Measures of adaptation to climatic change and variability (Adaptation Metrics)

Adaptation metrics may be defined as quantitative, semi-quantitative or qualitative measures for monitoring the effectiveness of adaptation actions. Research on adaptation metrics has been very limited, despite an urgent need from diverse stakeholders ranging from governments to donor agencies to implementing organizations. Adaptation metrics are useful in several ways, as they help to (a) identify the most promising adaptation options, (b) prioritize sectors, regions and locations for adaptation funding, and (c) monitor progress in responding to the adverse impacts of climate change. Metrics are also crucial to compare adaptation efforts across countries as well as to assess compliance, especially when such countries receive adaptation funds under the international climate regime. Allocation of adaptation funds by the Adaptation Fund Board may be easier if quantitative adaptation metrics can be developed quickly.

What constitutes "effective adaptation" is highly context-dependent however. Diverse perspectives of different stakeholders on adaptation and its components make it difficult to assess the progress using a few indicators, especially at high spatial scales such as the national level. Further, there are many methodological challenges in development of adaptation metrics. There is no consensus yet on whether approaches should be deductive or inductive, locally-specific or spatially-scalable, and based on past experiences or linked to future projections. Integration of both inductive and deductive approaches may be desirable, but further research is necessary to find ways towards successful integration. Likewise, an optimal mix of qualitative and quantitative metrics is perhaps more important rather than one type of measures. Qualitative indicators may be especially useful in data-poor regions.

Participating stakeholders agreed that adaptation metrics should be policy-relevant, scalable, transferable, context-specific and comparable. Metrics should also capture the multi-dimensional nature of adaptation. As metrics applicable at one level (e.g. household) may not necessarily be relevant at other levels, caution must be exercised in using metrics of narrow scope. Metrics in the agriculture and water sectors could be complex due to complex interaction of social, economic and environmental factors. Metrics should be used to measure adaptive capacity of people as well as policies and institutions. Applying metrics in decision making has a capacity angle which needs to be considered with priority. However, metrics should not be developed hastily and an undue emphasis on metrics should not lead to administrative hurdles. Both analytical and policy challenges associated with adaptation metrics can be overcome through effective engagement of policy makers and other stakeholders in pilot testing under field conditions.

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