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Biodiversity indicators in national 
forest inventories 

Simplified variables - 
biodiversity indicators - can be 
used to draw information on 
status and trends in forest 
biodiversity from standardforest 
inventory data. 

Forest fragmentation 

—as shown here in 

central Amazonia ~ has 

major effects on the 

biodiversity of forest 

ecosystems and can 

serve as one useful 

Indicator of forest 

biodiversity status 

Adrian C. Newton and Valerie 
Kapos are respectively programme 
head and advisor in the Forests 
Drylands and Freshwaters Programme 
of the United Nations Environment 
Progr^mme'sWorld Conservation 
Monitoring Centre (UNEP-WCMC), 
Cambridge, United Kingdom. 

A. C. Newton and V. Kapos 

Assessments of forest biodiversity 
- the diversity within forest spe- 
cies, between species and of for- 
est ecosystems - are essential if forest re- 
sources are to be effectively conserved and 
sustainably managed (Hunter, 1999). As- 
sessments are needed to provide informa- 
tion necessary to support biodiversity-related 
decision-making in forest policy and man- 
agement. However, assessment of forest 
biodiversity presents a number of challenges. 
First, because of the complexity of 
biodiversity, information about it needs to 
be assembled and expressed based on sim- 
plified variables, typically in the form of in- 
dicators (Noss, 1990, 1999). Second, since 
decisions relating to forests are made at a 
variety of scales, biodiversity data and indi- 
catois need to be aggregated across differ- 
ent scales for monitoring and reporting 
purposes (Noss, 1990; Turner, 1995). 

The Global Forest Resources Assessment 
2000 (FRA 2000) incorporated some key 
indicators intended to contribute towards 
a better understanding of the status and 
trends in forest biological diversity, spe- 
cifically relating to the naturalness, pro- 
tection status and fragmentation of forest 
ecosystems. In addition to estimates of for- 

est area and changes in forest cover, FRA 
2000 provided statistics on the proportion 
of forest area incorporated within pro- 
tected areas, the distribution of forest area 
by ecological zone and the number of en- 
demic and threatened species for seven 
species groups. This information provides 
a useful basis for monitoring future 
changes in the status of forest ecosystems 
and associated biodiversity. However, the 
conclusions to the assessment highlighted 
the need to monitor not only forest quan- 
tity, but also forest quality, and suggested 
that future action focus on the further de- 
velopment, testing and implementation of 
indicators related to commonly agreed 
criteria for sustainable forest management 
(FAO, 2001c). 

This article explores how future global 
forest assessments might provide more 
detailed information on status and trends 
in forest biodiversity, specifically through 
the use of indicators. Such indicators should 
be appropriate for use at the local scale, 
but should provide information that can be 
readily aggregated at larger scales (FAO, 
2001c). To ensure that future assessments 
are practicable, they should, as far as pos- 
sible, employ indicators of biodiversity that 

Unasytia 210, Vol 53. 2002 

can be drawn from data collected by stand- 
ard forest inventories. In addition, the pro- 
posed indicators should build on the many 
international initiatives that have attempted 
to develop forest biodiversity indicators in 
recent years. The article first provides an 
overview of these initiatives, with reference 
to their policy context. It then considers the 
various frameworks proposed for indicator 
development and selection. Finally, it ex- 
amines the application of forest inventory 
data to such indicators. 


The United Nations Conference on Envi- 
ronment and Development fUNCED) in 
1992 recognized the need to develop indi- 
cators to enable countries to make informed 
decisions regarding sustainable develop- 
ment (Chapter 40 of Agenda 21). During 
the decade following UNCED, many inr- 
tiatives, including an initiative of the UN 
Commission on Sustainable Development 
(CSD), have sought to identify indicators 
of sustainable development. Relatively few 
of the indicators presented by CSD relate 
exphcitly to forest biodiversity, but relevant 
ones include forest area as percentage of 
land area, area of selected key ecosystems 
and protected area as percentage of total 
area (CSD, 2001). 

The Convention on Biological Diversity 
(CBD) provides a more explicit policy 
context for indicators of biodiversity. Ar- 
ticle 7 of the convention requires parties 
to identify and monitor "components of 
biological diversity important for its con- 
servation and sustainable use" and to iden- 
tify processes or activities likely to have 
adverse effects on biodiversity. The text 
of the convention also recognizes the role 
of indicators in assisting parties with moni- 
toring the status of biodiversity and the 
effects of measures taken for its conserva- 
tion and sustainable use. To date, CBD has 
sought to encourage parties and govern- 
ments to identify appropriate biodiversity 

indicators for use in managing biological 
diversity at the local and national levels 
and in assessing implementation of the 
convention, and to increase regional co- 
operation and capacity-building for the 
development and use of such indicators 
(CBD, 2001). Decisions of the Confer- 
ences of the Parties have emphasized the 
need to adopt an ecosystem approach in 
indicator development. Proposals have 
also been made for a core set of 
biodiversity indicators suitable for use by 
parties in compiling their national reports 
and in evaluating the effectiveness of 
measures taken (CBD, 1997a). Indicators 
specifically relating to forest biodiversity 
have also been proposed (CBD, 1997b). 

Chapter 1 1 of Agenda 21 and the so-called 
"Forest Principles" call for the identifica- 
tion of criteria and indicators for evaluat- 
ing progress in national efforts to practice 
sustainable forest management. As a result, 
a large number of national, regional and 
international initiatives have been devel- 
oped, including the International Tropical 
Timber Organization (ll'lO), Pan-Euro- 
pean (or "Helsinki"), Montreal, Tarapoto, 
Lepaterique, Near East, Dry Zone Asia and 
Dry Zone Africa processes, which have 
each generated sets of criteria and indica- 
tors (Grayson and Maynard, 1997; FAO, 
2001a). Currently, about 150 countries are 
participating in these processes (FAO, 
2001b). While the different processes share 
similar objectives and overall approach, 
they differ in structvire and specific content 
(FAO, 2001b). However, all of the ten ma- 
jor processes have identified the conserva- 
tion of forest biological diversity among the 
criteria for sustainability, and many of the 
numerous indicators that relate specifically 
to the biodiversity criterion are common to 
more than one process (CBD, 1997b). 

A series of field evaluations of criteria and 
indicators undertaken by the Center for In- 
ternational Forestry Research (CIFOR) in 
a number of different countries indicated 
that most, if not all, of the proposed criteria 

and indicators relating to biodiversity for 
use at the local level were in some sense 
deficient (Prabhu et ai, 1996). In particu- 
lar, most of the criteria and indicators ad- 
dressed compliance with good forest 
stewardship rather than direct assessment 
of the impacts of forest management on 
biodiversity. The study acknowledged that 
such direct assessment is costly, is Umited 
by data availabihty and is rarely part of 
forest management practices. It also rec- 
ognized the importance of establishing 
clear links between forest management and 
biodiversity maintenance before indicators 
based on management processes can be 
accepted as appropriate proxies for meas- 
urement of management impacts on 
biodiversity. In response, CIFOR proposed 
a preliminary list of indicators that could 
be used to evaluate these impacts, together 
with a practical framework for applying 
biodiversity criteria and indicators in field 
situations (Stork et al, 1997). 


In order for meaningful mdicators to be 
developed, some form of framework or 
conceptual model is required (Holdgate, 
1996) that makes explicit both definitions 
and the relationships among the phenom- 
ena of interest and the indicators. The most 
widely used is the "pressure-state-re- 
sponse" (PSR) framework, which was de- 
veloped by the Organisation for Economic 
Co-operation and Development (OECD, 
1993) on the basis of the "stress-response" 
model developed by Friend and Rapport 
(1979). The PSR framework states that 
human activities (such as clearance of for- 
est for agriculture) exert pressures on the 
environment, which can induce changes in 
the state of the environment (for example, 
the extent of forest cover). Society may then 
respond to changes in pressures or state 
with policies and programmes intended to 
prevent, reduce or mitigate pressures and 

UtusylvB 210. Vol- 53. 2002 

thereby reduce environmental damage. In- 
dicators provide tools for elucidating PSR 
relationships, both at the reporting stage and 
during policy analysis. 

The PSR framework has been widely ap- 
plied to indicator development; for exam- 
ple, it is explicitly recognized by CBD 
(CBD, 1997a). CSD has used a variant of 
this approach, namely the "driving force- 
state-response" (DSR) framework (CSD, 
2001 ). This framework uses the term "driv- 
ing force" instead of "pressure" to accom- 
modate social, economic and institutional 
indicators more accurately and to acknowl- 
edge that their impact on sustainable devel- 
opment may be both positive and negative. 
The European Envirorunent Agency (EEA, 
1998) further expanded the PSR scheme to 
include drivers and impacts, forming the 
DPSIR framework. 

A number of other indicator frameworks 
have been proposed. Hyman and Leibowitz 
(2001) suggested that a conceptual model 
based on ecological principles could make 
it possible to evaluate the relationships be- 
tween proposed indicators and assessment 
"endpoints", such as biodiversity. Noss 
(1990) presents a hierarchical framework 
for development of biodiversity indicators, 
recognizing that three attributes of 
biodiversity - composition, structure and 
function - can be considered at a number 
of different scales or levels of organization. 
The framework of Stork et al. (1997) is 
based on a conceptual model of the rela- 
tionship between anthropogenic activities 
affecting forests and the processes that in- 
fluence biodiversity. 

Research in this area has been character- 
ized by a high degree of confusion in the 
terminology adopted and uncertainty about 
which methods are the most appropriate. 
For example, the tertns "framework" and 
"conceptual model" are often used inter- 
changeably. The authors support the sug- 
gestion of Boyle (1998) that a conceptual 
model and a framework are both required 
for indicatbr development, the former to 

defme the relationship between the indica- 
tor and the endpoint, and the latter to cat- 
egorize the variables and defme which are 
appropriate for assessment. 


The many approaches for assessing 
biodiversity (Groombridge and Jenkins, 
1996; Jermy et al.. 1995; Heywood, 1995; 
Beattie, Majer and Oliver, 1993) vary with 
respect to sampling intensity and require- 
ment for taxonomic expertise, and therefore 
cost. Where the aim is explicitly to address 
changes over time, methods are required 
that are repeatable and that can provide 
comparable results between sampling 
events. As resources are often limiting, ap- 
proaches need to be as efficient and cost 
effective as possible so that they can be sus- 
tained over time. 

Biodiversity assessments should be inte- 
grated with inventories of other variables 
carried out to provide the information re- 
quired for future global forest assessments 
(which will address other characteristics such 
as biophysical status and development of 
forests, forest use and benefits derived from 
forests) (FAO, 2001c). Biodiversity assess- 
ment should also be undertaken in a manner 
that ensures accordance with the criteria and 
indicators processes with which a particular 
country is affiliated, together with interna- 
tional reporting obUgations such as those of 
CBD and CSD. 

Forest inventories and biodiversity survey 
methodologies are similar in many ways, 
but also have a number of differences 
(Vanclay, 1998). Methods of forest inven- 
tory have principally been developed for 
estimating the standing volume of wood in 
forests and for monitoring changes in stand 
structure and growth with time. They do not 
generally incorporate measures of other 
ecosystem components such as animals or 
non-woody plants (Burley and Gauld, 
1 995). Quantitative data on forest structure 
from forest inventories usually take the form 

of hstings of individual trees with diameter 
(and sometimes height) measurements, or 
of total numbers of trees in each diameter 
class. Unfortunately, many traditional for- 
est inventories focus so strongly on the po- 
tential for timber harvest that they provide 
Uttle or no information on the smaller trees 
or their spatial distribution. 

In recent years, there has been an increas- 
ing effort to establish temporary and/or per- 
manent sample plots explicitly for the 
purposes of biodiversity assessment in for- 
ests. For example, in 1986, the United Na- 
tions Eiducational, Scientific and Cultural 
Organization (UNESCO) Man and the Bio- 
sphere Programme (MAB) and the 
Smithsonian Institution began a joint ini- 
tiative to establish a global network of for- 
est areas under different management 
regimes, together with protocols for 
biodiversity monitoring. These protocols 
have been adopted at nearly 200 research 
sites in 23 countries (Dallmeier and 
Comiskey, 1998). 

In many countries, however, forest inven- 
tories are inadequate or entirely lacking. In 
addition, a study by Kapos and Jenkins 
(2002) indicated that existing forest inven- 
tories, surveys or networks of permanent 
plots are often inadequate to provide a rep- 
resentative assessment of forest bio- 
diversity. Biodiversity assessment will 
therefore often require the design and im- 
plementation of an appropriate inventory 
system. The following section suggests how 
such an inventory might be designed and 
implemented in practice, focusing on the 
use of biodiversity indicators proposed by 
existing criteria and indicators processes in 
conjunction with standard forest inventory 


Most of the forest biodiversity indicators 
that have been proposed to date have been 
developed for the national level and are not 

Unasylva 210. Vol 53. 2002 

appropriate for use at the forest manage- 
ment unit (FMU) level (Stork etai. 1997). 
Although national-level indicators are re- 
quired for the development and updating 
of national and international policy instru- 
ments (Castafieda, 2001), some important 
changes in biodiversity can only be de- 
tected at the local scale. Data collected 
within the FMU can potentially be aggre- 
gated or extrapolated to a larger scale to 
assist with reporting at the national or re- 
gional level (Raison, Flinn and Brown. 
200 1 ). Trends in indicators observed at the 
FMU level could be used to adjust forest 
management approaches to ensure that na- 
tional goals are met. 

Selection of indicators 

The selection of indicators for use in any 
particular assessment will depend on the 
precise objectives of the assessment (which 
must be clearly defined) and on the frame- 
work for indicator development that has 
been adopted. In addition, the relationship 
between selected indicators and endpoints 
should be analysed using appropriate sta- 
tistical approaches (Hyman and Leibowitz, 

2001). Many indicators of forest 
biodiversity have been poorly tested and 
require rigorous validation in order to be 
interpreted with confidence (Noss, 1999). 
Existing and proposed biodiversity indi- 
cators that are appropriate for implementa- 
tion at the FMU level can be divided into 
eight general groups: 

• forest area by type, and successional 
stage relative to land area; 

• protected forest area by type, succes- 
sional stage and protection category 
relative to total forest area; 

• degree of fragmentation of forest 

• rate of conversion of forest cover (by 
type) to other uses; 

• area and percentage of forests affected 
by anthropogenic and natural distur- 

• complexity and heterogeneity of for- 
est structure; 

• numbers of forest-dependent species; 

• conservation status of forest depend- 
ent species. 

Indicators of genetic variation are not con- 
sidered here, as they generally require so- 

Estimates of the total 

numbers and 

conservation status of 


species - lilte this 

Amazonian sloth - are 

Important indicators of 

forest biodiversity 

phisticated laboratory-based analyses 
(Namkoong et al, 1996; but see Jennings 
c/ a/., 2001). 

Some indicators, such as area of different 
forest types and protected forest area, are 
common to all of the criteria and indicator 
processes and international reporting obli- 
gations (see Table). They tend to require 
both spatial data on forest cover and ground- 
based inventory data, which help to define 
forest types. These data can then be com- 
bined with mapped data on protected areas 
and their management status (Iremonger, 
Ravilious and Quinton, 1997). 

Most processes also include indicators 
relating to forest composition, principally 
in terms of species richness and the pres- 
ence of species of particular conservation 
concern (threatened or endemic species). 
These indicators clearly require data fi-om 
forest inventory and other survey types to 
generate species lists, which can be cross- 
referenced to national and international as- 
sessments of species status such as Red 
Lists and the appendices to the Convention 
on International Trade in Endangered Spe- 
cies of Wild Fauna and Flora (CITES) (e.g. 

Unasylva 210. Vol 53.2002 

Digitized by tine Internet Arciiive 

in 2010 witii funding from 

UNEP-WCIVIC, Cambridge 

Indicators relating to 
forest fragmentation 
require spatial data on 
forest cover at the 
landscape scale and 
can include measures 
of the size, shape and 
connectivity of forest 

Dallmeier and Comiskey, 1998b; Vanclay, 
1998; Hawthorne and Juam Musah, 1993). 

Other indicators, such as forest fragmen- 
tation and rate of forest conversion, are less 
conunonly included, while forest structure 
and area affected by disturbance are recog- 
nized by few of the processes. Indicators 
relating to forest fragmentation require spa- 
tial data on forest cover at the landscape scale 
and can include measures of the size, shape 
and connectivity of forest patches, or indi- 
ces that combine these attributes (e.g. Kapos, 
Lysenko and Lesslie, 2000). 

Structural characteristics of forest stands 
are relatively easy to assess (Ferris-Kaan. 
Peace and Humphrey, 1998; Boyle and 
Sayer, 1995) and are of fundamental im- 
portance for biodiversity (Noss, 1990, 1999; 
Ferris and Humphrey 1999). Forest stands 
tend to be structurally heterogeneous, both 
vertically and horizontally; structural com- 
plexity may determine habitat availability 
and may thus influence diversity of plant, 
animal and microbial communities (Ferris 
and Humphrey, 1999). Measures of forest 
structure that can contribute to indicators 
include canopy cover, vertical sUTJCture of 
the canopy and size or age distribution of 

Inclusion of biodiversity indicators in sets of indicators developed by international criteria and indicators processes, international 
organizations and the Convention on Biological Diversity 

Measures of forest 

structure that can 

contribute to 


indicators include 

canopy cover, vertical 

structure of the 

canopy and size or 

age distribution of 

trees (shown, central 


General biodivereity indicator 

Montreal Pan- Tarapolo Dry 

European Zone 


Dry Lepaterique Near African ITTO CIFOR 
Forest East Timber 

Asia Organization 

Forest area fay type, and successional stage 
relative to land area 

Protected forest area by type, successional stage 
and protection category relative to total forest area 

Degree of fragmentation of forest types 
Rate of conversion of forest cover (by type) 
to ottier uses 

Area and percentage of forests affected by 
antfiropogenic and natural disturbance. 

Complexity and heterogeneity of forest structure 

Numbers of forest-dependent species 

ConsefvaSon status of forest-dependent species 

















































' Refers to a provisional list of forest biodiversity indicators, published but not officially endorsed {CBD. 1997b). 

UnasyIva210.Vol 53.2002 

The incidence and intensity of both natu- 
ral and antliropogenic disturbance can pro- 
foundly influence forest structure and 
composition, and therefore affect the avail- 
abiUty of habitat for different groups of or- 
ganisms. Disturbances may be caused by 
small-scale processes such as the senes- 
cence and death of individual trees, or large- 
scale processes such as hurricanes or fire. 
Assessing disturbance can be difficult, how- 
ever; indicators of disturbance may need to 
be developed or adapted at the local level 
according to the characteristics of the site 
(Ramirez-Marcial, Gonzalez-Espinosa and 
Williams-Linera, 2001). 

Methods of assessment and analysis 

The data required for the biodiversity indi- 
cators considered here can largely be pro- 
vided through traditional forest inventory 
approaches, supported by the apphcation of 
remote sensing and geographic information 
system (GIS) technologies. In some cases, 
additional field survey techniques may be 
needed to inventory taxa not usually in- 
cluded in forest inventory. Careful attention 
needs to be paid to samphng design, strati- 
fication and survey methods both within 
forest inventory and in supplementary smd- 
ies (Dallmeier and Comiskey, 1998a; 
Bachmann, Kohl and Paivinen, 1998; Boyle 
and Boontawee, 1995;Vanclay, 1998). Re- 
mote-sensing images can provide a basis 
for stratifying field samphng efforts as well 
as for mapping distributions of species that 
are closely associated with distinctive veg- 
etation types. Although it may provide in- 
dications of ecosystem-level diversity as 
indicated by spatial distribution of differ- 
ent vegetation types, remote sensing can- 
not yet provide direct information on 
species-level diversity (Taimer, Kapos and 
Adams, 1998). Remote sensing and GIS can 
be used both to generate spatial data, for 
example on forest cover distribution, and 
to extrapolate the results of intensive ground 
studies. GIS can also be used to combine 
data from a range of sources; for example, 

spatial data concerning species distributions 
or protected areas can be laid over maps of 
forest cover to examine the Unkages be- 
tween them. 

Appropriate summary and presentation of 
data are also critical in the effective use of 
indicators. To aggregate results of forest 
inventory at the local scale for reporting at 
the national scale, and to monitor change 
over time, data can be summarized by cat- 
egories and presented in relation to forest 
area. For example, forest fragmentation as 
evaluated by an index of spatial integrity 
can be expressed as forest area belonging 
to each class of spatial integrity (see Fig- 
ures 1 and 2). A country might characterize 
the strucmral complexity of its forest re- 
sources in terms of the total area of forest 
within different classes of canopy openness, 
crown depth or numbers of canopy layers. 
Species richness could similarly be pre- 
sented as the area of forest possessing more 
than a certain number of tree species per 

unit area or per 1 000 individual trees. Such 
categories could be expressed in qualitative 
terms determined according to local or na- 
tional conditions. For example, disturbance 
classes of high, medium or low timber ex- 
traction could be defined based on the fre- 
quency of cut stumps encountered in 
inventory plots. 


A considerable effort has been devoted to 
the development of indicators for sustain- 
able forest management in recent years, and 
many of these indicators are related to for- 
est biodiversity. However, Uttle progress has 
been made in implementing these at the lo- 
cal level or in evaluating their relevance or 
reUabihty as a basis for decision-making. 
Future research and the development of con- 
ceptual models concerning the processes 
influencing forest biodiversity are likely to 
generate new insights about the relationships 
between indicators and the variables or 

Forest cover of Belize 

classified by spatial 

integrity index, which 

combines measures of 

patch size, shape and 

isolation (summarized 

statistically in Figure 2) 

M 40 CO 

^---X. ^ 

tndex of spatial Integrity 

■ 1 -Highly fragmented 

■ 2 

m 3 

@ 4 

ES 5 

□ 6 


□ 8 

□ 9 

■ io-Mign spatial integrity 

Uoasflva 210, Vol. 33. 2002 

7 000 

6 GOO 

5 000 

4 000 

S 3000 

2 000 

1 000 

4 5 6 

Spatial integrity class'' 

8 9 10 

■1 = lowest or most fragmented. 10 = core forest in large expanses. 

Forest area of Belize 
by spatial integrity 
class - statistical 

processes of interest and about the uncer- 
tainty surrounding these relationships. 

A variety of different frameworks are 
available for the development and imple- 
mentation of biodiversity indicators. Al- 
though some of these (notably the 
pressure-state-response framework) are 
now in widespread use, future research is 
likely to produce more refined methods of 
structuring and organizing indicators. In 
particular, there is a need to develop practi- 
cal tools that can assist in the development 
and application of biodiversity indicators, 
based on such frameworks. The provision 
of such tools, together with a programme 
of capacity building, would help increase 
the use of indicators among decision- 
makers and would improve the quality' of 
environmental monitoring. To date, despite 
the international effprt focusing on indica- 
tor development, such indicators have only 
rarely been implemented in a practical way 
to inform policy development or manage- 
ment interventions. 

The eight general indicators for forest 
biodiversity identified in this article are 

consistent with those developed by criteria 
and indicators processes but are amenable 
to practical implementation at the local 
level. It may be necessary to adapt each of 
these indicators to local circumstances and 
forest characteristics. Methodologies for 
assessing these variables are available and 
could be implemented at relatively low cost 
through integration with standard forest in- 
ventory approaches. 

Aggregating information collected at the 
local scale for the purposes of national-level 
assessment and reporting to international 
processes and conventions can be achieved 
by summarizing data in categorical forms 
and combining them in relation to forest 
area. While reports to CBD have so far fo- 
cused principally on response measures 
undertaken by parties to the convention, it 
is likely that in fijture consideration wUl be 
given to monitoring the effectiveness of 
these response options and their impact on 
biodiversity. The approaches outhned here 
would provide an appropriate method for 
evaluating such impacts on biodiversity 
associated with forest ecosystems. ♦ 



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