Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.

Adaptive management provides a useful framework for managing natural resources in the face of uncertainty. An important component of adaptive management is identifying clear, measurable conservation objectives that reflect the desired outcomes of stakeholders. A common objective is to have a sustain...

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Main Authors: Adam W Green, Larissa L Bailey
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144786&type=printable
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author Adam W Green
Larissa L Bailey
author_facet Adam W Green
Larissa L Bailey
author_sort Adam W Green
collection DOAJ
description Adaptive management provides a useful framework for managing natural resources in the face of uncertainty. An important component of adaptive management is identifying clear, measurable conservation objectives that reflect the desired outcomes of stakeholders. A common objective is to have a sustainable population, or metapopulation, but it can be difficult to quantify a threshold above which such a population is likely to persist. We performed a Bayesian metapopulation viability analysis (BMPVA) using a dynamic occupancy model to quantify the characteristics of two wood frog (Lithobates sylvatica) metapopulations resulting in sustainable populations, and we demonstrate how the results could be used to define meaningful objectives that serve as the basis of adaptive management. We explored scenarios involving metapopulations with different numbers of patches (pools) using estimates of breeding occurrence and successful metamorphosis from two study areas to estimate the probability of quasi-extinction and calculate the proportion of vernal pools producing metamorphs. Our results suggest that ≥50 pools are required to ensure long-term persistence with approximately 16% of pools producing metamorphs in stable metapopulations. We demonstrate one way to incorporate the BMPVA results into a utility function that balances the trade-offs between ecological and financial objectives, which can be used in an adaptive management framework to make optimal, transparent decisions. Our approach provides a framework for using a standard method (i.e., PVA) and available information to inform a formal decision process to determine optimal and timely management policies.
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spelling doaj-art-20429c1a4bcb44bfaaa15262b8d65e312025-08-20T02:15:38ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011012e014478610.1371/journal.pone.0144786Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.Adam W GreenLarissa L BaileyAdaptive management provides a useful framework for managing natural resources in the face of uncertainty. An important component of adaptive management is identifying clear, measurable conservation objectives that reflect the desired outcomes of stakeholders. A common objective is to have a sustainable population, or metapopulation, but it can be difficult to quantify a threshold above which such a population is likely to persist. We performed a Bayesian metapopulation viability analysis (BMPVA) using a dynamic occupancy model to quantify the characteristics of two wood frog (Lithobates sylvatica) metapopulations resulting in sustainable populations, and we demonstrate how the results could be used to define meaningful objectives that serve as the basis of adaptive management. We explored scenarios involving metapopulations with different numbers of patches (pools) using estimates of breeding occurrence and successful metamorphosis from two study areas to estimate the probability of quasi-extinction and calculate the proportion of vernal pools producing metamorphs. Our results suggest that ≥50 pools are required to ensure long-term persistence with approximately 16% of pools producing metamorphs in stable metapopulations. We demonstrate one way to incorporate the BMPVA results into a utility function that balances the trade-offs between ecological and financial objectives, which can be used in an adaptive management framework to make optimal, transparent decisions. Our approach provides a framework for using a standard method (i.e., PVA) and available information to inform a formal decision process to determine optimal and timely management policies.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144786&type=printable
spellingShingle Adam W Green
Larissa L Bailey
Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
PLoS ONE
title Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
title_full Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
title_fullStr Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
title_full_unstemmed Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
title_short Using Bayesian Population Viability Analysis to Define Relevant Conservation Objectives.
title_sort using bayesian population viability analysis to define relevant conservation objectives
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0144786&type=printable
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