Biodiversity indicators for national use: experience and guidance

B I N U

Biodiversity Indicators for
National Use

Experience and Guidance

Digitized by the Internet Archive
in 2010 with funding from
UNEP-WCMC, Cambridge

http://www.archive.org/details/biodiversityindi05bubb

Biodiversity Indicators for
National Use

Experience and Guidance

Philip Bubb, Martin Jenkins, Valerie Kapos

in collaboration with

Netherlands Environmental Assessment Agency

(MNP-RIVM)

ECUADOR =

Ecociencia and the Ministry of the Environment

KENYA
Kenya Wildlife Service

THE PHILIPPINES
' The Bureau of Fisheries and Aquatic Resources (BFAR) and
The Protected Areas and Wildlife Bureau (PAVWB)

UKRAINE
The Ukrainian Land and Resource Management Center (ULRMC)
The State Statistics Committee of Ukraine
The Council for Studying the Productive Forces of Ukraine of
The National Academy of Sciences of Ukraine

UNEP World Conservation
Monitoring Centre

219 Huntingdon Road

Cambridge CB3 ODL

United Kingdom

Tel: +44 (0) 1223 277314

Fax: +44 (0) 1223 277136

Email: info@unep-wemc.org
Website: www.unep-wcmc.org

THe UNEP Wortp CONSERVATION MONITORING CENTRE is the
biodiversity assessment and policy implementation arm of the
United Nations Environment Programme (UNEP), the world’s
foremost intergovernmental environmental organization. UNEP-
WCMC aims to help decision makers recognize the value of
biodiversity to people everywhere, and to apply this knowledge
to all that they do. The Centre's challenge is to transform complex
data into policy-relevant information, to build tools and systems
for analysis and integration, and to support the needs of nations
and the international community as they engage in joint
programmes of action.

UNEP-WCMC provides objective, scientifically rigorous products
and services that include ecosystem assessments, support for
implementation of environmental agreements, regional and global
biodiversity information, research on environmental threats and
impacts, and development of future scenarios for the living world.

© UNEP-WCMC 2005

Citation: Bubb, P, Jenkins, J, Kapos,V,, (2005). Biodiversity Indicators for
National Use: Experience and Guidance. UNEP-WCMC, Cambridge, UK.

URL: http://www.unep-wemc.org/resources/publications/binu

Written by Philip Bubb, Martin Jenkins and Valerie Kapos in
collaboration with MNP-RIVM and the national partners.

A Banson production
Printed in the UK by Cambridge Printers

The contents of this report do not necessarily reflect the views or
policies of the United Nations Environment Programme, the
UNEP World Conservation Monitoring Centre, or the supporting
and contributing organizations. The designations employed and the
presentations do not imply the expressions of any opinion
whatsoever on the part of these organizations concerning the legal
status of any country, territory, city or area or its authority, or
concerning the delimitation of its frontiers or boundaries.

Supporting organizations

Defra

Department for Environment Food and Rural Affairs (DEFRA)
Nobel House

17 Smith Square

London SWI P 3}R, UK

http://www.defra gov.uk/

DFID

The Department for International Development (DFID)
94 Victoria Street

London SWE SJL, UK

http://www.dfid.gov.uk/

GEF

Global Environment Facility (GEF)
GEF Secretariat

1818 H Street, NW

Washington, DC 20433, USA
http://www.gefweb.org/

The Netherlands Ministry of Foreign Affairs
The Netherlands Ministry of Foreign Affairs

PO Box 2006!

2500 EB The Hague, The Netherlands
http:/Awww.minbuza.nl/

Swiss Agency for the Environment, Forests and
Landscape

Swiss Agency for the Environment, Forests and Landscape (SAEFL)
CH-3003 Bern, Switzerland

http://www.umwelt-schweiz.ch/

UNEP

United Nations Environment Programme (UNEP)
United Nations Avenue, Gigiri

PO Box 30552, 00100

Nairobi, Kenya

http://www.unep.org/

Cover images (clockwise from top):

The first ever map of agricultural ecosystems in Ukraine was
derived by the BINU team by combining data on land use with
satellite derived landcover data. The resulting map shows that
about 70% of the national territory is in agricultural ecosystems;
Flamingo, Kenya (Emily Short/UNEP/Topham); Fuchsia sp., Andean
rainforest (W. Ferwerda); Fish farm, Philippines (Victor T.
Manausala/UNEP/Topham).

Preface

The BINU project team at

his booklet is based on the results of a
project carried out between 2002 and 2005
on biodiversity indicators for national use,
or BINU for short. The BINU project was funded
by the Global Environment Facility (GEF), UNEP,
the governments of the United Kingdom (Depart-
ment for International Development (DFID) and
Department for Environment, Food and Rural
Affairs (DEFRA)), the Netherlands (the Dutch Min-
istry of Foreign Affairs), Switzerland (the Swiss
Agency for Environment, Forests and Landscapes)
and the participating countries.

The BINU project was developed as a collab-
oration between UNEP-WCMC, the Netherlands
Environmental Assessment Agency (MNP-RIVM),
Ecociencia and the Ministry of the Environment in
Ecuador, Kenya Wildlife Service in Kenya, the Bureau
of Fisheries and Aquatic Resources (BFAR) and the
Protected Areas and Wildlife Bureau (PAVB) in the
Philippines, and the Ukrainian Land and Resource
Management Center (ULRMC), the State Statistics
Committee of Ukraine and the Council for Studying

ioe

UNEP-WCMC, Cambridge, UK in July 2003.

for National Use

Biodiversity Indicators

the Productive Forces of Ukraine of the National
Academy of Sciences of Ukraine.

More results and interim outputs of the
project can be found on the CD-ROM included
with this report. The final reports of the project
will be available in the second half of 2005.

Further information can be obtained from:
www.unep-wcmc.org/collaborations/BINU
or from

Philip Bubb,

BINU Project Co-ordinator,
UNEP-WCMC

E-mail: philip.bubb@unep-wcmc.org

Further information on the Ukraine BINU results
can be found at:
http://www.ulrmc.org.ua/services/binu/index.htm|

Further information on the Ecuador BINU results
can be found at:
http://www.socioambientalecuador.info/

UNEP-WCMC, MNP-RIVM and the national BINU
partner organisations wish to thank the many
organisations that provided financial and in-kind
support to the project, as well as the members of
the project Steering Committee for their advice.

The authors would also like to thank the co-
ordinators of the four BINU country teams — Vasyl
Prydatko in Ukraine, Anderson Koyo in Kenya,
Malki Saenz in Ecuador, and Noel Barut in the
Philippines — for their collaboration in producing
this report, as well as their commitment to
producing biodiversity indicators for the

conservation and wise management of their
country’s biodiversity. The results of each country
are the product of extensive teams involving many
types of institutions, which are acknowledged in
the national reports on the CD-ROM which
accompanies this document.

Equally, we would like to thank Ben ten Brink,
Tonnie Tekelenburg, and Mireille de Heer of the
Netherlands Environmental Assessment Agency
(MNP-RIVM) for their great contribution to all
stages of the BINU project, including this report.
The BINU project originated from a proposal by
Ben ten Brink.

4m

e

Biodiversity Indica

Introduction

n the past few decades there has been growing

understanding that human well-being’ is

fundamentally linked to the state of the
environment. One manifestation of this is the
increasing acceptance of biological diversity
(‘biodiversity’) as an important focus for human
concerns. At international level this has perhaps
been most clearly expressed by the entry into
force and continuing implementation of the
Convention on Biological Diversity (CBD).
Through this and other mechanisms, biodiversity
has become the subject of many national and
international policies and regulations.

One result of this is a growing perception of
the need for reliable ways to assess both the state
of biodiversity in countries and the effectiveness
of measures designed to help maintain it. Calls to
meet this need have been voiced in many different
arenas, particularly at international level under
the CBD. One of the earlier decisions made by
the Conference of the Parties to the CBD urged
Parties to identify indicators of biological
diversity as a high priority. It also called on Parties
to collaborate on a voluntary pilot project to
demonstrate the use of successful assessment and
indicator methodologies.

Taking this as a starting point, four country
partners, UNEP-WCMC and MNP-RIVM
designed a project on biodiversity indicators for
national use (BINU) at a workshop in Kenya in
2000, funded by the GEF. As part of the workshop
the team reviewed work on_ biodiversity
indicators to date and found that, although much
had been written about them, most of this was
from a theoretical standpoint and much of it
lacked focus and clarity. Our first endeavour was
therefore to try to ensure that everyone on the
project team had a common understanding of
what indicators were and what biodiversity might
be. In our discussion on indicators we took our
cue from other disciplines such as economics and
medicine. We decided that we could describe
indicators as: ‘measures or metrics based on
verifiable data that conveyed information about
more than just themselves’. Examples from other
disciplines included relatively simple measures
such as body temperature and retail price indices,

and more complex measures such as human
development and quality of life indices.

Our understanding of biodiversity was based in
broad terms on that given in the CBD, namely ‘the
variability among living organisms from all sources
including, inter alia, terrestrial, marine and other
aquatic ecosystems and the ecological complexes of
which they are a part; this includes diversity within
species, between species and of ecosystems’.

Having established this, the BINU team
decided that the focus of the project should be
on biodiversity indicators for use within
countries, and particularly for use at national
level. Very quickly we agreed on two fundamental
aspects of indicators:

Q They were only of any use if they addressed
questions to which someone wanted to know
the answer.

OQ They were only feasible if the data to generate
them could be obtained.

From the first of these aspects we developed
a question-led approach, in which stakeholders
were to be identified and asked what their most
important questions about biodiversity were.
Armed with these questions, the national team
would seek out relevant information from
wherever it might be found. There would then
follow an indicator development phase, in which
attempts would be made to use the information
gathered to generate indicators that would
respond in a meaningful way to questions asked
by the stakeholders. It was then intended to test
these indicators by presenting them to the
stakeholders, and to refine them further on the
basis of any feedback obtained.

Because of the complexity of the issue,
we also decided that each country partner would
concentrate on one major biome: agricultural
ecosystems in Ukraine; marine and coastal eco-
systems in the Philippines; inland waters in Kenya;
and forests in Ecuador (later expanded to include
all terrestrial ecosystems). We also agreed that
each country should have as much flexibility as
possible in deciding the best way to implement
the process.

Biodiversity Indicators for

Biodiversity indicators for national use: the process

Identify stakeholders

Identify policy
objectives & targets

Identify
key questions

Gather data
Select indicators

Calculate indicators

Present to stakeholders

Improve & develop
new indicators
and monitoring systems

While the primary aim of the project was the
development of a tested core set of indicators for
each country (and each biome), we also viewed it
as an opportunity for learning about the indicator
development and application process itself. In
particular we considered the following questions
as likely to be important:

Q How useful is the indicator approach in
communicating issues on biodiversity to a wide
range of people?

Q What are the major constraints on indicator
development?

Q What are the major constraints on indicator
uptake?

Q How helpful were conceptual frameworks in
developing useful indicators?

Q To what extent are experiences common to
the different country partners and to what
extent do they diverge?

Q How far are the same approaches applicable
at different scales and in different ecosystems?

This booklet draws on experiences gained in
implementing the BINU project to attempt to
answer some of these questions, in the hope that
this will be useful to others intending to develop
indicators of their own. For each major step in the
process, we have set out how what happened in
practice related to our original intentions and what
conclusions and recommendations we can draw
from this. We conclude with some general lessons
and pointers to the future.

ys
. BSZ
National Us« : C4

ine Brecess

Policies and targets

All countries have policies in place that have
direct or indirect impact on_ biodiversity.
Optimistically, it might be expected that these
policies would have clearly stated objectives and
explicit targets. Demonstrating progress towards
these targets should, in theory, provide a major
role for biodiversity indicators. In _ reality,
biodiversity-relevant policies are scattered
through a wide variety of sectors and many do
not include clear objectives or targets. Often
policies in different sectors are not well
coordinated and may sometimes be contradictory
or even antagonistic.

Because of the broad range of instruments
and sectors concerned, we found during the
BINU project that it was often difficult to identify
and analyse relevant policies comprehensively.
Obvious policies that were relatively accessible
included national biodiversity strategies and
action plans (NBSAP), protected areas systems
plans and endangered species legislation. Relevant
policies in natural resource management sectors
included national forest plans, fisheries policies,
water policies, land-use plans and environmental
impact legislation. Even when the relevant policies
could be found, their objectives were often
framed very generally and no mechanisms for
measuring progress were specified. In other
instances the declared indicators did not match
the policy objectives and targets.

To maximize the role of biodiversity
indicators in supporting policies, we found it
important to engage with policy makers across a
wide range of sectors, including those falling
outside the normal areas of expertise of the
indicator development team.

Involving stakeholders

There are many different groups with interests
in biodiversity. Some of these, such as government
conservation agencies, conservation-focused non-
governmental organizations (NGOs) and relevant
departments in both universities and research
institutions, are relatively obvious. Others,
including government agencies responsible for

management of natural resources and land-use
planning, agencies with an interest in rural
development and indigenous peoples groups, are
less obvious. Many groups also have an important
direct or indirect impact on biodiversity without
necessarily having a conscious interest in it, such
as those involved with road construction or
agriculture. These are potentially some of the
most important groups to reach in com-
municating information about biodiversity but are
also some of the hardest to engage with. Some
important groups may be surprising at first sight —
in Ukraine, for example, military ecologists
became engaged in the BINU process as they had
responsibility for large areas of land whose
management could have impacts on biodiversity.

We found that the indicator development
teams had varied connections with other
stakeholder groups, generally having closest links
with those whose interests were most closely
aligned with their own, usually natural resource
management agencies, conservation NGOs and
academics working in the area. It was important
that the teams made particular efforts to engage
those outside their normal spheres and that
appropriate mechanisms for engagement were
used. These varied greatly with circumstances and
depended, for example, on whether such
consultation was a common practice locally and
whether different stakeholder groups were
accustomed to engaging in discussions with each
other — under some circumstances, it was
evident that the presence of some stakeholder
groups could inhibit the frank expression of
views and concerns by others.

We also found that a major barrier to
meaningful interaction with stakeholders proved
to be the lack of common concepts and
understanding of what biodiversity is and why it
may be important. As a general rule it is evident
that consultation processes need to include
discussions of these issues from the beginning.
This is to try to ensure that stakeholders,
including members of the indicator development
team, understand each other as clearly as
possible. However, because of the multi-
dimensional nature of the term biodiversity, and

the different and sometimes irreconcilable value-
sets of each group involved, ultimate agreement
on terms and issues will never be reached.
Instead, it is more important to acknowledge that
there will be some areas where individuals and
groups will have to agree to disagree.An example
of this is the assessment of the intrinsic value of
biodiversity. Conceptual frameworks such as the
pressure-state-response framework can help to
clarify issues and provide a relatively stable
framework for discussion (see below).

Many stakeholders may not in the first
instance be clear what questions they have
regarding biodiversity-related policies and
management. They may also differ widely in their
awareness and understanding of the relationships
between biodiversity and their own interests.
Presentation of potential indicators can help to
stimulate stakeholders’ thinking and awareness of
questions that may be important to them. This
requires that teams leading the process play a
proactive role, which inevitably means that their
own values and interests are likely to come to the
fore. This is not necessarily a problem provided
that it is openly acknowledged, that teams make
every effort to respond to outside ideas, and that
it leads to fruitful results.

Identify key questions

After initial discussions regarding what is meant
by ‘biodiversity’ and what are biodiversity-related
issues (and policies), groups consulted typically
came up with a hundred or more questions
covering an enormous range of subjects. Many of
these initial questions, however, proved not to be
the kind that are amenable to being addressed
through indicators. Sometimes it was apparent
that the groups or individuals involved had a very
different understanding of what they were being
asked to do from that of the project team. This in
itself was a valuable lesson. At the very least it
showed what a complicated concept biodiversity
is and how important it is to develop tools for
communicating at least some aspects of it to non-
specialists.

It became evident that the consultation
process should be regarded, even in this initial
stage, as iterative — that is a preliminary session of
eliciting questions should lead to further
discussion and explanation, led by the project
teams, and further refinement of the questions.

Here again it is important that teams are able and
prepared to facilitate through keeping discussions
constructive and moving forward without
dominating or leading too much — there is a
tendency to tell people that they have asked the
‘wrong’ questions if the questions concerned do
not fit into the framework originally anticipated
by the project team.

Even after such a process of clarification and
refinement of questions asked, there would
typically be 50 or more questions that were
thought likely to be amenable to being addressed
by biodiversity indicators. This was generally
regarded as too large a number to be dealt with
satisfactorily under the project, and likely to be
unfeasibly large under most indicator processes.
To deal with this, some questions were prioritized
and groups of others synthesized into more
general overarching questions. High-priority
questions were generally those that were asked
by the largest number or widest range of people.
Grouping questions together was an analytical
exercise generally carried out by the core project
teams. As noted above, established conceptual
frameworks, particularly pressure-state-response
and its variants (e.g. driver-pressure-state-impact-
response), were often helpful in organizing
questions, although there was a risk of trying to
assign all the key questions to this framework
beyond the point of meaningful analysis. The GEF’s
biodiversity programme framework for assessing
the impact of conservation programmes alse
proved useful in some instances.

The synthesized questions selected proved to
be very general in most cases. All the countries
had questions about the state of biodiversity of
their focal ecosystems and what were the main
factors causing pressures on this biodiversity. The
pressure-related questions reflected the priorities
of each country and the institutions conducting
the work. For example, in Ecuador the questions
included the effects of population increase,
poverty levels and infrastructure on terrestrial
biodiversity. Identification of ownership and users
of wetlands was identified as an important issue in
Kenya. Key questions on the impacts of land-use
change on biodiversity were identified in Ecuador
and Ukraine, and later in Kenya. Questions related
to response measures included ‘What agricultural
lands could be returned to the natural state
in the near future?’ in Ukraine, and “What is
the contribution of protected areas to the

conservation of terrestrial
Ecuador.

biodiversity?’ in

It proved crucial to retain an understanding of
the specific questions underlying the general
ones, in order to ensure that the indicators
selected produced answers that are applicable to
as many as possible of the original questions.
Thus, for example, several individual questions
about trends in the status of particular
ecosystems and of individual species might be
combined into a single question on the ‘status of
biodiversity’. The indicators chosen to address
this general question could be composite indices
of species trends (see below), but strong interest
by a particular stakeholder group in trends in one
species or group (e.g. flamingos as important for
ecotourism in Kenya) meant that trends in those
individual species might be the most meaningful
indicator for addressing the general question. It
also proved important for teams to track who
asked which questions as this information is key
to subsequent effective communication of the
indicators.

Gathering data

We found in all cases that the data readily
available for answering key questions were far
from complete or ideal. However, teams who
thought outside the immediate sphere of
conservation found many additional data that
could be applied to answering biodiversity
questions in a diverse range of locations and
sources. Thus, for example, catch statistics
collected by the fisheries department in Kenya
were useful for providing information on wetland
condition while national socio-economic statistics
collected for agricultural and development
purposes proved helpful in Ecuador.

Understandably, teams found it difficult to
identify and gain access to data sets that were in
sectors outside their normal realm of expertise.
Similarly, individuals tended to think of data at the
particular spatial scales that they tended to use in
their other work. It became evident, therefore,
that creative thinking and a broad approach were
important in locating and gathering the maximum
amount of potentially useful information.
However, we also found that there was a danger
of diluting effort by being uncritical about which
data were likely to be of the greatest use. This
could be solved through constant reference to

the key questions and their component original
questions, as well as logistic and technical
considerations.

Relevant data came in many different forms,
including spatially mapped data (these days usually
in the form of digital geographic information
systems (GIS)), statistical compendia and survey
results. Statistics and survey results usually
needed to be geographically referenced in some
way to be useful.

Sometimes it was possible to make use of
existing expertise and experience, as well as data
sets per se, to generate information for building
indicators. This was especially true where ‘hard’
data were lacking but researchers and managers
had large amounts of accumulated experience of
the ecosystems and species of interest. For
example, the team from Ukraine asked a body of
experts to estimate population levels of 128
indicator species in the agricultural landscape
relative to a fixed baseline, and were able to
combine the resulting data into a single species
trend index (see below). While it is important to
track the uncertainty in these kinds of data, such
‘soft’ approaches have the additional advantage
of preserving knowledge that is often unrecorded
in any formal sense and which may disappear
as individuals move on or reach the end of
their careers.

Generating indicators

Using the available data to produce indicators
that respond to specific key questions requires a
combination of creative thinking and scientific
rigour. Creative thinking is required because the
indicators with the greatest impact are often
produced by applying and presenting data in
novel ways and by combining different kinds of
data in ways that may not seem immediately
obvious.

Creative thinking is also required in
developing methods for presenting data to non-
specialists. Scientists and technicians used to
dealing with large amounts of complex data may
find it hard to understand the problems that
non-specialists have in dealing with and under-
standing such data. Complicated graphs with a
dozen different variables on them, or densely
packed tables with rows of figures to six decimal
places are difficult even for those with some

technical expertise to interpret. For non-
specialists they are often incomprehensible, not
to say alienating.

For this reason, it is generally necessary to
simplify in order to convey useful information to a
wide audience. The art in developing indicators is
to simplify without losing scientific credibility. This
requires a thorough understanding of the concepts
being dealt with, competence in handling data and
the confidence to experiment and innovate. None
of these is straightforward, and it is important not
to underestimate the challenges in developing
robust, resonant indicators. Whatever procedures
are followed, and whatever indicators are
produced, it is of fundamental importance that they
remain scientifically defensible — many issues
related to biodiversity are contentious and may
involve conflict between different interest groups.
Indicators that are pressed into service in such
conflicts are likely to be subjected to close and
sometimes hostile scrutiny. This has occurred, for
example, with the global Living Planet Index of
WWF-World Wide Fund for Nature, which has
been attacked by those who wish to dispute that
there is any kind of global biodiversity crisis. To
counter these attacks it proved vital that the
methods used to produce it, and the underlying
data, were scientifically defensible. In general,
procedures used in indicator generation must be
transparent and testable, sources of data verifiable
and any potential weaknesses or biases
acknowledged.

Most of the indicators developed resolved
themselves into two fundamental types: map-
based or spatial indicators and graph or index-
based indicators. Map-based indicators were
often found to have considerable initial appeal, as
end-users generally find maps_ intrinsically
attractive. However, because much GIS work is
relatively new, map-based data sets often do not
exist as time series, but rather as single data
sets. These may be useful for generating
snapshots of a particular characteristic at one
point in time, but cannot demonstrate change
over time, which is one of the most important
attributes normally looked for in indicators.
However, reliable snapshot maps can be useful as
baselines against which to monitor future change

Biodiversity Indicators for National Use

— because of the rapid advance of mapping
techniques, and particularly those based on
remote sensing, it may be expected that most
map-based variables will be much more
frequently monitored in future. However, some
current GIS data sets incorporate information
gathered at different times (e.g. national forest
maps may be compilations of a number of local
maps made at very different times, extending
frequently over a period of years) and do not
therefore even show a reliable snapshot at any
one time.

The visual appeal of maps may mask the fact
that they can be hard to interpret meaningfully.
Graphs, on the other hand, particularly those
showing simple changes over time (frequently as
trend lines), are generally quite easy to interpret,
although they may be less appealing. We found
that the most effective forms of communication
often combined the two approaches.

Where data were scanty and not directly
amenable to mapping or graphing as trend lines,
other approaches were investigated. For example,
in Kenya the team looking at freshwater swamps
worked on developing scorecards as a way of
capturing information on a wide range of
variables. This generated some _ interesting
preliminary results, but also raised a number of
issues, not least that of how to combine such an
approach with other methods when trying to
present a wider picture. This remains unresolved
at present.

Although most teams tested similar
indicator approaches, we found that some were
most appropriate to particular ecosystem types.
Indicators based on mapping and measures
of extent proved most appropriate for
quantifying land cover, particularly forests
(including mangroves), and were not very helpful
for aquatic or marine systems. Indicators and
indices based on direct population measures
were most useful in open ecosystems where
population census is practical, for example birds
in wetlands and nesting sea turtles. Indirect
measures such as fish catch per unit effort were
especially helpful in aquatic systems, both marine
and freshwater.

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Biodiversity Indicators for National Use

EXAMPLES OF INDICATORS GENERATED BY NATIONAL TEAMS

The BINU teams produced a great many indicators. A few examples are presented here
to illustrate some key points in generating and presenting indicators. Further detail is
included on the CD-ROM accompanying this report. Final outputs will be available in the
second half of 2005.

Map-based indicators

Previous work in Ecuador has resulted in a valuable series of ecosystem and land use maps.

These are visually attractive and can be used in several different ways. For example, side-by-side
presentation of maps of ecosystem distribution and land use intensity allow people to identify visually
the ecosystems under pressure from intensification (Figs | and 2).

Fig |: Potential distribution of native Fig 2 Distribution of current land use (2001)
ecosystems in Ecuador in Ecuador

MEE 0=quUe himedo amazonico
{GEBE Bosque nUmedo amazénico inuncable
MMR Bosque numedo de la costa

GEE Bosque himedo montano occidental
EE Bosque himedo montano anental
(MG Bosque seco montano occidental
MBM Bosque seco monteno onental

HY Bosque seco occidental

HR Natural

_ Pastos plantados
Cultivos de ciclo corto

Arboricultura

___ Area erosionada 0 intervenida
Arroz

MY Palma africana

HM Camaroneras
Otros

| Vegetacion himeda interandina
Vegetacron seca interandina

However, the very complexity of the maps makes it difficult for users to extract much meaningful
information, and a graphical summary of statistics derived from combining the maps is likely to be
more useful. Such summaries make quantitative assessments feasible and enable users to make direct
comparisons between categories (Fig 3).

Fig 3: Percentage remaining natural area of major terrestrial ecosystem types in Ecuador

Dry interandean vegetation | 5%
Moist interandean vegetation | 21%
Coastal moist forest 27%
Western dry forest 35%
Western montane moist forest | 36%
Mangrove | 49%
Swamp | 56%
Eastern montane dry forest | 62%
Eastern montane moist forest 70%
Dry paramo 75%
Amazionian moist forest 771%
Moist paramo 82%
Seasonally flooded Amazonian moist forest 86%
Permanent snow and ice 89%

On the other hand, simplified maps may be able to convey a very clear message, particularly
where time series exist. The loss of forest cover in the catchment of lake Nakuru in Kenya is a cause
of increasing pressure on the wetland resulting from siltation and changes in the surrounding hydrology.

Fig 4: Lake Nakuru catchment basin: changes in forest cover 1930-1998

1930 1970
GH Natural forest
MO Plantation forest
8 illegal felling
1986 1998 GE Freshwater

The maps (Fig 4) are a clear way to show how these pressures have increased over time. Time series
data derived from maps can also be very useful without the accompanying map (Fig 5).

Species trend indicators
In many countries there are data on trends in the populations of species that are important because
they are of economic value, because they are culturally significant or because they have been the subject
of scientific study.
Fig 5: State of mangrove cover for all For example, the Kenya Wildlife Services and
mangrove sites in the Philippines 1918-1993 various researchers have over the decades
censused water birds on several lakes in Kenya. As
a result many time series of population estimates
(Fig 6A) are available. Though these data are too
complex in their raw form to be interpreted by
most people, they can be simplified into meaningful
indicators in different ways to answer different
questions.

Calculating a multi-species trend indicator
using the method of the Living Planet Index (6B)
provides an overview of the trend in species status
over time in these wetlands and by implication of
the trend in biodiversity status more generally.

e
£
2
=)
=
3
2
<

1918 1970 1980 1988 1993

2
4S dy Biodiversity Indicators for National Use
eS .

Fig 6A: Population trends for eight bird
species on Lake Naivasha, 1981-2000

Fig 6B: Composite index for eight bird
species on Lake Naivasha, 1981-2000

1,200

800

400

Population ('000,000)

1.0

0.5

Index

1981 1990 2000

Fig 6C: Combined Lesser Flamingo
populations on three Kenyan lakes, 1954-2003

Fig 6D: Ukraine’s changing agrobiodiversity
1950-2010

1.0

= 08

Ss

o

=} * 0.6

i 3

5 = 04

ime

2 02

1955 1969 1974 1992 1995 1997 1999 200! 2003 1950 1970 1990 2000 2010

=

However, the Kenyan team found that a different approach was more appropriate for those primarily
interested in the economic value and use of wetlands. In this case the trends in a single species key for
ecotourism, the lesser flamingo (6C) proved more meaningful.

In other circumstances where species census data are lacking, the expertise and experience of
researchers as well as conservation practitioners are a valuable source of information that can be
harnessed in semi-quantitative form to provide similar indicators. For example, in Ukraine, experts
were asked to provide estimates of the populations of species relative to a historical baseline (1950).
These estimated tends were then combined using the LPI technique to show changing agrobiodiversity

status (6D).

Indirect measures

Other sources of data also serve to provide information on the state of ecosystems and the causes

of trends within them. In this case, fisheries data on landings in the Philippines (Fig 7) show how the
magnitude of pressure on fish changes over time. Exploitation rate, the ratio of fisheries-induced
mortality to total mortality, shown here for demersal species (Fig 8) both an indication of pressure

over time and, when compared to a standard threshold value of 0.5, an instantaneous measure of species

Fig 7: Marine capture fisheries production in
the Philippines, 1970-1994

Fig 8: Average exploitation rate (E) of
marine fish in the Philippines, 1955-1995

1.0 - a Small pelagic
mam Demersal
08-

Catch (million tonnes)

1970 1975 1980 1985 1990 1995

0.6 a

= Threshold value

Exploitation rate (E)

1960 1980 1992

s Ly
Ay

Biodiversity Indicators for National Use :

status (stable or over-exploited). Assessing the relative importance Fig 9: Causes of species population change
of different causes of biodiversity change is frequently problematic. in agroecosystems in Ukraine

The Ukraine team also assessed the principal causes of the changes

in species populations. The resulting data (Fig 9) are expressed as 40

the fraction of species for which the each cause of change is the
principal one.

WB % of species affected

Measures of Response io
Many of the key questions called for indicators of how effective 0
actions are in conserving biodiversity. These were some of the most
problematic for the BINU teams to supply, but several options did
emerge in the Philippines. A very effective one came from the
statistics gathered by sea turtle protection programmes (Fig 10)
which show increases in both the number of eggs produced and the
proportion conserved over the time since the programme was
implemented.

Important indicators of effectiveness can be generated from GIS overlays of protected areas
and land cover, which were used in Ecuador to identify the degree of ecosystem conversion within
protected areas.

Combining a map of the protected areas of Ecuador, with maps of both ecosystem distribution and
land use intensity allowed the Ecuadorean team to assess the
amount of the remaining ‘natural’ area (i.e. the area neither Fig 10: Sea turtle eggs conserved or
converted nor in a mosaic in the process of conversion) included in expoited on the Philippine Turtle Islands

Ce S-- =.

ion

Land use change |
Improper nature
management
Exploitation
Habitat loss
Fragmentati
Disturbance
Factors abroad
Natural succession
Eutrophication

Lowering groundwater

the national system of protected areas.

As before, the map (Fig | 1) is attractive and informative, but a
graphical representation of this analysis may be more easily
understood (Fig 12). It shows that although approximately 25 per
cent of the country’s natural area is protected, some ecosystems are
very poorly protected. The user can grasp immediately which
ecosystems are best covered by the protected areas system in their
natural state.

200 1) Eggs conserved

| Eggs exploited

150

100

Turtle eggs ('000)

50

Fig 11: Location of continental terrestrial

protected areas in the Ecuadorean National
System of Protected Areas (SNAP) in 2003,
in relation to ecosystem status in 2001 Fig 12: Protection of remaining natural area of major
(converted, mosaic in the process of terrestrial ecosystems in Ecuador (2001!)

conversion, or natural).

Permanent snow and ice fest}

Seasonally flooded Amazonian moist forest Poi ea
Moist paramo ‘See

Eastern montane moist forest at |

Swamp CERTIONES,

Dry parame REE

Amazonian moist forest eS a
As a ee

Mangrove

Western montane moist forest EE OS OES
Coastal moist forest MMU Ra aah AT Te atl td

Moist interandean vegetation SS) es veins ea ae |
Eastern dry forest TER

Eastern montane dry forest Be Se Taisies t a]
RIL S A ET

Dry interandean vegetation

gees Natural
manees Mosaic
Converted

mmmem Proportion of ecosystem natural and proteced
Proportion of ecosystem natural and not protected
_ Proportion of ecosystem converted or mosaic

13

Biodiversity Indicators for National Use

Continued stakeholder input and review

As an integral part of the BINU project, it was
envisaged that key stakeholders would be asked to
review the indicators produced and give feedback on
which ones were the most understandable and useful
for answering their questions about biodiversity, and
therefore appropriate for supporting decision
making. A key first step was the critical review of
indicators by the teams themselves and others
directly involved in indicator development. In this
process it was important to refer both to the original
questions, remembering who asked them, and to the
synthesized key questions.

All the teams found it difficult to conduct a
wider review of the indicators within the time frame
of the initial indicator development process (two
years), which made meticulous internal review even
more important. They recognized that ultimately
they would need feedback from both the
stakeholders involved in the initial consultations and
from a broad range of end-users of the indicators.
Establishing meaningful contact with the latter group
may be more problematic than continuing to interact
with the more familiar stakeholders.

We learned that workshops may not be the best
format for this review, but that more valuable
feedback might be obtained from _ informal
interactions between members of the development
teams and single or small groups of individuals,
especially if they have been provided in advance with
indicator examples. This approach has the added
advantage of effectively marketing the indicators and
building support for them, which is vital to ensure
their uptake and continued use.

Countries also found that different groups had
greatly differing expectations of the degree to which
they expected to be involved in indicator review as an
ongoing process. In Kenya, for example, four different
general categories of stakeholder had distinct
expectations of their involvement. Local communities
and resource users were mainly interested in the end
results of the process to the extent to which these
could empower them in decision making and
resource use. Policy makers and regulators were also
mainly interested in the end results of the process, to
provide them with background information on the
state of the resource. Resource management and
research institutions, on the other hand, often
became actively involved in the _ indicator
development process, using it to build their own
capacity and understanding. Non-governmental

organizations were also often interested in the
process as much as in the end-product, seeing it as a
possible way of enhancing the participation of the
wider community in decision making.

Whatever the perspectives of different
stakeholders and end-users, it became evident that
continuing to seek guidance from them beyond the
initial stages of development is fundamental to
ensuring that the indicators are appropriate and to
promoting their uptake and continued use. This
consultation should be regarded as an ongoing,
iterative process.

Organization and sustainability

Being a relatively new subject, biodiversity indicators
require capacity and new ways of thinking that may
not exist within a single agency. We found that both
NGOs and government agencies were able to work
in successful partnerships to generate indicators, and
that such partnerships helped to resolve problems of
capacity. The need for additional capacity was not
solely in technical areas but also for some teams in
such areas as communication and writing skills.
Therefore, teams made up of several individuals with
diverse backgrounds and training were found likely
to be most effective in generating and commu-
nicating indicators.

The ways that indicator development teams
organized their work varied widely, from very
centralized work by a few individuals (Ecuador), to
work by specialized task forces focusing on particular
subsets of the ecosystem or issue (Kenya), to
outsourcing of large amounts of the work
(Philippines). Each approach was found to have its
advantages and disadvantages. A team that is limited
in numbers and scope is likely to have a more
consistent overview of the resources available and
the materials it has generated. However, it loses
some opportunities for cross-fertilization between
disciplines and for mutual motivation among team
members. There may also be less perceived incentive
for careful documentation in this case. Sub-groups
focused on subsets of the ecosystem or issue allow
energies to be concentrated on the most relevant
areas for each subset, but can then present problems
in generalizing the indicators chosen to broader
scales. Outsourcing to specialists has the advantage
of harnessing advanced skills and knowledge, but can
be difficult to manage in a coordinated fashion.
and = different

Working in partnerships

organizational configurations makes even more
important the need to document carefully the work
that is done, and especially the data that are collated.
Careful management of data and their associated
metadata is vital. Drafting a fact sheet for each
indicator is an important means of documentation to
ensure clarity and continuity in its future use. We
found that this process was also an important step in
clarifying both the design and the use of the indicator
within the team, and that the drafting process
sometimes highlighted methodological problems that
needed to be resolved.

The existence of such clear documentation is a
major factor in ensuring the uptake and sustainability
of the indicators. Involving representatives of national
statistical agencies as stakeholders early in the
indicator development process provided one
effective way to promote uptake. Both Ecuador and
Ukraine did this and report that inclusion of
biodiversity indicators in national statistical
summaries is now officially planned.

The greatest utility of the indicators will arise
from their sustained use and repeated calculation to
show trends and progress (monitoring). This
monitoring can itself foster further continuity and
raise awareness of new issues that need to be
addressed both by policy and indicators. Therefore,
the establishment of monitoring systems is vital
to ensure that subsequent biodiversity-related
decisions are based on appropriate and timely
information.

General conclusions

Concepts of biodiversity in general and biodiversity
indicators in particular are new. Certainly
biodiversity is a concept that appears to have
become ever more difficult to define as the term
itself has gained currency. With little fundamental
agreement as to what it actually means, it is not
surprising that it is hard to gain consensus on what
makes a good indicator for it.

Our way of trying to deal with this was to turn
the process round and allow a range of people to
determine what questions they wanted answered
about biodiversity, however they understood the
term. Members of the BINU teams quickiy grasped
the value of this approach. It did represent, however,
a major departure from the way most people were
accustomed to carry out their work and proved
difficult to sustain through later phases of the

process. That is, when data were being assembled and
indicators developed, it was easy to lose sight of the
key questions and those who had asked them.
Different stakeholders want indicators for different
purposes and will use them in different ways; the
scientific teams who develop indicators have to make
special efforts to understand these different needs
and uses. Identifying the users of indicators and
involving them throughout the development process
is key to ensuring both the usefulness and use of the
indicators.

Indicators could be used, for example, for raising
awareness and stimulating policy development, for
monitoring progress towards targets, or as analytic
tools for trying to understand particular processes. It
is very easy to confuse these different roles when
carrying out indicator development.

Most importantly, it became increasingly evident
that indicators were likely to be of only very limited
use to most stakeholders unless they could be
directly linked to actions — that is responses — of
some kind. The main interest, for example, of users of
renewable natural resources such as fishers was in
ensuring that their resource base was maintained
and could continue to deliver benefits to them into
the future. That is, their main concern was that
effective management should be in place. Without
an existing responsive management or policy
framework for indicators to feed into, their role will
continue to be highly compromised. Having said that,
there are examples where development of effective
indicators can itself apparently drive policy and
management decisions: in the United Kingdom, the
national adoption of an indicator based on the
population status of farmland and woodland birds
has led to the development of policies and targets
aimed at reversing declines in these, which should
ultimately lead to changed management practices on
the ground.

In the BINU process it proved difficult within the
30-month project period to develop a finely honed
suite of biodiversity indicators that were widely taken
up by stakeholder groups. Nevertheless, the project
process itself generally helped to raise the profile of
biodiversity as an issue within the country concerned,
stimulating discussion of the subject in sectors that
had previously given it little consideration. In addition,
participants in the project enhanced their individual
capacities substantially both through implementing
the process and through interacting with other teams
and international partners.

s for National Use

Overall, considerable interest in biodiversity
indicators was generated in the countries that took
part in the project. However, it was evident that,
given the generally limited resources available for

The future

he BINU project was begun at a time when

few had any understanding of what

biodiversity indicators were. We believe that
the project has shown that, even from a very basic
starting point and with limited resources, it is
possible to make great strides in the development
of biodiversity indicators in a relatively short space
of time. In all the participating countries we have
shown that there is a potential user-base for such
indicators, and that data already exist to enable at
least some useful indicators to be developed.

The international profile of biodiversity
indicators has increased considerably while the
BINU project has been in progress. Most
importantly, they are closely linked to the 2010
biodiversity target, agreed by the Parties to the
Convention on Biological Diversity at their 6th
meeting in April 2002 and by the participants at the
World Summit on Sustainable Development in the
autumn of that year. This target is to achieve, by 2010,
a significant reduction in the current rate of
biodiversity loss at global, regional and national levels.
The work done under the BINU project makes a
notable contribution to efforts to measure progress

activities related to biodiversity in these and other
developing countries, external support will still be
needed if substantial further progress is to be made.

towards the target, particularly at the national level.
There is a strong relationship between many of the
indicators developed under BINU and the list of
indicators agreed by the CBD Conference of the
Parties (in February 2004) for assessing and
communicating progress towards the 2010
biodiversity target at the global level (Table |). This
means that national and global level indicators can be
mutually reinforcing and this in turn should help
ensure that coherent messages about biodiversity
are conveyed to a wide range of audiences.

It is important therefore that momentum in
biodiversity indicator development is maintained in
the countries already involved but equally
important that as many other countries as possible
begin their own processes. Encouragingly, some
have already started out — Uganda, for example, is
beginning to use indicators of the kind discussed
above in its state of the environment reporting. The
partners in the BINU project are very keen to
share their experiences and to support other
countries’ efforts to develop biodiversity indicators
for their own national needs, including tracking
progress towards the 2010 target.

Table |: Indicators proposed by CBD COP7 for monitoring progress towards the 2010 target

Change in extent of selected biomes, ecosystems & habitats

Change in species abundance and distribution
Coverage of protected areas
Change in status of threatened species

Marine trophic index

Trends in genetic diversity of domesticated plants & animals

Water quality in inland waters
Nitrogen deposition; numbers and costs of alien invasions

Connectivity and fragmentation of ecosystems

Occurrence among BINU teams’ indicators
Ecuador Kenya _ Philippines Ukraine

Vv Vv v ¥
Vv Vv vv
vv v ¥ v
v v
v

v
* * * *

SN
SS

Health and well-being of people in biodiversity-dependent communities MA

* Other pressure indicators were developed by the BINU countries.

eD-ROM of the BINU
project interim reports

This CD-ROM presents the interim reports of the four national teams of the ‘Biodiversity Indicators for
National Use’ (or BINU for short) project, as of December 2004.The final reports will be available in the
second half of 2005.

The aims and formats of each national team’s reports vary according to the needs and audiences of their
country, as the project’s outputs are firstly for national use. The structure of the reports also reflects the
different ways in which the project was organised in each country. The CD-ROM contains an introduction
to the reports.

Biodiversity Indicators for
National Use

Experience and Guidance

This booklet gives a summary of the experience of a GEF-funded project carried out
between 2002 and 2005 on biodiversity indicators for national use, or BINU for short.
The overall aim of the project was to develop operational national-level biodiversity
indicators to support planning and decision-making in the four participating countries:
Kenya, Ecuador, Ukraine and Philippines. The project includes dissemination of the
approaches it has developed, so as to support the production of biodiversity indicators
by other countries and at global level under the CBD.

The BINU project developed a process, or series of steps, in producing biodiversity
indicators for national use. This report presents our experience and lessons learned so
far at each stage, although it is not intended to be a detailed manual on how to
undertake this work. Some examples are given of the indicators that have been
developed, and copies of interim reports of the national partners are included on the
CD-ROM with this booklet. The final results of the project will be available in the
second half of 2005.

The project*has shown that even from a very basic starting point and with limited
resources, tt is possible to make great strides in the development of biodiversity
indicators in a relatively short space of time. In all the participating countries we have
shown that there is a potential user-base for such indicators, and that data already exist
to enable at least some useful indicators to be developed. The partners in the BINU
project are very keen to share their experiences and to support other countries’
efforts to develop biodiversity indicators for their own national needs, including
reporting on the tracking of progress towards the ‘2010 biodiversity target’.

www.unep.org

United Nations Environment Programme

P.O. Box 30552, Nairobi, Ken
UNEP-WCMC Tel: +254 (0) 20 ee 3
219 Huntingdon Road, Cambridge CB3 ODL, United Kingdom Pere Sa (020 62382)

é ‘ Email: cpiinfo@unep.org
Tel: +44 (0) 1223 277314 Website; www.unep.org

Fax: +44 (0) 1223 277136
E-mail: info@unep-wemc.org
Website: www.unep-wcmc.org

February 2005