2014•Wiley StatsRef: Statistics Reference OnlineRequires access

P opulation V iability A nalysis

Michael A. McCarthy, Hugh P. Possingham

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Abstract

Abstract Population viability analysis (PVA) assesses risks of population decline of species, and how those risks can be managed. Typically, stochastic population models are used to characterize the deterministic and stochastic components that govern changes in population size. Sources of stochasticity include demographic stochasticity due to the chance birth and death of individuals, stochasticity in the environment that is common to all individuals, chance variation in genetic composition, and spatial structure. These factors can interact to create extinction vortices that drive population decline. Predicted risks of population decline from PVA models are usually uncertain due to imprecise parameter estimates, imperfect knowledge about factors that influence dynamics, and uncertainty about future conditions. Despite these sources of uncertainty, changes in risks due to management can be predicted more reliably. Using these changes in risk, PVA can help determine efficient management strategies for reducing high contemporary rates of extinction.

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Abstract Population viability analysis (PVA) assesses risks of population decline of species, and how those risks can be managed. Typically, stochastic population models are used to characterize the deterministic and stochastic components that govern changes in population size. Sources of stochasticity include demographic stochasticity due to the chance birth and death of individuals, stochasticity in the environment that is common to all individuals, chance variation in genetic composition, and spatial structure. These factors can interact to create extinction vortices that drive population decline. Predicted risks of population decline from PVA models are usually uncertain due to imprecise parameter estimates, imperfect knowledge about factors that influence dynamics, and uncertainty about future conditions. Despite these sources of uncertainty, changes in risks due to management can be predicted more reliably. Using these changes in risk, PVA can help determine efficient management strategies for reducing high contemporary rates of extinction.

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Available abstract

Abstract Population viability analysis (PVA) assesses risks of population decline of species, and how those risks can be managed. Typically, stochastic population models are used to characterize the deterministic and stochastic components that govern changes in population size. Sources of stochasticity include demographic stochasticity due to the chance birth and death of individuals, stochasticity in the environment that is common to all individuals, chance variation in genetic composition, and spatial structure. These factors can interact to create extinction vortices that drive population decline. Predicted risks of population decline from PVA models are usually uncertain due to imprecise parameter estimates, imperfect knowledge about factors that influence dynamics, and uncertainty about future conditions. Despite these sources of uncertainty, changes in risks due to management can be predicted more reliably. Using these changes in risk, PVA can help determine efficient management strategies for reducing high contemporary rates of extinction.

Key concepts: Extinction (optical mineralogy), Population, Population viability analysis, Imperfect, Population size, Stochastic modelling, Population decline, Biology

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