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Estimating population extinction thresholds with categorical classification trees for Louisiana black bears

Overview of attention for article published in PLoS ONE, January 2018
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Title
Estimating population extinction thresholds with categorical classification trees for Louisiana black bears
Published in
PLoS ONE, January 2018
DOI 10.1371/journal.pone.0191435
Pubmed ID
Authors

Jared S. Laufenberg, Joseph D. Clark, Richard B. Chandler

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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 29%
Other 2 29%
Student > Ph. D. Student 1 14%
Student > Master 1 14%
Unknown 1 14%
Readers by discipline Count As %
Environmental Science 1 14%
Agricultural and Biological Sciences 1 14%
Chemistry 1 14%
Medicine and Dentistry 1 14%
Unknown 3 43%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 January 2018.
All research outputs
#10,614,844
of 13,955,826 outputs
Outputs from PLoS ONE
#101,446
of 146,764 outputs
Outputs of similar age
#237,059
of 358,044 outputs
Outputs of similar age from PLoS ONE
#3,054
of 4,764 outputs
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