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Predicting Population Risks from Multiple Stressors: Mercury Contamination and Habitat Alteration on Nesting Common Loons
Citation:
Nacci, D., A. Kuhn, J. Grear, G. Thursby, AND J. Copeland. Predicting Population Risks from Multiple Stressors: Mercury Contamination and Habitat Alteration on Nesting Common Loons. Chapter 2, Advances in Environmental Research. Nova Science Publishers, Inc, Hauppauge, NY, 63:79-148, (2018).
Impact/Purpose:
The approach and methods described in this book chapter illustrate a scientific process for ecological risk assessment applicable to any category of wildlife or combination of stressors. The data rich example that was selected addresses an important environmental problem, and provided an opportunity to test results for consistency with wild populations influenced by multiple, concurrent stressors. This form of model testing produces confidence in the usefulness of these methods generically to develop risk-based determinations that support the development of regulatory criteria at the state, regional or national levels. General impacts from this contribution include improved understanding by managers and scientists of links between human activities, natural dynamics, ecological stressors and ecosystem condition.
Description:
This chapter describes the first demonstration of a logical framework developed by the US Environmental Protection Agency to integrate best available data, methods and models to estimate risks to wildlife populations from multiple stressors. This approach responds to the need for greater realism and ecological significance in the estimation of the effects on wildlife of human-mediated stressors. Specifically, this approach provides a mechanism to link quantitatively adverse outcomes at the population level and increasing levels of specific single or a combination of multiple stressors. This demonstration was applied to estimate risks to the common loon (Gavia immer) from dietary mercury and nesting habitat degradation, over a range of realistic stressor levels. Information from field observations, controlled studies, and environmental data were used to estimate demographic parameters, and to develop biological response models for mercury and habitat suitability for loons nesting in the state of New Hampshire, USA, where the common loon is listed as a ‘threatened species’. Stressor-specific biological response models were used to modify population model parameters (developed from a reference population), and models were used to project quantitative population-level responses for varying combinations of environmentally-realistic stressor levels. Site-specific model projections and field observations were generally coherent, suggesting the usefulness of this approach as a basis for management decisions to mitigate the effects of chemicals and other human-mediated stressors.
