Biodiversity Indicators for Policy Purposes

Several partially overlapping lists of desirable attributes of biodiversity indicators for policy purposes exist (CBD 2003a, 2003c, 2003d). An integrated list of criteria would include the following:

• Relevant to biodiversity policymaking

• Simple and easily understood

• Broadly accepted

• Scientifically credible

• Quantitative

• Normative (allowing comparison with a baseline situation and a policy target)

• Measurable in a sufficiently accurate way at an affordable cost

• Responsive to changes at policy-relevant time and space scales

• Usable for scenarios of future projections

• Allows aggregation and disaggregation between ecosystem, national, and international scales

• Usable in various composite indicators and for different purposes

To date, the bulk of the biodiversity research and media attention has been on species composition, whereas much of the policy-level justification for biodiversity conservation rests implicitly on ecosystem-level, functional attributes. This results in a mismatch between the type of information available and that needed for policy. Although all stakeholders acknowledge the variety of scales and aspects of biodiversity, in practice biodiversity indicators have focused on the species level and on a single compositional measure: species richness. Although the ecosystem approach is widely espoused, in reality measures of ecosystem diversity have seldom gone beyond statements about the areal extent of prominent ecosystem types, such as forests.

There is no single all-purpose, universally good indicator in the field of biodiversity. The challenge is to find a small set of complementary indicators (because it is apparent that one indicator will not suffice) that is simultaneously easy to grasp, widely applicable, and sensitive. The suitability of a particular indicator depends on the purpose for which it is used. Even for a specified purpose, there are generally two or three indicators that could satisfy the criteria equally well. On the other hand, once the purpose has been defined, it is possible to eliminate entire indicator categories as inappropriate. Thereafter, practical considerations may further reduce the suitable candidate indicators to two or three options. Some indicators, such as hybrid indicators that are arbitrarily weighted summations of mixtures of states, pressures, and responses, should be avoided.

Various types of biodiversity indices are applicable at different stages in the policy process. Indices that identify priority areas for conservation action, such as The Last of the Wild, Hotspots, or complementarity indices, are aimed at the planning phase and are usually calculated only once. Performance monitoring tools, repeated on a regular basis, are operational phase indicators used as early warning measures and for evaluating current and future policies.

The authors of this chapter have been involved in the development of two closely related biodiversity indices, which reflect our convictions about what type of measures are likely to meet the criteria listed in this chapter and thereby fulfill policy needs while remaining scientifically legitimate. They are the Natural Capital Index (NCI; CBD 1997a, 1997b; ten Brink 2000; CBD 2003a, 2003c) and the Biodiversity Intactness Index (BII; Scholes and Biggs 2004, 2005). In principle, both measure the deviation of abundance of a broad spectrum of species from some reference state. The NCI uses actual population estimates of a limited number of species, supplemented where necessary by statistical population models. Its disadvantage is that such comprehensive data are available only in well-studied, low-biodiversity areas. The BII is more applicable in species-rich but data-poor regions.

It uses a panel of experts to assess the impacts of various types of human actions on abundance within functional groups of species. Its disadvantage is the uncertainty associated with such judgments. The numbers produced by both indices are easy to understand and explain, and they integrate both species-level information (richness, abundance) and ecosystem-level information (area extent of ecosystems, overlaid by area extent of human activities). They are structural and compositional but can be adapted for functional views as well when applied to functional types.

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