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6 - Population viability analysis for conservation: the good, the bad and the undescribed

Published online by Cambridge University Press:  29 January 2010

Andrew G. Young
Affiliation:
Division of Plant Industry CSIRO, Canberra
Geoffrey M. Clarke
Affiliation:
Division of Entomology, CSIRO, Canberra
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Summary

ABSTRACT

Population viability analysis (PVA) is used in a variety of ways to solve conservation problems. These uses are defined in part by data availability and theoretical and biological understanding, and in part by social, regulatory and political context. The use of a PVA in one context does not preclude or invalidate its use in another. In this paper we attempt to discuss objectively the role of PVA in population management and conservation planning. We emphasise its role in organising information, engaging stake-holders, and making decisions. To be successful, some traditional views about population models and decision-making need to be suspended and reviewed.

INTRODUCTION

The use of population models in conservation biology is at a crossroads. In the 1980s many believed that population viability analysis (PVA) would provide a comprehensive framework for threatened-species management. Early enthusiasm has been tempered by problems with lack of data, lack of validation, and several studies that have demonstrated the sensitivity of results to uncertainty in the data (Taylor, 1995; Ruckelshaus et al., 1997). More and more conservation ecologists are expressing disappointment at the inability of PVA to provide verifiable answers, to be impregnable to misinterpretation or to make the work of an academic conservation ecologist any easier (Doak & Mills, 1994; Beissinger & Westphal, 1998). Others who view PVA from a more applied perspective and have tried to use it to help with environmental legislation, land-use planning and making decisions about the management of populations have also been disappointed (Hamilton & Moller, 1995; Harcourt, 1995).

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Publisher: Cambridge University Press
Print publication year: 2000

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