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Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recaptur...

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Autores principales: Clement, Matthew J., Converse, Sarah J., Royle, J. Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5606903/
https://www.ncbi.nlm.nih.gov/pubmed/28944018
http://dx.doi.org/10.1002/ece3.3284
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author Clement, Matthew J.
Converse, Sarah J.
Royle, J. Andrew
author_facet Clement, Matthew J.
Converse, Sarah J.
Royle, J. Andrew
author_sort Clement, Matthew J.
collection PubMed
description If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.
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spelling pubmed-56069032017-09-24 Accounting for imperfect detection of groups and individuals when estimating abundance Clement, Matthew J. Converse, Sarah J. Royle, J. Andrew Ecol Evol Original Research If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size. John Wiley and Sons Inc. 2017-08-08 /pmc/articles/PMC5606903/ /pubmed/28944018 http://dx.doi.org/10.1002/ece3.3284 Text en Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Ecology and Evolution published by John Wiley & Sons Ltd This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Clement, Matthew J.
Converse, Sarah J.
Royle, J. Andrew
Accounting for imperfect detection of groups and individuals when estimating abundance
title Accounting for imperfect detection of groups and individuals when estimating abundance
title_full Accounting for imperfect detection of groups and individuals when estimating abundance
title_fullStr Accounting for imperfect detection of groups and individuals when estimating abundance
title_full_unstemmed Accounting for imperfect detection of groups and individuals when estimating abundance
title_short Accounting for imperfect detection of groups and individuals when estimating abundance
title_sort accounting for imperfect detection of groups and individuals when estimating abundance
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5606903/
https://www.ncbi.nlm.nih.gov/pubmed/28944018
http://dx.doi.org/10.1002/ece3.3284
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