|Document Type:||Journal Article|
|Title:||Use of population viability analysis models for Atlantic and Pacific salmon recovery planning|
|Author:||John A. Sweka, Thomas C. Wainwright|
|Journal:||Reviews in Fish Biology and Fisheries|
|Keywords:||salmon, population viability analysis, adaptive management, risk, uncertainty, endangered species,|
Uncertainty and risk abound in making natural resource management decisions. Population viability analysis (PVA) includes a variety of qualitative or quantitative analyses to predict the future status of a population or collection of populations and to predict the risk of extinction (or quasi-extinction) over time given some assumptions of the factors driving population dynamics. In this paper, we review the various PVA models applied to Atlantic and Pacific salmon for determination of listing under the Endangered Species Act and in planning recovery actions. We also review the numerous cautions involved in developing PVA models and in interpreting their results. There have been a larger number of PVA models applied to Pacific salmon compared to Atlantic salmon due to the greater geographic range and number of species of Pacific salmon. Models for both Atlantic and Pacific salmon have ranged from simple models that view populations as simply a number of organisms to complex age- or stage-structured models depending on the purpose of the model and available data for model parameterization. The real value of PVA models to salmon conservation is not in making absolute predictions of the risk of extinction, but rather in evaluating relative effects of management alternatives on extinction risk and informing decision making within an adaptive management framework. As computing power, quantitative techniques, and knowledge of mechanistic linkages between terrestrial, freshwater, and marine environments advance, PVA models will become an even more powerful tool in conservation planning for salmon species.
|Theme:||Recovery, Rebuilding and Sustainability of Marine and Anadromous Species|
Investigate ecological and socio-economic effects of alternative management strategies or governance structures.
Develop methods to use physiological and biological information to predict population-level processes.