E.R.N. (1989a). Identification of landuse and physiographic parameters in computer
simulation of soil erosion. In Agricultural engineering: land and water use, eds Dodd A. and Grace, M.
Balkema Publications, Rotterdam. Pp. 757-764.

Gunawardena, E.R.N. (1989b). Hydrological and soil erosion studies on Pinus in Sri Lanka. In
Reforestation with pinus in Sri Lanka, eds Gunasena, H.P.M., Gunatilleke S. and Perera, A.H. Pp. 46-55.

Gunawardena, E.R.N. (1991). Priorities in forest hydrology research in the uplands. In Multipurpose tree
species in Sri Lanka: research and development, ed. Gunasena, H.P.M. Pp. 19-29.

Gunawardena, E.R.N. (1995). Importance of natural forets in Sri Lanka for soil conservation and
hydrology. Environmental Management in Forestry Development Project, Forest Department. IUCN - The
World Conservation Union, Colombo. 39 pp.

Gunawardena, E.R.N. (1996). Impact of land use conversions on water yield. In Forestry for development,
eds H.S. Amarasekera and S.G. Banyard. Department of Forestry and Environmental Science, University of
Sri Jayewardenepura, Nugegoda, Sri Lanka. Pp. 13-17.

Haigh, M.J., Rawat, J.S. and Bisht, H.S. (1988). Hydrological impact of deforestation in the central
Himalaya. In Hydrology of mountain areas. Pp. 419-433.

Hamilton, L.S. and King, P.N. (1983). Tropical forested watersheds: hydrological and soils response to
major uses or conversions. Westview Press, Boulder, USA. 155 pp.

Hibbert, A.R. (1967). Forest treatment effects on water yield. Proceedings of the International Symposium
on Forest Hydrology. Pergamon Press, Oxford. Pp. 527-543.

Holdsworth, E.W.H. (1872). Catalogue of the birds found in Ceylon, with some remarks on the habitat and
local distribution and descriptions of two new species peculiar to the island. Proceedings of the Zoological
Society of London 1872.

Howard, P.C. (1991). Guidelines for the selection of forest nature reserves and their application nationally
and locally. In Nature conservation in tropical forests: principles and practice, ed. Howard, P.C. Forest
Department, Kampala. Pp. 69-85.

Hudson, N.W. (1981). Soil conservation. Betsford, London. Pp. 33-38, 47-74.

Hughell, D.A. (1993). Environmental Information Management System user’s manual. Environmental
Management in Forestry Development Project, Forest Department. IUCN - The World Conservation Union,
Colombo. 130 pp.

Hunter, M.L. Jr, Jacobsen, G.L. Jr, and Webb, T. Jr (1988). Paleoecology and the coarse-filter approach
to maintaining biological diversity. Conservation Biology 2: 375-385.

IUCN (1989). Sri Lanka. Forest Sector Development Project. Environmental Mearapemeut Component. The
World Conservation Union, Gland, Switzerland. 42 pp.

IUCN (1990). IUCN Directory of South Asian protected areas. Compiled by M.J.B. Green, World
Conservation Monitoring Centre. I[UCN-The World Conservation Union, Gland, Switzerland and
Cambridge, UK. 294 pp.

IUCN (1994a). Guidelines for protected area management categories. 'UCN Commission on National Parks
and Protected Areas with the assistance of the World Conservation Monitoring Centre. IUCN-The World

Conservation Union, Switzerland and Cambridge, UK. 261 pp.

IUCN (1994b). 1994 IUCN Red list of threatened animals. Compiled by the World Conservation Monitoring
Centre. IUCN-The World Conservation Union. Gland, Switzerland and Cambridge, UK.

132

IUCN/UNEP/WWE (1980). World conservation strategy: living resource conservation for sustainable
development. \UCN/UNEP/WWF, Gland, Switzerland. 44 pp.

Jaakko Poyry International Oy. (1986). Forestry Master Plan for Sri Lanka. Forest Resources Development
Project, Ministry of Lands and Land Development, Colombo. 146 pp.

Jansen, M. (1989). Sri Lanka - biological diversity and tropical forests. Status and recommended
conservation needs. Revised version. USAID/Sri Lanka, Colombo. 70 pp.

Joshuwa, W.D. (1977). Soil erosive power of rainfall in the different climatic zones of Sri Lanka. JASH-
AISH Publication No. 122. Pp. 51-61.

Juvik, J O. and Ekern, P.C. (1978). A climatology of mountain fog on Mauna Loa. Hawaii Island. Water
Resources Research Centre, University of Hawaii, Technical Report No. 118. 70 pp.

Kalutara and Ratnapura. Paper presented at a Seminar on the review of the protected areas network of the
low country wet zone based on the results of the National Conservation Review. Forest Department,

Battaramulla, Sri Lanka. 4 pp.

Karunaratne, P.B. (1992). Fauna of the Samanalawewa area. Special Scientific Publications Series of the
Wildlife and Nature Protection Society of Sri Lanka 1(2): 1-63.

Kirkpatrick, J.B. (1983). An iterative method for establishing priorities for the selection of nature reserves:
.an example from Tasmania. Biological Conservation 25: 127-134.

Kirkpatrick, J.B. ‘and Brown, M.J. (1991). Planning for species conservation. In Nature conservation: cost
effective biological surveys and data analysis, eds C.R. Margules and M.P. Austin. CSIRO, Australia.
Pp. 83-89. j

Kotagama, S. (nd). Species list: vertebrates of Sri Lanka. Unpublished.

Kotagama, S.W. (1992). Meeting new challenges: the Sri Lankan national policy on wildlife conservation.
Paper presented at IVth World Congress on National Parks and Protected areas, Caracas, Venezuela. 14 pp.

Krishnarajah, P. (1982). Soil erosion and conservation in the upper Mahaweli watershed. Paper presented at
the Annual Session of the Soil Science Society of Sri Lanka, 13 November 1982. 15 pp.

Kunkle, S.H. and Dye, A.J. (1981). The effects of forest clearing on soils and sedimentation. In Tropical
agricultural hydrology, ed. Lal, R. and Russell, E.W. Pp. 99-109.

Lal, R. (1976). Soil erosion on alfisols in western Nigeria. Effects of rainfall characteristics. Geoderma 16:
389-401.

Leader-Williams, N., Harrison, J. and Green, M.J.B. (1990). Designing protected areas to conserve natural
resources. Science Progress 74: 189-204.

Legg, C. and Jewell, N. (1995). A 1:500,000-scale forest map of Sri Lanka: the basis for a National Forest
Geographic Information System. Sri Lanka Forester Special Issue (Remote sensing): 3-21.

Legg, C. and N. Jewell (1992). A new 1:500,000 scale forest map of Sri Lanka. ODA Forest and Land
Use Mapping Project, Forest Department, Colombo. 12 pp.

Lesslie, R.G. and Taylor, $.G. (1985). The wilderness continuum concept and its implication for Australian
wilderness preservation policy. Biological Conservation 32: 309-333.

Lesslie, R.G., Mackey, B.G. and Preece, K.M. (1988). A computer based method of wilderness evaluation.
Environmental Conservation 15: 225-232.

133

Linsley, R.K., Kohler, M.A. and Paulhus, J.L.H. (1982). Hydrology for engineers. 3rd Edition. McGraw-
Hill, New York. Pp. 71-74.

Liyanage, S, (1996). Proposed minimum protected areas net-work for the low-country wet zone of Sri
Lanka in the districts of Matara, Galle,

MacKinnon, J., MacKinnon, K., Child, G. and Thorsell, J. (1986). Managing protected areas in the
tropics. \UCN, Gland, Switzerland and Cambridge, UK. Pp. 46-47.

Margules, C.R. (1989). Introduction to some Australian developments in conservation evaluation. Biological
Conservation 50: 1-11.

Margules, C.R. and Usher, M.B. (1981). Criteria used in assessing wildlife conservation potential: a
review. Biological Conservation 21: 79-109.

Margules, C.R., Nicholls, A.O. and Pressey, R.L. (1988). Selecting networks of reserves to maximise
biological diversity. Biological Conservation 43: 63-76.

Margules, C.R., Pressey, R.L. and Nicholls, A.O. (1991). Selecting nature reserves. In Nature
conservation: cost effective biological surveys and data analysis, eds C.R. Margules and M.P. Austin.
CSIRO, Australia. Pp. 90-97.

Mayr, E. (1969). Principles of systematic zoology. McGraw-Hill, New York.

McNeely, J.A. (1988). Economics and biodiversity: developing and using economic incentives to conserve
biological resources. \UCN, Gland, Switzerland. 236 pp.

McNeely, J.A. (1996). Who cares about forest biodiversity? Global Biodiversity 6(2): 14-23.

McNeely, J.A., Harrison, J. and Dingwall, P. (Eds) (1994). Protecting nature: regional reviews of
protected areas. \UCN, Gland, Switzerland and Cambridge, UK. 402 pp.

McNeely, J.A., Miller, K.R., Reid, W.V., Mittermeier, R.A. and Werner, T.B. (1990). Conserving the
world’s biological diversity. UCN, Gland, Switzerland; WRI, CI, WWF-US, and the World Bank,
Washington, DC. 193 pp.

Meher-Homji, V.M. (1980). The link between rainfall and forest clearance: case studies from western
Karnataka. Transactions of the Institute of Indian Geographers 2: 59-65.

Meher-Homji, V.M. (1988). Effects of forests on precipitation in India. In Forests, climate and hydrology,
eds Reynolds E.R.C. and Thompson F.B. The United Nations University, Tokyo, Japan. Pp. 51-77.

Melton, M.A. (1958). Correlation structure of morphomeric properties of drainage systems and their
controlling agents. Journal of Geology 66: 442-460.

MEPA (1994). National Environmental Action Plan 1992-1996. NEAP Update ’94. Draft. Ministry of
Environment and Parliamentary Affairs, Colombo. 95 pp.

Morgan, R.P.C. (1980). Soil erosion. Longman, UK. 113 pp.
Morgan, R.P.C., Morgan, D.D.V. and Finney, H.F. (1982). Stability of agricultural eco-systems:
documentation of a simple model for soil erosion. Soil erosion assessment. IIASA Collaborative Paper CP-

82-59.

Mowjood, M.I.M. and Gunawardena, E.R.N. (1992). Designing and testing of a rotating screen fog
collector. Agricultural Engineering 4(1). In press.

134

MTEWA. (1994). Strategy for the preparation of a biodiversity action plan for Sri Lanka. Prepared by
IUCN-The World Conservation Union, Sri Lanka for the Environment Division, Ministry of Transport,
Environment and Women’s Affairs, Colombo. 87 pp.

Navaratne, N.M.G. (1985). Hydrometric network. In Some aspects of water resources of Sri Lanka with
special reference to hydrology. The National Committee of Sri lanka for the International Hydrological
Programme. Irrigation Department, Colombo, Sri Lanka. Pp 1-12.

NEDECO (1984). Sediment transport in the Mahaweli Ganga. Irrigation Department, Colombo. 74 pp.
NERC (1975). Flood studies report. Vol. 1. Hydrological studies. Whitefrias Press, London. 550 pp.

Nicholls, A.O. (1991). Examples of the use of generalised linear models in analysis of survey data for
conservation evaluation. In Nature conservation: cost effective biological surveys and data analysis, eds
Margules, C.R. and Austin, M.P. CSIRO, Australia. Pp. 54-63.

Noss, R.F. (1991). Protecting habitats and biological diversity. Part I: Guidelines for regional reserve
systems. National Audubon Society, New York.

Noss, R.F. (1992). The wildlands project: land conservation strategy. Wild Earth Special Issue: 10-25.

OECD (1996). Saving biological diversity: economic incentives. Organisation for Economic Co-operation
and Development, Paris. 155 pp.

Oyabande, L. (1988). Effects of tropical forests on water yield. In Forests, climate and hydrology, Eds
Reynolds, E.R.C. and Thompson, F.B. The United Nations University, Tokyo, Japan. Pp. 16-49.

Pereira, H.C. (1989). The role of forests in watershed management. In Policy and practice in the
management of tropical watersheds, ed. Pereira, H.C. Westview Press. Pp. 57-77.

Perera, M.B.A. (1989). Planned landuse for the tea country. Sri Lanka Journal of Tea Science 58(2): 92-
103.

Perera, W.R.H. (1977). The development of the forest resources of Sri Lanka. Sri Lanka Forester 13(1-2).

Ponnadurai, D.K., Gomez, G.E.M. and Kandiah, A. (1977). Effect of selective felling on the hydrological
parameters of a wet zone catchment. Paper presented at the Asian Regional Meeting of the International
Hydrological Programme National Committee of Unesco and WHO Regional Meeting of Working Group on
Hydrology, Colombo, Sri Lanka. 10 pp.

Premalal, W.P.R. (1986). Development of an erosivity map for Sri Lanka. A research report submitted for
the requirement of the B.Sc. degree. Department of Agricultural Engineering, University of Peradeniya, Sri
Lanka. 65 pp.

Ratnapala, R. and Arudpragasam, K.D. (nd). A check-list of land snails of Sri Lanka. UNESCO: Man and
the Biosphere National Committee for Sri Lanka Publication No. 13. Natural Resources, Energy and
Science Authority of Sri Lanka. Colombo. 10 pp.

Santiapillai, C. and de Silva, M. (1994). An action plan for the conservation and management of elephant
(Elephas maximus) in Sri Lanka. Draft. Department of Zoology, University of Peradeniya. Peradeniya.

21 pp.

Soule, M.E. (1983). Applications of genetics and population biology: the what, where and how of nature
reserves. In Conservation, science and society. Unesco-UNEP. Pp. 252-264.

Soule, M.E. (1987). Viable populations for conservation. Cambridge University Press, Cambridge.

135

Soule, M.E. and Wilcox, B.A. (1980). Conservation biology: an evolutionary - ecological perspective.
Sinauer, Sunderland, USA. 393 pp.

Stocking, M.A. (1984). Land use planning - Phase II, Sri Lanka. UNDP/FAO AGOF: SRL/84/032. Report
submitted to Ministry of Lands and Land Development, Colombo. 55 pp.

Sumithraarachchi, B. (1986). A report on steps taken to conserve Orchidaceae in Sri Lanka. Phyta, Journal
of the Botanical Society of the University of Peradeniya 3(1): 26-41.

TEAMS (1991). Review of forest management plans for environmental conservation. 2 volumes. Final
report to Forestry Planning Unit, Ministry of Lands, Irrigation and Mahaweli Development. TEAMS,
Colombo.

Tejwani, K.G. (1977). Trees reduce floods. Indian Farming 26(11): 57.

UNDP/FAO/GOSL (1989). Environmental management in forestry developments. Project Document.
Mission Report SRL/89/012. 90 pp.

UNEP (1995). Global biodiversity assessment. Cambridge University Press, Cambridge.

Unesco (1978). Tropical forest ecosystems. Unesco/UNEP/FAO, Paris.

Usher, M.B. (Ed.)(1986). Wildlife conservation evaluation. Chapman and Hall, London. 394 pp.

Vane-Wright, R.I., Humphries, C.J. and Williams, P.H. (1991a). Biodiversity reserves: setting new
priorities for the conservation of wildlife. Parks 2: 34-38.

Vane-Wright, R.I., Humphries, C.J. and Williams, P.H. (1991b). What to protect? - systematics and the
agony of choice. Biological Conservation 55: 235-254.

Wiersum, K.F. (1984). Surface erosion under various tropical agroforestry systems. In Proceedings of the
Symposium on Effect of Forest Landuse on Erosion and Slope Stability, eds. O’ Loughlin, C.L. and Pearce,
A.J. Pp. 231-239.

Wijesinghe, L.C.A.de S., Gunatilleke, I.A.U.N., Jayawardana, $.D.G., Kotagama, S.W. and Gunatilleke,
C.V.S. (1993). Biological conservation in Sri Lanka. A national status report. Revised version. 1993.
IUCN-The World Conservation Union, Sri Lanka Country Office. Colombo. 100 pp.

Wilcox, B.A. (1984). In situ conservation of genetic resources: determinants of minimum area
requirements. In National parks, conservation and development: the role of protected areas in sustaining

society, eds McNeely, J.A. and Miller, K.A. Smithsonian Institution Press, Washington, DC. Pp. 639-647.

Wischmeir, W.H. and Smith, D. (1965). Predicting rainfall erosion losses from croplands east of Rocky
Mountains. US Department of Agriculture, Agricultural Handbook 282. 47 pp.

Wischmeir, W.H. and Smith, D. (1958). A rainfall erosion index for a universal soil equation. Journal of
the Soil Science Society of America 23: 246-249.

World Conservation Monitoring Centre (1994). Biodiversity data sourcebook. World Conservation Press,
Cambridge, UK. 155 pp.

World Conservation Monitoring Centre (1992). Global biodiversity: status of the Earth’s living resources.
Chapman & Hall, London. 594 pp.

136

Designated Areas of Sri Lanka

|
| |
KEY
FOREST SECTOR

Bo Proposed Reserve
___ Forest Reserve

Hl Conservation Forest * -
344 see Annex 1

WILDLIFE SECTOR

J National Park

=|

: Nature Reserve

23 Sanctuary

WM Strict Natural Reserve
207 see Annex 1

* includes Sinharaja NHWA

6

‘WORLD CONSERVATION
MONTTORING CENTRE

Projection Lambert Azimuthal,

CM 81 degrees, Lat of Centre Proj 8 degrees

March 1997
‘ >
21 (
mS

137

139

140

Annex 1

LIST OF DESIGNATED AREAS

Nationally designated areas are listed alphabetically, by responsible administration. Where
known, their boundaries are shown in the maps immediately preceding this annex.

Proposed reserve is an administrative rather than legal designation for forests originally
intended for notification as forest reserves. Boundary demarcation, as a prelude to
notification, never took place due the tide of events over recent decades when forest land was
released for use outside the forestry sector at an increasingly rapid rate.

The 12 national parks comprise a total of 24 independently notified blocks.

Notified area is the area originally notified or, in the case of proposed reserves, declared as
protected. Present area is the notified area corrected for land released from forest or
proposed reserves subsequent to their establishment. MAB area is the area declared by the
Forest department as a national Man and Biosphere Reserve. GIS area is the area computed
from the digitised boundaries, using a Geographic Information System. It should provide the
most accurate estimate, provided that the digitised boundaries reflect any changes following
land releases. Comparison between the three estimates of area for any given site suggests that
this may not always be the case for forest or proposed reserves.

Area (ha)
EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date
FOREST DEPARTMENT
1 Agra-Bopats PR 9105.4 6933.6 0.0 619.4 NUW
3. Akkiriyan FR 8179.5 7684.0 0.0 8220.4 JAF
2 Akkiriyan PR 2681.0 2681.0 0.0 2815.1 MUL JAF
4 Alapalawala PR 182.1 181.7 0.0 27.8 KEG
5 Alawala-Ataudakanda PR 352.8 352.8 0.0 SHl7/ GAM
6 Alutabendawewa PR 440.2 384.0 0.0 487.5 ANU
7 Amanawala~Ampane PR 518.0 514.0 0.0 56.7 KEG
9 Ambaliyadde PR 61.7 61.7 0.0 107.4 NUW
10 Ambanmukalana FR 15/05/1896 1085.9 1004.8 0.0 1180.8 PUT
11 Anaolundewa PR 29640.2 28957.1 5$0511.7 29422.6 ANU POL
12 Andankulam FR 10/06/1921 15158.7 14835.0 0.0 15113.6 MUL VAV
13. Angurukandayaya PR 139.2 139.2 0.0 125.3 KUR
15 Arachchikotuwa PR 0.8 0.8 0.0 6.4 PUT
17 Attavillu FR 21/06/1912 9009.1 5179.4 0.0 8695.3 PUT
16 Attavillu PR 429.4 429.4 0.0 462.9 PUT
18 Aturupana FR 14/11/1941 24.8 24.8 0.0 48.0 KEG
19 Ayagama PR 661.7 214.3 0.0 633.3 RAT
20 Badagama PR 24.7 24.7 0.0 40.7 KAL
21 Badagamuwa FR 01/06/1894 228.7 213.9 20.2 241.0 KUR
22 Badapeliyagoda FR 28/10/1938 49.9 49.9 0.0 45.7 KUR
24 Badullakele FR 11/10/1940 182.3 147.7 0.0 179.8 MTR
23 Badullawala PR 42.9 41.0 0.0 52.7 KEG
26 Bajjangoda PR 175.9 175.9 0.0 173.7 GAM
27 Bakinigahawela FR 27/05/1921 200.3 200.3 0.0 90.0 MON
28 Bambarabotuwa FR# 04/07/1890 5440.3 5440.3 0.0 1181.4 RAT
29 Bandarawela PR 15.4 12.6 0.0 10.5 BAD
30 Banhedawaka PR 159.0 159.0 0.0 158.4 KUR
33 Barigoda FR 11/03/1921 78.5 78.5 0.0 147.8 KUR

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date

32 Barigoda PR 72.7 72.7 0.0 0.0 KUR
34 Baron's Cap PR 38121.4 37397.1 1012.1 37516.2 BAT
35 Bedigantota PR 8093.7 7527.2 0.0 8679.4 HAM
37 Beraliya (Akuressa) PR 1859.9 1645.5 0.0 0.0 GAL MTR
38 Beraliya (Kudagala) PR 4241.1 2571.8 0.0 4.4 GAL
39 Bibilehela PR 610.0 606.3 0.0 721.0 BAD MON
40 Bogawantalawa PR 4289.7 4289.7 0.0 3781.6 NUW
42 Botale PR 276.1 276.1 0.0 313.4 KAL
45 Campbell's Land FR 22/03/1902 292.6 292.6 0.0 278.3 KAN MTL
46 Chamalankulam FR 10/06/1921 3281.7 3281.7 0.0 3371.4 MUL
47 Chunavil FR 10/06/1921 2298.6 2298.6 0.0 2110.4 JAF
49 Chundankadu FR 01/03/1940 16746.3 5690.3 0.0 17599.4 TRI
50 Chundankadu PR 11051.5 8443.7 0.0 10417.4 TRI
52. Conical Hill PR 1569.5 707.5 0:0) 1721-3 NUW
53 Dambakele FR mle: 71.2 0.0 60.4 NUW
54 Dambukanda PR 41.7 41.7 0.0 0.0 GAM
55 Dambulla FR 29/01/1937 172.3 169.5 0.0 82.3 KEG
56 Dambulla Oya PR 104.4 103.2 0.0 75.8 MTL
57 Dambuluwana FR 12/04/1943 485.2 401.1 0.0 292.4 RAT
58 Dambuwa PR 1062.3 1062.3 0.0 74.3 KUR
59 Dampitiya PR 97.1 11.1 0.0 62.1 KUR
60 Dandeniya-Aparekka FR 02/12/1938 560.0 348.3 0.0 588.2 MTR
61 Daragoda FR 07/01/1921 748.9 748.9 374.4 658.7 MON
62 Darakulkanda PR 457.6 141.7 0.0 235.2 GAL
63 Dawatagolla FR 05/03/1937 43.2 34.7 0.0 56.1 KUR
64 Debetgama Bossella PR 103.2 103.2 0.0 215.1 KEG
65 Dediyagala FR 06/09/1940 3789.9 3789.9 0.0 3866.0 GAL MTR
66 Degadaturawa PR 161.9 161.9 0.0 268.3 KUR
67 Dehelgamuwa FR 03/05/1940 58.0 4.1 0.0 66.4 KUR
68 Delgoda PR 998.0 998.0 0.0 1013.5 RAT
69 Dellawa PR# 2034.0 2236.3 0.0 1250.5 GAL MTR
70 Delmella Yatagampitiya PR 2033.7 1413.3 0.0 55.8 KAL
71 Delwela PR# 1560.9 1560.1 0.0 1531.9 RAT
72 Demanagammana PR 114.9 114.1 0.0 53.5 RAT
73 Dewalakanda FR 04/08/1939 112.5 112.5 0.0 111.0 KUR
74 ~~ ~Digalla FR 18/06/1948 90.3 87.0 0.0 60.9 KUR
75 Dikkele Mukalana FR 22/07/1921 336.4 308.1 0.0 324.5 KUR
76 Diwalakada PR 281.1 144.3 0.0 313.5 KAL
77 Diyadawa FR# 21/08/1936 2578.2 2447.7 404.8 2504.9 MTR
78 - Doluwakanda PR 400.6 400.6 400.8 499.1 * KUR
79 Dotalugala PR 1871.7 1871.7 1619.4 86.0 KAN MTL
80 Dunkanda PR 301.1 301.1 0.0 488.4 KUR
82 Elagomuwa PR 870.1 870.1 0.0 15.2 MTL
83 Elawaka PR 168.3 168.3 0.0 67.6 KUR
84 Ella PR 52.2 §2.2 0.0 75.1 BAD
86 Eluwana FR 02/12/1892 85.6 85.6 0.0 150.9 KEG
85 Eluwana PR 28.3 28.3 0.0 0.0 KEG
87 Epilagala PR 42.5 42.5 0.0 52.3 KEG
88 Erabaduwala PR 17.4 17.4 0.0 6.0 KEG
89 Erabedda PR 1538.9 1538.8 0.0 13.8 BAD
91 Etabedda FR 08/05/1875 91.1 70.8 0.0 63.5 RAT
92 Etakaduwa PR 7689.0 7689.0 0.0 6318.0 ANU
93 Etaritiya PR 1558.0 1428.5 0.0 1482.8 PUT
94 Ettalapitiya PR 269.1 269.1 0.0 236.5 BAD
96 Gal Oya PR 9036.6 8897.4 0.0 8493.4 POL
100 Galaha PR 242.8 242.8 0.0 0.0 - KAN
101 Galgiriyakanda PR 1182.5 1182.5 0.0 1208.7 KUR
102 Galketiyagama PR 40.5 40.5 0.0 122.3 KUR
103 Galkuliya PR 4775.3 4127.8 0.0 4723.6 PUT
104 Gallendakuttiya FR 21/02/1936 89.3 89.1 0.0 20.3 MTR
105 Galpalama PR 73.6 68.0 0.0 70.6 NUW
106 Galway’s Land PR 56.7 56.7 0.0 0.0 NUW
108 Gangekumbura FR 11/11/1938 156.4 156.3 0.0 19.7 KEG
109 Getadivula PR 581.5 581.5 0.0 573.3 KUR
110 Getamarawa-Dunkolahena PR 129.7 129.7 0.0 87.4 COL
112 Gilimale-Eratne PR# 5832.7 4838.8 40.4 61.5 RAT
113 Giritale PR 1077.3 1063.1 0.0 574.2 POL
114 Godagandenikanda PR 55.8 55.8 0.0 21.3 KEG
115 Gonadeniya FR 16/12/1921 414.4 414.4 0.0 339.8 HAM
116 Gonagama PR 457.7 235.1 0.0 467.1 KUR
117 Gondenikanda FR 04/07/1941 73.0 72.4 0.0 61.4 KEG
118 Gorakadola FR 23/09/1938 191.9 191.1 0.0 230.0 KUR
120 Habarakada PR 209.6 209.6 202.4 271.4 GAL

142

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date

121 Habilikanda PR 180.9 180.9 0.0 198.1 KUR
122 Hakgala FR 423.2 423.2 0.0 22.6 NEW BAD
124 Halagiriya FR 20/12/1940 40.5 18.1 0.0 40.4 KEG
125 Halpankanda PR 159.3 158.5 0.0 22.8 GAM
126 Hambantota PR 1165.5 1125.0 0.0 1170.8 HAM
127 Haputale FR 08/07/1921 141.3 141.1 0.0 119.7 BAD
128 Harasbedda PR 364.2 364.2 0.0 279.1 NUW
129 Haycock FR# 362.0 362.0 364.3 380.8 KAL
130 Helapandeniya PR 136.0 21.4 0.0 83.8 RAT
131 Henegedaralanda PR 731.7 729.6 0.0 671.2 KUR
132 Heraliyawala PR 13.8 13.8 0.0 0.0 KUR
134 Hidellana FR 08/05/1875 48.6 48.6 0.0 27.3 RAT
133 Hidellana-Weralupe PR 136.8 128.1 0.0 181.6 RAT
136 Hinna PR 1021.8 1021.8 0.0 1088.4 ANU
141 Humpitikanda PR 36.4 19.4 0.0 28.8 KEG
142 Hurulu FR 20/11/1942 25511.1 25217.7 0.0 25497.6 ANU POL
143 Imbulpitiya FR 05/09/1941 12.2 12.2 0.0 19.1 KEG
145 Inamaluwa FR 03/03/1944 1896.9 1863.6 0.0 2013.0 MTL
144 Inamaluwa PR 309.6 309.6 0.0 263.4 MTL
146 Indikada Mukalana PR 786.1 747.5 0.0 176.6 COL
147 Ingiriya FR# 07/08/1929 407.0 282.6 0.0 449.3 KAL
148 Ipolagama PR 4451.5 4203.7 0.0 4805.1 PUT
149 Irampaikulam FR 10/06/1921 944.9 944.9 0.0 969.7 MUL VAV
150 Iranaimadu FR 16/05/1930 8321.8 7541.8 1417.0 8083.0 JAF MUL
151 Irasenthirankulam FR 10/06/1921 1458.4 1116.5 0.0 1477.6 VAV
152. Iriminna FR 03/05/1940 25.8 25.8 0.0 16.7 KUR
153 Iriyagahahena PR 44.5 44.5 0.0 0.0 RAT
154 Iriyagahahena Mukalana FR 24/06/1927 74.5 44.1 0.0 172.5 RAT
155 Issenbessawewa FR 07/06/1901 441.9 441.9 300.0 455.7 ANU
156 Judges Hill PR 10.9 10.7 0.0 50.1 BAD
157 Kadawatkele PR 283.3 267.1 0.0 258.0 KUR
158 Kaduruwewa PR 120.2 120.2 0.0 102.0 KUR
160. Kahalla FR 11/10/1935 3397.7 3292.5 0.0 3337.9 ANU
159 Kahalla PR 34.0 34.0 0.0 0.0 ANU
162 Kaharagala PR 31.8 31.8 0.0 32.7 KAL
163 Kala Oya PR 4949.7 4949.7 0.0 5127.5 KUR
165 Kalugala PR 3365.0 2705.9 0.0 3149.3 KUR
166 Kalugala PR# 4630.1 4288.0 0.0 1087.1 KAL
168 Kalugalkanda FR 10/11/1933 62.5 62.5 0.0 0.0 MTR
167 Kalugalkanda PR 153.0 152.9 0.0 197.3 - KUR
170 Kananpella FR 295.2 263.5 0.0 298.6 COL
172 Kandapola Sita Eliya FR 20/05/1892 2721.2 2615.9 20.2 1819.1 NUW
171 Kandapola Sita Eliya PR 109.6 97.9 0.0 1067.1 NUW
173 Kandawattegoda PR# 404.7 358.6 0.0 0.0 GAL
174 Kankaniyamulla FR 20/12/1940 1108.0 1047.9 161.9 310.5 KUR
175 Kanneliya FR# 06/07/1934 6114.4 6024.5 40.4 249.6 GAL
176 Kantalai FR 31/01/1902 40007.7 37479.3 0.0 46663.5 TRI
177 Kanugollayaya PR 211.7 119.5 0.0 254.1 KUR
178 Kanumuldeniya FR 13/09/1940 678.7 678.7 20.2 674.2 HAM MTR
179 Kaparella Uswewa FR 16/12/1921 564.4 564.4 0.0 558.4 HAM
180 Kaparella Uswewa PR 214.5 214.5 0.0 3.1 HAM
181 Karagahatenna PR 55.4 55.4 0.0 0.0 GAM
182 Karandana FR 30/06/1899 77.8 77.8 0.0 86.0 RAT
183 Karandekumbura PR 72.8 72.8 0.0 52.0 BAD
184 Karawita PR 1375.9 1211.8 0.0 269.7 RAT
185 Karunkalikulam FR 8037.1 6398.9 0.0 8432.0 VAV
189 Kebalawita PR 114.9 114.9 0.0 6.2 GAM
190 Kekanadura FR# 15/11/1935 401.7 379.9 0.0 453.5 MTR
191 Kelani Valley FR 11/09/1903 1155.1 1155.1 0.0 152.3 KEG
192 Kelani Valley PR 2944.9 2906.2 0.0 Srl KAN
193 Kelunkanda FR 16/06/1939 249.0 196.3 0.0 270.7 GAL
194 Kendahena FR 29/07/1932 69.2 69.2 0.0 77.2 KUR
195 Kendahena PR 0.2 0.2 0.0 109.2 KUR
196 Ketangilla PR 86.2 86.2 0.0 0.0 KEG
197 Kikilimana PR 4868.4 4580.6 809.7 4879.2 NUW
198 Kilinochchi FR 11190.7 10784.7 1417.0 11144.5 JAF
503 Kinniya PR 14.2 14.2 0.0 0.0 TRI
200 Kirigala Mukalana PR 18.8 18.8 0.0 35.4 KAL
201 Kirinda Mahayayakele FR 19/07/1940 374.1 252.7 0.0 0.0 MTR
202 Kirindigolla FR 05/03/1937 171.0 171.0 0.0 26.6 KUR
203 Kitulgala PR 265.9 263.0 0.0 48.7 KEG
204 Kivulpona FR 21/08/1936 21.6 21.6 0.0 22.9 KEG
205 Kobahadunkanda PR 890.3 890.3 0.0 0.0 RAT

143

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date

206 Kohile PR 12.1 12.1 0.0 112.6 BAD
208 Kombala-Kottawa PR# 2289.7 1624.6 202.4 121.9 GAL
209 Koralai FR 04/01/1929 7774.0 3664.0 0.0 7564.6 BAT
210 Koralai PR 1165.5 1102.4 0.0 1181.3 BAT
211 Kotagama FR 01/11/1935 29.5 29.5 0.0 39.3 KEG
212 Kotakanda PR 254.8 242.7 0.0 212.4 GAM
213 Kotakitulakanda PR 60.7 60.7 0.0 55.2 BAD
214 Kudagalkanda FR 151.8 25.7 0.0 236.2 MTR
215 Kudaganga FR 141.3 137.4 0.0 139.7 KAL
217 Kudumiriya PR 2144.8 2144.8 0.0 2153.0 RAT
218 Kulamiruppu A & B FR 10/06/1921 5036.1 4277.3 0.0 1714.2 MUL
219 Kumbalpola PR 102.8 96.3 0.0 - 79.0 KUR
220 Kumbukkan PR 08/04/1927 37635.8 37635.8 0.0 26332.7 AMP
169 Kumburugamuwa FR 03/03/1893 1523.2 1480.7 0.0 6.8 RAT
221 Kurana Madakada PR 1391.2 1161.4 0.0 31.9 KAL
222 Labugama-Kalatuwana FR 16/03/1992 2150.1 2150.1 0.0 0.0 COL KAL RAT
224 Latpandura PR 42.1 42.1 0.0 41.8 KAL
225 Lenagala FR 23/12/1897 33.8 30.0 0.0 38.1 KEG
226 Lewala FR 13/01/1893 31.7 30.0 0.0 27.0 KEG
227 Likolawewa FR 24/07/1936 3462.2 3462.2 0.0 0.0 KUR
228 Likolawewa FR 19/07/1940 325.7 325.7 0.0 3382.3 ANU
230 Lunu Oya FR 01/09/1939 3647.4 3647.4 0.0 3945.2 ANU
232 Ma Eliya FR 02/08/1935 383.6 381.2 0.0 261.1 KUR
234 Madampe FR# 10/02/1893 237.3 224.8 0.0 248.5 RAT
233 Madampe PR# 40.5 40.5 0.0 33.8 RAT
235 Madhu PR 22547.2 22346.4 1417.0 22307.8 MAN
237 Madunagala FR 06/04/1992 975.2 975.2 0.0 0.0 HAM
241 Magurugoda FR 25/05/1934 275.4 241.0 0.0 0.0 RAT
242 Magurugoda PR 45.7 24.7 0.0 267.8 RAT
243 Maha Irampaikulam FR 804.8 416.3 0.0 801.0 VAV
244 Mahagama FR 368.7 227.1 0.0 406.6 KAL
245 Mahakaluweragoda FR 21/07/1922 238.6 238.6 0.0 283.8 HAM
247 Mahakanda PR 170.6 103.0 9.0 164.2 GAM
248 Mahakudagala PR 1762.5 1638.7 0.0 317.4 NUW
249 Mahapitakanda FR 16/12/1921 797.4 722.3 0.0 745.8 HAM
250 Mahaweliganga PR 6475.0 6475.0 0.0 2639.6 TRI
251 Mahaweliganga North and South FR 22/12/1939 9209.5 8642.1 0.0 5968.3 TRI
253 Malambure FR 19/07/1935 1012.3 929.8 0.0 1109.2 GAL
254 Mamadu FR 230.2 230.2 0.0 222.3 VAV
256 Manapaya PR 314.0 314.0 0.0 318.9 KUR
257 Mandakalar FR 8387.1 7577.7 0.0 8355.9 JAF
258 Maniyangama-Timbiripola FR 04/11/1892 209.0 209.0 0.0 212.1 KEG
259 Manuwangama-Nariyagama FR 07/12/1894 537.6 244.2 0.0 385.7 PUT
260 Maoye Ella FR 24/02/1888 48.6 48.6 0.0 82.1 KAN
261 Maragalkanda FR 14/07/1939 117.1 20.0 0.0 125.4 KUR
273 Marakele FR 08/05/1875 76.9 76.9 0.0 99.8 RAT
272 Marakele PR 131.5 106.2 0.0 138.7 RAT
262 Masimbula FR 13/12/1889 20.2 20.2 0.0 0.0 RAT
504 Masimbula PR 255.0 255.0 0.0 299.2 RAT
263 Masmullekele FR 21/07/1939 805.4 618.0 20.2 715.2 MTR
264 Mavillu FR 10/06/1921 14601.1 14601.1 0.0 14574.6 MAN
265 Mawattagama PR 2152.9 1512.6 0.0 2178.8 KUR
266 Medaulpota PR 2340.2 2340.2 0.0 2374.5 MTL POL
267 Medawachchiya PR 2892.5 2878.4 0.0 2933.0 ANU
268 Meeambakanda FR 01/09/1939 124.6 124.6 0.0 160.4 _ KUR
269 Meegahatenna PR 282.8 277.4 0.0 80.2 KAL
270 Meepilimana FR 02/11/1906 981.8 771.5 0.0 362.0 NUW
271 Melkulam FR 10/06/1921 2197.2 1931.6 0.0 2166.0 MUL VAV
274 Messana PR# 724.4 433.8 0.0 705.8 RAT
275 Middeniya FR 03/10/1941 372.7 372.5 0.0 103.5 HAM
276 Migollegama PR 141.2 141.2 0.0 80.0 BAD
277 Mihintale FR 14/11/1924 3308.2 2462.9 0.0 3270.3 ANU
279 Minneriya PR 2444.3 828.0 809.7 3392.8 POL
282 Minuwangeta PR 746.2 139.2 0.0 22.1 KUR
283 Mipitikanda PR 235.9 235.9 0.0 284.4 KUR
284 Mirigamkanda PR 139.3 139.2 0.0 13.6 GAM
285 Miriyagalla FR 123.7 123.1 0.0 124.3 COL
286 Mitirigala FR 511.5 353.7 0.0 500.1 GAM
287 Moragolla FR 22/11/1895 21.3 19.9 0.0 24.2 KUR
288 Morahela FR# 31/03/1893 930.5 846.9 0.0 545.5 RAT
289 Morapitiya-Runakanda PR# 7012.5 6732.5 0.0 7108.1 KAL
290 Moturampatana PR 319.3 235.9 0.0 110.2 KUR
291 Mudungoda PR 774.2 774.2 0.0 832.1 KUR

144

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date
292 Mudunkotuwa PR 78.1 78.1 0.0 89.4 RAT
293 Mulatiyana FR 25/08/1944 3277.5 3148.9 404.8 3603.5 MTR
294 Muwagankanda FR 20/03/1931 164.8 132.1 0.0 134.8 RAT
295 Nagancholai FR 01/07/1932 6771.3 6447.5 1417.0 6824.8 MUL
296 Nagolla FR 03/05/1940 123.1 123.1 0.0 38.3 KUR
297 Nahalla PR 35.1 35.1 0.0 51.4 KAL
298 Nahiti Mukalana FR# 13/12/1889 195.7 195.7 0.0 186.1 RAT
299 Nainamadu FR 10/06/1921 9817.4 9740.5 0.0 9436.9 MUL VAV
300 Nakapaduwan FR 10/06/1921 4149.7 2931.6 0.0 4026.0 JAF
301 Nakele PR 80.9 80.9 0.0 93.1 PUT
302 Nakele Mukalana FR 14/11/1924 39.8 29.3 0.0 0.0 KUR
303 Nakiyadeniya PR# 2292.1 2235.5 0.0 1267.2 GAL
304 Namalgomuwa PR 72.8 72.8 0.0 18.1 KEG
305 Namandiya FR 22/04/1921 861.4 790.6 0.0 963.3 MON
306 Namunukula PR 279.3 279.3 0.0 416.9 BAD
307 Nanu Oya PR 420.8 415.9 0.0 269.5 NUW
308 Naranbedda FR 16/06/1939 Sile7/ 51.7 0.0 15.2 KEG
309 Nawagatta PR 62.7 54.6 0.0 54.3 KUR
310 Neenthavil FR 10/06/1921 8125.1 7720.5 0.0 8296.7 MAN
311 Nelawa if FR 13/02/1942 48.0 48.0 0.0 57.9 KUR
312 Nelligalkanda FR 12/08/1938 50.0 : 50.0 0.0 us KUR
313 Nellikele PR 1152.5 1152.5 1133.6 1238.2 AMP
315 Neluketiya Mukalana PR 2625.2 2384.4 0.0 2020.1 KAL
316 Netiyapana FR 13/02/1942 18.0 Dees 0.0 25.1 KEG
317 Nettipolagama FR 14/04/1944 1.0 1.0 0.0 0.0 KUR
318 Neugalkanda PR 376.0 376.0 0.0 417.5 KUR
- 319 Nikawehera PR 33.2 33.2 0.0 5.9 MTL
320 Nikawekanda a PR 151.8 151.8 0.0 140.9 KUR
323 Nugampola PR 339.9 339.9 0.0 486.6 KUR
324 Nuwaragala FR 28/06/1929 42150.8 33943.8 6072.8 4273.3 AMP BAT
325 Nuwaragala ; PR 154.6 154.6 0.0 0.0 BAT
326 Nuwaragam FR 24/05/1935 2584.8 2314.6 2100.0 2757.5 ANU
327 Ohiya PR 1925.5 1769.1 4251.0 2068.9 BAD NUW
328 Olabedda FR 28/04/1933 153.6 73.0 0.0 41.8 GAL
329 Oliyagankele FR# 08/09/1939 488.6 486.0 20.2 437.0 MTR
330 Omunugala FR 18/03/1927 54221.8 53666.6 2024.2 0.0 AMP BAT
331 Ottery-Queenswood PR 52.6 52.6 0.0 0.0 NUW
333 Padawiya PR 97901.7 97664.3 0.0 99284.9 ANU
334 Pallai FR 10/06/1921 460.9 460.9 0.0 744.7 JAF
335 Pallegama-Himbiliyakada PR 4547.2 4547.2 0.0 968.7 MTL
336 Pallekele FR 04/02/1896 14513.8 12721.4 0.0 74.3 KUR
339 Pallepattu FR 23/09/1892 680.9 657.9 0.0 49.9 RAT
340 Panagoda PR 266.3 266.3 0.0 127.6 GAL
341 Panama PR 37635.8 36907.4 0.0 38119.5 AMP.
342 Panikkankulam FR 7303.8 6534.9 1417.0 6828.3 MUL
343 Panilkanda FR 18/03/1927 588.1 588.1 0.0 630.1 MTR
344 Pankulam-Northern Block PR 53871.8 52355.9 0.0 57170.1 TRI
345 Pannagama PR 165.9 164.9 0.0 193.5 KUR
348 Pannala FR 12/05/1893 129.9 129.0 0.0 135.5 RAT
346 Pannala PR 1173.7 769.1 0.0 1191.2 NUW
347 Pannawa-Geppalawa PR 316.5 314.4 0.0 389.8 KUR
349 Pansalhinna PR 123.4 123.4 0.0 131.9 KUR
350 Panwewa Fk 01/03/1940 241.7 241.7 0.0 247.9 KUR
351 Paradeniya FR 08/10/1897 31.2 Sp) 0.0 38.9 KEG
352 Paragaharuppe FR 01/03/1940 54.0 54.0 0.0 51.0 KUR
353 Parantan FR 22/09/1946 2897.1 2897.1 0.0 1544.3 MUL VAV
356 Paspolakanda PR 112.5 107.4 0.0 24.4 KEG
357 Pattipola FR 23/09/1938 394.9 393.3 1214.6 430.6 BAD
358 Pattipola~-Ambawela PR 1498.0 1480.3 0.0 1954.5 NUW
359 Peak Wilderness PR 5665.7 5665.7 0.0 4381.5 KEG NUW
362 Pedro PR 6879.7 6757.0 6882.5 7554.8 NUW
363 Pelawatta FR 110.0 110.0 0.0 104.0 KAL
365 Pelwehera FR 27/03/1936 1925.9 1925.9 0.0 1962.3 MTL
364 Pelwehera PR 240.0 240.0 0.0 117.0 MTL
367 Plenda West PR 145.3 145.3 0.0 153.6 KAL
368 Polawattakanda FR 29.4 0.3 0.0 29.4 KAL
369 Polgahakanda FR 18/09/1942 862.3 577.4 0.0 887.6 GAL
370 Polgahawila PR 304.7 286.6 0.0 237.5 _ GAL
371 Polgolla FR 02/03/1888 53.6 51.5 0.0 68.2 KUR
372 Polhunnawa FR 06/01/1933 193.0 193.0 0.0 23.9 GAL
373 Polkatukanda FR 01/03/1940 151.5 151.5 0.0 155.3 KUR
375 Pomparippu FR 7021.3 7021.3 0.0 0.0 PUT
376 Potawa PR 77.2 77.2 0.0 52.2 MTL

145

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
Name and national designation date

377 Potuwewa PR 241.6 99.6 0.0 219.9 KUR

378 Preston-Elsmere PR 60.7 60.7 0.0 0.0 NUW

380 Puwarasankulam FR 4377.6 4292.6 0.0 3649.8 VAV

382 Pyrendawa FR 24/10/1890 361.3 360.4 0.0 285.1 PUT

381 Pyrendawa PR 125.5 110.6 0.0 60.1 PUT

383 Ragalla PR 268.1 268.1 0.0 279.1 NUW

384 Rajawaka PR 2387.6 2387.6 0.0 77.4 RAT

385 Rambodagalla PR 202.3 202.3 0.0 124.8 KUR

388 Rammalakanda FR# 21/05/1926 1698.1 1406.7 404.8 1724.6 HAM MTR
386 Rammalakanda PR 453.7 453.7 0.0 0.0 RAT

387 Rammalakanda PR 4.8 4.8 0.0 385.5 MTR

389 Ranwala PR 1117.7 867.5 0.0 1186.2 RAT

390 Ranwaragalakanda PR# 192.1 192.1 0.0 125.5 KAL

391 Rathkarawwa PR 4050.5 4021.4 0.0 0.0 RAT

393 Rawanella PR 331.8 331.8 0.0 376.6 BAD

394 Rilagala PR 566.6 566.6 0.0 507.2 KAN NUW
397 Rugam PR 2143.6 2139.6 0.0 117.4 BAT

404 Sangappale PR 4694.8 4505.8 0.0 4536.5 KUR

405 Sawarangalawa PR 6309.5 5530.0 0.0 7096.1 KUR PUT
406 Sellankandal 4 FR 02/09/1892 4268.6 4265.8 0.0 3779.5 PUT

407 Sellankandal PR 5526.0 "4542.2 0.0 5738.3 PUT

412 Sinharaja FR 21/05/1926 3724.6 3663.9 0.0 0.0 GAL MTR
413. Sinharaja FR 08/05/1875 2428.1 2428.1 0.0 2694.8 RAT

414 Sinharaja NHWA_ 21/10/1988 11187.0 11187.0 0.0 0.0 GAL MTR RAT
411 Sinharaja PR 2772.1 2772.1 0.0 3054.3 RAT

416 Siyambalangamuwa FR 19/08/1938 63.7 63.3 0.0 56.5 KEG
- 420 Sundapola FR 306.9 121.6 10.1 60.0 KUR

421 Talagahakanda = _ FR 30/09/1949 60.4 60.4 0.0 72.9 RAT

422 Talagomuwa FR 04/12/1936 81.3 81.3 0.0 58.3 KUR

424 Tandikele PR 370.3 290.2 0.0 46.6 RAT

425 Tanduwan c FR 10/06/1921 1115.3 791.6 0.0 1146.3 MUL

427 Taranagala FR 05/09/1941 28.3 28.3 0.0 38.7 KEG

428 Tawalama PR 167.5 167.5 0.0 197.5 GAL

431 Teravil Oddusuddan FR 10/06/1921 38595.8 36552.1 2024.2 38042.6 MUL

432 Tibbutukanda PR 233.9 233.9 0.0 255.3 RAT

433 Timbiriwewa PR 1274.0 56.8 0.0 1043.6 KUR

434 Tonigala PR 1486.8 937.3 0.0 1546.2 PUT

435 Tonikallu PR 655.9 136.3 0.0 0.0 VAV

439 Udalelegama FR 23/12/1921 17.9 17.9 0.0 28.8 BAD

440 Udapolakanda PR 63.9 63.9 0.0 98.3 KUR

441 Udawattakele FR 15/10/1897 104.0 103.0 102.0 118.7 KAN

443 Ulinduwewa FR 17/10/1902 104.7 104.7 0.0 104.4 RAT

444 Unaliya PR 1400.2 1096.7 0.0 1540.0 PUT

445 Uragaha PR 1567.3 1567.3 0.0 98.8 GAL

446 Usangoda PR 277.2 252.9 0.0 25.4 HAM

447 Vaddakachchi FR 7109.5 7109.5 0.0 6953.3 JAF VAV
448 Vannivilankulam FR 10/06/1921 10953.9 10529.0 0.0 10879.6 MAN MUL VAV
449 Vappiah-Verugal FR 03/10/1941 4372.6 4344.7 0.0 3655.5 TRI

451 Veppal PR 10518.7 10114.0 0.0 10495.0 MAN

453 Viharekele FR# 26/04/1935 825.1 625.1 0.0 861.6 MTR

454 Wagawatta PR 143.3 113.0 0.0 105.7 KAL

455 Walankanda FR 03/04/1890 832.9 711.5 0.0 938.9 RAT

456 Walawe Basin FR# 08/09/1893 3237.5 3229.7 0.0 1739.3 RAT

457 Walbotalekanda PR 41.7 41.7 0.0 49.6 GAM

458 Wanniyagama PR 15596.6 14417.8 0.0 15843.6 . PUT

459 Waratalgoda PR 1889.9 1889.9 0.0 1940.0 RAT

462 Waulkele FR 25/08/1944 20.7 20.7 0.0 22.1 KUR

463 Wedakanda PR 5180.0 5180.0 0.0 4248.4 ANU

464 Wedasitikanda FR 07/09/1978 1343.4 1343.4 1344.1 541.7 HAM MON
465 Weerakulicholai-Elavankulam PR 30128.9 29192.4 0.0 30664.7 PUT

466 Wegodapola PR 418.5 398.2 0.0 492.3 MTL

467 Weherabendikele PR 285.7 275.0 0.0 334.2 PUT

468 Welegama PR 639.0 639.0 0.0 747.2 BAD

470 Welhella-Ketangilla FR 13/04/1896 128.8 114.6 0.0 164.6 KEG

471 Welihena FR# 15/11/1935 333.1 296.8 0.0 337.4 MTR

472 Welikanda PR 242.0 43.1 0.0 421.7 KAN

473 Welikumbura FR 12/02/1937 80.9 80.9 0.0 64.8 KUR

474 Wellana FR 23/12/1932 85.4 85.4 0.0 99.1 MTR

475 Weuda Mukalana FR 14/06/1918 152.1 152.1 0.0 144.7 “KUR

476 Wewelkandura PR 429.0 429.0 0.0 459.1 RAT

477 Wilikulakanda PR 352.2 310.0 0.0 274.4 GAM

484 Wilpotha PR 2665.3 2547.5 0.0 2683.6 PUT

487 Yagirala FR 3014.7 2390.2 0.0 2999.8 KAL

146

Area (ha)

EMD Notification Notified Present MAB* GIS District(s)
No. Name and national designation date

486 Yagirala PR# 34.1 34.1 0.0 0.0 KAL

489 Yakdessakanda PR 1011.7 1010.9 0.0 1464.9 KUR

490 Yakkatuwa FR 26/06/1931 296.2 296.2 0.0 75.4 GAL

494 Yalapitiya PR 43.3 43.3 0.0 58.7 KEG

495 Yatale PR 56.9 56.9 0.0 61.5 KAN KUR
496 Yoda Ela FR 10/02/1950 2288.2 1585.6 0.0 1733.7 ANU

DEPARTMENT OF WILDLIFE CONSERVATION

8 Ambalangoda-Hikkaduwa Rocky Islets Ss 25/10/1940 1.3 13 0.0 0.0 GAL

14 Anuradhapura Ss 27/05/1938 3500.7 3500.7 0.0 3525.7 ANU

31 Bar Reef Marine Ss 03/04/1992 30670.0 30670.0 0.0 28036.0 PUT

36 ~— Belllanwila-Attidiya Ss 25/07/1990, 60.0 60.0 0.0 400.6 COL

43 Buddhangala Ss 01/11/1974 1841.3 1841.3 OL0 ie 2821.5 AMP.

44° Bundala NP 31/12/1992 6215.9 6215.9 0.0 4664.6 HAM

51 Chundikulam Ss 01/03/1938 11149.1 11149.1 0.0 11107.5 JAF MUL
95 Flood Plains NP 07/08/1984 17350.7 17350.7 0.0 16989.7 POL

97 Gal Oya Valley NP 12/02/1954 25899.9 25899.9 0.0 36043.7 MON

98 Gal Oya Valley North-East Ss 12/02/1954 12432.0 12432.0 0.0 12332.7 AMP MON
99 Gal Oya Valley South-West S 12/02/1954 15281.0 15281.0 0.0 18168.2 AMP MON
107 Galway’s Land S 01/03/1938 56.7 56.7 0.0 0.0 NUW

111 Giant's Tank Ss 24/09/1954 3941.2 3941.2 0.0 4008.0 MAN

119 Great Sober Island s 21/03/1963 64.5 64.5 0.0 65.9 TRI

123. Hakgala SNR 01/03/1938 1141.6 1141.6 0.0 1198.4 BAD NUW
135 Hikkaduwa Marine S 18/05/1979 44.5 44.5 0.0 0.0 GAL

137 Honduwa Island Ss 19/11/1973 8.0 8.0 0.0 0.0 GAL

139 Horagolla Ss 05/10/1973 13.4 13.4 0.0 0.0 GAM

140 Horton Plains NP 16/03/1988 3159.8 3159.8 0.0 3015.2 NUW

161 Kahalla-Pallekele Ss 11/07/1989 21690.0 21690.0 0.0 23172.5 ANU KUR
164 Kalametiya Kalapuwa Ss 28/06/1984 712.0 712.0 0.0 2453.1 HAM

186 Katagamuwa Ss 27/05/1938 1003.6 1003.6 0.0 1222.3 HAM

187 Kataragama Ss 27/05/1938 837.7 837.7 0.0 594.4 MON

188 Kegalle S 14/03/1941 113.3 113.3 0.0 107.4 KEG

199 Kimbulwan Oya Ss 21/06/1963 492.1 492.1 0.0 610.0 KUR

207 Kokilai Lagoon S 18/05/1951 2995.0 2995.0 0.0 5361.2 MUL TRI
216 Kudumbigala Ss 28/09/1973 4403.0 4403.0 0.0 4409.1 AMP

223. Lahugala-Kitulana NP 31/10/1980 1554.0 1554.0 0.0 4911.0 AMP

229 Little Sober Island Ss 21/03/1963 6.5 6.5 0.0 0.0 TRI

231 Lunugamvehera NP Proposed 2071.8 2071.8 0.0 0.0 HAM MON
236 Madhu Road Ss 28/06/1968 26676.9 26676.9 0.0 27398.6 MAN MUL
238 Madunagala Ss 29/06/1993 791.0 791.0 0.0 0.0 HAM

239 Maduru Oya Block | NP 09/11/1983 51469.4 51469.4 0.0 $8752.2 BAD AMP POL
240° Maduru Oya Block 2 NP 16/09/1985 7381.2 7381.2 0.0 0.0 “AMP

246 Mahakanadarawa Wewa s 09/12/1966 0.0 0.0 0.0 1679.7 ANU

252 Maimbulkande-Nittambuwa s 31/10/1972 21.8 21.8 0.0 0.0 GAM

278 Mihintale Ss 27/05/1938 999.6 999.6 0.0 0.0 ANU

280 Minneriya-Giritale s 28/07/1938 6693.5 6693.5 0.0 5914.3 POL

281 Minneriya-Giritale Block 1 NR 12/02/1988 7529.1 7529.1 0.0 8674.8 POL

999 Muthurajawella Ss Proposed 0.0 0.0 0.0 0.0 COL

314 Nelugala JC 16/01/1970 10360.0 10360.0 0.0 0.0 BAT POL
321 Nilgala JC Proposed 0.0 0.0 0.0 0.0 AMP POL
322 Nimalawa S 03/02/1993 1065.9 1065.9 0.0 985.0 HAM

332 Padaviya Tank Ss 21/06/1963 6475.0 6475.0 0.0 6486.4 ANU

337 Pallemalala S 23/10/1942 13.8 13.8 0.0 0.0 HAM

354 Parapuduw Nun's Island Ss 17/08/1988 189.8 189.8 0.0 1517.9 GAL

355 Parititivu Island Ss 18/05/1973 97.1 97.1 0.0 0.0 JAF

361 Peak Wilderness s 01/11/1940 22379.2 22379.2 0.0 0.0 KEG NUW RAT
366 Pigeon Island Ss 01/11/1974 47 47 0.0 0.0 TRI

374 Polonnaruwa s 27/05/1938 1521.6 1521.6 0.0 1750.0 POL

392 Ravana Ella Ss 18/05/1979 1932.0 1932.0 0.0 1910.1 BAD

395 Ritigala SNR 07/11/1941 1528.2 1528.2 0.0 1521.3 ANU

396 Riverine NR 23/07/1991 824.2 824.2 0.0 0.0 AMP POL
398 Ruhuna Block | NP 25/02/1938 13679.2 13679.2 0.0 14462.4 HAM

399 Ruhuna Block 2 NP 03/09/1954 9931.0 9931.0 0.0 33389.2 MON

400 Ruhuna Block 3 NP 28/04/1967 40775.4 40775.4 0.0 41254.3 MON

401 Ruhuna Block 4 NP 09/10/1969 26417.7 26417.7 0.0 26314.3 MON

402 Ruhuna Block 5 NP 05/10/1973 6656.2 6656.2 0.0 2238.9 MON

403 Sagamam S 21/06/1963 616.4 616.4 0.0 0.0 AMP

408 Senanayake Samudra S 12/02/1954 9323.9 9323.9 0.0 0.0 MON

409 Seruwila-Allai Ss 09/10/1970 15540.0 15540.0 0.0 12908.4 TRI

410 Sigiriya S 26/01/1990 5099.0 5099.0 0.0 5163.7 POL MTL
417 Somawathiya Block | NP 02/09/1986 21056.5 21056.5 0.0} 38984.8 POL TRI
418 Somawathiya Block 2 NP 12/05/1987 16589.2 16589.2 0.0} POL TRI
419 Sri Jayawardenapura Bird Ss 09/01/1985 449.2 449.2 0.0 0.0 COL

426 Tangamalai Ss 01/03/1938 131.5 131.5 0.0 194.1 BAD

430 Telwatta s 25/02/1938 1424.5 1424.5 0.0 0.0 GAL

436 © Trikonamadu NR 24/10/1986 25019.2 25019.2 0.0 24125.7 POL BAT
437 Trinconmalee Naval Headworks Ss 21/06/1963 18130.3 18130.3 0.0 18021.6 TRI

438 Uda Walawe NP 30/06/1972 30821.0 30821.0 0.0 31666.0 MON) RAT
442 Udawattakele s 01/03/1938 104.0 104.0 0.0 0.0 KAN

147

Area (ha)

EMD Notification Notified Present MAB* GIS District (s)
No. Name and national designation date

450 Vavunikulam Ss 21/06/1963 4856.3 4856.3 0.0 7721.6 MAN MUL
452 Victoria-Randenigala-Rantambe Ss 30/01/1987 42087.1 42087.1 0.0 43236.0 KAN NUW
460 Wasgomuwa Lot | NP 07/08/1984 29036.0 29036.0 0.0} 42698.6 POL MTL
461 Wasgomuwa Lot 2 NP 07/08/1984 4612.7 4612.7 0.0} POL

469 Welhella-Ketagille Ss 18/02/1949 134.2 134.2 0.0 0.0 KEG

478 Wilpattu Block | NP 25/02/1938 54953.2 54953.2 0.0} ANU PUT
479 Wilpattu Block 2 NP 28/04/1967 7021.4 7021.4 0.0} PUT

480 Wilpattu Block 3 NP 27/08/1969 22981.4 22981.4 0.0} 132255 .0 ANU

481 Wilpattu Block 4 NP. 05/12/1969 25252.9 25252.9 0.0} ANU

482 Wilpattu Block 5 NP 07/12/1973 21484.8 21484.8 0.0} PUT

483 Wilpattu North Ss 25/02/1938 1877.7 1877.7 0.0} MAN

485 Wirawila-Tissa Ss 27/05/1938 4164.2 4164.2 0.0 3034.2 HAM

491 Yala SNR 25/02/1938 28904.7 28904.7 HAM

492 Yala East Block | NP 05/12/1969 17863.4 17863.4 0.0} 18372.4 AMP

493 Yala East Block 2 NP. 25/12/1969 285.2 285.2 0.0} AMP

™ Area designated as a national Man and Biosphere Reserve by the Forest Department.
# Recently designated as a Conservation Forest by the Forest Department, but not in law

148

Annex 2

IMPORTANCE OF NATURAL FORESTS FOR CONTROLLING SOIL EROSION

EMD Rainfall Erosivity Slope Erodibility Erosion _ Erosion
District No. Forest name (mm yr") (J m? yr") (mm') (t ha? yr") rank
MAT 497 Kalubowitiyana 4189 42653 0.48 0.22 2669.1 1
GAL 120 Habarakada 4397 44723 0.41 0.22 2041.9 2
GAL 509 Auwegalakanda 4500 45748 0.38 0.22 1794.2 3
KEG NUW RAT 361 Peak Wilderness 4320 43957 0.36 0.22 1547.3 4
RAT 274 Messana 3753 38315 0.38 0.22 1502.7 5
KEG 191 Kelani Valley 4933 50056 0.32 0.22 1392.2 6
GAL 506 Tiboruwakota 4350 44255 0.34 0.22 1389.5 7
RAT 529 Dotalugala 4075 41519 0.33 0.22 1228.0 8
RAT 386 Rammalakanda 3440 35201 0.35 0.22 1171.2 9
RAT 476 Wewelkandura 4036 41131 0.32 0.22 1143.9 10
KEG 515 Dedugalla-Nangala 4900 49728 0.29 0.22 1135.9 11
RAT 432 Tibbutukanda 2500 25848 0.36 0.27 1116.6 12
MAT 501 Aninkanda 3250 33310 0.35 0.22 1108.3 13
GAL 511 Bambarawana 4150 42265 0.31 0.22 1103.2 14
KAL 129 Haycock 4263 43390 0.30 0.22 1060.6 15
MAT 77 Diyadawa 3410 34902 0.33 0.22 1032.3 16
GAL 510 Yakdehikanda 3600 36793 0.32 0.22 1023.3 17
GAL 508 Hindeinattu 3083 31649 0.34 0.22 993.7 18
KEG 551 Usgala 5295 53658 0.26 0.22 985.2 19
RAT 530 Appalagala 2610 26942 0.36 0.22 948.4 20
MAT 500 Derangala 3500 35798 0.30 0.22 875.1 21
MTL 565 Makulussa 2428 25131 0.32 0.27 857.8 22
GAL 253 Malambure 3937 40146 0.28 0.22 854.9 23
KAN 522 Knuckles 3184 32654 0.31 0.22 852.3 24
KEG U Amanawala-Ampane 5371 54414 0.24 0.22 851.3 25
GAL 69 Dellawa 3759 38375 0.28 0.22 817.1 26
RAT 549 Alutwelawisahena 4050 41270 0.27 0.22 817.1 26
BAD 306 Namunukula 2314 23997 0.35 0.22 798.4 28
RAT 184 Karawita 4184 42604 0.26 0.22 782.2 29
RAT 205 Kobahadunkanda 3801 38793 0.27 0.22 768.1 30
RAT 527 Angamana 3800 38783 0.27 0.22 767.9 31
RAT 455 Walankanda 3455 35350 0.28 0.22 752.7 32
RAT 348 Pannala 3448 35280 0.28 0.22 751.3 33
RAT 543 Handuwelkanda 3950 40275 0.26 0.22 739.5 34
RAT 456 Walawe Basin 3121 32027 0.29 0.22 731.6 35
KAN 192 Kelani Valley 5260 53310 0.22 0.22 700.8 36
RAT 544 Gorangala 4400 44753 0.24 0.22 700.1 37
RAT 528 Asantanakanda 3400 34803 0.27 0.22 689.1 38
RAT 68 Delgoda 3939 40166 0.25 0.22 681.8 39
RAT 133 Hidellana-Weralupe 4100 41768 0.24 0.22 653.4 40
KEG 514 Sembawatte 4891 49638 0.22 0.22 652.5 41
KEG 513 Batahena 5368 54384 0.21 0.22 651.4 42
MAT 343 Panilkanda 3133 32146 0.27 0.22 636.5 43
MAT 499 Silverkanda 3380 34604 0.26 0.22 635.3 44
MTL 572 Menikdeniya 1750 18385 0.32 0.27 627.5 45
MTL 562 Sacombe 2313 23987 0.28 0.27 626.9 46
RAT 294 Muwagankanda 3854 39320 0.24 0.22 615.1 47
KAN 100 Galaha 2788 28713 0.28 0.22 611.4 48
KAN 521 Wewegalatana 2408 24932 0.30 0.22 609.5 49
KAL 269 Meegahatenna 4480 45549 0.22 0.22 598.8 50
NUW 197 Kikilimana 2729 28126 0.28 0.22 598.9 50
RAT 548 Dumbara 4400 44753 0.22 0.22 588.3 51
BAD 610 Kithedallakanda 2299 23848 0.30 0.22 582.9 52
KUR 78 Doluwakanda 1850 19380 0.30 0.27 581.4 53
RAT 288 Morahela 3600 36793 0.24 0.22 575.6 54
KAL 516 Boralugoda 4250 43260 0.22 0.22 568.7 55
MTL 561 Opalagala 2867 29499 0.24 0.27 566.4 56
RAT 241 Magurugoda 4188 42643 0.22 0.22 560.6 57
RAT 545 Handapan Ella 3475 35549 0.24 0,22 556.1 58
RAT 459 Waratalgoda 4564 46385 0.21 0.22 555.6 59
KUR 318 Neugalkanda 1902 19898 0.32 0.22 553.4 60
RAT 443 Ulinduwewa 3100 31818 0.25 0.22 540.1 61
RAT 217 Kudumiriya 3603 36823 0.23 0.22 529.1 62
RAT 71 Delwela 3587 36663 0.23 0.22 526.8 63
RAT 535. Kuragala 2200 22863 0.26 0.27 515.2 64

149

EMD Rainfall Erosivity Slope Erodibility Erosion _ Erosion

District No. Forest name (mm yr") (J m? yr") (mm'') (t ha” yr") rank
a ar ee

RAT 112 Gilimale-Eratne 4652 47260 0.20 0.22 513.4 65
KUR 489 Yakdessakanda 1872 19599 0.31 0.22 511.6 66
GAL 507 Homadola 3800 38783 0.22 0.22 509.8 67
BAD 468 Welegama 2665 27489 0.26 0.22 504.7 68
BAD NUW 327 Ohiya 2252 23380 0.28 0.22 497.9 69
RAT 546 Gongala 3100 31818 0.24 0.22 497.8 70
KUR 80 Dunkanda 1796 18843 0.28 0.27 492.4 71
ANU 395 Ritigala 1550 16395 0.30 0.27 491.9 72
KAL 512 Vellihallure 4400 44753 0.20 0.22 486.2 73
RAT 540 Galbokaya 2220 23062 0.25 0.27 480.5 74
GAL 328 Tawalama 4340 44156 0.20 0.22 479.7 75
KUR 552 Butawella 2103 21898 0.28 0.22 466.3 77
KUR 256 Manapaya 1850 19380 0.30 0.22 473.7 78
RAT 538 Gallegodahinna 2300 23858 0.24 0.27 458.1 79
BAD 392 Ravana Ella 1900 19878 0.29 0.22 454.0 80
KAL 289 Morapitiya-Runakanda 4466 45409 0.19 0.22 445.2 81
RAT 28 Bambarabotuwa 3979 40564 0.20 0.22 440.7 82
KAN 519 Guruyalle 2636 27201 0.22 0.27 438.8 83
COL 222 Labugama-Kalatuwana 3950 40275 0.20 0.22 437.6 84
GALMTRRAT 414 Sinharaja 3946 40235 0.20 0.22 437.1 85
KUR 157 Kadawatkele 1850 19380 0.26 0.27 436.7 86
MON 583 Velihela 1450 15400 0.29 0.27 431.7 87
RAT 537 Narangattahinna 2350 24355 0.23 0.27 429.5 88
MON 580 Dummalahela 1550 16395 0.28 0.27 428.5 89
BAD 611 Keeriyagolla 2654 27380 0.24 0.22 428.3 90
HAM 388 Rammalekanda 2837 29201 0.23 0.22 419.6 91
MTL 571 Gederagalpatana 1769 18574 0.26 0.27 418.5 92
MTL 566 Gosgahapatana 1914 20017 0.25 0.27 417.0 93
MAT 498 Kurulugala 3400 34803 0.21 0.22 416.9 94
POL 598 Gunner’s Quoin 1450 15400 0.28 0.27 402.5 95
KUR 101 Galgiriyakanda 1450 15400 0.28 0.27 402.5 96
RAT 550 Kiribatgala 3263 33440 0.21 0.22 400.5 97
GAL 175 Kanneliya 3984 40614 0.19 0.22 398.2 98
KAL 166 Kalugala 4450 45250 0.18 0.22 398.2 98
KAL 390 Ranwaragalakanda 3950 40275 0.19 0.22 394.9 100
MAT 138 Horagala-Paragala 3209 32902 0.21 0.22 394.1 101
MTL 568 Beliyakanda 1650 17390 0.26 0.27 391.9 102
KAN NUW 394 Rilagala 4373 44484 0.18 0.22 391.5 103
NUW 362 Pedro 2523 26077 0.23 0.22 374.7 104
GAL 38 Beraliya (Kudagala) 3660 37390 0.19 0.22 366.6 105
NUW 40 Bogawantalawa 2699 27828 0.22 0.22 365.8 106
RAT 547 Paragala 4500 45748 0.17 0.22 359.1 107
NUW 1 Agra-Bopats 2398 24833 0.23 0.22 356.8 108
BAD NUW 123 Hakgala 2176 22624 0.24 0.22 353.9 109
RAT 19 Ayagama 4421 44962 0.17 0.22 352.9 110
NUW 172 Kandapola Sita Eliya 2157 22435 0.24 0.22 351.0 111
GAL 65 Dediyagala 3437 35171 0.19 0.22 344.8 112
KEG 4 Alapalawala 2789 28723 0.21 0.22 344.0 113
RAT 72 Demanagammana 3813 38912 0.18 0.22 342.4 114
RAT 541 Kabarakalapatana 3400 34803 0.19 0.22 341.2 115
MAT 293 Mulatiyana 3034 31161 0.20 0.22 338.5 116
RAT 532 Talawegoda 4200 42763 0.17 0.22 335.7 117
MTL 570 Tottawelgola 1627 17161 0.24 0.27 329.5 118
GAL 303 Nakiyadeniya 3561 36405 0.18 0.22 320.4 119
BAD 426 Tangamalai 2348 24335 0.22 0.22 319.9 120
RAT 57 Dambuluwana 4479 45539 0.16 0.22 316.6 121
MON 588 Wadinahela 1853 19410 0.22 Ona 313.1 122
RAT 504 Masimbula 3084 31659 0.19 0.22 310.4 123
MON 581 Monerakelle 1524 16137 0.24 0.27 309.8 124
RAT 169 Kumburugamuwa 2225 23111 0.20 0.27 308.2 125
RAT 533 Mulgama 2450 25350 0.19 0.27 305.0 126
COL 146 Indikada Mukalana 3800 38783 0.17 0.22 304.4 127
BAD 609 Madigala 1850 19380 0.24 0.22 303.2 128
GAL 37 Beraliya (Akuressa) 2671 27549 0.20 0.22 299.3 129
MON 604 Viyanahela 1750 18385 0.22 0.27 296.6 130
GAL 369 Polgahakanda 4051 41280 0.16 0.22 287.0 131
HAM 464 Wedasitikanda 1062 11540 0.27 0.27 280.4 132
MTL 567 Amsawagama 2186 22723 0.19 0.27 273.4 133
MON 582 Lolehela 1450 15400 0.23 0.27 271.6 134
KUR 553 Talpattekanda 1550 16395 0.22 0.27 264.5 135
MON 585 Kitulhela 1550 16395 0.22 0.27 264.5 135
MTL 560 Galboda 2316 24017 0.18 0.27 259.4 137
RAT 389 Ranwala 2496 25808 0.19 0.22 253.0 138
MTL 563 Talabugahaela 2250 23360 0.18 0.27 252.3 139
GAM 247 Mahakanda 3115 31967 0.17 0.22 250.9 140

150

EMD Rainfall Erosivity Slope Erodibility Erosion _ Erosion

District No. Forest name (mm yr") (J m? yr") (mm") (t ha yr") rank
NUW 383 Ragalla 2205 22912 0.20 0.22 248.9 141
MON 577 Korathalhinna 1450 15400 0.22 0.27 248.5 142
MON 578 Ulgala (old) 1450 15400 0.22 0.27 248.5 142
KAL 221 Kurana Madakada 3988 40653 0.15 0.22 248.4 144
KAL 487 Yagirala 4464 45390 0.14 0.22 241.6 145
KAL ils} Neluketiya Mukalana 4458 45330 0.14 0.22 241.3 146
KAN 518 Hopewell 2250 23360 0.22 0.17 237.3 147
KAL 70 Delmella Yatagampitiya 4339 44146 0.14 0.22 235.0 148
MON 591 Murutukanda 1672 17609 0.20 0.27 234.8 149
ANU 639 Katupotakanda 1350 14405 0.22 0.27 232.4 150
RAT 234 Madampe 3233 33141 0.16 0.22 230.4 15]
MON x 584 Guruhela 1450 15400 0.21 0.27 226.4 152
MON 605 Balanagala 1750 18385 0.19 0.27 221.2 153
NUW 128 Harasbedda 2421 25062 0.18 0.22 220.5 154
MON 576 Ulgala 1515 16047 0.20 0.27 214.0 155
RAT 272 Marakele 4550 46245 0.13 0.22 212.3 156
KAN NUW 452 Victoria-Randenigala-Rantambe 1963 20505 0.22 0.17 208.3 157
MTL 564 Heratgedara 2062 21490 0.17 0.27 207.0 158
GAL 173 Kandawattegoda 2550 26345 0.17 0.22 206.8 159
RAT 298 Nahiti Mukalana 3303 33838 0.15 0.22 206.8 159
RAT 542 Digandala 3300 33808 0.15 0.22 206.6 161
NUW 140 Horton Plains 2534 26186 0.17 0.22 205.5 162
ANU 635 Manawewakanda 1449 i 15390 0.20 0.27 205.2 163
MON 589 Begahapatana 1805 18932 0.18 0.27 204.5 164
NUW 248 Mahakudagala 2171 22574 0.18 0.22 198.7 165
MON 606 Dyabodahela 1750 18385 0.18 0.27 198.6 166
COL 170 Kananpella 3650 37290 0.14 0.22 198.5 167
MTL 573 Puswellagolla 1699 17878 0.18 0.27 193.1 168
- KUR 66 Degadaturawa 1500 15898 0.19 0.27 191.3 169
MON 579 Diggala 1668 17569 0.18 0.27 189.7 170
NUW 52 Conical Hill 2292 23778 0.17 0.22 186.6 171
KAN 520 Illukkanda 2594 26783 0.16 0.22 186.2 172
KAL 147 Ingiriya 3917 39947 0.13 0.22 183.4 173
BAD 608 Welanwita 2119 22057 0.17 0.22 173.1 174
COL 285 Miriyagalla 3655 37340 0.13 0.22 171.4 175
MTL 82 Elagomuwa 2146 22325 0.15 0.27 167.4 176
MON 586 Diggalahela 1450 15400 0.18 0.27 166.3 177
KAN MTL 45 Campbell’s Land 2626 27101 0.15 0.22 165.6 178
KAN 517 Matinapatana 2070 21569 0.19 0.17 163.4 179
BAD MON 39 Bibilehela 2050 21370 0.15 0.27 160.3 181
MTL 335 Pallegama-Himbiliyakada 2320 24057 0.14 0.27 157.2 182
MON 607 Rediketiya 1750 18385 0.16 0.27 156.9 183
RAT 384 Rajawaka 2295 23808 0.14 0.27 155.5 184
MAT 453 Viharakele 2444 25291 0.15 0.22 154.6 185
MAT 471 Welihena 2723 28067 0.14 0.22 149.4 186
MAT 329 Oliyagankele 2465 25499 0.14 0.22 135.7 187
HAM 178 Kanumuldeniya 2432 25171 0.14 0.22 134.0 188
RAT 536 Hapugala 2275 23609 0.13 0.27 133.0 189
NUW 307 Nanu Oya 2335 24206 0.14 0.22 128.9 190
RAT 534 Galleletota 2400 24853 0.14 0.27 162.4 190
ANU 633 Labunoruwa 1430 15201 0.15 0.27 114.0 191
GAL 208 Kombala-Kottawa 2680 27639 0.12 0.22 108.1 192
MON 587 Westminster Abbey 1550 16395 0.14 0.27 107.1 193
NUW 270 Meepilimana 2173 22594 0.13 0.22 103.7 194
KUR 131 Henegedaralanda 1750 18385 0.13 0.27 103.6 195
MTL 558 Masawa 1750 18385 0.13 0.27 103.6 195
MON 305 Namandiya 1671 17599 0.13 0.27 99.1 197
MON 590 Randeniya 1950 20375 0.12 0.27 97.8 198
KAN 442 Udawattakele 1950 20375 0.15 0.17 96.2 199
GAL 62 Darakulkanda 3457 35370 0.10 0.22 96.1 200
RAT 539 Hataramune 2260 23460 0.11 0.27 94.6 201
NUW 358 Pattipola-Ambawela 2229 23151 0.12 0.22 90.5 202
MON 595 Radaliwinnekota 1750 18385 0.12 0.27 88.2 203
MAT 263 Masmullekele 2076 21629 0.12 0.22 84.6 204
KUR 177 Kanugollayaya 1950 20375 0.12 0.22 79.7 205
ANU 640 Getalagamakanda 1300 13908 0.12 0.27 66.8 206
ANU 645 Puliyamkulam 1350 14405 0.11 0.27 58.1 207
MON 27 Bakinigahawela 1650 17390 0.10 0.27 58.0 208
ANU 634 Puliyankulama 1500 15898 0.10 0.27 53.0 209
POL 596 Kudagala North 1850 19380 0.09 0.27 Seas 210
MON 575 Dewagiriya 1713 18017 0.09 0.27 48.6 211
ANU 636 Aruwewa 1350 14405 0.10 0.27 48.0 212
RAT 531 Kudagoda 2625 27091 0.07 0.27 44.2 213
HAM 249 Mahapitakanda 2368 24534 0.08 0.22 42.6 214
MON 594 Golupitiyahela 1750 18385 0.08 0.27 39.2 215

151

EMD Rainfall Erosivity Slope Erodibility Erosion _ Erosion

District No. Forest name (mm yr") (J m? yr") (mm") (t ha" yr") rank
MAT 201 Kirinda-Mahayayakele 1940 20276 0.08 0.22 35.2 216
KUR 232 Ma Eliya 1550 16395 0.08 0.27 35.0 217
KUR 629 Tambutakanda 1150 12415 0.09 0.27 33.5 218
AMP MON 98 Gal Oya Valley North-East 1750 18385 0.07 0.27 30.0 219
AMP MON 99 Gal Oya Valley South-West 1600 16893 0.07 0.27 27.6 220
POL 96 Gal Oya 1600 16893 0.07 0.27 27.6 220
MAT 60 Dandeniya-Aparekke 1839 19271 0.07 0.22 25.6 222
MON 97 Gal Oya Valley 1700 17888 0.06 0.27 21.5 223
MTL 569 Etabendiwela 1650 17390 0.06 0.27 20.9 224
ANU 647 Ranawekanda 1550 16395 0.06 0.27 19.7 225
MTL 144 Inamaluwa 1550 16395 0.06 0.27 19.7 225
POL 597 Badanagala 1750 18385 0.05 0.27 15.3 227
POL MTL ; 460 Wasgomuwa Lot | 1700 17888 0.05 0.27 14.9 228
MAT 24 Badullakele 2070 21569 0.05 0.22 14.6 229
MON 592 Sitarama 1072 11639 0.06 0.27 14.0 230
POL 281 Minneriya-Giritale Block | 1489 15788 0.05 0.27 13.2 231
POL 279 Minneriya 1690 17788 0.04 0.27 9.5 232
HAM 237 Madunagala 1150 12415 0.04 0.27 9.1 233
ANU KUR 161 Kahalla-Pallekele 1600 16893 0.04 0.27 9.0 234
POL 280 Minneriya-Giritale 1568 16574 0.04 0.27 8.8 235
MAT 190 Kekanadura 1721 18097 0.03 0.22 4.4 236
ANU 632 Ratmale Kanda 1550 16395 0.02 0.27 22 237
ANU 463 Wedakanda 1350 "14405 0.02 0.27 1.9 238
HAM 526 Keulakada Wewa 1300 13908 0.02 0.27 1.9 238
MON 593 Bolhindagala 1186 12773 0.02 0.27 Wf 240
POL 600 Palliyagodella Tulana 1738 18266 0.01 0.33 0.7 241
POL 602 Mutugalla Tulana 1750 18385 0.01 0.33 0.7 241
PUT 10 Ambanmukalana 1625 17141 0.01 0.33 0.7 241
-BAD AMP POL 239 Maduru Oya Block | 1850 19380 0.01 0.27 0.6 244
HAM 44 Bundala 878 9709 0.01 0.48 0.6 244
MON RAT 438 Uda Walawe 1600 16893 0.01 0.27 0.6 244
POL 502 Medirigiriya Tulana 1735 18236 0.01 0.27 0.6 244
POL 599 Mahamorakanda 1600 16893 0.01 0.27 0.6 244
POL 601 Kumadiya Tulana 1750 18385 0.01 0.27 0.6 244
POL 603 Sinnakallu 1750 18385 0.01 0.27 0.6 244
POL MTL 410 Sigiriya 1600 16893 0.01 0.27 0.6 244
PUT 17 Attavillu 1334 14246 0.01 0.33 0.6 244
ANU 278 Mihintale 1350 14405 0.01 0.27 0.5 253
ANU 496 Yoda Ela 1363 14535 0.01 0.27 0.5 253
ANU 631 Dematawewa 1550 16395 0.01 0.27 0.5 253
ANU 637 Andarawewa 1350 14405 0.01 0.27 0.5 253
ANU 638 Pahala Mawatawewa 1350 14405 0.01 0.27 0.5 253
ANU 641 Galkulama Tirrapane 1312 14027 0.01 0.27 0.5 253
ANU 642 Galmaduwa 1350 14405 0.01 0.27 0.5 253
ANU 643 Marasinhagama 1350 14405 0.01 0.27 0.5 253
ANU 644 Tambaragalawewa 1350 14405 0.01 0.27 0.5 253
ANU 646 Medalassa Korale 1450 15400 0.01 0.27 0.5 253
ANU POL 11 Anaolundewa 1450 15400 0.01 0.27 0.5 253
ANU POL 142 Hurulu 1450 15400 0.01 0.27 0.5 253
KUR 165 Kalugala 1533 16226 0.01 0.27 0.5 253
KUR 630 Bogodayagama 1350 14405 0.01 0.27 0.5 253
MTL 574 Hiriwaduna 1550 16395 0.01 0.27 0.5 253
PUT 406 Sellankandal 1179 12704 0.01 0.33 0.5 253
PUT 407 Sellankandal 1209 13002 0.01 0.33 0.5 253
PUT 554 Aruakalu 1150 12415 0.01 0.33 0.5 253
HAM 186 Katagamuwa 1100 11918 0.01 0.27 0.4 271
HAM 491 Yala 1000 10923 0.01 0.27 . 0.4 271
HAM 525 Miyandagala 1050 11420 0.01 0.27 0.4 271
KUR 404 Sangappale 1150 12415 0.01 0.27 0.4 271
MON 187 Kataragama 1050 11420 0.01 0.27 0.4 271
MON 399 Ruhuna Block 2 1050 11420 0.01 0.27 0.4 271
MON 400 Ruhuna Block 3 1100 11918 0.01 0.27 0.4 271
MON 401 Ruhuna Block 4 1250 13410 0.01 0.27 0.4 271
MON 402 Ruhuna Block 5 1150 12415 0.01 0.27 0.4 271
PUT 458 Wanniyagama 1250 13410 0.01 0.27 0.4 271
PUT 465 Weerakulicholai-Elavankulam 1110 12017 0.01 0.27 0.4 271

Table 3 of hydrology report. [re-ranked and ordered by Rank, District, Number]

152

Annex 3

IMPORTANCE OF NATURAL FORESTS FOR PROTECTION OF HEADWATERS

Stream Stream Catchment Catchment Distance Distance Sumof Headwaters

District EMD No. Forest name number rank number rank (km) rank ranks rank
KEG NUW RAT 361 Peak Wilderness 295 5 3 3 355 4 12 1
NUW 40 Bogawantalawa 175 9 3 3 591 2 14 2
NUW 140 Horton Plains 73 23 3 3 607 1 27 3
GAL MTR RAT 414 Sinharaja 337 3 2 13 298 1S 31 4
ANU KUR 161 Kahalla-Pallekele $2 34 3 3 343 5 42 5
ANU POL 142 Hurulu 51 37 3 3 255 19 59 6
NUW 1 Agra-Bopats 179 8 1 47 337 6 61 7}
NUW 362 Pedro 354 2 1 47 308 14 63 8
NUW 197 Kikilimana 255 6 1 47 312 11 64 9
ANU POL 11 Anaolundewa 38 50 4 1 260 18 69 10
MTL 573 Puswellagolla 47 40 2 13 282 17 70 1]
RAT 545 Handapan Ella 75 20 2 13 188 40 73 12
KAN 522 Knuckles 510 1 1 47 232 28 76 13
NUW 172 Kandapola Sita Eliya 153 10 1 47 254 21 78 14
BAD 608 Welanwita 62 27 2 13 172 42 82 15
KAN NUW . 452 Victoria-Randenigala-Rantambe 318 4 1 47 204 36 87 16
BAD NUW 327 Ohiya 74 22 1 47 255 19 88 17
MAT 77 Diyadawa 73 23 2 13 158 53 89 18
NUW 52 Conical Hill 48 39 1 47 333 8 94 19
GAL 69 Dellawa 77 18 2 13 145 66 97 20
NUW 248 Mahakudagala 76 19 1 47 221 31 97 20
BAD 306 Namunukula 20 83 2) 13 333 8 104 22
MTL 571 Gederagalpatana 22 78 2 13 309 13 104 22
NUW 358 Pattipola-Ambawela 37 55 1 47 337 6 108 24
POL MTL 410 Sigiriya 14 103 3 3 431 3 109 25
KAN 520 Illukkanda 79 17 1 47 161 51 115 26
MON 607 Rediketiya 63 26 2 13 134 78 117 27
BAD NUW 123 Hakgala 38 50 1 47 252 22 119 28
GAL 175 Kanneliya 245 7 2 13 109 103 123 29
RAT 546 Gongala 38 50 2 13 147 64 127 30
GAL 303 Nakiyadeniya 46 4) 3 3 131 84 128 31
MTL 335 Pallegama-Himbiliyakada 58 29 1 47 151 61 137 32
KAN 100 Galaha 22 78 1 47 287 16 141 33
AMP MON 99 Gal Oya Valley South-West 45 42 2 13 124 88 143 34
GAL 65 Dediyagala 111 12 2 13 102 118 143 34
POL MTL 460 Wasgomuwa Lot | 113 11 1 47 120 90 148 36
RAT 456 Walawe Basin 53 32 1 47 132 81 160 37
MTL 565 Makulussa 23 75 1 47 191 39 161 38
KAN NUW 394 Rilagala 14 103 1 47 310 12 162 39
KAN 517 Matinapatana 16 93 1 47 252 22 162 39
MTL 561 Opalagala 24 73 1 47 172 42 162 39
GAL 328 Tawalama 33 59 2 13 118 92 164 42
NUW 307 Nanu Oya 12 112 1 47 330 10 169 43
MON 589 Begahapatana 14 103 2 13 157 54 170 44
MON 579 Diggala 12 112 2 13 169 45 170 44
MON 606 Dyabodahela 22 78 2 13 133 79 170 44
MTL 560 Galboda 24 73 1 47 161 51 171 47
BAD AMP POL 239 Maduru Oya Block | 25 71 1 47 157 54 172 48
HAM 388 Rammalekanda 43 45 2 13 103 115 173 49
NUW 270 Meepilimana 13 107 1 47 253 22 176 50
GAL 506 Tiboruwakota 12 112 2 13 154 58 183 51
KAN 518 Hopewell 12 112 1 47 236 27 186 52
MON 595 Radaliwinnekota 9 133 2 13 172 42 188 53
MON 305 Namandiya 10 124 2 13 155 55 192 54
GAL 509 Auwegalakanda 10 124 2 13 149 62 199 55
KAN 519 Guruyalle 13 107 1 47 169 45 199 55
KUR 165 Kalugala 8 146 2 13 188 40 199 55
RAT 384 Rajawaka 62 27 1 47 100 125 199 55
KAN MTL 45 Campbell's Land 10 124 1 47 231 29 200 59
NUW 383 Ragalla 10 124 1 47 224 30 201 60
RAT 112 Gilimale-Eratne 94 15 1 47 94 139 201 60
KAL 289 Morapitiya-Runakanda 52 34 1 47 101 122 203 62
KAN 192 Kelani Valley 52 34 1 47 101 122 203 62
MTL 562 Sacombe 13 107 1 47 164 49 203 62
RAT 28 Bambarabotuwa 45 42 1 47 103 115 204 65

Stream Stream Catchment Catchment Distance Distance Sum of Headwaters

District EMD No. Forest name number rank number rank (km) rank ranks rank
RAT 288 Morahela 31 63 1 47 114 96 206 66
BAD 392 Ravana Ella 81 16 1 47 92 144 207 67
MTL 564 Heratgedara 15 98 1 47 148 63 208 68
ANU 463 Wedakanda 42 47 1 47 103 115 209 09
ANU 496 Yoda Ela 14 103 1 47 152 60 210 70
BAD 610 Kithedallakanda 9 133 1 47 212 34 214 71
KUR 552 Butawella 16 93 1 47 136 74 214 71
MTL 566 Gosgahapatana 11 118 1 47 164 49 214 71
BAD 426 Tangamalai 8 146 1 47 253 22 215 74
RAT 528 Asantanakanda 23 75 1 47 116 93 215 74
RAT 217 Kudumiriya 56 30 1 47 94 139 216 76
POL 281 Minneriya-Giritale Block 1 18 89 1 47 124 88 224 77
GAL 369 Polgahakanda 20 83 2 13 99 129 225 78
RAT 71 Delwela 31 63 1 47 102 118 228 79
KAN 521 Wewegalatana i) 153 1 47 . 216 32 232 80
NUW 128 Harasbedda 7 153 1 47 214 33 233 81
BAD 468 Welegama 21 81 1 47 108 107 235 82
KEG 551 Usgala 36 57 1 47 97 132 236 83
POL 96 Gal Oya 20 83 1 47 107 110 240 84
BAD 609 Madigala 3 195 2 13 214 33 241 85
GAL 38 Beraliya (Kudagala) 43 45 2 13 71 183 241 85
KUR 101 Galgiriyakanda 3 195 2 13 210 35 243 87
BAD 611 Keeriyagolla 6 162 1 47 204 36 245 88
ANU 395 Ritigala 9 133 1 47 145 66 246 89
HAM 491 Yala 41 48 4 1 61 197 246 89
KEG 514 Sembawatte 27 67 1 47 97 132 246 89
MON 576 Ulgala 6 162 2 13 136 74 249 92
KUR 78 Doluwakanda 9 133 1 47 136 74 254 93
KUR 318 Neugalkanda 9 133 1 47 136 74 254 93
RAT 205 Kobahadunkanda 32 61 1 47 90 146 254 93
RAT 68 Delgoda 26 69 1 47 94 139 255 96
KUR 489 Yakdessakanda 17 91 1 47 102 118 256 97
KEG 191 Kelani Valley 30 65 1 47 91 145 257 98
GAL 37 Beraliya (Akuressa) 37 55 2 13 64 190 258 99
KAL 166 Kalugala 51 37 1 47 76 174 258 99
MAT 497 Kalubowitiyana 5 174 2 13 140 72 259 101
RAT 184 Karawita 30 65 1 47 89 147 259 101
PUT 465 Weerakulicholai-Elavankulam 26 69 3 3 66 188 260 103
RAT 455 Walankanda 19 88 1 47 100 125 260 103
MTL 563 Talabugahaela 6 162 1 47 157 54 263 105
MON RAT 438 Uda Walawe 64 25 1 47 62 193 265 106
MON 97 Gal Oya Valley 104 13 1 47 58 205 265 106
RAT 459 Waratalgoda 33 59 1 47 83 159 265 106
MON 605 Balanagala 38 50 1 47 78 169 266 109
MTL 572 Menikdeniya 7 153 1 47 145 66 266 109
ANU 635 Manawewakanda 5 174 1 47 165 47 268 11
RAT 549 Alutwelawisahena 11 118 1 47 109 103 268 11
RAT 432 Tibbutukanda 15 98 1 47 100 125 270 113
MAT 499 Silverkanda 11 118 1 47 108 107 272 114
POL 279 Minneriya a 153 1 47 137 73 273 115
RAT 386 Rammalakanda 12 112 1 47 105 114 273 115
MAT 293 Mulatiyana 96 14 1 47 52 214 275 117
AMP MON 98 Gal Oya Valley North-East 75 20 1 47 56 209 276 118
RAT 389 Ranwala 27 67 | 47 82 162 276 118
KUR 131 Henegedaralanda 9 133 1 47 113 97 277 120
MON 575 Dewagiriya 3 195 2 13 142 2. the) 278 121
MTL 82 Elagomuwa 5 174 1 47 154 58 279 122
POL 280 Minneriya-Giritale 6 162 1 47 141 71 280 123
POL 502 Medirigiriya Tulana 53 32 1 47 59 202 281 124
MON 591 Murutukanda 21 81 1 47 87 154 282 125
RAT 531 Kudagoda 10 124 1 47 106 112 283 126
RAT 534 Galleletota 13 107 1 47 97 132 286 127
COL 222 Labugama-Kalatuwana 54 31 1 47 55 210 288 128
KAL 315 Neluketiya Mukalana 38 50 1 47 62 193 290 129
KAN 442 Udawattakele 1 218 1 47 239 26 291 130
MAT 138 Horagala-Paragala 41 48 1 47 61 197 292 131
RAT 274 Messana 8 146 1 47 112 99 292 131
RAT 530 Appalagala 9 133 1 47 106 112 292 131
GAL 208 Kombala-Kottawa 17 91 3 3 59 202 296 134
MON 581 Monerakelle 25 71 1 47 74 178 296 134
RAT 544 Gorangala 16 93 1 47 85 156 296 134
RAT 542 Digandala 8 146 1 47 109 103 296 134
HAM 249 Mahapitakanda 13 107 2 13 72 181 301 138
MTL 567 Amsawagama 2 207 1 47 165 47 301 138

District

RAT
MON
ANU
ANU
KUR
MTL
KAL
ANU
GAL
KEG
RAT
KAL
KEG
RAT
ANU
MTL
KEG
KAL
KUR
KUR
MAT
GAL
MON
MTL
MON
KUR
RAT
POL
RAT
COL
RAT
MTL
RAT
RAT
RAT
BAD MON
MON
MON
ANU
MON
ANU
RAT
ANU
PUT
RAT
GAL
RAT
MON
RAT
KAL
KUR
GAL
MAT
RAT
KEG
RAT
KAL
RAT
RAT
COL
MON
RAT
POL
KAL
MAT
MAT
KAL
RAT
MON
RAT
KUR
ANU
PUT
RAT

EMD No.

537

Forest name

Kabarakalapatana
Randeniya
Labunoruwa
Getalagamakanda
Kadawatkele
Tottawelgola
Kurana Madakada
Mihintale
Malambure
Dedugalla-Nangala
Wewelkandura
Yagirala
Alapalawala
Dotalugala
Ratmale Kanda
Masawa
Amanawala-Ampane
Delmella Yatagampitiya
Dunkanda
Kanugollayaya
Kurulugala
Habarakada
Viyanahela
Inamaluwa
Ruhuna Block 5
Manapaya
Madampe
Gunner's Quoin
Ayagama
Indikada Mukalana
Dambuluwana
Etabendiwela
Kiribatgala
Pannala

Paragala
Bibilehela
Ruhuna Block 3
Ruhuna Block 4
Galkulama Tirrapane
Bakinigahawela
Katupotakanda
Kuragala
Ranawekanda
Wanniyagama
Magurugoda
Homadola

Nahiti Mukalana
Wadinahela
Hapugala
Haycock
Degadaturawa
Hindeinattu
Panilkanda
Kumburugamuwa
Batahena
Hataramune
Ingiriya
Handuwelkanda
Mulgama
Miriyagalla
Ruhuna Block 2
Angamana
Mutugalla Tulana
Vellihallure
Viharakele
Aninkanda
Boralugoda
Demanagammana
Korathalhinna
Ulinduwewa
Sangappale
Medalassa Korale
Attavillu
Narangattahinna

Stream
number

w

w
COCODADNFOUNUWAN

— b =
wi

SCOPN KN OCWADNIAWND—-WUrY

a)

SO AH OH

i=)
oS

—-SO-ANFUMH—HK— ROHN WAONWHNUWODRENHNAIM—-UABSdDd

Stream Catchment Catchment

rank

153

93
195
174
133
184

61
162

57
124
133

42
153
174
195
218
146

98
153
207
162

89
133
218

98
218
207
184
124

83
118
218
184
207
118
133

75

93
218
174
218
146
218

83
162

98
218
146
153
162
207
184
162
133
195
174
118
195
207
133
162
195
207
112
124
184
218
218
174
184
153
218
124
218

155

number

rank

Distance
(km)

109

147
127

132

108

107
119
143

131

133
132

115
102

128
101
112

115

113

112

111

Distance
rank

118
178
220
185
86
122
99
188
176
235
218
94
138
97
169
99
236
157
222
102
181
174
169
125
185
173
202
142
165
224
147
136
211
220
157
147
244
232
178
147
147
193
184
218
154
250
159

Sum of Headwaters

ranks rank
303 140
305 141
306 142
308 143
312 144
312 144
313 146
316 147
318 148
318 148
327 150
329 151
329 151
331 153
333 154
334 155
335 156
336 157
336 157
338 159
338 159
341 161
344 162
344 162
345 164
346 165
348 166
349 167
349 167
350 169
350 169
351 171
353 172
353 172
353 172
356 175
357 176
358 177
359 178
359 178
362 180
362 180
364 181
366 183
366 183
367 185
367 185
374 187
374 187
378 189
379 190
382 19]
382 191
382 191
384 194
386 195
389 196
389 196
390 198
39] 199
395 200
399 201
401 202
403 203
403 203
409 205
412 206
412 206
414 208
415 209
418 210
419 211
421 212
424 213

Stream Stream Catchment Catchment Distance Distance Sumof Headwaters
District EMD No. Forest name number rank number rank (km) rank ranks rank

RAT 538 Gallegodahinna 1 218 1 47 83 159 424 213
MON 594 Golupitiyahela 3 195 1 47 69 185 427 215
RAT 133 Hidellana-Weralupe 1 218 1 47 82 162 427 215
RAT 504 Masimbula 1 218 1 47 79 167 432 217
RAT 272 Marakele 1 218 1 47 79 167 432 217
GAL 511 Bambarawana 6 162 1 47 44 224 433 218
COL 170 Kananpella 5 174 1 47 53 213 434 219
RAT 294 Muwagankanda 1 218 1 47 78 169 434 219
RAT 548 Dumbara 3 195 1 47 62 193 435 222
GAL 510 Yakdehikanda 4 184 1 47 57 208 439 223
RAT 532 Talawegoda 1 218 1 47 75 176 441 224
RAT 540 Galbokaya 2 207 1 47 60 199 453 225
MAT 60 Dandeniya-Aparekke 6 162 1 47 22 246 455 226
POL 600 Palliyagodella Tulana 3 195 1 47 52 214 456 227
POL 601 Kumadiya Tulana 1 218 1 47 63 191 456 227
HAM 178 Kanumuldeniya 5 174 1 47 30 236 457 229
GAL 62 Darakulkanda 4 184 1 47 33 232 463 230
MON 585 Kitulhela 1 218 1 47 60 199 464 231
MON 583 Velihela 1 218 1 47 60 199 464 231
MAT 201 Kirinda-Mahayayakele 4 184 1 47 27 240 471 233
MAT 471 Welihena 3 195 1 47 34 230 472 234
PUT 407 Sellankandal 4 184 1 47 26 242 473 235
MON 584 Guruhela 1 218 1 47 54 211 476 236
GAM 247 Mahakanda 1 218 1 47 52 214 479 237
GAL 173 Kandawattegoda 4 184 1 47 7 249 480 238
KAL 269 Meegahatenna 2 207 1 47 34 230 484 239
MON 592 Sitarama 2; 207 1 47 33 232 486 240
MAT 500 Derangala 1 218 1 47 45 223 488 241
HAM 464 Wedasitikanda 2 207 1 47 30 236 490 242
HAM 526 Keulakada Wewa 1 218 1 47 41 226 491 243
MON 587 Westminster Abbey 1 218 1 47 41 226 491 243
MON 593 Bolhindagala 1 218 1 47 38 228 493 245
MON 586 Diggalahela 1 218 1 47 37 229 494 246
KAL 390 Ranwaragalakanda 1 218 1 47 29 239 504 247
MON 187 Kataragama 1 218 1 47 25 243 508 248
MAT 263 Masmullekele 1 218 1 47 17 247 512 249
PUT 406 Sellankandal 1 218 1 47 13 248 513 250
ANU 634 Puliyankulama 0 251 0 251 0 251 753 251
ANU 644 Tambaragalawewa 0 251 0 251 0 251 753 251
ANU 638 Pahala Mawatawewa 0 251 0 251 0 251 753 251
ANU 645 Puliyamkulam 0 251 0 251 0 251 753 251
ANU 636 Aruwewa 0 251 0 251 0 251 753 251
ANU 637 Andarawewa 0 251 0 251 0 251 753 251
ANU 643 Marasinhagama 0 251 0 251 0 251 753 251
ANU 642 Galmaduwa 0 251 0 251 0 251 753 251
ANU 631 Dematawewa 0 251 0 251 0 251 753 251
HAM 525 Miyandagala 0 251 0 251 0 251 753 251
HAM 44 Bundala 0 251 0 251 0 251 753 251
HAM 237 Madunagala 0 251 0 251 0 251 753 251
HAM 186 Katagamuwa 0 251 0 251 0 251 753 251
KUR 232 Ma Eliya 0 251 0 251 0 251 753 251
KUR 630 Bogodayagama 0 251 0 251 0 251 753 251
KUR 629 Tambutakanda 0 251 0 25) 0 251 753 251
KUR 553 Talpattekanda 0 251 0 251 0 251 753 251
MAT 190 Kekanadura 0 251 0 251 0 251 753 251
MAT 24 Badullakele 0 251 0 251 0 «251 753 251
MAT 329 Oliyagankele 0 251 0 251 0 251 753 251
MON 582 Lolehela 0 251 0 251 0 251 753 251
MON 580 Dummalahela 0 251 0 251 0 251 753 251
MON 578 Ulgala (old) 0 251 0 251 0 251 753 251
MTL 574 Hiriwaduna 0 251 0 251 0 251 753 251
MTL 568 Beliyakanda 0 251 0 251 0 251 753 251
POL 603 Sinnakallu 0 251 0 251 0 251 753 251
POL 599 Mahamorakanda 0 251 0 251 0 251 753 251
POL 597 Badanagala 0 251 0 251 0 251 753 251
POL 596 Kudagala North 0 251 0 251 0 251 753 251
PUT 554 Aruakalu 0 251 0 251 0 251 753 251
PUT 10 Ambanmukalana 0 251 0 251 0 251 753 251

156

Annex 4

IMPORTANCE OF NATURAL FORESTS FOR FLOOD CONTROL

Rainfall Area Steam freq. Mean flood Flood

District EMD No. Forest name (mm yr") (km?) (km) (m?s"') rank
KEG NUW RAT 361 Peak Wilderness 4320 280.45 1.18 418.10 1
KAN : $22 Knuckles 3184 300.00 1.34 312.71 2
GAL MTR RAT 414 Sinharaja 3946 111.87 2.69 260.07 3
GAL 175 Kanneliya 3984 60.25 3.77 186.05 4
KAN NUW 452 Victoria-Randenigala-Rantambe 1963 428.56 0.71 159.33 5
RAT 112 Gilimale-Eratne 4652 48.39 2.19 144.41 6
NUW 362 Pedro 2523 67.57 4.19 117.19 7
KAL 289 Morapitiya-Runakanda 4466 67.33 0.74 103.94 8
NUW 197 Kikilimana 2729 45.81 4.34 95.69 9
KAN 192 Kelani Valley 5260 29.06 1.51 91.89 10
GAL 65 Dediyagala 3437 37.9 Ql! 87.22 11
RAT 28 Bambarabotuwa 3979 54.40 0.96 84.67 12
NUW 1 Agra-Bopats 2398 69.34 2.41 84.37 13
KAL 166 Kalugala 4450 42.88 1.03 83.50 14
NUW 40 Bogawantalawa 2699 42.90 3.38 78.51 15
RAT 545 Handapan Ella 3475 36.00 1.78 68.50 16
POL MTL 460 Wasgomuwa Lot | 1700 359.89 0.34 65.72 17
GAL 69 Dellawa 3759 22.36 2.9 65.47 18
* KAL 487 Yagirala 4464 23.90 1.63 65.02 19
KAL 315 Neluketiya Mukalana 4458 23.84 1.43 60.47 20
RAT 459 Waratalgoda 4564 18.90 1.80 57.80 21
MAT 77 Diyadawa 3410 24.48 2.52 57.72 22
MAT 293 _ Mulatiyana 3034 31.49 2.25 57.55 23
COL 222 Labugama-Kalatuwana 3950 21.50 1.91 54.67 24
MON 97 Gal Oya Valley 1700 259.00 0.29 54.65 25
ANU KUR 161 Kahalla-Pallekele 1600 377.40 0.17 52.77 26
RAT 217 Kudumiriya 3603 21.45 2.19 51.78 27
GAL 38 Beraliya (Kudagala) 3660 25.72 1.48 50.42 28
RAT 456 Walawe Basin 3121 32.30 1.52 49.94 29
GAL 303 Nakiyadeniya 3561 22.36 1.74 46.93 30
KEG 19] Kelani Valley 4933 11.55 2.16 46.61 31
KAN 520 Illukkanda 2594 39.00 1.41 44.00 32
KEG 514 Sembawatte 4891 12.00 1.83 43.72 33)
MON RAT 438 Uda Walawe 1600 308.21 0.16 43.39 34
AMP MON 98 Gal Oya Valley North-East 1750 124.32 0.56 43.05 35
NUW 172 Kandapola Sita Eliya 2157 26.16 4.21 42.89 36
KEG 551 Usgala 5295 7.00 3.43 42.55 37
GAL 328 Tawalama 4340 10 3.2 42.46 38
BAD 608 Welanwita 2119 85.00 0.58 40.91 39
RAT 184 Karawita 4184 12.12 2.31 40.24 40
NUW 140 Horton Plains 2534 31.60 1.74 39.78 41
MAT 138 Horagala-Paragala 3209 18.12 2.15 38.11 42
BAD AMP POL 239 Maduru Oya Block 1 1850 514.69 0.04 38.11 42
KAL 221 Kurana Madakada 3988 11.61 2.32 36.52 44
MTL 335 Pallegama-Himbiliyakada 2320 45.47 0.99 35.98 45
RAT 71 Delwela 3587 15.60 1.79 35.58 46
GAL 253 Malambure 3937 9.3 3.12 34.61 47
KAL 70 Delmella Yatagampitiya 4339 14.13 1.13 33.41 48
ANU POL 142 Hurulu 1450 252.18 0.17 33.35 49
RAT 205 Kobahadunkanda 3801 8.90 3.37 33.10 50
RAT 546 Gongala 3100 16.00 2.19 33.06 51
RAT 68 Delgoda 3939 9.98 2.40 32.18 §2
RAT 384 Rajawaka 2295 23.88 2.35 32.05 53
ANU POL 11 Anaolundewa 1450 289.57 0.12 31.06 54
POL 502 Medirigiriya Tulana 1735 80.00 0.60 30.35 55
AMP MON 99 Gal Oya Valley South-West 1600 152.81 0.24 29.52 56
MTL 573 Puswellagolla 1699 100.00 0.41 29.31 57
BAD 392 Ravana Ella 1900 20.73 3.99 28.96 58
BAD NUW 327 Ohiya 2252 17.69 3.11 28.05 59
RAT 288 Morahela 3600 8.47 2.95 2759 60
COL 146 Indikada Mukalana 3800 7.48 3.08 27.28 61
RAT 547 Paragala 4500 9.00 1.44 27.19 62
HAM 388 Rammalekanda 2837 14.07 2.22 26.55 63
NUW 248 Mahakudagala 2171 16.39 3.36 26.04 64
MON 607 Rediketiya 1750 39.00 1.38 25.72 65

157

Rainfall Area Steam freq. Mean flood Flood

District EMD No. Forest name (mm yr") (km?) (km”) (m's") rank
GAL 37 Beraliya (Akuressa) 2671 16.46 1.8 25.11 66
GAL 369 Polgahakanda 4051 SHIT, 3.12 24.08 67
RAT 528 Asantanakanda 3400 8.00 2.25 21.21 68
GAL 506 Tiboruwakota 4350 6 1.83 20.85 69
KAN NUW 394 Rilagala 4373 5.67 1.94 20.63 70
RAT 455 Walankanda 3455 7.12 2.39 20.25 71
GAL 208 Kombala-Kottawa 2680 16.25 1.11 19.50 72
NUW 358 Pattipola-Ambawela 2229 14.80 2.09 19.47 73
RAT 57 Dambuluwana 4479 4.01 2.74 19.00 74
KAL 512 Vellihallure 4400 4.25 2.59 18.91 75
RAT 549 Alutwelawisahena 4050 8.00 1.13 18.83 76
RAT 544 Gorangala 4400 4.00 2:75 18.54 77
GAL ; 120 Habarakada 4397 2.1 8.1 18.70 78
NUW 52 Conical Hill 2292 7.08 5.94 18.49 79
MON 400 Ruhuna Block 3 1100 407.75 0.05 18.05 80
PUT 465 Weerakulicholai-Elavankulam 1110 291.92 0.08 17.96 81
KEG 7 Amanawala-Ampane 5371 5.14 0.97 17.60 82
HAM 491 Yala 1000 289.05 0.10 17.14 83
RAT 389 Ranwala 2496 8.68 2.77 16.67 84
POL 96 Gal Oya 1600 88.97 0.19 16.61 85
ANU 463 Wedakanda 1350 51.80 0.69 16.23 86
BAD NUW 123 Hakgala 2176 11.42 eM 16.13 87
MAT 499 Silverkanda 3380 7.25 1:52 15.86 88
MON 401 Ruhuna Block 4 1250 264.18 0.05 15.48 89
KEG 515 Dedugalla-Nangala 4900 2.75 2.55 15.03 90
BAD 468 Welegama 2665 6.39 2.97 14.61 91
RAT 476 Wewelkandura 4036 4.29 1.86 14.37 92
GAL 509 Auwegalakanda 4500 2.5 3.2 13.9] 93
> GAL 507 Homadola 3800 3 3.67 13.86 94
RAT 386 Rammalakanda 3440 4.54 2.20 13.24 95
PUT 458 Wanniyagama 1250 144.18 0.10 13.13 96
RAT 274 Messana 3753 4.34 1.84 13.08 97
RAT 19 _ Ayagama 4421 2.14 3.73 12.91 ; 98
KAL 147 Ingiriya 3917 2.83 3.18 12.77 99
MTL 561 Opalagala 2867 3.50 4.86 12.48 100
POL 281 Minneriya-Giritale Block | 1489 75.29 0.17 12.45 101
RAT 541 Kabarakalapatana 3400 6.75 1.04 12.39 102
MAT 343 Panilkanda 3133 5.88 1.58 12.25 103
MTL 560 Galboda 2316 6.00 3.17 11.85 104
RAT 241 Magurugoda 4188 2.41 2.90 11.66 105
GAL 511 Bambarawana 4150 2.48 2.82 11.62 106
KAL 129 Haycock 4263 3.62 1.38 11.50 107
MON 605 Balanagala 1750 8.00 3.63 1.11 108
POL MTL 410 Sigiriya 1600 50.99 0.22 11.07 109
RAT 432 Tibbutukanda 2500 4.50 3.56 10.94 110
RAT 529 Dotalugala 4075 1.75 4.57 10.83 111
KAN 100 Galaha 2788 2.43 7.00 10.65 112
RAT 531 Kudagoda 2625 6.50 1.54 10.38 113
KUR 552 Butawella 2103 10.50 1.24 10.32 114
MTL 571 Gederagalpatana 1769 15.00 1.07 10.24 115
MAT 497 Kalubowitiyana 4189 2.72 1.84 10.23 116
KUR 489 Yakdessakanda 1872 10.11 1.68 10.00 117
HAM 249 Mahapitakanda 2368 7.22 1.52 9.81 118
MON 606 Dyabodahela 1750 11.00 1.64 9.67 119
MON 581 Monerakelle 1524 16.50 1.15 9.45 120
POL 280 Minneriya-Giritale 1568 66.94 0.10 9.36 121
KEG 513 Batahena 5368 3.00 0670 9.23 122
MTL 565 Makulussa 2428 3.25 4.62 9.14 123
RAT 169 Kumburugamuwa 2225 14.81 0.47 9.09 124
RAT 536 Hapugala 2275 6.00 1.83 8.76 125
MAT. 498 Kurulugala 3400 2.85 2.11 8.62 126
NUW 270 Meepilimana 2173 7.72 1.30 8.52 127
RAT $27 Angamana 3800 1.75 3.43 8.51 128
MTL 564 Heratgedara 2062 6.50 1.85 8.24 129
MON 591 Murutukanda 1672 8.00 2.25 8.19 130
MON 402 Ruhuna Block 5 1150 66.56 0.18 8.12 131
PUT 17 Attavillu 1334 51.79 0.17 7.87 132
POL 600 Palliyagodella Tulana 1738 96.00 0.03 7.86 133
COL 285 Mirtyagalla 3655 1.23 5.69 7.78 134
RAT 534 Galleletota 2400 3525 3.38 7.68 135
NUW 307 Nanu Oya 2335 4.16 2.40 ~ 7.65 136
COL 170 Kananpella 3650 2.64 1.52 7.51 137
RAT 298 Nahiti Mukalana 3303 1.96 3.07 7.32 138
BAD 306 Namunukula 2314 2.79 4.30 7.28 139
KAN MTL 45 Campbell's Land 2626 2.93 2.73 7.12 140

158

Rainfall Area Steam freq. Mean flood Flood

District EMD No. Forest name (mm yr") (km?) (km) (ms!) rank
a a a ae ed ed Mee
MAT 453 Viharakele 2444 6.25 0.94 7.10 141
KAL 269 Meegahatenna 4480 2.77 0.72 i 7.06 142
RAT 548 Dumbara 4400 1.00 4.00 7.00 143
RAT 542 Digandala 3300 1.00 8.00 6.78 144
KAN 519 Guruyalle 2636 1.75 5.71 6.77 145
MTL 566 Gosgahapatana 1914 7.50 1.20 6.75 146
RAT 550 Kiribatgala 3263 3.00 1.33 6.74 147
MTL 562 Sacombe 2313 2.50 4.40 6.71 148
RAT 530 Appalagala 2610 2.00 4.00 6.23 148
HAM 178 Kanumuldeniya 2432 6.79 0.64 6.21 150
RAT 535 Kuragala 2200 BE25) 2.77 6.17 151
MAT 501 Aninkanda 3250 Pps} 1.79 6.08 152
BAD MON 39 Bibilehela 2050 6.06 1.15 6.07 153
ANU 496 Yoda Ela 1363 15.86 0.69 6.07 153
ANU 395 Ritigala 1550 15.28 0.52 6.06 155
RAT 234 Madampe 3233 2.25 ‘ 1.78 6.05 156
KAN 517 Matinapatana 2070 2.50 4.80 6.04 157
MON 604 Viyanahela 1750 9.00 0.89 5.99 158
NUW 128 Harasbedda 2421 3.64 1.65 5.93 159
MON 590 Randeniya 1950 3.00 4.00 5.92 160
KUR 165 Kalugala 1533 27.06 0.18 5.67 151
MON 595 Radaliwinnekota 1750 9.00 0.78 5.59 162
MON 588 Wadinahela 1853 7.00 1.00 5.56 163
MON 589 Begahapatana 1805 3.25 3.69 5.48 164
RAT 443 Ulinduwewa 3100 1.05 5.73 5.47 165
GAL 508 Hindeinattu 3083 2) 2 5.47 165
MTL 82 Elagomuwa 2146 8.70 0.46 5.47 165
NUW 383 Ragalla 2205 2.68 2.98 5.47 165
MON 305 Namandiya 1671 7.91 1.01 5.39 169
MAT 471 Welihena 2723 2.97 1.36 5.30 170
MON 399 Ruhuna Block 2 1050 99.31 0.05 5.25 171
KUR 131 Henegedaralanda 1750 7.30 0.96 5.22 172
KEG 4 Alapalawala 2789 1.82 2.75 5.19 173
GAL 173 Kandawattegoda 2550 3.59 1.11 5.13 174
MON 576 Ulgala 1515 15.00 0.40 5.04 175
KUR 318 Neugalkanda 1902 3.76 2.13 5.02 176
KUR 404 Sangappale 1150 45.06 0.13 5.01 177
GAL 62 Darakulkanda 3457 1.42 2.11 4.9] 178
KAN 518 Hopewell 2250 1.25 8.00 4.90 179
RAT 543 Handuwelkanda 3950 1.50 1.33 4.87 180
KAN 521 Wewegalatana 2408 2.00 3.00 4.83 181
POL 279 Minneriya 1690 8.28 0.72 c 4.80 182
KAL 516 Boralugoda 4250 1.00 2.00 4.70 183
GAL 510 Yakdehikanda 3600 1 3) 4.62 184
BAD 609 Madigala 1850 13.50 0.22 4.47 185
MTL 144 Inamaluwa 1550 9.10 0.67 4.44 186
PUT 407 Sellankandal 1209 45.42 0.09 4.37 187
MON 579 Diggala 1668 2.50 4.40 4.33 188
RAT 532 Talawegoda 4200 2.34 0.43 4.30 189
KUR 78 Doluwakanda 1850 4.01 1.50 4.26 190
RAT 504 Masimbula 3084 2.55 0.78 4.16 19]
MTL 572 Menikdeniya 1750 4.50 1.33 4.11 192
BAD 426 Tangamalai 2348 1.32 4.56 4.06 193
RAT 539 Hataramune 2260 2.00 2.50 4.04 194
KUR 157 Kadawatkele 1850 2.67 2.62 4.04 194
KUR 80 Dunkanda 1796 3.01 2.32 4.03 196
RAT 533 Mulgama 2450 2.00 2.00 4.02 197
BAD 610 Kithedallakanda 2299 1.00 7.00 3.90 198
MON 577 Korathalhinna 1450 15.00 0.27 3.87 199
RAT 348 Pannala 3448 1.29 1.55 3.86 200
BAD 611 Keeriyagolla 2654 1.25 3.20 3.83 201
KAL 390 Ranwaragalakanda 3950 1.92 0.52 3.71 202
RAT 272 Marakele 4550 1.06 0.94 3.69 203
RAT 538 Gallegodahinna 2300 2.00 2.00 3.69 203
MTL 563 Talabugahaela 2250 3.00 1.00 3.54 205
ANU 278 Mihintale 1350 10.00 0.50 3.44 206
RAT 133 Hidellana-Weralupe 4100 1.28 0.78 3.41 207
RAT 294 Muwagankanda 3854 1.32 0.76 3.17 208
MTL 570 Tottawelgola 1627 8.00 0.38 3.17 208
MAT. 60 Dandeniya-Aparekke 1839 3.48 1.07 3.17 208
MON 575 Dewagiriya 1713 6.00 0.50 3.09 211
RAT 72 Demanagammana 3813 1.14 0.88 2.98 212
RAT 537 Narangattahinna 2350 2.50 0.80 2.87 213
MON 27 Bakinigahawela 1650 2.00 2.50 2.65 214
POL 598 Gunner's Quoin 1450 4.50 0.89 2.60 215

159

Rainfall Area Steam freq. Mean flood Flood

District EMD No. Forest name (mm yr") (km?) (km) (m’s") rank
ANU 640 Getalagamakanda 1300 7.00 0.57 : 2.60 215
KUR 101 Galgiriyakanda 1450 11.83 0.17 2.51 217
MAT 201 Kirinda-Mahayayakele 1940 2.53 0.91 2.40 218
RAT 540 Galbokaya 2220 1.75 1.14 2.37 219
ANU 635 Manawewakanda 1449 3.25 1.23 2.33 220
MAT 500 Derangala 3500 0.75 1.33 2.31 221
ANU 632 Ratmale Kanda 1550 7.00 0.29 2.31 221
MTL 567 Amsawagama 2186 4.50 0.22 2.22 223
MON 594 Golupitiyahela 1750 2.00 1.50 2.21 224
GAM 247 Mahakanda 3115 1.03 0.97 2.20 225
MAT 263 Masmullekele 2076 6.18 0.14 2.14 226
PUT 406 Sellankandal 1179 42.66 0.02 2.04 227
ANU 633 Labunoruwa 1430 3.00 1.00 1.93 228
KUR 177 Kanugollayaya 1950 1.20 1.67 1.75 229
HAM 464 Wedasitikanda 1062 13.43 0.15 1.73 230
POL 602 Mutugalla Tulana 1750 4.25 . 0.24 1.62 231
POL 601 Kumadiya Tulana 1750 4.00 0.25 1.59 232
ANU 647 Ranawekanda 1550 5.75 0.17 1,52 233
KAN 442 Udawattakele 1950 2.07 0.48 1.48 234
MON 592 Sitarama 1072 8.00 0.25 1.47 235
MTL 558 Masawa 1750 3.10 0.32 1.46 236
KUR 256 Manapaya 1850 3.14 0.27 1.44 237
MON 585 Kitulhela 1550 4.50 0.22 1.40 238
MTL 569 Etabendiwela 1650 3.25 0.31 1.37 239
KUR 66 Degadaturawa 1500 1.62 1.23 1.36 230
ANU 641 Galkulama Tirrapane 1312 4.50 0.22 1,12 241
MON 584 Guruhela 1450 2.75 0.36 1.09 242
MON 187 Kataragama 1050 8.38 0.12 1.02 243
MON 586 Diggalahela 1450 2.00 0.50 0.98 244
MON 583 Velihela 1450 2.00 0.50 0.98 244
HAM 526 Keulakada Wewa 1300 3 0.33 0.96 246
ANU 646 Medalassa Korale 1450 1.75 0.57 0.94 247
MON 593 Bolhindagala 1186 3.75 0.27 0.92 248
ANU 639 Katupotakanda 1350 M375 0.57 0.85 249
ANU 636 Aruwewa 1350 1.50 0 0 250
HAM 186 Katagamuwa 1100 10.04 0 0 250
ANU 638 Pahala Mawatawewa 1350 3.25 0 0 250
HAM $25 Miyandagala 1050 3 0 0 250
ANU 642 Galmaduwa 1350 2.50 0 0 250
HAM 237 Madunagala 1150 9.75 0 0 250
ANU 634 Puliyankulama 1500 1.50 0 0 250
ANU 643 Marasmhagama 1350 1.00 0 0 250
ANU 637 Andarawewa 1350 4.00 0 0 250
HAM 44 Bundala 878 62.16 0 0 250
ANU 645 Puliyamkulam 1350 1.25 0 0 250
MON 578 Ulgala (old) 1450 2.25 0 0 250
MON 587 Westminster Abbey 1550 8.00 0 0 250
PUT 554 Aruakalu 1150 21.00 0 0 250
MON 580 Dummalahela 1550 1.25 0 0 250
MON 582 Lolehela 1450 4.00 0 0 250
PUT 10 Ambanmukalana 1625 10.05 0 0 250
POL 603 Sinnakallu 1750 4.50 0 0 250
POL 599 Mahamorakanda 1600 1.75 0 0 250
POL 597 Badanagala 1750 2.00 0 0 250
POL 596 Kudagala North 1850 4.75 0 0 250
MTL 574 Hiriwaduna 1550 9.50 0 0 250
MAT 329 Oliyagankele 2465 4.86 0 a 0 250
KUR 232 Ma Eliya 1550 3.81 0 0 250
KUR 630 Bogodayagama 1350 1.00 0 0 250
ANU 644 Tambaragalawewa 1350 3.50 0 0 250
ANU 631 Dematawewa 1550 8.00 0 0 250
KUR 629 Tambutakanda 1150 2.50 0 0 250
MTL 568 Beliyakanda 1650 2.50 0 0 250
KUR 553 Talpattekanda 1550 1.50 0 0 250
MAT 190 Kekanadura 1721 3.8 0 0 250
MAT 24 Badullakele 2070 1.48 0 0 250

160

Annex 5

LIST OF FORESTS INVENTORIED FOR SPECIES

List of forests surveyed during the NCR, together with the number of transects and plots
inventoried. Notified and present areas are given for each forest, where appropriate and
known. Present area accounts for lands released subsequent to notification. The composition
of units of contiguous forest, comprising two or more designated forests, is also provided.

INDIVIDUAL FORESTS

EMD Notification Area (ha) No. New Species
No. Forest name date Designation Notified Present Transects Plots Pen. Last Districts
ANURADHAPURA
636 Aruwewa OSF 150.0 150.0 3 9 }7/ 1.8 ANU
* 641 Galkulama Tirrapane OSF 450.0 450.0 1 5 2.9 12.8 ANU
640 Getalagamakanda OSF 700.0 700.0 1 6 0.0 0.0 ANU
* 136 Hinna PR 1021.8 1021.8 1 4 15.4 0.0 ANU
* 160 Kahalla 11/10/1935 FR 3397.7 3292.5 1 5 8.5 3.3 ANU
161 Kahalla-Pallekele 11/07/1989 § 21690.0 21690.0 3 11 2.7 2.6 ANU KUR
653 Kokkebe OSF 0.0 0.0 2 10 1.6 0.0 ANU
633 Labunoruwa OSF 300.0 300.0 2 10 1.9 0.0 ANU
635 Manawewakanda OSF 325.0 325.0 1 8 1.6 0.0 ANU
* 277 Mihintale 14/11/1924 FR 3308.2 2462.9 1 5 We) 0.0 ANU
333 Padawiya PR 97901.7 97664.3 6 27 0.0 0.0 ANU
* 650 Pallankulama OSF 0.0 0.0 1 5 4.4 15.1 ANU
* 645 Puliyamkulam OSF 125.0 125.0 1 3) 13.9 10.0 ANU
634 Puliyankulama OSF 150.0 150.0 2 10 2.0 2.0 ANU
647 Ranawekanda OSF 575.0 575.0 1 5 4.3 4.1 ANU
395 Ritigala 07/11/1941 SNR 1528.2 1528.2 4 18 3.5 5.0 ANU
* 651 Semewa OSF 0.0 0.0 1 3 16.1 8.8 ANU
463 Wedakanda PR 5180.0 5180.0 3 15 1.6 0.0 ANU
* 652 Wellamudawa OSF 0.0 0.0 1 3 25.0 12.5 ANU
BADULLA
* 39 Bibilehela PR 610.0 606.3 2 10 8.2 0.0 BAD MON
123 Hakgala 01/03/1938 SNR 1141.6 1141.6 1 8 0.0 2.0 BAD NUW
306 Namunukula PR 279.3 279.3 2 7 2.8 0.0 BAD
327 Ohiya PR 1925.5 1769.1 2 9 4.9 0.0 BAD NUW
* 392 Ravana Ella 18/05/1979 § 1932.0 1932.0 1 5 43.2 6.4 BAD
* 426 Tangamalai 01/03/1938 S 131.5 131.5 1 5 6.8 2.2 BAD
608 Welanwita OSF 8500.0 8500.0 2tna10 2.0 1.9 BAD
GALLE
* 509 Auwegalakanda OSF 250.0 250.0 1 4 10.9 3.7 GAL
* 511 Bambarawana OSF 248.0 248.0 1 4 15.2 8.1 GAL
37 Beraliya (Akuressa) PR 1859.9 1645.5 2 20 2.1 1.1 GAL MTR
38 Beraliya (Kudagala) PR 4241.1 2571.8 1 8 3.1 1.8 GAL
* 62 Darakulkanda PR 457.6 141.7 1 6 17.2 4.7 GAL
65 Dediyagala 06/09/1940 FR 3789.9 3789.9 1 17 0.0 0.0 GAL MTR
69 Dellawa PR 2034.0 2236.3 3 IS} 3.5 2.5 GAL MTR
* 120 Habarakada PR 209.6 209.6 1 4 13.4 11.2 GAL
* 508 Hindeinattu OSF 200.0 200.0 1 4 20.8 7.4 GAL
* 507 Homadola OSF 300.0 300.0 1 5 6.3 5.9 GAL
* 173 Kandawattegoda PR 404.7 358.6 1 5) 6.6 10.9 GAL
175 Kanneliya 06/07/1934 FR 6114.4 6024.5 1 24 0.9 0.4 GAL
208 Kombala-Kottawa PR 2289.7 1624.6 2 14 0.0 1.6 GAL
* 253 Malambure 19/07/1935 FR 1012.3 929.8 1 7 8.6 1.2 GAL
303 Nakiyadeniya PR 2292.1 2235.5 2 12 292} 0.9 GAL
369 Polgahakanda 18/09/1942 FR 862.3 577.4 1 8 AR; 0.0 GAL

Area (ha)

New Species

Last Districts

GAL MTR RAT
GAL
GAL

HAM
HAM
HAM
HAM MTR
HAM
HAM
HAM
HAM
HAM MTR
HAM
HAM
HAM MON

EMD Notification pe ae AB He
No. Forest name date Designation Notified Present Transects Plots Pen.
a a
414 Sinharaja 21/10/1988 NHWA 11187.0 11187.0 7 46 0.3
* 505 Tawalama OSF 1000.0 1000.0 1 5 8.0
* 506 Tiboruwakota OSF 600.0 600.0 1 7 3.0
HAMBANTOTA
* 44 Bundala 31/12/1992 NP 6215.9 6215.9 1 5 14.7
523 Kahanda Kalapuwa OSF 200.0 200.0 1 3 0.0
* 164 Kalametiya Kalapuwa 28/06/1984 S 712.0 712.0 1 5 77.8
* 178 Kanumuldeniya 13/09/1940 FR 678.7 678.7 1 5 2.6
* 186 Katagamuwa 27/05/1938 S 1003.6 1003.6 1 6 2.4
* 526 Keulakada Wewa OSF 300.0 300.0 1 5) 15.6
* 237 Madunagala 06/04/1992 FR 975.2 975.2 1 3 20.8
* 525 Miyandagala OSF 300.0 300.0 1 2 100.0
388 Rammalakanda 21/05/1926 FR 1698.1 1406.7 2 16 Nay
* 524 Rekawa Kalapuwa OSF 50.0 50.0 1 3 20.0
398 Ruhuna Block 1 25/02/1938 NP 13679.2 13679.2 2 24 1.4
* 464 Wedasitikanda 07/09/1978 FR 1343.4 1343.4 1 5 0.0
KALUTARA
* 70 Delmella Yatagampitiya PR 2033.7 1413.3 1 2 100.0
* 129 Haycock FR 362.0 362.0 1 6 10.3
* 147 Ingiriya 07/08/1929 FR 407.0 282.6 1 6 5.0
166 Kalugala PR 4630.1 4288.0 2 15 2.3
* 269 Meegahatenna PR 282.8 277.4 1 3 27.1
289 Morapitiya-Runakanda PR 7012.5 6732.5 2 22 0.4
315 Neluketiya Mukalana PR 2625.2 2384.4 3 10 4.0
* 390 Ranwaragalakanda PR eps 192.1 1 4 16.i
512 Vellihallure OSF 425.0 425.0 1 al 3.9
* 659 Wathurana PVA: 18.0 0.0 1 5 1.9
487 Yagirala FR 3014.7 2390.2 2 11 3.6
* 486 Yagirala PR 34.1 34.1 1 5) 14.7
KANDY
* 79 Dotalugala PR 1871.7 1871.7 1 5 5.1
$22 Knuckles OSF 30000.0 30000.0 8 40 0.7
394 Rilagala PR 566.6 566.6 1 5 2.6
* 442 Udawattakele 01/03/1938 S$ 104.0 104.0 1 5 20.0
KEGALLE
* 7 Amanawala-Ampane PR 518.0 514.0 1 6 75
* 513 Batahena OSF 300.0 300.0 1 5 14.3
191 Kelani Valley 11/09/1903 FR 1155.1 1155.1 1 11 1.8
657 Kurulukele ? 0.0 0.0 1 4 2.9
361 Peak Wilderness 01/11/1940 S 22379.2 22379.2 2 22 0.4
* 514 Sembawatte OSF 1200.0 1200.0 1 5 10.3
* 551 Usgala OSF 700.0 700.0 1 6 8.5
KURUNEGALA
* 78 Doluwakanda PR 400.6 400.6 1 5 11.1
* 80 Dunkanda PR 301.1 301.1 1 5 7.8
* 101 Galgiriyakanda PR 1182.5 1182.5 1 8 2.0
* 256 Manapaya PR 314.0 314.0 1 5 13.8
318 Neugalkanda PR 376.0 376.0 3) 14 1.1
336 Pallekele 04/02/1896 FR 14513.8 12721.4 3 13 iN)
489 Yakdessakanda PR 1011.7 1010.9 2 10 0.0
MONARAGALA
* 589 Begahapatana OSF 325.0 325.0 1 5) 7.0
593 Bolhindagala OSF 375.0 375.0 1 5 2.8
* 575 Dewagiriya OSF 600.0 600.0 1 4 17.9
* 579 Diggala OSF 250.0 250.0 1 5 14.5
* 594 Golupitiyahela OSF 200.0 200.0 1 6 24.6
* 584 Guruhela OSF 275.0 275.0 1 5 7.0
* 187 Kataragama 27/05/1938 S 837.7 837.7 1 5 4.5
* 585 Kitulhela OSF 450.0 450.0 1 5 L2ES)
* 577 Korathalhinna OSF 1500.0 1500.0 1 5 10.9
582 Lolehela OSF 400.0 400.0 1 2) BE)

162

EMD Notification Area (ha) No. New Species

No. Forest name date Designation Notified Present Transects Plots Pen. Last Districts
* 581 Monerakelle OSF 1650.0 1650.0 2 10 10.3 4.1 MON
* 591 Murutukanda OSF 800.0 800.0 1 5 19.2 7.1 MON
* 595 Radaliwinnekota OSF 900.0 900.0 1 6 75.4 9.7 MON
590 Randeniya OSF 300.0 300.0 1 3) 4.4 2.2 MON
400 Ruhuna Block 3 28/04/1967 NP 40775.4 40775.4 4 28 2.9 1.0 MON
* 401 Ruhuna Block 4 09/10/1969 NP 26417.7 26417.7 2 5 veal 16.0 MON
* 399 Ruhuna Block 2 03/09/1954 NP 9931.0 9931.0 2 13 3.6 5.1 MON
438 Uda Walawe 30/06/1972 NP 30821.0 30821.0 3 15 0.0 0.0 MON RAT
* 576 Ulgala OSF 1500.0 1500.0 1 5 Tel 3.4 MON
* 583 Velihela OSF 200.0 200.0 1 5 12.8 2.1 MON
* 604 Viyanahela OSF 900.0 900.0 1 5 9.7 1.4 MON
588 Wadinahela OSF 700.0 700.0 1 5 0.0 2.0 MON
MATALE
* 567 Amsawagama OSF 450.0 450.0 1 5 9.6 8.8 MTL
* 654 Arangala OSF 0.0 0.0 1 3 11.6 15.7 MTL
568 Beliyakanda OSF 250.0 250.0 2 10 2.9 1.4 MTL
* 660 Elagamuwa OSF 0.0 0.0 1 5 2.3 10.4 MTL
* 82 Elagomuwa- - PR 870.1 870.1 1 4 25.0 4.5 MTL
* 569 Etabendiwela OSF 325/05 325.0 1 3 28.9 17.4 MTL
560 Galboda OSF 600.0 600.0 2 10 2.4 0.0 MTL
571 Gederagalpatana OSF 1500.0 1500.0 4 19 1.6 1.6 MTL
574 Hiriwaduna OSF 950.0 950.0 2 10 4.5 2.9 MTL
* 144 Inamaluwa PR 309.6 309.6 1 5 12.8 4.1 MTL
* 655 Kaludiyapokuna OSF 0.0 0.0 2 10 3.3 6.2 MTL
656 Kosgahakele 2 0.0 0.0 1 5 0.0 0.0 MTL
572 Menikdeniya ~ OSF 450.0 450.0 2 10 4.3 0.0 MTL
* 561 Opalagala OSF 350.0 350.0 1 5 a7. 1.9 MTL
335 Pallegama-Himbiliyakada PR 4547.2 4547.2 2 10 5.0 2.9 MTL
* 376 Potawa i PR Tee Fe) 1 5 5.8 5.5 MTL
573 Puswellagolla OSF 10000.0 10000.0 5 25 0.8 0.0 MTL
* 562 Sacombe OSF 250.0 250.0 1 5) Teg 5.8 MTL
570 Tottawelgola OSF 800.0 800.0 2 10 0.0 0.0 MTL
MATARA
* 501 Aninkanda OSF 75.0 75.0 1 5 13.8 9.2 MTR
* 24 Badullakele 11/10/1940 FR 182.3 147.7 1 5 3.9 8.3 MTR
* 60 Dandeniya-Aparekka 02/12/1938 FR 560.0 348.3 1 5 P28) 7.4 MTR
* 500 Derangala OSF 50.0 50.0 1 4 12.4 4.3 MTR
77 Diyadawa 21/08/1936 FR 2578.2 2447.7 2 17 2.1 1.5 MTR
* 138 Horagala-Paragala OSF 1800.0 1800.0 1 4 12.8 8.4 MTR
* 497 Kalubowitiyana OSF 100.0 100.0 1 5 14.9 3.9 MTR
* 190 Kekanadura 15/11/1935 FR 401.7 379.9 1 5 8.8 3.6 MTR
* 201 Kirinda Mahayayakele 19/07/1940 FR 374.1 252.7 1 6 11.6 3.4 MTR
* 498 Kunulugala OSF 175.0 175.0 1 4 12.6 5.9 MTR
* 263 Masmullekele 21/07/1939 FR 805.4 618.0 1 6 des} 7.8 MTR
293 Mulatiyana 25/08/1944 FR 3277.5 3148.9 4 29 0.5 2.0 MTR
329 Oliyagankele 08/09/1939 FR 488.6 486.0 4 16 eS 1.8 MTR
* 343 Panilkanda 18/03/1927 FR 588.1 588.1 1 5 6.1 6.7 MTR
* 499 Silverkanda OSF 1000.0 1000.0 1 5 8.8 2.6 MTR
* 453 Viharekele 26/04/1935 FR 825.1 625.1 1 6 8.0 7.4 MTR
* 471 Welihena 15/11/1935 FR 333.1 296.8 1 6 8.8 4.7 MTR
NUWARA ELIYA
* 1 Agra-Bopats PR 9105.4 6933.6 1 9 6.7 5.1 NUW
* 40 Bogawantalawa PR 4289.7 4289.7 1 6 18.6 11.9 NUW
* 52 Conical Hill PR 1569.5 707.5 1 8 5.9 3.8 NUW
* 96 Gal Oya PR 9036.6 8897.4 1 5 8.0 0.0 POL
140 Horton Plains 16/03/1988 NP 3159.8 3159.8 3 16 AS) 0.0 NUW
* 172 Kandapola Sita Eliya 20/05/1892 FR 2721.2 2615.9 1 g 7.4 3.6 NUW
192 Kelani Valley PR 2944.9 2906.2 1 7 4.6 1.7 NUW
* 197 Kikilimana PR 4868.4 4580.6 2 9 29.5 3.7 NUW
* 248 Mahakudagala PR 1762.5 1638.7 1 5 6.8 - 4.8 NUW
* 270 Meepilimana 02/11/1906 FR 981.8 771.5 1 6 1.8 5.2 NUW
358 Pattipola-Ambawela PR 1498.0 1480.3 1 10 3.1 3.0 NUW
362 Pedro PR 6879.7 6757.0 3 18 1.8 1.8 NUW

163

Area (ha) No. New Species

EMD Notification Bynes Ee er ee CSN AD Breese
No. Forest name date Designation Notified Present Transects Plots Pen. Last Districts
POLONNARUWA
* 113 Giritale PR 1077.3 1063.1 1 4 8.0 0.0 POL
502 Medirigiriya Tulana OSF 8000.0 8000.0 2 8 4.1 3.9 POL
* 279 Minneriya PR 2444.3 828.0 1 5 10.7 9.7 POL
* 280 Minneriya-Giritale 28/07/1938 S 6693.5 6693.5 1 5 8.7 4.2 POL
* 281 Minneriya-Giritale Block 1 12/02/1988 NR 7529.1 7529.1 3 16 6.0 1.2 POL
410 Sigiriya 26/01/1990 S$ 5099.0 5099.0 2 10 2.4 1.2 POL MTL
460 Wasgomuwa Lot 1 07/08/1984 NP 29036.0 29036.0 6 49 2.0 0.7 POL MTL
PUTTALAM
* 556 Chilaw Lake OSF 300.0 300.0 1 5 Tea 0.0 PUT
* 407 Sellankandal PR 5526.0 4542.2 1 5} 12.8 2.1 PUT
458 Wanniyagama PR 15596.6 14417.8 2 10 0.0 1.6 PUT
RATNAPURA
* 549 Alutwelawisahena OSF 800.0 800.0 1 5 8.5 4.1 RAT
* 530 Appalagala OSF 200.0 200.0 1 5 14.0 13.6 RAT
* 528 Asantanakanda OSF 800.0 800.0 1 4 7.8 9.4 RAT
* 19 Ayagama 2 PR 661.7 214.3 1 5 5.6 3.4 RAT
28 Bambarabotuwa 04/07/1890 FR 5440.3 © 5440.3 1 10 1.2 2.4 RAT
* 68 Delgoda PR 998.0 998.0 1 5 6.8 2.7 RAT
71 Delwela PR 1560.9 1560.1 1 12 1.7 0.6 RAT
* 538 Gallegodahinna OSF 200.0 200.0 1 5 8.5 5.3 RAT
* 534 Galleletota OSF 325.0 325.0 1 6 12.9 0.0 RAT
112 Gilimale-Eratne PR 5832.7 4838.8 5 28 3.3 1.1 RAT
* 546 Gongala OSF 1600.0 1600.0 1 5 10.9 7.1 RAT
* 544 Gorangala~ OSF 400.0 400.0 1 3 46.2 15.2 RAT
545 Handapan Ella OSF 3600.0 3600.0 3 12 0.6 1.7 RAT
* 536 Hapugala OSF 600.0 600.0 1 5 11.3 8.6 RAT
539 Hataramune : OSF 200.0 200.0 1 6 0.0 3.1 RAT
* 541 Kabarakalapatana OSF 675.0 675.0 1 3 22.5 13.6 RAT
184 Karawita PR 1375.9 1211.8 1 9 15 1.4 RAT
550 Kiribatgala OSF 300.0 300.0 1 8 3.2 4.2 RAT
* 205 Kobahadunkanda PR 890.3 890.3 1 6 5.2 2.2 RAT
* 531 Kudagoda OSF 650.0 650.0 1 5 19.8 8.0 RAT
217 Kudumiriya PR 2144.8 2144.8 1 8 2.8 2.2 RAT
* 535 Kuragala OSF 325.0 325.0 1 5 10.2 9.3 RAT
* 504 Masimbula PR 255.0 255.0 1 5) Hell 3.3 RAT
* 274 Messana PR 724.4 433.8 1 6 26.0 8.4 RAT
288 Morahela 31/03/1893 FR 930.5 846.9 1 7 3.4 3.3 RAT
533 Mulgama OSF 200.0 200.0 1 5 5.0 3.2 RAT
298 Nahiti Mukalana 13/12/1889 FR 195.7 195.7 2 12 1.8 4.5 RAT
* 537 Narangattahinna OSF 250.0 250.0 1 5 21.1 7.3 RAT
* 547 Paragala OSF 900.0 900.0 1 5 3he7/ 6.9 RAT
384 Rajawaka PR 2387.6 2387.6 2 11 0.9 3.5 RAT
* 386 Rammalakanda PR 453.7 453.7 1 5 5.0 5.6 RAT
532 Talawegoda OSF 450.0 450.0 1 8 1 1.1 RAT
* 432 Tibbutukanda PR PES) 233.9 1 4 13.0 4.4 RAT
455 Walankanda 03/04/1890 FR 832.9 gi liles) 2 10 7, 3.9 RAT
* 456 Walawe Basin 08/09/1893 FR 3237-5) 3229.7 1 8 6.3 1.4 RAT
459 Waratalgoda PR 1889.9 1889.9 2 10 4.8 4.6 RAT
* 476 Wewelkandura PR 429.0 429.0 1 5} 14.5 7.1 RAT

Inadequately inventoried forest (i.e. number of previously unrecorded woody plant species in penultimate or last plot <= 5% of the
cumulative number of species, as shown in the 10th and 11th columns of the table).

Key to designations:

(Qa Conservation Forest NP National Park

FR Forest Reserve NR Nature Reserve
NHWA _ National Heritage Wilderness Area Ss Sanctuary

OSF Other State Forest SNR Strict Natural Reserve
PR Proposed Reserve

164

CONTIGUOUS FORESTS

EMD Contiguous

No. forest name Composition (numbers of individual forests)
-414 Sinharaja (N=14) 19, 68, 69, 70, 77, 205, 289, 315, 414, 459, 499, 545, 546, 547
-522 Knuckles /Wasgomuwa (N=9) 79, 82, 335, 460, 461, 522, 560, 561, 562, 563, 564
-140 Central Highlands (N=14) 1, 40, 52, 123, 140, 172, 192, 270, 307, 358, 361, 456, 468, 530, 549, 551
-175 KDN (N=4) 65, 175, 234, 328, 303, 505
-28 Bambarabotuwa (N=4) 28, 274, 288, 528, 529
-455 Walankanda (N=6) 71, 298, 348, 386, 455, 476, 541, 542
-208 Kombala-Kottawa (N=2) 173, 208
-343 Panilkanda (N=2) 343, 501
-362 Pedro (N=2) 100, 248, 362
-487 Yagirala (N=3) 486, 487, 512
-129 Haycock (N=2) 120, 129
-253 Malambure (N=2) 253, 369
-281 Mineriya (N=2) 113, 281
-39 Bibilehela (N=2) 39, 608
-398 Ruhuna/Yala (N=8) 186, 187, 398, 399, 400, 401, 402, 491
-573 Puswellagolla (N=4) 410, 569, 571, 573
-161 Kalahalla-Pallekele ( N=2) 161, 336
-144 Inamaluwa (N=2) 144, 574
-640 Getamalagamakanda (N=2) 640, 641
-164 Mangroves (N=3) 164, 523, 524

165

Annex 6

SUMMARY OF WOODY PLANT DIVERSITY WITHIN INDIVIDUAL FORESTS

The number of families, genera, species and endemic species are summarised for each forest,
together with the number of species that are rare (i.e. recorded only within that particular
forest), nationally threatened according to Wijesinghe er al. (1993) and globally threatened
according to the WCMC Plants Database (23 December 1994).

Species recorded within individual forests can be identified from the species/forest matrix in
Annex 1, Volume 2.

EMD Rare/ aiimeakenespetes
No. Forest name Families Genera Species Rare Endemic Endemic National Global
* 1 Agra-Bopats 33 63 79 1 40 0 5 13
* 549 Alutwelawisahena Sil 111 147 0 89 0 9 56
* 7 Amanawala-Ampane 46 85 98 1 53 1 9 29
* 567 Amsawagama 30 50 57 (0) 10 0 1 1
* 501 Aninkanda 50 100 120 1 64 1 6 40
* 530 Appalagala 32 60 66 1 14 1 2 3
* 654 Arangala 28 46 51 0 8 0 1 0
636 Aruwewa 27 49 55 1 a 0 2 1
* 528 Asantanakanda 45 102 128 1 75 0 4 45
* 509 Auwegalakanda 47 105 134 0 81 0 12 53
* 19 Ayagama 55 124 147 1 70 1 12 49
* 24 Badullakele 42 72 84 0 40 0 1 29
28 Bambarabotuwa 54 123 169 1 113 0 il) 77
* 511 Bambarawana 51 114 136 0 68 0 7 44
* 513 Batahena 51 115 138 0 72 (0) 12 45
* 589 Begahapatana 28 53 60 1 8 0 1 0
568 Beliyakanda 30 56 70 0 12 0 D 0
37 Beraliya (Akuressa) 60 136 189 1 109 0 15 75
38 Beraliya (Kudagala) 55 123 163 1 96 0 12 66
* 39 Bibilehela 30 53 61 1 6 0 0 1
40 Bogawantalawa 25 45 67 0 42 0 8 11
593 Bolhindagala 18 32 37 0 3 0 1 0
* 44 Bundala 20 34 35 5 3 0 0 1
* 556 Chilaw Lake 10 11 13 3 1 0 0 0
* 52 Conical Hill 26 37 53 0 29 0 3) 6
* 60 Dandeniya-Aparekka 41 82 95 0 51 0 8 29
* 62 Darakulkanda 52 109 128 0 63 0 8 46
65 Dediyagala 56 125 188 0 124 0 18 87
* 68 Delgoda 49 107 150 1 96 1 14 67
69 Dellawa 62 146 203 1 111 Oo 9 76
* 70 Delmella Yatagampitiya 46 98 110 0 55) 0 8 38
71 ~+Delwela 50 126 173 0 102 0 18 68
* 500 Derangala 39 83 93 0 40 0 4 26
* 575 Dewagiriya 19 36 42 z 4 0 4 2
* 579 Diggala 26 47 55 0 12 0 3 4
77 Diyadawa 59) 139 197 1 116 (0) 16 7s)
* 78 Doluwakanda 24 42 48 2 25 1 2 14
* 79 Dotalugala 39 73 81 2 31 0 6 9
* 80 Dunkanda 34 63 68 2 16 0 4 6
* 660 Elagamuwa 29 41 48 1 5 0 0 0
* §82 Elagomuwa 35 59 67 0 8 0 2 0
* 569 Etabendiwela 23 39 46 0 6 0 1 1
* 96 Gal Oya 35 63 75 0 12 0 1 0
560 Galboda 37 70 85 0 14 0 2 2
* 101 Galgiriyakanda 29 46 55 2 9 0 0 1
* 641 Galkulama Tirrapane 21 38 39 0 5) 0 i 1

166

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Forest name

Gallegodahinna
Galleletota
Gederagalpatana
Getalagamakanda
Gilimale-Eratne
Gintale
Golupitiyahela
Gongala
Gorangala
Guruhela
Habarakada
Hakgala
Handapan Ella
Hapugala
Hataramune
Haycock
Hindeinattu
Hinna
Hiriwaduna
Homadola
Horagala-Paragala
Horton Plains
Inamaluwa
Inginya
Kabarakalapatana
Kahalla
Kahalla-Pallekele
Kahanda Kalapuwa
Kalametiya Kalapuwa
Kalubowitiyana
Kaludiyapokuna
Kalugala
Kandapola Sita Eliya
Kandawattegoda
Kanneliya
Kanumuldeniya
Karawita
Katagamuwa
Kataragama
Kekanadura
Kelani Valley
Kelani Valley
Keulakada Wewa
Kikilimana
Kiribatgala
Kirinda Mahayayakele
Kitulhela
Knuckles
Kobahadunkanda
Kokkebe
Kombala-Kottawa
Korathalhinna
Kosgahakele
Kudagoda
Kudumiriya
Kuragala
Kurulugala
Kurulukele
Labunoruwa
Lolehela
Madunagala
Mahakudagala
Malambure
Manapaya
Manawewakanda
Masimbula
Masmullekele

Families

Genera

167

Species

Rare

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Threatened species

National Global

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Forest name

Medirigiriya Tulana
Meegahatenna
Meepilimana
Menikdeniya
Messana

Mihintale
Minneriya
Minneriya-Giritale

Minneriya-Giritale Block 1

Miyandagala
Monerakelle
Morahela

Morapitiya-Runakanda

Mulatiyana
Mulgama
Murutukanda
Nahiti Mukalana
Nakiyadeniya
Namunukula
Narangattahinna
Neluketiya Mukalana
Neugalkanda
Ohiya
Oliyagankele
Opalagala
Padawiya
Pallankulama

Pallegama-Himbiliyakada

Pallekele
Panilkanda
Paragala
Pattipola-Ambawela
Peak Wilderness
Pedro
Polgahakanda
Potawa
Puliyamkulam
Puliyankulama
Puswellagolla
Radaliwinnekota
Rajawaka
Rammalakanda
Rammalakanda
Ranawekanda
Randeniya
Ranwaragalakanda
Ravana Ella
Rekawa Kalapuwa
Rilagala

Ritigala

Ruhuna Block 1
Ruhuna Block 2
Ruhuna Block 3
Ruhuna Block 4
Sacombe
Sellankandal
Sembawatte
Semewa
Sigiriya
Silverkanda
Sinharaja
Talawegoda
Tangamalai
Tawalama
Tibbutukanda
Tiboruwakota
Tottawelgola

Families

108

Genera

168

Species

76
94
58
92
143
41
31
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85
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121
152
244
204
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Threatened species
Global

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EMD Rare/ Threatened species

No. Forest name Families Genera Species Rare Endemic Endemic National Global
438 Uda Walawe 32 60 74 0 6 0 1 0
* 442 Udawattakele 31 45 51 0 14 0 1 3
* 576 Ulgala 28 51 58 1 9 0 4 2
* 551 Usgala 52 119 152 1 92 0 12 64
* 583 + Velihela 26 43 48 0 9 0 1 1
$12 Vellihallure 52 111 132 0 64 0 7 42
* 453 Viharekele 44 90 108 0 62 0 9 41
* 604 Viyanahela 36 63 73 0 12 0 2 2
588 Wadinahela 27 44 50 1 4 0 1 0
455 Walankanda 58 131 181 1 101 1 13 63
* 456 Walawe Basin 53 107 145 2 70 0 11 44
458 Wanniyagama 29 54 64 0 8 0 1 1
459 Waratalgoda 61 155 217 1 126 0 22 85
460 Wasgomuwa Lot 1 49 120 151 9 22 0 5 2
* 659 Wathurana 44 89 112 5 66 3) 12 43
463 Wedakanda 25 50 61 0 10 (0) 2 1
* 464 Wedasitikanda 21 32 39 0 4 0 1 0
608 Welanwita 35 84 103 3 13 1 3 1
* 471 Welihena g 41 80 107 0 74 0 13 60
* 652 Wellamudawa 18 29 32 0 2 0 0 0
* 476 Wewelkandura 52 119 156 0 89 0 13 59
* 486 Yagirala 52 109 137 1 1) 1 11 50
487 Yagirala 57 130 171 1 89 0 16 64
489 Yakdessakanda 34 62 Wil 2 16 0 3 5

* Inadequately inventoried forest.

169

Annex 7

SUMMARY OF FAUNAL DIVERSITY WITHIN INDIVIDUAL FORESTS

The number of families, genera, species and endemic species are summarised for each forest,
together with the number of species that are rare (i.e. recorded only within that particular
forest), nationally threatened according to Wijesinghe er al. (1993) and globally threatened
according to IUCN (1995).

Species recorded within individual forests can be identified from the species/forest matrix in
Annex 2, Volume 2. It should be noted that all forests were inadequately inventoried for
fauna.

Codes for higher taxa are as follows:

A = Birds, B = Amphibians, I = Butterflies, K = Molluscs, M = Mammals, P = Fishes, R = Reptiles.

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
1 Agra-Bopats A 15 18 19 0 8 0 8 1
1 Agra-Bopats B 1 1 5 0 2 0 2 0
1 Agra-Bopats I 0 0 0 0 0 0 0 0
1 Agra-Bopats K 0 0 0 0 0 0 0 0
1 Agra-Bopats M 5 ii 7 0 1 0 3 0
1 Agra-Bopats R 1 1 1 0 1 0 1 0
Total 22 27 82 0 12 0 14 1
7 Amanawala-Ampane A 17, 19 22 0 7 0 8 1
a Amanawala-Ampane B 2 2 2 0 1 0 1 0
7 Amanawala-Ampane I 3 5 5 0 1 0 0 1
7 Amanawala-Ampane K 3 5) 5 0 5 0 0 0
7 Amanawala-Ampane M 5 6 6 0 0 0 1 0
7 Amanawala-Ampane R 2 3 3 0 2 0 3 0
Total 32 40 43 0 16 0 13 2
19 Ayagama A 13 15 20 0 7 0 7 1
19 Ayagama B 2 3 3 0 2 0 2 0
19 Ayagama I 1 1 1 0 0 0 0 0
19 Ayagama K 1 2 3 0 3 0 0 0
19 Ayagama M 6 6 6 0 1 0 1 0
19 Ayagama R 2 2 2 0 2 0 2 0
Total 25 29 35 0 15 0 12 1
24 Badullakele A 9) 9 10 0 2 0 2 0
24 Badullakele B 2 2 2 1 1 0 1 0
24 Badullakele I 2 2 2 0 0 0 0 0
24 Badullakele K 2 2 4 0 4 0 0 0
24 Badullakele M 4 5 5 0 3 0 2 0
24 Badullakele R 1 1 1 0 1 0 1 0
Total 20 21 24 1 11 0 6 0
28 Bambarabotuwa A 16 20 22 0 7 0 6 2
28 Bambarabotuwa B 1 1 1 0 1 0 1 0
28 Bambarabotuwa If 3 9 12 0 0 0 0 0
Bambarabotuwa K 3 4 4 0 4 0 0 0
28 Bambarabotuwa M 4 4 4 0 1 0 1 0

170

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
28 Bambarabotuwa R 5 8 9 0 5 One 5) 0
Total 32 46 52 0 18 0 13 2
siy/ Beraliya (Akuressa) A 17 25 29 0 5 0 5 0
37 Beraliya (Akuressa) B 1 1 2 0 1 0 1 0
37 Beraliya (Akuressa) I 0 0 0 0 0 0 0 0
37 Beraliya (Akuressa) K 4 8 11 0 11 0 0 0
37 Beraliya (Akuressa) M 6 8 8 0 3 0 2 0
37 Beraliya (Akuressa) R 5 11 11 0 7 0 8 (0)
Total 33 53 61 0 27 0 16 0
38 Beraliya (Kudagala) A 18 21 24 0 3 0 3} 0
38 Beraliya (Kudagala) B 2 2 3 0 2 0 2 0
38 Beraliya (Kudagala) I 1 2 2 0 0. 0 0 0
38 Beraliya (Kudagala) K 5 i 7 0 6 0 0 0
38 Beraliya (Kudagala) M 6 6 6 0 1 0 1 0
38 Beraliya (Kudagala) R 4 6 6 0 3 0 2 0
Total 36 44 48 0 15 0 8 0
39 Bibilehela A 22 37 42 0 3 0 3 0
39 Bibilehela B 0 0 0 0 0 0 0 0
39 Bibilehela I 4 4 4 0 0 0 0 0
39 Bibilehela K 2 2 2 0 1 0 0 0
39 Bibilehela M 7 8 8 0 0 0 1 0
39 Bibilehela R 3 4 5 1 3 1 2 0
Total 38 55 61 1 7 1 6 0
40 Bogawantalawa A 11 16 18 0 3 0 5 0
40 Bogawantalawa B 1 1 5 0 2 0 2 0
40 Bogawantalawa I 3 3 3 1 0 0 0 0
40 Bogawantalawa K 3 3 3 0 3 0 0 0
40 Bogawantalawa M 4 5 5 0 1 0 2 0
40 Bogawantalawa R 1 2 2 0 2 0 22 0
Total 23 30 36 1 11 0 11 0
44 Bundala A 15 18 20 0 1 0 1 0
44‘ Bundala B 0 0 0 0 0 0 0 0
44 Bundala I 4 7 8 0 0 0 0 0
44 Bundala K 1 1 1 0 0 0 0 0
44 Bundala M 8 8 8 0 0 0 2 1
44 Bundala R 1 2 2 0 0 0 0 0
Total 29 36 39 0 1 0 3 1
52 Conical Hill A 10 14 15 0 3 0 4 1
52 Conical Hill B 1 2 3 0 2 0 2 0
52 Conical Hill I 2 2 2 0 1 0 0 0
52 Conical Hill K 4 5 5 1 a 1 0 0
52 Conical Hill M 5 fl 7 0 0 0 2 0
52 Conical Hill R 1 2 2 0 2 0 2 0
Total 23 32 34 1 12 1 10 1
60 Dandeniya-Aparekka A 10 12 12 0 0 0 0 0
60 Dandeniya-Aparekka B 0 0 0 0 0 0 0 0
60 Dandeniya-Aparekka I 0 0 0 0 0 0 0 0
60 Dandeniya-Aparekka K 8 4 5) 0 5) 0 0 0
60 Dandeniya-Aparekka M 2 2 2 0 0 0 0 0
60 Dandeniya-Aparekka R 2 3 3 0 2 0 2 0
Total V7) 21 22 0 7 0 2 0
62 Darakulkanda A 10 11 12 0 2 0 2 0
62 Darakulkanda B 1 1 1 0 0 0 0 0
62 Darakulkanda I 1 1 1 0 1 0 0 1
62 Darakulkanda K 3 4 4 0 4 0 0 0
62 Darakulkanda M 6 6 6 0 1 0 1 0
62 Darakulkanda R 3 3} 3) 0 2 0 1 0
Total 24 26 27 0 10 0 4 1

171

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
65 Dediyagala A 14 17 20 0 4 0° 4 (0)
65 Dediyagala B 1 1 2 0 0 0 0 0
65 Dediyagala I 1 1 1 0 0 0 0 0
65 Dediyagala K 4 7 8 0 7 0 0 0
65 Dediyagala M 8 8 8 0 1 0 2 0
65 Dediyagala R 4 8 8 0 5 0 4 0
Total 32 42 47 0 17 0 10 0
68 Delgoda A 12 15 17 0 6 0 i 0
68 Delgoda B 1 2 2 0 2 0 2 0
68 Delgoda I 0 0 0 0 0 0 0 0
68 Delgoda K 2 3 3 0 3 0 0 0
68 Delgoda M 6 6 6 0 1 0 1 0
68 Delgoda R 2 3 3 0 3 0 1 0
Total 23 29 31 0 15 0 11 0
69 Dellawa A 20 32 37 0 12 0 13 3
69 Dellawa B 3 5 5 1 5 1 5 0
69 Dellawa I 8 9 12 0 1 0 0 1
69 Dellawa K 8 4 5 0 5 0 0 0
69 Dellawa M 7 8 8 0 2 0 3 0
69 Dellawa R 5 11 12 0 6 0 5 0
Total . 41 69 79 1 31 1 26 4
70 Delmella Yatagampitiya A 14 17 19 0 5 0 5 1
70 Delmella Yatagampitiya B 0 0 0 0 0 0 0 0
70 Delmella Yatagampitiya I 2 4 4 0 0 0 0 0
70 Delmella Yatagampitiya K 2 2 2 0 2 0 0 0
70 Delmella Yatagampitiya M 5 5 5 0 0 0 1 0
70 Delmella Yatagampitiya R 0 0 0 0 0 0 0 0
Total 23 28 30 0 7 0 6 1
71 Delwela A 16 19 21 0 9 0 10 1
71 Delwela B 3) 5 6 0 4 0 3 0
71 Delwela I 2 5) 5 0 1 0 0 1
71 Delwela K 2 3 3 0 3 0 0 0
71 Delwela M 7 8 8 0 3 0 2 0
71 Delwela R 4 7 8 0 6 0 5 0
Total 34 47 51 0 26 0 20 2
77 Diyadawa A 19 29 34 0 ©) 0 8 1
77 Diyadawa B 1 1 1 0 1 0 1 0
77 Diyadawa I 4 12 16 0 1 0 0 1
77 Diyadawa K 3 5 6 0 6 0 0 0
77 Diyadawa M 8 10 10 0 2 0 4 0
77 Diyadawa R 5 9 12 0 6 0 5 0
Total 40 66 79 0 25 0 18 2
78 Doluwakanda A 9 12 14 0 0 0 1 0
78 Doluwakanda B 0 0 0 0 0 0 0 0
78 Doluwakanda I 0 0 0 0 0 0 0 0
78 Doluwakanda K 2 2 2 0 2 0 0 0
78 Doluwakanda M 1 1 1 0 0 0 0 0
78 Doluwakanda R 2 4 4 0 3 0 4 0
Total 14 19 21 10) 5) 0 8) 0
79 Dotalugala A 11 13 14 0 6 0 6 0
go Dotalugala B 1 1 2 0 0 0 0 0
79 Dotalugala I 1 1 1 0 0 0 0 0
79 Dotalugala K 0 0 0 0 0 0 0 0
79 Dotalugala M 6 6 6 0 1 0 1 0
79 Dotalugala R 4 4 4 1 4 1 3 1
Total 23 25 27 1 11 1 10 1
80 Dunkanda A 16 19 21 0 1 0 1 0
80 Dunkanda B 0 0 0 0 0 0 0 0
80 Dunkanda I 3 5 5 0 0 0 0 0

172

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
80 Dunkanda K 2 2 2 0 2 0 0 0
80 Dunkanda M 7 7 7 0 0 0 1 0
80 Dunkanda R 1 1 1 10) 1 10) 1 0)
Total 29 34 36 0 4 0 3 0
82 Elagomuwa A 15 15 20 0 2 0 Dy} 0
82 Elagomuwa B 0 0 0 0 0 0 0 (0)
82 Elagomuwa I 5 9 10 0 0 0 0 0
82 Elagomuwa K 0 0 0 0 0 0 0 0
82 Elagomuwa M 6 6 6 0 0 0 0 0
82 Elagomuwa R 1 1 1 0 0 0 0 (0)
Total 27 31 37 0 2 0 2 0
96 Gal Oya A 8 8 10 0 2 0 2 0
96 Gal Oya B 0 0 0 0 0 0 0 0
96 Gal Oya I 5 8 11 0 0 0 0 0
96 Gal Oya K 3 3 3 1 2 1 0 0
96 Gal Oya M 6 U Hl 0 1 0 1 1
96 Gal Oya R 1 1 1 0 1 0 1 0
Total 23 27 32 1 6 1 4 1
101 Galgiriyakanda A 18 21 24 0 2 0 2 0
101. Galgiriyakanda B 0) 0 0 10) 0 0 0 0
101 Galgiriyakanda I 3 5 5 0 0 0 0 0
101 Galgiriyakanda K 3 3 3 0 2 0 0 0
101 Galgiriyakanda M 7 9 9 0 1 0 1 0
101 Galgiriyakanda R 2 3 4 0 2 0 2 0
Total 33 41 45 0 7 0 5) 0
112. Gilimale-Eratne A 21 31 34 0 10 0 10 2
112 Gilimale-Eratne B 2 4 0 4 0 4 0
112 Gilimale-Eratne I 3 7 9 0 1 0 0 1
112 Gilimale-Eratne K 4 7 12 0 10 0 0 0
112. Gilimale-Eratne M 8 12 12 0 3 0 4 0
112 Gilimale-Eratne R 5 9 13 0 10 0 8 0
Total 43 70 84 0 38 0 26 3
113. Giritale A 7 7 9 0 1 0 1 0
113 Giritale B 0 0 0 0 0 0 0 0
113 Giritale I 1 1 1 0 0 0 0 0
113 Giritale K 3 5 3) 0 3 0 0 0
113 Giritale M 8 9 9 0 0 0 2 1
113 Giritale R 1 2 2 0 0 0 0 0
Total 20 24 26 0 4 0 3 1
120 Habarakada A 13 16 17 0 5 0 6 0
120 Habarakada B 2 2 2 0 1 0 1 0
120 Habarakada I 2 2 2 0 0 0 0 0
120 Habarakada K 4 4 5 0 75 0 0 0
120 Habarakada M 4 4 4 0 0 0 0 0
120 Habarakada R 4 5 5 0 3 0 1 0
Total 29 33 35 0 14 0 8 0
123 Hakgala A 16 21 22 0 6 0 ah 0
123. Hakgala B 1 1 2 0 1 0 1 0
123 Hakgala I 0 0 0 0 0 0 0 0
123 Hakgala K 1 1 2 0 1 0 0 0
123. Hakgala M 4 5 5 0 1 0 2 0
123 Hakgala R 1 1 1 0 1 0 1 0
Total 23 29 32 0 10 0 11 0
129 Haycock A 11 11 13 0 4 0 4 0
129 Haycock B 2 2 3 0 2 0 2 0
129 Haycock I 2 3 3 0 0 0 0 0
129 Haycock K 5 7 9 1 9 1 0 0
129 Haycock M 5 6 6 0 2 0 2 0
129 Haycock R 4 7 8 0 4 0 3 0

173

Threatened species

EMD Higher Rare} Seesee Seer ees
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
Total 29 36 42 1 21 1 11 0
136 Hinna A 14 15 16 0 2 0 2 0
136 ~=Hinna B 1 1 1 0 0 0 0 0
136 ~=Hinna I 6 12 17 1 1 1 0 0
136 Hinna K 1 1 1 0 1 0 0 0
136 =Hinna M 6 6 6 0 0 0 1 1
136 ~=Hinna R 2 2 2 0 1 0 1 (0)
Total 30 37 43 1 5 1 4 1
138 Horagala-Paragala A 16 18 22 0 6 0 6 0
138 Horagala-Paragala B 0 0 0 0 0 0 0 0
138 Horagala-Paragala I 2 2 2 0 0 0 0 0
138 Horagala-Paragala K 3 4 4 0 4 0 0 0
138 Horagala-Paragala M 6 6 6 0 1 0 2 0
138 Horagala-Paragala R 2 2 2 0 1 0 0 0
Total 29 32 36 0 12 0 8 0
140 Horton Plains A 16 25 26 2 5 0 7 1
140 Horton Plains B 2 2 7 0 3 0 3 0
140 Horton Plains I 1 1 1 0 0 0 0 0
140 Horton Plains K 2 2 2 0 1 0 0 0
140 Horton Plains M 6 7 i, 0 1 0 3 0
140 Horton Plains R 2 4 4 0 4 0 4 0
Total 29 41 47 2 14 0 17 1
144 Inamaluwa A 14 17 21 0 1 0 1 0
144 Inamaluwa B 0 0 0 0 0 0 0 0
144. Inamaluwa I 4 6 6 0 0 0 0 0
144 Inamaluwa K 0 0 0 0 0 0 0 0
144 Inamaluwa M 7 7 7 0 0 0 2 1
144 Inamaluwa R 0 0 0 0 0 0 0 0
Total 25 30 34 0 1 0 3} 1
147 — Ingiriya A 16 18 21 0 5 0 5 1
147 Ingiriya B 1 1 1 0 1 0 1 0
147 Ingiriya I 1 1 1 0 0 0 0 0
147 Ingiriya K 3 4 4 0 4 0 0 0
147 Ingiriya M 5) 5) 5 0 1 0 1 0
147 Ingiriya R 3 3 3 0 2 0 1 0
Total 29 32 35 0 13 0 8 1
160 Kahalla A 16 21 24 0 1 0 1 0
160 Kahalla B 0 0 0 0 0 0 0 0
160 Kahalla I 2 3 3 0 0 0 0 0
160 Kahalla K 0 0 0 0 0 0 0 0
160 Kahalla M 7 7 7 0 1 0 1 1
160 Kahalla R 0 0 0 0 0 0 0 0
Total 25 31 34 0 D2 0 2 1
161. Kahalla-Pallekele A 24 34 39 0 2 0 2 0
161 Kahalla-Pallekeie B 1 1 2 0 1 0 1 0
161 Kahalla-Pallekele I 5 3} 20 0 0 0 0 0
161 Kahalla-Pallekele K 0 0 0 0 0 0 0
161 Kahalla-Pallekele M 7 8 8 0 0 0 2 1
161 Kahalla-Pallekele R 2 2 2 0 2 0 2 0
Total 39 58 71 0 5) 0 7 1
164 Kalametiya Kalapuwa A 19) 22 25 0 1 0 1 0
164 Kalametiya Kalapuwa B 0 0 0 0 0 0 0 0
164 Kalametiya Kalapuwa I 1 1 1 0 0 0 0 0
164 Kalametiya Kalapuwa K 0 0 0 0 0 0 0 0
164 Kalametiya Kalapuwa M 2 2 2 0 0 0 0 0
164 Kalametiya Kalapuwa R 0 0 0 0 0 0 0 0
Total 22 25 28 0 1 0 1 0
166 Kalugala A 14 18 20 0 8 0 9 0

174

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
166 = Kalugala B 2 4 5 0 3 0 3 0
166 Kalugala I 3 6 6 0 1 0 0 1
166 =Kalugala K 3 4 5 0 5 0 0 0
166 Kalugala M a 9 9 0 3 0 3 0
166 = Kalugala R 4 8 8 0 4 0 5 0
Total 88 49 53 0 24 0 20 1
172 Kandapola Sita Eliya A 13 14 14 0 6 0 6 1
172 Kandapola Sita Eliya B 2 4 Y 0 3 0 3 0
172. Kandapola Sita Eliya I 3 4 4 1 (0) 0 10) 0
172 Kandapola Sita Eliya K 3 3 5 0 4 0 0 0
172 Kandapola Sita Eliya M Wf 9 9 0 i 0 2 0
172. Kandapola Sita Eliya R 1 2 2 0 2 0 2 0
Total 29 36 41 1 16 0 13 1
173 Kandawattegoda A 8 8 9 0 1 0 1 0)
173 Kandawattegoda B 1 1 1 0 1 0 1 0
173 Kandawattegoda I 2 2 2 0 0 0 0 0
173 Kandawattegoda K 4 7 8 0 8 0 0 0
173 Kandawattegoda M 3 3 3 0 0 0 0 0
173 Kandawattegoda R 3 4 4 0 2 0 1 0
Total 21 25 ay} 0 12 0 3 0
175 Kanneliya A 15 21 22 0 7 0 7 0
175 Kanneliya B 2 4 6 0 2, 0 2 0
“175 Kanneliya I 2 4 5 0 1 0 0 1
175 Kanneliya K 6 8 12 0 10 0 0 0
175 Kanneliya M 7 10 10 0 3 0 3 0
175 Kanneliya R 4 5 5 0 2 0 1 0
Total 36 52 60 0 25 0 13 1
178 Kanumuldeniya A 9 10 11 0 1 0 1 0
178 Kanumuldeniya B 0 0 0 0 0 0 0 0
178 Kanumuldeniya I 0 0 0 0 0 0 0 0)
178 Kanumuldeniya K 2 2 2 0 2 0 0 0
178 Kanumuldeniya M 5 6 6 0 2 0 1 0
178 Kanumuldeniya R 2 2 3 0 2 0 0 0
Total 18 20 22 0 7 0 2 0
184 = Karawita A 17 22 24 0 8 0 7 1
184 Karawita B 1 1 1 0 1 0 1 0
184 Karawita I 0 0 0 0 0 0 0 0
184 Karawita K 3 5) 7 0 7 0 0 0
184 Karawita M 6 7 7 0 1 0 2 0
184 Karawita R 4 6 6 0 4 0 4 0
Total 31 41 45 0 21 0 14 1
186 Katagamuwa A 16 19 23 0 0 0 0 (0)
186 Katagamuwa B 2 2 2 0 1 0 1 0
186 Katagamuwa I 6 9 9 1 0 0 0 0
186 Katagamuwa K 2 2 2 0 1 0 0 0
186 Katagamuwa M 6 7 7 0 0 0 2 2
186 Katagamuwa R 1 1 1 0 1 0 1 0
Total 33 40 44 1 3 0 4 2
187 Kataragama A 11 13 15 0 2 0 2 0
187 Kataragama B 0 0 0 0 0 0 0 0
187 Kataragama I 5 6 6 0 0 0 0 0
187 Kataragama K 3 3 3 0 1 0 0 0
187 Kataragama M 6 6 6 0 0 0 3 2
187 Kataragama R 3 3 3 0 1 0 2 0
Total 28 31 33 0 4 0 7 2
190 Kekanadura A 8 8 10 0 4 0 4 0
190 Kekanadura B 0 0 0 0 0 0 0 0
190 Kekanadura I 0 0 0 0 0 0 0 0
190 Kekanadura K 3 3 4 0 4 0 0 0

175

Threatened species

EMD Higher Rare?) . 2 uSu soe cae

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
190 Kekanadura M 5; 5 5 0 1 0 1 0
190 Kekanadura R 1 1 2 0 2 0 0
Total 17 17 21 0 11 0 6 0
191 Kelani Valley A 18 22 24 0 5 0 5 0
191 Kelani Valley B 2 2 4 0 1 0 0 0
191 Kelani Valley I 1 1 1 0 0 0 0 0
191 Kelani Valley K 4 6 6 0 6 0 0 0
191 = Kelani Valley M 6 6 6 0 1 0 2 0
191 Kelani Valley R 4 7 8 0 3 0 4 0
Total ~ 35 44 49 0 16 0 11 0
192 Kelani Valley A 12 12 14 0 4 0 4 0
192 Kelani Valley B 2) 2 3 0 2 0 1 0
192 Kelani Valley I 1 2 2 0 0 0 0 0
192 Kelani Valley K 2 3 3 0 3 0 0 0
192 Kelani Valley M 6 6 6 0 2 0 2 0
192 Kelani Valley R 4 10 11 0 8 0 7 0
Total 3 27 35 39 0 19 0 14 0
197 Kikilimana A 9 9 11 0 3 0 3 0
197 Kikilimana B 2 4 6 0 4 0 4 0
197 Kikilimana I 3 3 3 0 1 0 0 0
197 Kikilimana K 5 5 5 2 4 2 0 0
197 Kikilimana M 5 6 6 0 1 0 0 0
“197 Kikilimana R 1 1 1 0 1 0 1 0
Total z 25 28 32 2 14 2 8 0
201 + Kirinda Mahayayakele A 9 9 10 0 1 0 1 0
201 + Kirinda Mahayayakele B 0 0 0 0 0 0 0 0
201 Kirinda Mahayayakele I 0 0 0 0 0 0 0 0
201 Kirinda Mahayayakele K 3 4 6 0 6 0 0 0
201 + Kirinda Mahayayakele M 7 7 7 0 2 0 3 0
201 Kirinda Mahayayakele R 2 3 3 0 2 0 i 0
Total 21 23 26 0 11 0 6 0
205 Kobahadunkanda A 16 18 20 0 5 0 5 0
205 Kobahadunkanda B 2 2 3 0 2 0 2 (0)
205 Kobahadunkanda I 2 2 2 0 1 0 0 1
205 Kobahadunkanda K 1 1 1 0 1 10) 0 0
205 Kobahadunkanda M 6 6 6 0 2 0 2 0
205 Kobahadunkanda R 3 5 5 0 4 0 3 0
Total 30 34 37 0 15 0 12 1
208 Kombala-Kottawa A 15 20 23 0 6 0 6 0
208 Kombala-Kottawa B 2 2 3 0 2 0 2 0
208 Kombala-Kottawa I 2 2 2 0 0 0 0 0
208 Kombala-Kottawa K 7 11 14 1 13 1 0 0
208 Kombala-Kottawa M 8 9 9 2 3 0 2 0
208 Kombala-Kottawa R 3 6 6 0 3 0 3 0
Total 37) 50 57 3 27 1 13 0
217 Kudumiriya A 12 14 17 0 8 0 ih 2
217 Kudumiriya B 2 3} 5 0 4 0 4 0
217. Kudumiriya I 1 1 1 0 0 0 0 0
217. Kudumiriya K 1 2 3 0 3 0 0 0
217 Kudumiriya M 3 3 3 0 0 0 0 (0)
217 Kudumiriya R 2 4 4 0 3 0 3 0
Total 21 27 33 0 18 0 14 2
237. Madunagala A 11 14 16 (0) 1 0 1 0
237. Madunagala B 0) 0 0 0 0 0 0 0
237 Madunagala I 1 1 1 0 0 0 0 0
237. Madunagala K 0 0 0 0 0 0 0 0
237 Madunagala M 6 6 6 0 1 0 1 1
237 Madunagala R 1 1 1 0 1 0 1 0
Total 19 22 24 0 3 0 3 1

176

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
248 Mahakudagala A 10 12 12 0 3 a) 3 0
248 Mahakudagala B 2 2} 3 0 1 0 0 0
248 Mahakudagala I 1 2 2: 0 0 0 0 0
248 Mahakudagala K 1 1 1 0 1 0 0 0
248 Mahakudagala M 4 5 5 0 1 0 1 0
248 Mahakudagala R 1 1 1 0 1 0 1 0
Total 19 23 24 0 7 0 5 0
253. Malambure A 13 15 17 0 6 0 6 0
253. Malambure B 2 2 2 0 1 0 1 0
253. Malambure I 2 4 4 0 1 0 0 1
253. Malambure K 5 d 9 0 9 0 0 0
253. Malambure M 6 7 7 0 3 0 2 0
253. Malambure R 4 5 5 0 35 0 2 0
Total 32 40 44 0 23 0 11 1
256 Manapaya A 14 15 17 0 1 0 1 0)
256 Manapaya B 0 0 0 0 0 0 0 0
256 Manapaya I 3 4 4 0 0 0 0 0
256 Manapaya K 1 1 1 0 1 0 0 0
256 Manapaya M 8 8 8 0 1 0 1 0
256 Manapaya R 1 1 1 0 0 0 0 0
Total 27 29 31 0 3 0 2 (0)
263 Masmullekele A 14 18 20 0 2 0 2 0
263 Masmullekele B 1 1 1 0 0 0 0 0
263 Masmullekele I 1 1 1 0 0 0 0 0
263 Masmullekele K 3 4 4 0 4 0 0 0
263 Masmullekele M 6 6 6 0 1 0 1 0
263 Masmullekele R Z 2 2 0 2 0 2 0
Total 27 32 34 0 9 0 5 0
269 Meegahatenna A 6 6 8 0 2 0 2 0
269 Meegahatenna B 0 0 0 0 0 0 0 0
269 Meegahatenna I 2 2 2 0 0 0 0 0
269 Meegahatenna K 0 0 0 0 0 0 0 0
269 Meegahatenna M 5 5 5 0 2 0 2 0
269 Meegahatenna R 2 3 3 0 2 0 1 0
Total NS) 16 18 (0) 6 0 5 0
270 = Meepilimana A 13 16 17 0 6 0 6 1
270 Meepilimana B 1 1 3 0 0 0 0 0
270 Meepilimana I 2: 2 2 0) 1 0 0 0
270 Meepilimana K 1 1 1 0 1 0 0 0)
270 Meepilimana M 5 6 6 0 1 0 2 0
270 Meepilimana R 2 3 3 0 3 0 3 0
Total 24 29 32 0 12 0 11 1
274 Messana A 14 18 21 0 7 0 8 0
274 Messana B 3 3 3 0 2 0 2 0
274 Messana I 4 4 5 1 1 0 0 0
274 Messana K 1 2 2 0 2 0 0 0
274 Messana M 5 5 5 0 1 0 1 0
274 + Messana R 3 4 4 0 4 0 4 0
Total 30 36 40 1 17 0 15 0
277 ~~ Mihintale A 12 14 17 0 1 0 1 0
277 ~~ Mihintale B 0 0 0 0 0 0 0 0
277 ~~ Mihintale I 4 6 7 0 0 0 0 0
277“ Mihintale K 2 2 2 0 1 0 0 0
277 ~~ Mihintale M 6 8 8 0 0 0 0 0
277 ~— Mihintale R 2 3 3 0 2 0 2 0
Total 26 33 37 0 4 0 3 0
279 Minneriya A 8 8 9 0 1 0 1 0
279 Minneriya B 0 0 0 0 0 0 0 0
279 Minneriya I 2 2 2 0 0 0 0 0

177

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
279 ~=Minneriya K 3 5 5 1 3 ie 0 0
279 ~=Minneriya M 8 10 10 0 1 0 2 1
279 = Minneriya R 1 2 2 0 2 0 2 0
Total 22 27 28 1 7 1 5 1
280 Minneriya-Giritale A 10 10 13 0 2 0 2 0
280 Minneriya-Giritale B 0 0 0 0 0 0 0 0
280 Minneriya-Giritale I 4 7 9 0 0 0 0 0
280 Minneriya-Giritale K 2 2 2 0 i 0 0 0
280 Minneriya-Giritale M 6 7 a 0 0 0 2 1
280 Minneriya-Giritale R 2 2 2 0 2 0 2 0
Total 24 28 33 0 5 0 6 1
281 Minneriya-Giritale Block 1 A 20 24 27 0 Ds 0 2 0
281 Minneriya-Giritale Block 1 B 2 2 3 0 2 0 1 0
281 Minneriya-Giritale Block 1 I 5 12 16 1 0 0 0 0
281 Minneriya-Giritale Block 1 K 3 3 3 0 1 0 0 0
281 Minneriya-Giritale Block 1 M 9 11 11 0 1 0 2 1
281 Minneriya-Giritale Block 1 R 2 4 4 0 3 0 3 0
Total 41 56 64 1 9 0 8 1
288 Morahela A 15 17 19 0 7 0 7 1
288 Morahela B 2 4 i 0 3 (0) 3 0
288 Morahela I 2 7 9 0 0 0 0 0
288 Morahela K 3 3 3 0 3 0 0 0
288 Morahela M i 9 9 0 2 0 3 1
288 Morahela R 3 6 9) 0 9 0 6 0
Total 32 46 56 0 24 0 19 2
289 Morapitiya~-Runakanda A 20 27 30 0 10 0 2) 2
289 Morapitiya-Runakanda B 3 5 6 0 5) 0 5 0
289 Morapitiya~-Runakanda I 3 6 8 0 0 0 0 0
289 Morapitiya-Runakanda K a 5 6 0 6 0 0 0
289 Morapitiya-Runakanda M 9 10 11 0 1 0 4 0
289 Morapitiya~-Runakanda R 3 8 9 0 4 0 4 0
Total 42 61 70 0 26 0 22 2
293 Mulatiyana A 22 31 37 0 6 0 6 0
293 Mulatiyana B 2 2 4 0 2 0 2 0
293 Mulatiyana I 2 5 6 0 1 0 0 1
293 Mulatiyana K 5 9 12 0 11 0 0 0
293 Mulatiyana M 8 11 11 0 3 0 4 0
293 Mulatiyana R 5 13 14 0 7 0 7 1
Total 44 Tk 84 0 30 0 19 2)
298 Nahiti Mukalana A 20 25 28 0 7 0 7 0
298 Nahiti Mukalana B 2 2 2 0 2 0 1 0
298 Nahiti Mukalana I 3 5 5 0 1 0 0 1
298 = Nahiti Mukalana K 1 2 2: 0 2 0 0 0
298 Nahiti Mukalana M 8 9 9 0 3 0 3) 0
298 Nahiti Mukalana R 4 8 9 0 5 0 6 1
Total 38 51 55 0 20 0 17 2
303 Nakiyadeniya A 17 21 26 0 8 0 8 1
303 Nakiyadeniya B 2 4 6 0 4 0 4 0
303 Nakiyadeniya I 3 3 3 0 1 0 0 1
303 Nakiyadeniya K 6 10 14 1 14 1 0 0
303. Nakiyadeniya M 5 5 5 0 0 0 0 0
303 Nakiyadeniya R 5 8 8 1 4 0 4 0
Total 38 51 62 2 31 il 16 2
306 Namunukula A 15 19 20 0 5 0 S} 1
306 = Namunukula B 1 1 3 0 1 0 1 0
306 Namunukula I 2 3 3 0 0 0 0 0
306 Namunukula K 1 1 1 0 0 0 0 0
306 Namunukula M 4 4 4 0 1 0 2 0
306 Namunukula R 0 0 0 0 0 0 0 0

178

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
a a a ae ro - hehgoe cr ae
Total 23 28 31 0 7 0 8 1
315 Neluketiya Mukalana A 16 18 22 0 7 0 7 1
315 Neluketiya Mukalana B 3 3 3 0 3} 0 3 0
315 Neluketiya Mukalana I 2 5 6 0 0 0 0 0
315 Neluketiya Mukalana K 3 6 8 0 8 0 0 0
315 Neluketiya Mukalana M 4 4 4 0 0 0 1 0
315 Neluketiya Mukalana R 2 4 4 0 2 0 3 0
Total 30 40 47 0 20 0 14 1
318 Neugalkanda A 22 37 46 0 5) 0 6 0
318 Neugalkanda B 2 2 2 0 1 0 1 0
318 Neugalkanda I 4 5) 0 0 0 0 0
318 Neugalkanda K 1 1 1 0 0 0 0 0
318 Neugalkanda M 7 9 10 0 2 0 1 0
318 Neugalkanda R 2 3 4 0 2 0 3 0
Total 38 57 70 0 10 0 11 0
327. Ohiya A 15 17 19 1 5 0 5 1
327. Ohiya B 1 1 3 0 0 0 0 0
327. Ohiya I 1 1 1 0 0 0 0 0
327. Ohiya K 1 1 1 0 1 0 0 0
327. Ohiya M 5 8 8 0 2 0 3 0
327. Ohiya R 2 2 2 0 2 0 2 0
Total 25 30 34 1 10 0 10 1
329 Oliyagankele A 8 9 10 0 1 0 2) 0
329 Oliyagankele B 1 1 1 0 1 0 1 0
329 Oliyagankele I 2 4 4 0 1 0 0 1
329 Oliyagankele K 3 4 4 1 4 1 0 0
329 = Oliyagankele M 5 5 5 0 1 0 1 0
329 Oliyagankele R 2 2 2 0 2 0 1 0
Total 21 25 26 1 10 1 5 1
333 Padawiya A 23 29 33 0 2 0 2 0
333 Padawiya B 2 4 7 0 3 0 3 0
333. Padawiya I 5 13 18 0 0 0 0 0
333. Padawiya K 4 5 5 0 3 0 0 0
333 Padawiya M 9 12 13 0 Z 0 3 1
333 Padawiya R 3 5 7 1 4 0 4 0
Total 46 68 83 1 14 0 12 1
335 Pallegama-Himbiliyakada A 23 33 39 0 3 0 4 0
335 Pallegama-Himbiliyakada B 1 1 1 0 0 0 0 0
335 Pallegama-Himbiliyakada I 5 9 10 0 0 0 0 0
335 Pallegama-Himbiliyakada K 2 2 2 0 0 0 0 0
335 Pallegama-Himbiliyakada M 9 11 11 0 1 0 3 1
335 Pallegama-Himbiliyakada R 3 4 4 0 3 0 3 0
Total 43 60 67 0 7] 0 10 1
336 ~—~Pallekele A 24 34 41 0 2 0 2 0
336 _—Pallekele B 0 0 0 0 0 0 0 0
336 _—~Pallekele I 4 6 6 0 0 0 0 0
336 —~ Pallekele K 3 3 3) 1 2 1 0 0
336 _—Pallekele M 9 12 12 0 1 0 2 1
336 ~~ Pallekele R 2 2 2 0 0 0 1 0
Total 42 57 64 1 5 1 5 1
343 Panilkanda A 15 19 22 (0) if 0 8 1
343 Panilkanda B 0 0 0 0 0 0 0 0
343 Panilkanda I 2 3 3 0 0 0 0 0
343 Panilkanda K 2 4 4 0 4 0 0 0
343 Panilkanda M 1 a 7 0 2 0 2 (0)
343 Panilkanda R 4 7 8 0 5 0 4 0
Total 30 40 44 0 18 0 14 1
358 Pattipola-Ambawela A 15 17 19 0 8 0 8 3

179

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
358 Pattipola~-Ambawela B 1 2 4 0 1 0 1 0
358 Pattipola-Ambawela I 2 2 2 0 1 0 0 0
358 Pattipola-Ambawela K 0 0 0 0 0 0 0 0
358 Pattipola~-Ambawela M 5 a 7 0 2 0 1 0
358 Pattipola-Ambawela R 1 1 1 0 1 0 1 0
Total 24 29 33 0 13 0 11 3
361 Peak Wilderness A 20 28 31 0 13 0 14 3
361 Peak Wilderness B 3 5 9 0 6 0 6 0
361 Peak Wilderness I 1 1 1 0 0 0 0 0
361 Peak Wilderness K 5 8 11 0 9 0 0 0)
361 Peak Wilderness M 7 8 8 0 2 0 4 0
361 Peak Wilderness R 5 7 12 0 9 0 6 0
Total 41 57 72 0 39 0 30 3)
362 Pedro A 18 26 30 1 6 0 i 1
362 Pedro B 1 1 5 0 1 0 1 0
362 Pedro I 3 5 6 0 0 0 0 0
362. ~=Pedro K 4 5 6 0 5 0 0 0
362 ~=Pedro M 8 9 10 0 1 0 5 0
362 Pedro R 1 3 3 0 3 0 3 0
Total 35 49 60 1 16 0 16 1
369 Polgahakanda A 12 14 16 0 3 0 4 0
369 Polgahakanda B 2 2 2 0 1 0 1 0
369 Polgahakanda I 3 4 4 0 1 0 0 1
369 Polgahakanda K 5 6 8 1 8 1 0 0
369 Polgahakanda M 8 @) 10 0 1 0 4 0
369 Polgahakanda R 3 5 6 0 4 0 3 0
Total 33 40 46 1 18 1 12 1
376 ~=Potawa A 21 27 31 0 5} 0 3 0
376 ~=Potawa B 0 0 0 0 0 0 0 0
376 ~=Potawa I 0 0 0 0 0 0 0 0
376 ~=Potawa K 0 0 0 0 0 0 0 0
376 = Potawa M 4 4 4 0 0 0 0 0
376 ~=Potawa R 2 2} 2 0 0 0 0 0
Total 27 33 37 0 3 0 5 0
384 Rajawaka A 20 29 33 1 4 0 4 0
384 Rajawaka B 1 1 1 0 1 0) 1 0
384 Rajawaka I 4 6 7 0 0 0 0 0
384 Rajawaka K 2 2 2 0 2 0 0 0
384 Rajawaka M ili 8 8 0 0 0 1 0
384 Rajawaka R 0 0 0 0 0 0 0 0
Total 34 46 51 1 7 0 6 0
386 Rammalakanda A 10 11 15 0 4 0 4 0
386 Rammalakanda B 1 1 1 0 “a 0 1 0
386 Rammalakanda I 3 4 4 0 1 0 0 1
386 Rammalakanda K 3 3 3 0 3 0 0 0
386 Rammalakanda M 5 > 5 0 2 0 2 0
386 Rammalakanda R 3 3 3 0 3 0 2 0
Total 25 27 31 0 14 0 9 1
388 Rammalakanda A 16 25 30 1 7 0 8 0
388 Rammalakanda B 2 5 6 0 5 0 5 0
388 Rammalakanda I 4 8 8 0 1 0 0 1
388 Rammalakanda K 3 6 6 0 5 0 0 0
388 Rammalakanda M i 8 8 0 3 0 2 0
388 Rammalakanda R 4 9 9 0 6 0 5) 0
Total 36 61 67 1 27 0 20 1
390 Ranwaragalakanda A 5) 12 15 0 2 0 2 10)
390 Ranwaragalakanda B 0 0 0 0 0 0 0 0
390 Ranwaragalakanda I 4 5 5 0 0 0 0 0
390 Ranwaragalakanda K 3 3 4 1 4 1 0 0

180

EMD Higher Rare/ _Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
390 Ranwaragalakanda M 4 4 4 0 1 0 1 0
390 Ranwaragalakanda 1 1 1 0 0 0 0 0
Total 21 25 29 1 7 1 3 0
392 Ravana Ella A 20 26 29 0 2 0 3 0
392 Ravana Ella B 0 0 0 0 0 0 0 0
392 Ravana Ella I 2! 3 3 0 0 0 0 0
392 Ravana Ella K 1 1 1 0 0 0 0 0
392 Ravana Ella M 5 5 5 0 0 0 0 0
392 Ravana Ella R 1 1 1 0 0 0 0 0
Total — 29 36 39 0 2 0 3 0
394 Rilagala A 10 11 12 0 4 0 4 0
394 Rilagala B 1 1 3 0 1 0 1 0
394 Rilagala I 2 3} 3 0 0 0 0 0
394 Rilagala K 3 3 4 0 3 0 (0) 0
394 = Rilagala M 0 0 0 0 0 0 0 0
394 Rilagala R 2 2 2 0 1 0 1 0
Total 18 20 24 0 9 0 6 0
395 Ritigala A 23 33 39 0 z, 0 2 0
395 Ritigala B 2 2 2 0 1 0 1 0
395 Ritigala I 5 8 11 0 0 0 0 0
395 Ritigala K 1 1 1 0 0 0 0 0
395 Ritigala M 7 9 10 0 4 0 4 1
“395 Ritigala R 4 6 7 0 4 0 4 0
Total 42 59 70 0 9 0 11 1
398 Ruhuna Block 1 A 23 31 36 0 1 0 1 0
398 Ruhuna Block 1 B 3 3 3 0 0 0 0 0
398 Ruhuna Block 1 I 3 4 4 0 0 0 0 0
398 Ruhuna Block 1 K 3 4 4 0 1 0 0 0
398 Ruhuna Block 1 M 13 5 16 0 1 0 5 2
398 Ruhuna Block 1 R v 12 13 2 5 1 7 1
Total 52 69 76 2} 8 1 13 3
399 Ruhuna Block 2 A 17 22 25 0 0 0 0 0
399 Ruhuna Block 2 B 0 0 0 0 0 0 0 0
399 Ruhuna Block 2 I 22 2 2 0 0 0 0 (0)
399 Ruhuna Block 2 K 3 3 3 0 1 0 0 0
399 Ruhuna Block 2 M 12 14 14 0 0 0 3 2
399 Ruhuna Block 2 R 3 5 6 0 3 0 3) 0
Total 37 46 50 (0) 4 0 6 2
400 Ruhuna Block 3 A 22 31 34 0 2 0 2 0
400 Ruhuna Block 3 B 0 0 0 0 0 0 0 0
400 Ruhuna Block 3 I 5 6 8 0 0 0 0 0
400 Ruhuna Block 3 K 4 5 10 1 6 1 0 0
400 Ruhuna Block 3 M 14 19 19 1 0 0 6 2
400 Ruhuna Block 3 R 3 di 10 1 4 0 4 0
Total 48 68 81 3 12 1 12 2
401 Ruhuna Block 4 A 11 12 13 0 1 0 1 0
401 Ruhuna Block 4 B 0 0 0 0 0 0 0 (0)
401 Ruhuna Block 4 I 5 6 8 0 0 0 0 0
401 Ruhuna Block 4 K 3 3 5 0 4 0 0 0
401 Ruhuna Block 4 M 7 8 8 0 0 0 4 2!
401 Ruhuna Block 4 R 3 4 4 0 3 0 3 0
Total 29 33 38 0 8 0 8 2
407 _— Sellankandal A 11 11 12 0 1 0 1 0
407 Sellankandal B 0 0 0 0 0 0 0 0
407 Sellankandal I 4 5 6 0 0 0 0 0
407 _ Sellankandal K 3 5 3 0 1 0 0 0
407 Sellankandal M 5 6 6 0 0 0 1 1
407 Sellankandal R 1 1 1 0 0 0 0 0
Total 24 26 28 0 2 0 2 1

181

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
410 — Sigiriya A 15 18 23 0 2 0 3 0)
410 — Sigiriya B 1 2 2 0 1 0 1 0
410 — Sigiriya I 5 9 13 1 0 0 0 0
410 — Sigiriya K 2 2 2 0 1 0 0 (0)
410 — Sigiriya M 7 7 7 0 0 0 2 1
410 — Sigiriya R 2 3 3 0 3 0 3 0
Total 32 41 50 1 7 0 9 1
414 Sinharaja A 25 37 44 1 16 0 18 2
414 — Sinharaja B 4 8 Ait 1 8 0 8 0
414 — Sinharaja I 6 9 11 1 1 0 0 1
414 Sinharaja K 5 8 15 0 14 0 0 0
414 — Sinharaja M 10 13 13 0 2 0 6 0
414 Sinharaja R 5 9 13 0 9 0 5 0
Total 55 84 107 3 50 0 37 3
426 Tangamalai A 16 20 21 0 4 0 5 1
426 Tangamalai B 1 1 4 0 2 0 2 0
426 Tangamalai I 2 3 3 0 0 0 0 0
426 Tangamalai K 1 1 ‘1 0 0 0 0 0
426 Tangamalai M 4 5 5 0 1 0 1 0
426 Tangamalai R 1 2 2 0 2 0 2) 0
Total 25 32 36 0 9 0 10 1
432 Tibbutukanda A 14 16 21 0 3 0 3 0
“432 Tibbutukanda B 2 3 3 0 2 0 2 0
432 Tibbutukanda ~ I 1 1 1 10) 0 0 0 0
432 Tibbutukanda K 3 4 4 0 4 0 0 0
432 Tibbutukanda M 2 2 2 0 0 0 0 0
432 Tibbutukanda R 3 4 4 0 2 0 3 0
Total 25 30 35 0 11 0 8 0
438 Uda Walawe A 24 29 34 0 2 0 2 0
438 Uda Walawe B 1 1 1 0 0 0 0 0
438 Uda Walawe I 4 6 10 0 0 0 0 0
438 Uda Walawe K 0 0 0 0 0 0 0 0
438 Uda Walawe M 12 14 14 0 0 0 3 1
438 Uda Walawe R 1 1 1 0 0 0 1 1
Total 42 51 60 0 2 0 6 2
442 Udawattakele A 13 17 22 0 3 0 3 0
442 Udawattakele B 1 1 1 0 1 0 1 0
442 Udawattakele I 3 3 3 0 0 0 0 0
442 Udawattakele K 0 0 0 0 0 0 0 0
442 Udawattakele M 4 4 4 0 1 0 1 0
442 Udawattakele R 1 1 1 0 1 0 1 0
Total 22 26 31 0 6 0 6 0
453 Viharekele A 9 10 13 0 4 0 4 0
453 Viharekele B 0 0 0 0 0 0 0 0
453 Viharekele I 0 0 0 0 0 0 0 0
453 Viharekele K 4 6 6 0 6 0 0 0
453 Viharekele M 3 3 3 0 0 0 0 0
453 Viharekele R 5 8 8 0 4 0 5 1
Total 21 27 30 0 14 0 9 1
455 Walankanda A 16 19 23 0 6 0 7 0
455 Walankanda B 1 2 4 0 2 0 2 0
455 Walankanda I 3 5 5 0 0 0 0 0
455 Walankanda K 3 4 5 0 5 0 0 0
455 Walankanda M 5 5 5 0 2 0 Z 0
455 Walankanda R 3 4 4 0 3 0 4 0
Total 31 39 46 0 18 0 15 0
456 Walawe Basin A 17 21 23 0 7 0 6 1
456 Walawe Basin B 1 1 0 0 0 0 0
456 Walawe Basin I 3 5 6 0 0 0 0 0

182

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
456 Walawe Basin K 2 2 2 0 1 0 0 0
456 Walawe Basin M 6 6 6 0 2 0 3 0
456 Walawe Basin R 3 3 3 0 5 0 2} (0)
Total 32 38 41 0 13 0 11 1
458 Wanniyagama A 15 20 21 0 1 0 1 0
458 Wanniyagama B 0 0 0 0 0 10) 0 0
458 Wanniyagama I 3 3 5 0 0 0 0 0
458 Wanniyagama K 2 2 2 0 1 0 0 10)
458 Wanniyagama M 9 12 12 0 1 0 3 2
458 Wanniyagama R 1 2 2 0 1 0 1 0
Total 30 39 42 0 4 0 5 2
459 Waratalgoda A 21 27 30 0 8 (0) 7 1
459 Waratalgoda B 2 2 3 0 2 0 2 0
459 Waratalgoda I 3 4 4 0 0 0 0 0
459 Waratalgoda K 2 3 6 0 6 0 0 0
459 Waratalgoda M 4 4 4 0 0 0 1 0
459 Waratalgoda R 4 8 8 0 5 0 6 0
Total 36 48 55 0 21 0 16 1
460 Wasgomuwa Lot 1 A 28 48 56 0 5 0 6 1
460 Wasgomuwa Lot 1 B 3 4 4 0 1 0 1 0
460 Wasgomuwa Lot 1 I 6 20 25 1 0 0 0 0
460 Wasgomuwa Lot 1 K 4 4 4 (0) 2 0 0 0
460 Wasgomuwa Lot 1 M 14 19 20 0 2 0 7 2
460 Wasgomuwa Lot 1 R 4 7 Gi 0 6 0 6 0
Total 59 102 116 1 16 0 20 3
463 Wedakanda A 24 31 36 0 2 0 2 0
463 Wedakanda B 1 1 2 0 1 0 1 0
463 Wedakanda I 5) 11 17 i 0 0 0 0
463 Wedakanda K 3) 3 3 0 1 0 0 0
463 Wedakanda M 8 10 10 0 0 0 2 1
463 Wedakanda R 3 5 5 0 2 0 2 0
Total 44 61 73 1 6 0 7 1
464 Wedasitikanda A 17 20 24 1 1 0 1 0
464 Wedasitikanda B 0 0 0 0 0 0 0 0
464 Wedasitikanda I 4 7 dl (0) 0 (0) 0 0
464 Wedasitikanda K 2 2 2 0 1 0 0 0
464 Wedasitikanda M 6 6 6 0 1 0 0 0
464 Wedasitikanda R 1 1 1 0 1 0 1 0
Total 30 36 40 1 4 0 2 0
471 Welihena A 12 12 13 0 3 0 3 0
471 Welihena B 0 0 0 0 0 0 0 0
471 Welihena I 1 1 1 0 0 0 0 0
471 Welihena K 0 0 0 0 0 0 0 0
471 Welihena M 3 3 3 0 0 0 0 0
471 Welihena R 2 a 3 1 1 0 0 0
Total 18 18 20 1 4 0 s) 0
476 Wewelkandura A 16 20 22 0 7 0 6 1
476 Wewelkandura B 2 2 2! 0 2 0 2 0
476 Wewelkandura I 1 1 1 0 0 0 0 0
476 Wewelkandura K 2 3 5 0 5 0 0 0
476 Wewelkandura M 5 5 5 0 1 0 2 0
476 Wewelkandura R 3 4 4 0 S| 0 2 0
Total 29 35 39 0 18 (0) 12 1
486 Yagirala A 11 12 14 0 3 0 3 0
486 Yagirala B 0 0 0 0 0 0 0 0
486 Yagirala I 3 4 4 0 0 0 0 0
486 Yagirala K 3) 4 5 0 5 0 0 0
486 Yagirala M 4 5 5 0 2 0 1 0
486 Yagirala R 2 4 5 0 2 0 B 0

183

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
fe hhc hl PS ee Ts BES
Total 23 30 33 0 12 0 7 0
487 Yagirala A 20 27 30 0 7 0 8 2
487 Yagirala B 2 4 4 0 4 0 4 0
487 Yagirala I 3 4 5 1 0 0 0 0
487 Yagirala K 3 4 5) 0 5 0 0 0
487 Yagirala M 6 8 9 0 3 0 2 0
487 Yagirala R 3 4 4 0 2 0 3 0
Total 37 51 57 1 21 0 17 2
489 Yakdessakanda A 25 38 44 0 1 0 1 0
489 Yakdessakanda B 0 0 0 0 0 0 0 0
489 Yakdessakanda I 2 4 4 0 0 0 0 0
489 Yakdessakanda K 1 1 1 0 1 0 0 0
489 Yakdessakanda M i 7 7 0 1 0 it 0
489 Yakdessakanda R 2 2 3 0 2 0 2 0
Total 37 52 59 0 5 0 4 0
497 Kalubowitiyana A 11 12 15 0 4 0 4 0
497 Kalubowitiyana B 2 3 3 0 3 0 3) 0
497 Kalubowitiyana I 2 5 6 0 1 0 0 1
497 Kalubowitiyana K 5 6 8 1 7 0 0 0)
497 Kalubowitiyana M 5 5 5 0 1 0 1 0
497 Kalubowitiyana R 2 3 3 0 2 0 1 0
Total 27 34 40 1 18 0 9 1
498 Kunulugala A 12 13 13 0 6 0 5 1
498 Kurulugala B 1 1 1 0 1 0 1 0
498 Kunulugala I 2 4 5 0 0 0 0 0
498 Kunulugala K 3 3 3 0 3 0 0 0
498 Kunulugala M 4 5 5 0 2 0 1 0
498 Kunulugala R 2 3 3 0 3 0 1 0
Total 24 29 30 0 15 0 8 1
499 Silverkanda A 11 13 16 0 5 0 6 0
499 Silverkanda B 2 2 3 0 1 0 1 0
499 Silverkanda I 1 1 1 0 0 0 0 0
499 Silverkanda K 4 4 5 0 5 0 0 0
499 Silverkanda M 6 6 6 0 1 0 2 0
499 Silverkanda R 2 3 4 0 4 10) 1 0
Total 26 29 35 0 16 0 10 0
500 Derangala A 10 14 17 0 3 0 3 0
500 Derangala B 0 0 0 0 0 0 0 0
500 Derangala I 2 3 5 0 0 0 0 0
500 Derangala K 1 1 1 0 1 0 0 0
500 Derangala M 7 7 7 0 1 0 2 0
500 Derangala R 1 2. 3 0 2 0 1 0
Total 21 27 33 0 tl 0 6 0
501 Aninkanda A 14 17 18 0 9 0 9 0
501 Aninkanda B 0 0 0 0 0 0 0 0
501 Aninkanda I 2 4 4 0) 0 0 0 0
501 Aninkanda K 1 1 1 0 1 (0) 0 0
501 Aninkanda M 7 8 8 0 2 0 3 0
501. Aninkanda R 3 3} 3 0 1 0 1 0
Total 27 33 34 0 13 0 13 0
502 Méedirigiriya Tulana A 17 20 22 0 3} 0 3 0
502 Medirigiriya Tulana B 0 0 0 0 0 0 0 0
502 Méedirigiriya Tulana I 4 6 8 0 0 0 0 0
502 Méedirigiriya Tulana K 3 4 4 0 2 0 0 0
502 Méedirigiriya Tulana M 9 10 10 0 0 0 2 1
S502. = Medirigiriya Tulana R 3 3 3 0 2 0 3 0
Total 36 43 47 0 7 0 8 1
504 Masimbula A 16 19 21 0 5) 0 5 0

184

Threatened species

EMD Higher Rare/
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
504 Masimbula B 1 1 1 0 0 0 0 0
504 Masimbula I 3 4 4 0 0 0 0 0
504 Masimbula K 1 1 1 0 1 0 0 0
504 Masimbula M 3 4 4 0 1 0 2 0
504 Masimbula R 2 2 2 0 1 0 0 0
Total 26 31 33 0 8 0 i 0
505 Tawalama A 9 12 14 0 3 0 3 0
505 Tawalama B 0 0 0 0 0 0 0 0
505 Tawalama I 2 3 3 0 0 0 0 0
505 Tawalama K 1 1 1 0 1 0 0 0
505 Tawalama M 7 8 8 0 2 0 2 1
505 Tawalama R 2 2 2 0 0 0 1 0
Total 21 26 28 0 6 0 6 1
506 Tiboruwakota A 11 13 16 0 5 0 5) 0
506 Tiboruwakota B 1 1 1 0 1 0 1 0)
506 Tiboruwakota I 2 2 2 0 0 0 0 0
506 Tiboruwakota K 4 6 7 0 7 0 0 0
506 Tiboruwakota M 5 5 5 0 1 0 2 0
506 Tiboruwakota R 2 3 3 0 3 0 2 0
Total 25 30 34 0 iy) 0 10 0
507. Homadola A 8 11 11 0 5 0 5 0
507 Homadola B 1 1 2 0 1 0 1 0
507 Homadola I 1 1 1 0 1 0 0 1
507 Homadola K 5 6 7 0 7/ 0 0 0
507 Homadola M 5 5 5 0 1 0 1 0
507 Homadola R 1 2 2 0 2 0 1 0
Total 21 26 28 0 17 0 8 1
508 Hindeinattu A 13 14 18 0 4 0 4 0
508 Hindeinattu B 0 0 0 0 0 0 0 0
508 Hindeinattu I 2 3 3 0 1 0 (0) 1
508 Hindeinattu K 4 7 7 0 7 0 0 0
508 Hindeinattu M 3 3 3 0 0 0 0 0
508 Hindeinattu R 1 1 1 0 1 0 0 0
Total 23 28 32 0 13 0 4 1
509 Auwegalakanda A 5 5 7 0 2 0 2 0
509 Auwegalakanda B 0 0 0 0 0 0 0 0
509 Auwegalakanda I 0 0 0 0 0 0 0 0
509 Auwegalakanda K 2 3 4 0 3 0 0 0
509 Auwegalakanda M 5 5 5) 0 0 0 0 0
509 Auwegalakanda R 1 1 1 0 1 0 1 0
Total 13 14 17 0 6 0 3 0
511 Bambarawana A 4 5 8 0 1 0 1 0
511 Bambarawana B 0 0 0 0 m0 0 0 0
511 Bambarawana I 2 2 2 0 1 0 0 1
511 Bambarawana K 3 4 4 0 3 0 0 0
511 Bambarawana M 3 3 3 0 0 0 0 0
511 Bambarawana R 3 3 3 0 1 0 1 0
Total 15 17 20 0 6 0 2 1
512‘ Vellihallure A 12 13 15 0 6 0 6 1
512‘ Vellihallure B 1 1 1 0 1 0 1 0
512‘ Vellihallure I 1 1 1 0 1 0 0 1
512‘ Vellihallure K 3 =| 3 0 3 0 0 0
512 Vellihallure M 4 5 5 0 1 0 2 0
512 Vellihallure R 1 1 1 0 1 0 0 0
Total 22 24 26 0 13 0 9 2
513 Batahena A 17 20 22 0 8 0 7 1
513. Batahena B 2 2 3 0 1 0 1 0
513 Batahena I 0 0 0 0 0 0 0 0
513 Batahena K 3 3 3 0 3 0 0 0

185

EMD Higher Rare/ _Threatened!species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
513 Batahena M 4 4 4 0 1 0 2 0
513. Batahena R 1 1 1 0 1 0 1 0
Total 27 30 33 0 14 0 11 1
514 Sembawatte A 10 11 13 0 5 0 5 0
514 Sembawatte B 3 3 3 0 2 0 2 0
514 Sembawatte I 1 1 1 0 0 0 0 0
514. Sembawatte K 3} 4 4 0 4 0 0 0
514 Sembawatte M 3 3 3 0 (0) 0 1 0
514 Sembawatte R 2 4 4 0 2 0 3 0)
Total 22 26 28 0 13 0 11 0
522 Knuckles A 26 42 50 0 10 0 12 2
522 Knuckles B 3 4 10 1 6 1 5 0
522 Knuckles I 4 11 16 0 0 0 0 0
522 Knuckles K 6 10 17 6 12 5 0 0
522 Knuckles M 12 17 18 1 3 0 6 0
522 Knuckles R 4 10 11 1 9 1 9 1
Total 55 94 122 9 40 7 32 3
523. Kahanda Kalapuwa A 8 8 9 0 0 0 0 0
523 Kahanda Kalapuwa B 1 1 1 0 0 0) 0 0
523. Kahanda Kalapuwa I 2 3 4 0 0 0 0 0
523 Kahanda Kalapuwa K 0 0 0 0 0 0 0 0
523. Kahanda Kalapuwa M 1 1 1 0 0 0 0 10)
523. Kahanda Kalapuwa R 0 0 0 0 0 0 0 0
Total 12 13 15 0 0 0 0 0
524 Rekawa Kalapuwa A ) 9 10 0 0 0 0 0
524 Rekawa Kalapuwa B 1 1 1 0 1 0 1 0
524 Rekawa Kalapuwa I 4 4 4 0 (0) 0 0 0
524 Rekawa Kalapuwa K 0 0 0 0 0 0 0 0
524 Rekawa Kalapuwa M 0 0 0 0 0 0 0 0
524 Rekawa Kalapuwa R 0 0 0 0 0 0 0 0
Total 14 14 15 0 1 0 1 0
525 Miyandagala A 11 11 12 0 0 0 0 0
525 Miyandagala B 0 0 0 0 0 0 0 0
525 Miyandagala I 4 6 8 0 0 0 0 0
525 Miyandagala K 1 1 1 0 0 0 0 0
525 Miyandagala M 3 3 3 0 0 0 0 0
525 Miyandagala R 0 0 0 0 0 0 0 0
Total 19 21 24 0 0 0 0 0
526 Keulakada Wewa A 13 15 19 0 0 0 0 0
526 Keulakada Wewa B 0 0 0 0 0 0 0 0
526 Keulakada Wewa I 2 3 3 0 0 0 0 0
526 Keulakada Wewa K 1 1 1 0 1 0 0 0
526 Keulakada Wewa M 6 8 8 0 0 0 1 1
526 Keulakada Wewa R 0 0 0 0 0 0 0 (0)
Total 22 27 31 0 1 0 1 1
528 Asantanakanda A 13 16 19 0 7 0 9 0
528 Asantanakanda B 2 2 2 0) 1 0 1 0
528 Asantanakanda I 3 4 4 0 0 0 0 0
528 Asantanakanda K 1 1 1 0 1 0 0 0
528 Asantanakanda M 5 5 5 0 1 0 2 0
$28 Asantanakanda R 1 2 2 0 2 0 1 0
Total 25 30 33 0 12 0 13 0
530 Appalagala A 18 24 30 0 4 0 5 0
530 Appalagala B 2 2 2 0 1 (0) 1 0
530 Appalagala I 5 12 15 0 0 0 0 0
530 Appalagala K 0 0 0 10) 0 0 0 0
530 Appalagala M 7 8 8 0 1 0 2 0
530 Appalagala R 0 0 0 0 0 0 0 0
Total 32 46 55 0 6 0 8 0

186

EMD Higher Rare/ _ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
531 Kudagoda A 20 24 30 0 4 0 5 0
531 Kudagoda B 0 0 0 0 0 0 0 0
531 Kudagoda I 2 3 5 0 0 0 0 0
531 Kudagoda K 2 2 2 1 2 1 0 0
531 Kudagoda M 6 7 7 0 1 0 0 0
531 Kudagoda R 1 1 1 0 1 0 1 0
Total 31 37 45 1 8 1 6 0
532 Talawegoda A 22 29 32 0 4 0 4 0
532 Talawegoda B 0 0 0 0 0 0 0 0
532 Talawegoda I 3 3 4 0 0 0 0 0
532 Talawegoda K 0 0 0 0 0 0 10) 0
§32 Talawegoda M a 9 9 1 2 0 1 0
532 Talawegoda R 2 3 3} 0 1 0 2 0
Total 34 44 48 1 7 0 fi 0
533 Mulgama A 19 22 26 0 2 0 2 0
533 Mulgama B 0 0 0 0 0 0 0 0
533 Mulgama I 1 1 1 0 0 0 0 0
533. Mulgama K 0 0 0 0 0 0 0 0
533 Mulgama M 6 7 7 0 1 0 1 0
533. Mulgama R 2 2 2 0 2 0 2 0
Total 28 32 36 0 5 0 5 0
534 Galleletota A 20 24 28 0 2 0 2 0
* 534 Galleletota B 0 0 0 0 0 0 0 0
534 Galleletota ~ I 5 8 8 1 0 0 0 0
534 Galleletota K 2 2 2 0 2 0 0 0
534 Galleletota M 7 8 8 0 0 0 2 1
534 Galleletota R 1 1 2 0 1 0 1 0
Total 35 43 48 1 5 0 5 1
535 Kuragala A 21 23 27 1 1 0 3 0
535 Kuragala B 0 0 0 0 0 0 0 0
535 Kuragala I 4 4 5) 0 0 0 0 0
535 Kuragala K 0 0 0 0 0 0 0 0
535 Kuragala M 7 8 8 0 1 0 1 0
535 Kuragala R 2 3 4 0 2 0 2 0
Total 34 38 44 1 4 0 6 0
536 Hapugala A 17 22 Zi 0 2 0 2 0
536 Hapugala B 1 1 1 0 0 0 0 0
536 Hapugala 1 4 8 0 0 0 0 0
536 Hapugala K 2 2 2 0 1 0 0 0
536 Hapugala M 7 8 8 0 0 0 1 0
536 Hapugala R 2 3 3 0 3 0 3 0
Total 33 43 49 0 6 0 6 0
537 Narangattahinna A 12 13 15 0 1 0 2 0
537 Narangattahinna B 0 0 0 0 0 0 0 0
537 +Narangattahinna I 5 7 2) 0 0 0 0 0
537 Narangattahinna K 1 1 1 0 0 0 0 0
537 +Narangattahinna M 4 5 5 0 1 0 0 0
537 Narangattahinna R 2 2 3 1 1 0 1 0
Total 24 28 33 1 3 0 3 0
538 Gallegodahinna A 19 25 30 0 4 0 4 0
538 Gallegodahinna B 1 1 1 0 0 0 0 0
538 Gallegodahinna I 4 5 3} 0 0 0 0 0
538 Gallegodahinna K 2 2 2 0 2 0 0 0
538 Gallegodahinna M 5 6 6 0 0 0 1 0
538 Gallegodahinna R 2 2 2 0 2 0 2 0
Total 33 41 46 0 8 0 7 0
539 Hataramune A 17 18 25 1 4 0 4 1
539 Hataramune B 0 0 0 0 0 0 0 0
539 Hataramune I 3 5 7 0 0 0 0 0

187

EMD Higher Rare/ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
539 Hataramune K 1 1 1 0 1 0 0 0
539 Hataramune M 4 4 4 0 0 0 0 0
539 Hataramune R 1 1 1 10) 1 0 1 0
Total 26 29 38 1 6 0 5 1
541 Kabarakalapatana A 8 8 8 0 4 0 3 1
541 Kabarakalapatana B 1 2 3 0 2 0 2 0
541 Kabarakalapatana I 3 3 3 0 0 0 0 0
541 Kabarakalapatana K 0 0 0 0 0 0 0 0
541 Kabarakalapatana M 3 3 3 0 1 0 2 1
541 Kabarakalapatana R 1 2 2 0 1 0 1 0
Total 16 18 19 0 8 0 8 2
544 Gorangala A 6 7 d. 0 2 0 3 0
544 Gorangala B 1 1 2 0 2 0 2 0
544 Gorangala I 0 0 0 0 0 0 0 0
544 Gorangala K 0 0 0 0 0 0 0 0
544 Gorangala M 5 5 5 0 1 0 0 0
544 Gorangala R 4 4 4 0 2 0 2 0
Total 16 17 18 0 7 0 a 0
545 Handapan Ella A 17 22 26 0 11 0 10 1
545 Handapan Ella B 3 5 8 0 4 0 4 0
545 Handapan Ella I 3 4 5 0 0 0 0 0
545 Handapan Ella K 2 4 6 0 5 0 0 0
“545 Handapan Ella M 7 7 8 0 1 0 2 1
545 Handapan Ella R 2) 2 3 0 2 0 0 0
Total 34 44 56 0 23 0 16 2
546 Gongala A 11 14 16 0 7 0 7 0
546 Gongala B 2 3 5 1 2 0 2 0
546 Gongala I 2 3 3 0 1 0 0 0
546 Gongala K 3 3 3 0 3 0) 0 0
546 Gongala M 6 a ii 0 2 0 D 0
546 Gongala R 1 1 2 0 2 0 0 0
Total 25 31 36 1 17 0 11 0
547‘ Paragala A 15 17 18 0 i; 0 8 0
547 Paragala B 1 1 1 0 1 0 1 0
547‘ Paragala I 0 0 0 0 0 0 0 0
547 Paragala K 1 2 2 0 2 0 0 0
547 Paragala M 4 5 5 0 2 0 1 0
547 Paragala R 1 3 3 0 2 0 3 0
Total 22 28 29 0 14 0 13 0
549 Alutwelawisahena A 12 12 13 0 7 0 6 1
549 Alutwelawisahena B 1 1 3 (0) 1 0 1 0
549 = Alutwelawisahena I 3 4 5 0 0 0 0 0
549 Alutwelawisahena K 3 4 4 0 4 0 0 0
549 ~Alutwelawisahena M 5) 5) 5 0 1 0 1 0
549 Alutwelawisahena R 4 5 5) 10) 4 0 3 0
Total 28 31 35 0 17 0 11 1
550 Kiribatgala A 16 21 23 0 5 0 6 0
550 Kiribatgala B 3 5 6 0 5 0 5 0
550 Kiribatgala I 1 2 2 0 1 0 0 1
550 Kiribatgala K 1 1 1 0 1 0 0 0
550 Kiribatgala M 7 7 7 0 2 0 2 0
550 Kiribatgala R 3 4 4 0 2 0 3 0
Total 31 40 43 0 16 0 16 1
551 Usgala A 12 14 15 0 4 0 5) 0
551 Usgala B 2 2 3 0 0 0 - 0 0
551 Usgala I 0 0 0 0 0 0 0 0
551 Usgala K 2, 3 3 0 3 0 0 0
551 Usgala M 2 2 2 0 0 0 0 0
551 Usgala R 3] 3 3 0 2 0 2 0

188

EMD Higher Rare/ _ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
Total 21 24 26 0 9 0 7 0
556 Chilaw Lake A 7 9 9 0 0 0 0 0
556 Chilaw Lake B 0 0 0 0 0 (0) 0 0
556 Chilaw Lake I 0 0 0 0 0 0 0 0
556 Chilaw Lake K 0 0 0 0 0 0 0 0
556 Chilaw Lake M 1 1 1 1 0 0 1 0
556 Chilaw Lake R 1 1 1 0 0 0 0 0
Total 9 11 11 1 0 0 1 0
560 Galboda A 20 25 32 0 4 0 5 0
560 Galboda B 0 0 0 0 0 0 0 0
560 Galboda I 4 6 7 0 0 0 0 0
560 Galboda K 1 1 1 0 1 0 0 0
560 Galboda M 7 8 8 0 1 0 2 1
560 Galboda R 2 2 2 0 1 0 1 0
Total 34 42 50 0 7 0 8 1
561 Opalagala A 17 19 23 0 3 0 4 0
561 Opalagala B 0 0 0 0 0 0 0 0
561 Opalagala I 1 2 3 0 0 0 0 0
561 Opalagala K 2 2 2 0 2 0 0 0
561 Opalagala M 2 2 2 0 1 0 0 0
561 Opalagala R 1 1 1 0 1 0 1 0
Total 23 26 31 0 7 0 5 0
562 Sacombe A 12 12 15 0 1 0 1 0
562 Sacombe B 1 2 2 0 1 0 1 0
562 Sacombe I 3 4 4 0 0 0 0 0
562 Sacombe K 1 1 1 0 1 0 0 0
562 Sacombe M 2 2 2 0 0 0 0 0
562 Sacombe R 2 2 2 1 2 1 2 0
Total 21 23 26 1 5 1 4 0
567 Amsawagama A 21 25 30 0 3 0 4 0
567 Amsawagama B 1 1 1 0 1 0 1 0
567 Amsawagama I 3 4 4 0 10) 0 0 0
567 Amsawagama K 0 0 0 0 0 0 0 0
567 Amsawagama M 5 5 5 0 1 0 0 0
567 Amsawagama R 2 2 2 0 0 0 1 0
Total 32 Sy) 42 0 5 0 6 0
568 Beliyakanda A 19 29 35 0 2 0 3 0
568 Beliyakanda B 1 1 1 0 0 0 0 0
568 Beliyakanda I 5 7 8 0 0 0 0 0
568 Beliyakanda K 0 0 0 0 0 0 0 0
568 Beliyakanda M 4 4 4 0 0 0 0 0
568 Beliyakanda R 1 1 1 0 0 0 0 (0)
Total 30 42 49 0 2 0 3 0
569 Etabendiwela A 12 14 18 0 1 0 1 0
569 Etabendiwela B 0 0 0 0 0 0 0 0
569 Etabendiwela I 3 4 5 0 0 0 0 0
569 Etabendiwela K | 3 3 0 Z 0 0 0
569 Etabendiwela M 3 3 3 0 1 0 0 0
569 Etabendiwela R 0 0 0 0 0 0 0 0
Total 21 24 29 0 4 0 1 0
570 = Tottawelgola A 22 29 34 0 3 0 4 0
570 Tottawelgola B 0 0 9 0 0 0 0 0
570 Tottawelgola I 5 10 11 0 0 0 0 0
570 Tottawelgola K 1 1 1 0 0 0 0 0
570 = Tottawelgola M 8 11 11 1 1 0 1 0
570 Tottawelgola R 2 3 3 0 1 0 2 0
Total 38 54 60 1 5 0 7 0
571 Gederagalpatana A 29 47 60 0 5 0 7 0

189

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
571 Gederagalpatana B 2 2 2 0 1 OF: 1 0
571 Gederagalpatana I 6 12 16 1 0 0 0 0
571 Gederagalpatana K 1 1 1 0 1 0 0 0
571 Gederagalpatana M 1 9 9 0 1 0 1 1
571 Gederagalpatana R 1 1 1 0 0 0 0 0
Total 46 72 89 1 8 0 0) 1
572 Menikdeniya A 21 28 32 0 2 0 2 0
572. Menikdeniya B 1 1 1 0 1 0 1 0
572. Menikdeniya I 5 8 10 0 0 0 0 0
572 Menikdeniya K 1 1 il 0 0 0 0 0
572 Menikdeniya M 8 9 10 1 74 0 2 0
572 Menikdeniya R 2 3 3 0 1 0 2 0
Total 38 50 57 1 6 0 7 0
573 Puswellagolla A 25 40 48 0 4 0 5 0
573 Puswellagolla B 1 1 1 0 0 0 0 0
573 Puswellagolla I 5 11 14 0 0 0 0 0
573 Puswellagolla K 4 4 4 0 2 0 0 0
573 Puswellagolla M 11 14 15 0 3 0 5) 1
573 Puswellagolla R 4 5 6 1 4 1 4 0
Total 50 75 88 1 {2} 1 14 1
574 Hiriwaduna A 21 27 33 0 2 0 2 0
574 Hiriwaduna B 0 0 0 0 0 0 0 0
574 Hiriwaduna I 5 8 9 0 0 0 0 0
574 Hiriwaduna K 0 0 0) 0 0 0 0 0
574 Hiriwaduna M 8 9 9 0 1 0 3 1
574 Hiriwaduna R 1 1 1 0 1 0 1 0
Total 35 45 52 0 4 0 6 1
575 Dewagiriya A 11 14 17 0 0 0 0 0
575 Dewagiriya B 0 0 0 0 0 0 0 0
575 Dewagiriya I 2 4 4 0 0 0 0 0
575 Dewagiriya K 0) 0 (0) 0 0 0 0 0
575 Dewagiriya M 8 10 10 0 0 0 2 2
575 Dewagiriya R 1 D 2 0 2 0 iD) 0
Total 22 30 33 0 2 (0) 4 2
576 ~—-Ulgala A 14 16 18 0 0 0 0 0
576 = Ulgala B 1 2 2 0 1 0 1 0
576 = Ulgala I 2 2 2 0 0 0 0 0
576 ~—- Ulgala K 2 2 2 0 1 0 0 0
576 = Ulgala M 7 9 9 0 1 0 0 0
576 ~—-Ulgala R 4 4 4 0 3 0 3 0
Total 30 35 37 0 6 0 4 0
577 Korathalhinna A 11 11 11 0 1 0 1 0
577‘ Korathalhinna B 1 1 1 0 0 0 0 0
577 Korathalhinna I 4 6 7 0 0 0 0 0
577 Korathalhinna K 1 2) 3 0 1 0 0 0
577 Korathalhinna M 6 6 6 0 1 0 2 0
577 Korathalhinna R 3 3 3 0 3 0 3 0
Total 26 29 31 0 6 0 6 0
579 Diggala A 18 26 29 0 2 0 3 0
579 Diggala B 0 0 0 (0) 0 0 0 0
579 Diggala I 2 3 3 0 0 0 0 0
579 Diggala K 1 1 1 0 0 0 0 0
579 Diggala M 8 8 8 0 0 0 1 1
579 Diggala R 2 3 4 0 3 0 3 0
Total 31 41 45 0 5 0 U/ 1
581 Monerakelle A 23 34 38 0 5 0 6 0
581 Monerakelle B 1 1 2 0 0 0 0 0
581 Monerakelle I 4 8 10 0 0 0 0 0
581 Monerakelle K 1 1 1 0 0 0 0 0

190

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
581 Monerakelle M 8 9 9 0 Z 0 1 0
581 Monerakelle R 3 4 5 0 4 0 4 0
Total 40 57 65 0 11 0 11 0
582 _Lolehela A 15 18 21 0 1 0 1 0
582 Lolehela B 1 1 1 0 1 0 1 0
582 Lolehela I 4 5 6 0 0 0 0 0
582 Lolehela K 1 1 1 0 0 0 0 (0)
582 Lolehela M 7 7 7 0 2 0 1 0
582 Lolehela R 3 4 4 0 8 (0) 3 0
Total 31 36 40 0 7 0 6 0
583 Velihela A 14 18 20 0 2 0 2 0
583 Velihela B 0 0 0 0 0 0 0 0
583 Velihela I 3 7 7 0 1 0 0 1
583 Velihela K 1 1 1 0 0 0 10) 0
583 Velihela M 3 3 3 0 1 0 0 0
583 Velihela R 3 4 4 0 3 0 3 0
Total 24 33 35 0 7 0 5 1
584 Gumuhela A 19 20 23 0 1 0 2 0
584 Guruhela B 0 0 0 0 0 0 0 0
584 Guruhela I S) 7 8 0 0 0 0 0
584 Guruhela K 1 1 1 0 0 0 0 0
584 Guruhela M 4 4 4 0 0 0 0 0
584 Guruhela R 3 5 6 0 5 0 4 0
Total 32 37 42 0 6 0 6 0
585 Kitulhela A 19 24 27 0 2 0 2 0
585 Kitulhela B 0 0 0 0 0 0 0 0
585 Kitulhela I 4 8 10 0 0 0 0 0
585 Kitulhela K 2 2 2 0 1 0 0 0
585 Kitulhela M 3 3 3 0 0 0 0 0
585 Kitulhela R 3 4 5 0 S) 0 4 0
Total 31 41 47 0 8 0 6 0
588 Wadinahela A 23 34 40 0 2 0 2 0
588 Wadinahela B 1 1 1 0 1 0 1 0
588 Wadinahela I 4 5 6 0 0 0 0 0
588 Wadinahela K 1 1 1 0 0 0 0 0
588 Wadinahela M 5 8 8 0 1 0 0 0
588 Wadinahela R 3 2) 3 0 2 0 2 0
Total 37 52 59 0 6 0 5 0
589 Begahapatana A 16 21 23 0 0 0 0 0
589 Begahapatana B 1 1 1 0 0 0 0 0
589 Begahapatana I 2 2 2 0 0 0 0 0
589 Begahapatana K 1 1 1 0 0 0 0 0
589 Begahapatana M 5 6 6 1 m0) 0 0 0
589 Begahapatana R 2 4 4 0 4 0 4 0
Total 27 35 37 1 4 0 4 0
590 Randeniya A 20 27 32 0 1 0 2 0
590 Randeniya B 1 1 1 0 0 0 0 0
590 Randeniya I 3 7 9 0 0 0 0 0
590 Randeniya K 1 1 1 0 0 0 0 0
590 Randeniya M 4 5) 5 0 1 0 0 0
590 Randeniya R 1 1 1 0 1 0 1 0
Total 30 42 49 0 3 0 3 0
591 Murutukanda A 21 25 28 0 1 0 3 0
591 Murutukanda B 1 1 1 0 0 0 0 0
591 Murmutukanda I 2 2 3 0 0 0 0 0
591 Murutukanda K 0 0 0 0 0 0 0 0
591 Murutukanda M 7 8 8 0 0 0 0 0
591 Munutukanda R 3 5 5 0 5 0 5 0
Total 34 41 45 0 6 0 8 0

191

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
593 Bolhindagala A 19 28 30 0 0 0 0 0
593 Bolhindagala B 0 0 0 0 0 0 0 0
593 Bolhindagala I 4 4 5 0 0 0 0 0
593 _ Bolhindagala K 1 1 0 0 0 0 0
593 Bolhindagala M 10 11 11 0 0 0 3 1
593 Bolhindagala R 2 23 2 0 1 0 1 0
Total 36 46 49 0 1 0 4 1
594 Golupitiyahela A 15 19 21 0 0 (0) 0 0
594 Golupitiyahela B 0 0 0 0 0 0 0 0
594 Golupitiyahela I 2 3 3 0 0 0 0 0
594 Golupitiyahela K 1 1 1 0 0 0 0 0
594 Golupitiyahela M 4 7 7 0 0 0 1 1
594 Golupitiyahela R 3 3 3 0 1 0 1 0
Total 28 33 35 0 1 0 2 1
595 _ Radaliwinnekota A 21 29 33 0 1 0 1 0
595 _ Radaliwinnekota B 1 1 1 0 1 0 1 0
595 Radaliwinnekota I 3 4 6 0 0 0 0 0
595 Radaliwinnekota K 1 1 1 0 0 0 0 0
595 Radaliwinnekota M 5 5 5 0 0 0 2 1
595 Radaliwinnekota R 2 2 2 0 1 0 1 0
Total 33 42 48 0 3 0 5 1
604 Viyanahela A 17 19 22 0 1 0 1 0
604 Viyanahela B 0 0 0 0 0 0 0 0
604 Viyanahela I 5 6 6 0 0 0 0 0
604 Viyanahela K 1 1 1 0 0 0 0 0
604 Viyanahela M 8 9 9 0 0 0 2 2
604 Viyanahela R 3 4 4 0 3 0 3 0
Total 34 39 42 0 4 0 6 2
608 Welanwita A 27 46 57 0 7 0 7 1
608 Welanwita B 0 0 0 0 0 0 0 0
608 Welanwita I 5 S 6 0 0 0 (0) 0
608 Welanwita K 2 2 2 0 1 0 0 0
608 Welanwita M 10 12 12 0 0 0 3 1
608 Welanwita R 3 3 4 0 8 0 2 0
Total 47 68 81 0 il 0 12 2
633. Labunommwa A 18 22 25 0 1 0 1 0
633 Labunormwa B 0 0 0 0 0 0 0 0
633. Labunormwa I 5 7 9 0 0 0 0 0
633. Labunormwa K 0 0 0 0 0 0 0 0
633 Labunoruwa M 7 9 9 0 2 0 4 22
633 Labunoruwa R 4 4 4 0 2 0 2 0
Total 34 42 47 0 5 0 7 2
634 Puliyankulama A 17 19 22 0 ‘| 0 1 0
634 Puliyankulama B 0 0 0 0 0 0 0 0
634 ~— Puliyankulama I 5 12 14 0 0 0 10) 0
634 = Puliyankulama K 0 0 0 0 0 0 0 0
634 = Puliyankulama M 7 7 7 0 0 0 2 1
634 = Puliyankulama R 2) 3 4 0 3 0 3 0
Total 31 41 47 0 4 0 6 1
635 Manawewakanda A 14 17 20 0 1 0 2 0
635 Manawewakanda B 0 0 0 0 0 0 0 0
635 | Manawewakanda I 5 10 12 0 0 0 0 0
635 Manawewakanda K 0 0 0 0 0 0 0 0
635 Manawewakanda M 9 %) 9 0 0 0 2) 1
635 Manawewakanda R 4 5 5 0 1 0 1 0
Total 32 41 46 0 2 0 5 1
636 Amiwewa A 19 25) 28 0 2 0 3 0
636 Armuwewa B 0 0 0 0 (0) 0 0 0
636 Aruwewa I 5 10 16 1 0 0 0 0

192

EMD Higher Rare/ _ Threatened species

No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
636 Ariwewa K 2 3 4 0 4 0 0 0
636 Aruwewa M 9 11 11 0 1 0 2 1
636 Aruwewa R 3 3 3 0 2 0) 2 0
Total 38 52 62 1 9 0 ei 1
640 Getalagamakanda A 13 13 17 0 1 0 1 0
640 Getalagamakanda B 1 1 1 0 1 0 1 0
640 Getalagamakanda I 4 o) 12 0 0 0 0 0
640 Getalagamakanda K 2 2 2 0 2 0 0 0
640 Getalagamakanda M 9 11 11 0 1 0 3 1
640 Getalagamakanda R 2 2} 2 0 1 0 2 0
Total 31 38 45 0 6 (0) a 1
641 Galkulama Tirrapane A 11 11 12 0 1 0 1 0
641 Galkulama Tirrapane B 0 0 0 0 0 0 0 0
641 Galkulama Tirrapane I 5 9 9 0 0 0 0 0
641 Galkulama Tirrapane K 2 2 2: 0 1 0 0 0
641 Galkulama Tirrapane M 5 7 7 0 0 0 1 0
641 Galkulama Tirrapane R 0 0 0 0 0 0 0 0
Total 23 29 30 0 2 0 2 0
645 Puliyamkulam A 12 14 15 0 1 0 1 0
645 Puliyamkulam B 0 0 0 0 0 0 0 0
645 Puliyamkulam I 3 4 5 0 0 0 10) 0
645 Puliyamkulam K 1 1 1 0 1 0 0 0
* 645 Puliyamkulam M 6 6 6 0 0 0 0 0
645 Puliyamkulam R 1 1 1 0 0 0 0 0
Total 23 26 28 0 2 0 1 0
647 Ranawekanda A 21 29 34 0 2 0 2 0
647 Ranawekanda B 0 0 0 0 0 0 0 0
647 Ranawekanda I 3 5 6 0 0 0 0 0
647 Ranawekanda K 1 1 1 0 1 0 0 0
647 Ranawekanda M 5 vi qf 0 2 0 2 1
647 Ranawekanda R 0 0 0 0 0 0 0 0
Total 30 42 48 0 5 0 4 1
650 ~~ Pallankulama A 14 18 22 0 1 0 2 0
650 Pallankulama B 0 0 0 0 0 0 0 0
650 ~~ Pallankulama I 5 9 12 0 0 0 0 0
650 ~~ Pallankulama K 1 1 1 0 1 0 0 0
650 Pallankulama M 6 8 8 0 0 0 1 1
650 Pallankulama R 0 0 0 0 0 0 0 0
Total 26 36 43 0 2 0 3 1
651 Semewa A 10 10 13 0 1 0 1 0
651 Semewa B 3 4 4 0 1 0 1 0
651 Semewa I 4 6 9 0 0 0 0 0
651 Semewa K 0 0 0 0 0 0 0 0
651 Semewa M 6 i ai 0 0 0 2 1
651 Semewa R 3 3 3} 0 2 0 2 0
Total 26 30 36 0 4 0 6 1
652 Wellamudawa A 14 15 16 0 1 0 1 0
652 Wellamudawa B 1 1 2 0 1 0 1 0
652 Wellamudawa I 4 7 11 0 0 0 0 0
652 Wellamudawa K 2 2 3 1 2 0 0 0
652 Wellamudawa M 3 4 4 0 0 0 1 1
652 Wellamudawa R 0 0 0 0 0 0 0 0
Total 24 29 36 1 4 0 3 1
653 Kokkebe A 13 15 17 0 2 0 2 0
653 Kokkebe B 0 0 0 0 0 0 0 0
653 Kokkebe I 5 7 9 0 0 0 0 0
653 Kokkebe K 3 3 3 0 2 0 0 0
653 Kokkebe M 10 12 12 0 0 0 3 2
653 Kokkebe R 3 4 4 0 2 0 2 0

193

EMD Higher Rare/ Threatened species
No. Forest name taxa Families Genera Species Rare Endemic Endemic National Global
Total 34 41 45 0 6 0 7 2
654 Arangala A 17 23 28 0 4 0 4 0
654 Arangala B 0 0 0 0 0 0 0 0
654 Arangala i 1 1 1 0 0 0 0 0
654 = Arangala K 1 1 1 0 1 0 0 0
654 Arangala M 5 5 5 0 0 0 1 0
654 = Arangala R 0 0 0 0 0 0 0 0
Total 24 30 35 0 5 0 5 0
655 Kaludiyapokuna A 26 39 46 0 2 0 3 0
655 Kaludiyapokuna B 1 1 1 0 1 0 1 (0)
655 Kaludiyapokuna I 5 9 10 0 0 0 0 0
655 Kaludiyapokuna K 1 1 1 1 1 1 0 0
655 Kaludiyapokuna M 7 9 10 0 2 0 3 1
655 Kaludiyapokuna R 3 4 4 0 1 0 1 0
Total 43 63 72 1 7 1 8 1
656 Kosgahakele A 18 22 28 0 1 0 1 0
656 Kosgahakele B 1 1 mal 0 1 0 1 0
656 Kosgahakele I 3 5 5 0 0 0 0) 0
656 Kosgahakele K 0 0 0 0 0 0 0 0
656 Kosgahakele M 7 9 9 0 2 0 2) 1
656 Kosgahakele R 1 1 1 0 1 (0) 1 0
Total 30 38 44 0 5 0 5 1
657‘ Kurulukele ~ A 17 19 21 0 2 0 2 0
657 = Kurulukele B 1 2 2 0 2 0 2 0
657. Kurulukele I 5 7 10 1 0 0 0 0
657 Kurulukele K 2 2 2 0 1 0 0 0
657 Kurulukele M 4 4 4 1 0 0 0 0
657.‘ Kurulukele R 2 2 2 0 1 0 1 0
Total 31 36 41 2 6 0 5 0
659 Wathurana A 17 20 23 0 5 0 5 0
659 Wathurana B 2 2 4 0 2) 0 2 0
659 Wathurana I 3 6 6 0 0 0 0 0
659 Wathurana K 1 1 2 0 2 0 0 0
659 Wathurana M 1 1 1 0 0 0 0 0
659 Wathurana R 2 2 2 0 2 0 1 0
Total 26 32 38 0 11 0 8 0
660 Elagamuwa A 15 18 21 0 1 0 1 0
660 Elagamuwa B 2 2 2 0 1 0 1 0
660 Elagamuwa I 4 5 8 0 0 0 0 0
660 Elagamuwa K 0 0 0 0 0 0 0 0
660 Elagamuwa M 5 6 6 0 2 0 1 0
660 Elagamuwa R 1 1 1 0 0 0 0 0
Total 27 32 38 0 4 0 3 0

194

Annex 8

SOIL/WATER CONSERVATION AND BIODIVERSITY ASSESSMENTS

The results of the soil and water conservation assessment and species diversity survey are
summarised below for units of contiguous forest. An asterisk indicates that a forest is
important for that particular attribute, important meaning that it warrants inclusion within a
minimum network of conservation forests with respect to that attribute. Units of contiguous
forest which were not included in either the soil and water conservation assessment or species
diversity survey are indicated.

Attributes are defined according to following criteria:

Soil erosion
Flood hazard
Fog interception

Woody plants

Endemic woody plants

Animals

Endemic animals

Unit of contiguous forest exceeds threshold of 300 t ha’ yr' (see
Annex 2 and Table 5.8).

Unit of contiguous forest exceeds threshold of 10 m’ s" yr! (see
Annex 4 and Table 5.8).

Unit of contiguous forest lies above 1,500 m (see Tables 5.4 and
5.8).

Unit of contiguous forest included within a minimum network of
forests necessary to conserve all woody plant species (see
Annex 7, Volume 2).

Unit of contiguous forest included within a minimum network of
forests necessary to conserve all endemic woody plant species
(see Annex 9, Volume 2).

Unit of contiguous forest included within a minimum network of
forests necessary to conserve all animal species (see Annex 8,
Volume 2).

Unit of contiguous forest included within a minimum network of
forests necessary to conserve all endemic animal species (see
Annex 10, Volume 2).

195

Forest
interception

No

Name

4] Alapalawala
Amanawala-Ampane

Ambanmukalana

567 | Amsawagama

Anaolundewa

637 | Andarawewa

527 | Angamana

654 | Arangala
554} Aruakalu
636 | Aruwewa
17 | Attavillu
509 | Auwegalakanda
597 | Badanagala
24 | Badullakele
27 | Bakinigahawela

605 | Balanagala

-28 | Bambarabotuwa (N=S5)

wn

Bambarawana
Batahena
589 | Begahapatana

568 | Beliyakanda

wn
Lo =
w

37 | Beraliya (Akuressa)

et as
Sree. | San
ee ee ne wee ee
ae ane ad
i as er
Me ane es ea
ile ee See gine
a ie a ee
ca ae ee ee ee
i ae ott Es
ae ae
cen eae
ic. ee aa I
cs Se a
nl sie eee
eo bass Seamer
ee ee eo

196

Not surveyed

Forest

Soil erosion Flood Fog
hazard interception

Zz
ry
°

*

579 | Diggala Not surveyed

586 | Diggalahela

78 | Doluwakanda

548 | Dumbara

580 | Dummalahela

Galgiriyakanda

538 | Gallegodahinna

534 | Galleletota

al

-64 | Getamalagamakanda (N =2)

112 | Gilimale-Eratne
594 | Golupitiyahela

566 | Gosgahapatana

[Gosetapaana
:
133 | Hidellana-Weralupe

138 | Horagala-Paragala

Not surveyed

i)

Not surveyed

roe)
a

wn
00

520 | Illukkanda

Inamaluwa (N=2)

197

Pood Woody plant speci
hazard
All All Endemic
eae ds 0

Kalahalla-Pallekele ( N=2)

Fog
interception

Soil erosion

Indikada Mukalana tev

147 | Ingiriya

60

497 | Kalubowitiyana

655

Kaludiyapokuna

Kalugala

170 | Kananpella

177 | Kanugollayaya

178 | Kanumuldeniya
184 | Karawita

639 | Katupotakanda

-17 | KDN (N=6)
Keeriyagolla
Kekanadura

Kelani Valley

526 | Keulakada Wewa

197 | Kikilimana

5 Kiribatgala

50
ne 2 ie en ee
cl Oe. a Ne
[ase el
(Seaver a ee
oy sas Ce
a Ra ee a 2S
es a
Cie 2 a
EME oe SS
a he oe
[eee ea |
ice ee ee | a
oa ee ee
eee a
Cis ti: a ner rs
ca er aT Te Oe a
Res Toles eae aa

198

Soil erosion Flood Fog Woody plant species
hazard interception

582 | Lolehela Not surveyed

232 | Ma Eliya Not surveyed

Madigala Not surveyed

237 | Madunagala

239 | Maduru Oya Block | Not surveyed

is)
os

Magurugoda Not surveyed

247 | Mahakanda Not surveyed

5 Mahamorakanda

99

a a
i eS
pa Te
pa
(a a a
ae a a a ee ae
tne tan
Pim | 1 | ft 1 | =

a ve PE Oey GS See
eo a ie ee ee
a a ee

| a a a oe Be
ea
ee we

Not surveyed

Not surveyed

Not surveyed

525 | Miyandagala

ne b=
rae i ee See

hazard interception

Forest Soil erosion

No | Name

306 | Namunukula

537 | Narangattahinna

318 | Neugalkanda

3

i)

7 | Ohiya

329 | Oliyagankele

33

w

Padawiya Not surveyed

638 | Pahala Mawatawewa
650 | Pallankulama Not surveyed
Palliyagodella Tulana
-34 | Panilkanda (N =2)
-36| Pedro(N=3) ~

376 | Potawa Not surveyed

645 | Puliyamkulam

634 | Puliyankulama

-57 | Puswellagolla (N=4)

595 | Radaliwinnekota

383 | Ragalla Not surveyed

aa eae
chit Sat a ae
[Ce Rs a a a ee
a a ee a ee
catia Na | onl
STs ae el ee ee ee
ay Ses ee a es
[Pare ae a
ae i ee ee |
eS eS
oe oes ae ee ee
[Se aE Sa

Tee OL Me ae

Not surveyed

Not surveyed

Tambaragalawewa

ea

570 | Tottawelgola
438 | Uda Walawe
442 | Udawattakele
576 | Ulgala

578 | Ulgala (old)
443 | Ulinduwewa
583 | Velihela

452

Victoria-Randenigala-Rantambe
453 | Viharekele
Viyanahela

5 Wadinahela

88
|
peer]

Flood
hazard

Fog
interception

201

jan | tate [an | nce

Not surveyed

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