Biodiversity indicators in national forest inventories

Biodiversity indicators in national

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

| 56

forest inventories

A.C. Newton and V. Kapos

ssessments 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-
cators 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-

Forest fragmentation [>
—as shown herein | —

central Amazonia — has
major effects on the

biodiversity of forest |

ecosystems and can
serve as one useful
indicator of forest
biodiversity status

J
>

”
Adrian C. Newton and Valerie
Kaposare respectively programme
head and advisor in the Forests
Drylands and Freshwaters Programme
of the United Nations Environment
Programme’s World Conservation
Monitoring Centre (UNEP-WCMC),
Cambridge, United Kingdom.

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

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Unasylva 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.

BIODIVERSITY INDICATORS:
POLICY CONTEXT AND INITIATIVES
The United Nations Conference on Envi-
ronment and Development (UNCED) 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 ini
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
explicitly 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

Unasylva 210, Vol. 53, 2002

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 11 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 (ITTO), 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 structure 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 al., 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 limited
by data availability 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).

FRAMEWORKS FOR THE
DEVELOPMENT OF BIODIVERSITY
INDICATORS

In order for meaningful indicators 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

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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 Environment 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 ef 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 terms “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 indicatér development, the former to

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

USE OF FOREST INVENTORIES TO
ASSESS BIODIVERSITY

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 obligations 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,
1995). Quantitative data on forest structure
from forest inventories usually take the form

of listings 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
little 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 Educational, 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
approaches.

BIODIVERSITY INDICATORS AND
NATIONAL FOREST INVENTORIES:
A PROPOSED APPROACH

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

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appropriate for use at the forest manage-
ment unit (FMU) level (Stork et al., 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,
2001). 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,

Estimates of the total
numbers and
conservation status of

forest-dependent }

species — like this
Amazonian sloth — are
important indicators of
forest biodiversity

Unasylva 210, Vol. 53, 2002

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
types;

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

* area and percentage of forests affected
by anthropogenic and natural distur-
bance;

* 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-

phisticated laboratory-based analyses
(Namkoong et al., 1996; but see Jennings
et al., 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
concer (threatened or endemic species).
These indicators clearly require data from
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.

SOdVMA

Digitized by the Internet Archive
in 2010 with funding from
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http:/Awww.archive.org/details/biodiversityindi0O2newt

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

Other indicators, such as forest fragmen-
tation and rate of forest conversion, are less
commonly 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 structure of
the canopy and size or age distribution of
trees.

V. KAPOS

Measures of forest
structure that can
contribute to
biodiversity
indicators include
canopy cover, vertical
structure of the
canopy and size or
age distribution of
trees (shown, central
Amazonia)

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
patches

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

African ITTO CIFOR CSD CBD*

General biodiversity indicator Montreal Pan- Tarapoto Dry Lepaterique Near f

European Zone Forest East Timber

Africa Asia Organization

Forest area by type, and successional stage
relative to land area Jv v v v v v v v v v v
Protected forest area by type, successional stage
and protection category relative to total forest area v Jv v v v v v v v v v v
Degree of fragmentation of forest types v v v v v v
Rate of conversion of forest cover (by type) y y
to other uses r v v v
Area and percentage of forests affected by
anthropogenic and natural disturbance. v v v v
Complexity and heterogeneity of forest structure v v v
Numbers of forest-dependent species v v v v v v v v v
Conservation status of forest-dependent species v v v v Gj v v v v v

* Refers toa ariel list of forest biodiversity indicators, published but not officially endorsed (CBD, 1997b).

Unasylva 210, Vol. 53. 2002

wr!

a 5 ee

Pa Satya iu ae

The incidence and intensity of both natu-
ral and anthropogenic disturbance can pro-
foundly influence forest structure and
composition, and therefore affect the avail-
ability 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, Gonzdlez-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 application 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 sampling design, strati-
fication and survey methods both within
forest inventory and in supplementary stud-
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 sampling 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 (Tanner, 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,

Unasylva 210, Vol. 53, 2002

spatial data concerning species distributions
or protected areas can be laid over maps of
forest cover to examine the linkages 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 structural 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.

CONCLUSIONS

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, little progress has
been made in implementing these at the lo-
cal level or in evaluating their relevance or
reliability 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

1

Forest cover of Belize
classified by spatial
integrity index, which
combines measures of
patch size, shape and
isolation (summarized
Statistically in Figure 2)

UNEP WCMC

Index of spatial integrity
i 1-Highly fragmented
2

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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 effort 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

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

Spatial integrity class?

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 future consideration will be
given to monitoring the effectiveness of
these response options and their impact on
biodiversity. The approaches outlined here
would provide an appropriate method for
evaluating such impacts on biodiversity
associated with forest ecosystems.

Wie * eos

7 8

2

Forest area of Belize
by spatial integrity
class — statistical
summary

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