Scaling up ecosystem benefits - a contribution to the economics of ecosystems and biodiversity (TEEB) study


Courtesy of European Environment Agency (EEA)


At the 2007 meeting of the environment ministers of the G8+5 in Potsdam, Germany, the European Commission launched The Economics of Ecosystems and Biodiversity (TEEB) study. Its aim is to assess the economic repercussions of global  biodiversity loss.

TEEB has reinforced the need for the economic valuation of changes in ecosystems at large geographical scales. Assessing the costs and benefits of changes in ecosystems includes the valuation of scarce, non-market goods and services. That requires
the use of specialised research methods that are commonly labour intensive because they frequently involve interviewing and detailed statistical analysis. Such techniques are often location-specific and become expensive and time-consuming when carried out across large geographical areas, including multiple ecosystem sites.

The costliness of economic valuation studies has led researchers to consider using data from existing primary research in novel ways. The research question that the present study addresses is if and how existing data on the economic value of
non‑market ecosystem services can be used through value transfer, taking into account the location, size, scarcity and other attributes of the individual ecosystem sites, the proximity of residential areas, and the purchasing power of (potential) users or other beneficiaries of the ecosystems.

Commonly value transfer takes primary data from one ecosystem site — the 'study site' — and applies them at another single and similar site — the 'policy site'. Scaling up builds on the methods and tools for value transfer by taking economic values from a particular study site (or sites) and extrapolating them to a larger geographical area.

The present report analyses options for scaling up existing estimates of ecosystem service values to larger geographical scales. It also presents a case study of wetlands at the European level and discusses the results and policy applications.

The case study looks into ways to improve large‑scale assessments by applying scaling up. The study assesses the economic value of a historical change in wetlands in the Netherlands and the Baltic states using a meta-analytic value transfer
function with coefficients for wetland size, wetland scarcity, per capita income and population density. The analysis concludes that the gains and losses in the study period (2000–2006, as determined by the availability of Corine Land Cover maps) more or less cancel each other out.

Based on this research, the report discusses the results of applying scaling up in a policy context, for example in TEEB. Successfully applying scaling up with the help of value transfer methods requires that the policy context be clearly and properly defined. No scaling-up exercise will ever be able to answer a question such as 'what is the value of all wetlands in Europe?' Scaling up may, however, help in answering a question like 'what is the benefit of halting wetland loss in Europe in comparison to a trend of continuing wetland loss over the next twenty years?'

The present report stresses the importance of natural scientific knowledge. If, in a specific area, there is a lack of scientific knowledge about important relationships between environmental pressures, ecosystem functioning, and the provision of ecosystem services, neither economic valuation nor scaling up will add anything to our understanding of these relationships.

Scaling up makes it possible to combine (several sets of) primary data and one or more value transfer methods to assess the economic value of changes in ecosystem services at a larger spatial scale. The magnitude of the change under study affects the direct applicability of values taken from primary research.

Primary valuation studies usually assess the values of ecosystem services under the assumption that all else would remain equal. A small change in ecosystem service provision (e.g. the loss of a small area) will not affect the value of services from other ecosystem sites. Non-marginal changes in ecosystem service provision, however, will affect the value of services from the remaining stock of ecosystems. As the ecosystem service becomes scarcer, its value will tend to increase. Moreover, scaling-up exercises must take account of cross-substitution effects between ecosystem services and diminishing returns to scale.

Value transfer and scaling up can generate substantial errors. These may be limited by carefully addressing potential measurement and generalisation errors and publication biases but they can never be totally avoided. Maximum acceptable
(transfer) errors may differ from case to case.

Cost‑benefit analyses of particular policy options or damage assessments for use in court will generally require a high level of accuracy. By contrast, less detail is normally needed for broad impact assessments of proposed policies or regulations, or studies that aim to underline the need for policy action in general terms, to prioritise between different policies (cost of inaction studies) or to raise awareness.

In the end, when primary data are too limited for a scaling up exercise — based on criteria to be developed — any value transfer method may lead to unacceptable transfer errors. In such circumstances, value transfer is not a viable option and primary research is necessary for a reliable outcome.

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