Time series sightability modeling of animal populations

Logistic regression models—or “sightability models”—fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-...

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Main Authors: Althea A ArchMiller, Robert M Dorazio, Katherine St. Clair, John R Fieberg
Format: Article in Journal/Newspaper
Language:unknown
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Online Access:https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190706
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190706&type=printable
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spelling ftrepec:oai:RePEc:plo:pone00:0190706 2023-05-15T13:13:28+02:00 Time series sightability modeling of animal populations Althea A ArchMiller Robert M Dorazio Katherine St. Clair John R Fieberg https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190706 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190706&type=printable unknown https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190706 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190706&type=printable article ftrepec 2020-12-04T13:33:13Z Logistic regression models—or “sightability models”—fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-based alternative for analyzing combined detection/non-detection and detection-only data was developed. This approach seemed promising, since it resulted in similar estimates as the mHT when applied to data from moose (Alces alces) surveys in Minnesota. More importantly, it provided a framework for developing flexible models for analyzing multiyear detection-only survey data in combination with detection/non-detection data. During initial attempts to extend the model-based approach to multiple years of detection-only data, we found that estimates of detection probabilities and population abundance were sensitive to the amount of detection-only data included in the combined (detection/non-detection and detection-only) analysis. Subsequently, we developed a robust hierarchical modeling approach where sightability model parameters are informed only by the detection/non-detection data, and we used this approach to fit a fixed-effects model (FE model) with year-specific parameters and a temporally-smoothed model (TS model) that shares information across years via random effects and a temporal spline. The abundance estimates from the TS model were more precise, with decreased interannual variability relative to the FE model and mHT abundance estimates, illustrating the potential benefits from model-based approaches that allow information to be shared across years. Article in Journal/Newspaper Alces alces RePEc (Research Papers in Economics)
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description Logistic regression models—or “sightability models”—fit to detection/non-detection data from marked individuals are often used to adjust for visibility bias in later detection-only surveys, with population abundance estimated using a modified Horvitz-Thompson (mHT) estimator. More recently, a model-based alternative for analyzing combined detection/non-detection and detection-only data was developed. This approach seemed promising, since it resulted in similar estimates as the mHT when applied to data from moose (Alces alces) surveys in Minnesota. More importantly, it provided a framework for developing flexible models for analyzing multiyear detection-only survey data in combination with detection/non-detection data. During initial attempts to extend the model-based approach to multiple years of detection-only data, we found that estimates of detection probabilities and population abundance were sensitive to the amount of detection-only data included in the combined (detection/non-detection and detection-only) analysis. Subsequently, we developed a robust hierarchical modeling approach where sightability model parameters are informed only by the detection/non-detection data, and we used this approach to fit a fixed-effects model (FE model) with year-specific parameters and a temporally-smoothed model (TS model) that shares information across years via random effects and a temporal spline. The abundance estimates from the TS model were more precise, with decreased interannual variability relative to the FE model and mHT abundance estimates, illustrating the potential benefits from model-based approaches that allow information to be shared across years.
format Article in Journal/Newspaper
author Althea A ArchMiller
Robert M Dorazio
Katherine St. Clair
John R Fieberg
spellingShingle Althea A ArchMiller
Robert M Dorazio
Katherine St. Clair
John R Fieberg
Time series sightability modeling of animal populations
author_facet Althea A ArchMiller
Robert M Dorazio
Katherine St. Clair
John R Fieberg
author_sort Althea A ArchMiller
title Time series sightability modeling of animal populations
title_short Time series sightability modeling of animal populations
title_full Time series sightability modeling of animal populations
title_fullStr Time series sightability modeling of animal populations
title_full_unstemmed Time series sightability modeling of animal populations
title_sort time series sightability modeling of animal populations
url https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190706
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190706&type=printable
genre Alces alces
genre_facet Alces alces
op_relation https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0190706
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0190706&type=printable
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