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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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2018-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5779663?pdf=render |
| _version_ | 1818985652269613056 |
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| author | Jared S Laufenberg Joseph D Clark Richard B Chandler |
| author_facet | Jared S Laufenberg Joseph D Clark Richard B Chandler |
| author_sort | Jared S Laufenberg |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-20T18:38:18Z |
| format | Article |
| id | doaj.art-ed0e6512b6354baea20cb0c458f3c297 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T18:38:18Z |
| publishDate | 2018-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-ed0e6512b6354baea20cb0c458f3c2972022-12-21T19:29:54ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01131e019143510.1371/journal.pone.0191435Estimating population extinction thresholds with categorical classification trees for Louisiana black bears.Jared S LaufenbergJoseph D ClarkRichard B ChandlerMonitoring 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.http://europepmc.org/articles/PMC5779663?pdf=render |
| spellingShingle | Jared S Laufenberg Joseph D Clark Richard B Chandler Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. PLoS ONE |
| title | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. |
| title_full | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. |
| title_fullStr | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. |
| title_full_unstemmed | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. |
| title_short | Estimating population extinction thresholds with categorical classification trees for Louisiana black bears. |
| title_sort | estimating population extinction thresholds with categorical classification trees for louisiana black bears |
| url | http://europepmc.org/articles/PMC5779663?pdf=render |
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