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ASSESSING RISKS TO WILDLIFE POPULATIONS FROM MULTIPLE STRESSORS: OVERVIEW OF PROBLEM AND RESEARCH NEEDS
Citation:
Munns Jr., W R. ASSESSING RISKS TO WILDLIFE POPULATIONS FROM MULTIPLE STRESSORS: OVERVIEW OF PROBLEM AND RESEARCH NEEDS. Ecology and Society. Resilience Alliance Publications, Waterloo, Canada, 11(1):art23, (2006).
Impact/Purpose:
To present issues related to the assessment of risks to wildlife populations and discuss reserch needs in this area.
Description:
Wildlife populations are experiencing increasing pressure from human-induced changes in the landscape. Stressors including agricultural and urban land use, introduced invasive and exotic species, nutrient enrichment, direct human disturbance, and toxic chemicals directly or indirectly influence the quality and quantity of habitat used by terrestrial and aquatic wildlife. Governmental agencies such as the U.S. Environmental Protection Agency are required to assess risks to wildlife populations (in its broadest definition) that result from these stressors, yet considerable uncertainty exists with respect to how such assessments should be conducted. This uncertainty is compounded by questions concerning the interactive effects of co-occurring stressors, appropriate spatial scales of analysis, extrapolation of response data among species and from organisms to populations, and imperfect knowledge and use of limited data sets. Further, different risk problems require varying degrees of sophistication, methodological refinement, and data quality. These issues suggest a number of research needs to improve methods for wildlife risk assessments, including continued development of population dynamics models to evaluate the effects of multiple stressors at varying spatial scales, methods for extrapolating across endpoints and species with reasonable confidence, stressor-response relations and methods for combining them in predictive and diagnostics assessments, and accessible data sets describing the ecology of terrestrial and aquatic species. Case study application of models and methods for assessing wildlife risk will help to demonstrate their strengths and weaknesses for solving particular risk problems.