Estimating population extinction thresholds with categorical classification trees for Louisiana black bears
Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well...
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description | Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs. |
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Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. 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Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.</description><subject>Animals</subject><subject>Bears</subject><subject>Biodiversity</subject><subject>Bioinformatics</subject><subject>Biology and Life Sciences</subject><subject>Biometrics</subject><subject>Capture-recapture studies</subject><subject>Clark, Richard B</subject><subject>Classification</subject><subject>Computer Simulation</subject><subject>Conservation</subject><subject>Conservation of Natural Resources</subject><subject>Demographics</subject><subject>Demography</subject><subject>Ecological Parameter Monitoring - statistics & numerical data</subject><subject>Ecology and Environmental Sciences</subject><subject>Endangered & extinct species</subject><subject>Endangered Species</subject><subject>Engineering and Technology</subject><subject>Environmental monitoring</subject><subject>Environmental protection</subject><subject>Extinction</subject><subject>Extinction, Biological</subject><subject>Female</subject><subject>Females</subject><subject>Fisheries</subject><subject>Louisiana</subject><subject>Male</subject><subject>Methods</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Monitoring</subject><subject>Natural resources</subject><subject>Parameter estimation</subject><subject>People and places</subject><subject>Population Dynamics - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Laufenberg, Jared S</au><au>Clark, Joseph D</au><au>Chandler, Richard B</au><au>Festa-Bianchet, Marco</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating population extinction thresholds with categorical classification trees for Louisiana black bears</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2018-01-01</date><risdate>2018</risdate><volume>13</volume><issue>1</issue><spage>e0191435</spage><epage>e0191435</epage><pages>e0191435-e0191435</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>29360863</pmid><doi>10.1371/journal.pone.0191435</doi><orcidid>https://orcid.org/0000-0002-8547-8112</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Animals Bears Biodiversity Bioinformatics Biology and Life Sciences Biometrics Capture-recapture studies Clark, Richard B Classification Computer Simulation Conservation Conservation of Natural Resources Demographics Demography Ecological Parameter Monitoring - statistics & numerical data Ecology and Environmental Sciences Endangered & extinct species Endangered Species Engineering and Technology Environmental monitoring Environmental protection Extinction Extinction, Biological Female Females Fisheries Louisiana Male Methods Models, Biological Models, Statistical Monitoring Natural resources Parameter estimation People and places Population Dynamics - statistics & numerical data Population statistics Population viability Research and Analysis Methods Sensitivity analysis Software Species extinction Stochastic Processes Stochasticity Survival Threatened species Thresholds Trees Ursidae Ursus americanus Ursus americanus luteolus Wildlife conservation |
title | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears |
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