A framework to quantify the strength of ecological links between an environmental stressor and final ecosystem services

Abstract

Anthropogenic stressors such as climate change, increased fire frequency, and pollution drive shifts in ecosystem function and resilience. Scientists generally rely on biological indicators of these stressors to signal that ecosystem conditions have been altered. However, these biological indicators are not always capable of being directly related to ecosystem components that provide benefits to humans and/or can be used to evaluate the cost-benefit of a change in health of the component (ecosystem services). Therefore, we developed the STEPS (Stressor-Ecological Production function-final ecosystem Services) Framework to link changes in a biological indicator of a stressor to final ecosystem services. The STEPS Framework produces "chains" of ecological components that explore the breadth of impacts resulting from the change in a stressor. Chains are comprised of the biological indicator, the ecological production function (EPF, which uses ecological components to link the biological indicator to a final ecosystem service), and the user group who directly uses, appreciates, or values the component. The framework uses a qualitative score (high, medium, low) to describe the strength of science (SOS) for the relationship between each component in the EPF. We tested the STEPS Framework within a workshop setting using the exceedance of critical loads of air pollution as a model stressor and the Final Ecosystem Goods and Services Classification System (FEGS-CS) to describe final ecosystem services. We identified chains for four modes of ecological response to deposition: aquatic acidification, aquatic eutrophication, terrestrial acidification, and terrestrial eutrophication. The workshop participants identified 183 unique EPFs linking a change in a biological indicator to a FEGS; when accounting for the multiple beneficiaries, we ended with 1104 chains. The SOS scores were effective in identifying chains with the highest confidence ranking as well as those where more research is needed. The STEPS Framework could be adapted to any system in which a stressor is modifying a biological component. The results of the analysis can be used by the social science community to apply valuation measures to multiple or selected chains, providing a comprehensive analysis of the effects of anthropogenic stressors on measures of human well-being.