An experimental test of a Bayesian method for inferring extinction with varying search efforts
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Abstract
Determining whether a species is extinct or extant is notoriously difficult, but is fundamental to both our understanding of biodiversity loss, and our ability to implement effective conservation measures. Many methods have been proposed in an attempt to infer quantitatively whether a species has gone extinct, with many seeking to do so by using sets of historic sighting events. Until recently, however, no methods have been proposed that explicitly take into account search effort (the proportion of a habitat searched when looking for a species), a key determinant of if/when historic sighting events have occurred. Here we present the first test of a recently proposed Bayesian approach for inferring the extinction status of a species from a set of historic sighting events where the search effort that has produced the sightings can be explicitly included in the calculation. We utilize data from a highly tractable experimental system, as well as simulated data, to test whether the method is robust to changing search efforts, and different levels of detectability of a species. We find that, whilst in general the method performs well, it is susceptible to both changes in search effort through time, as well as how detectable a species is. In addition, we show that the value of the prior expectation that the species is extant has a large impact on the accuracy of the methods, and that selecting correct priors is critical for accurate inference of extinction status.
Cite this as
2014. An experimental test of a Bayesian method for inferring extinction with varying search efforts . PeerJ PrePrints 2:e466v1 https://doi.org/10.7287/peerj.preprints.466v1Author comment
This is a submission to PeerJ for review.
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Supplemental Information
Dataset 1 - Paramecium caudatum time series
Paramecium caudatum time series data from Clements et al. (2013).
Additional Information
Competing Interests
The authors declare they have no competing interests.
Author Contributions
Christopher Clements conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.
Tamsin Lee analyzed the data, wrote the paper, reviewed drafts of the paper.
Micheal A McCarthy contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.
Funding
CC was supported by an Early Career Researcher Grant from the Australian Research Council (ARC) Centre of Excellence for Environmental Decisions (CEED). MM was supported by CEED and an ARC Future Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
