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State space and movement specification in open population spatial capture–recapture models
With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long‐term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture–recap...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206188/ https://www.ncbi.nlm.nih.gov/pubmed/30397470 http://dx.doi.org/10.1002/ece3.4509 |
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author | Gardner, Beth Sollmann, Rahel Kumar, N. Samba Jathanna, Devcharan Karanth, K. Ullas |
author_facet | Gardner, Beth Sollmann, Rahel Kumar, N. Samba Jathanna, Devcharan Karanth, K. Ullas |
author_sort | Gardner, Beth |
collection | PubMed |
description | With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long‐term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture–recapture methods. Spatial capture (SCR) models for open populations make efficient use of capture–recapture data, while being robust to design changes. Relatively few studies have implemented open SCR models, and to date, very few have explored potential issues in defining these models. We develop a series of simulation studies to examine the effects of the state‐space definition and between‐primary‐period movement models on demographic parameter estimation. We demonstrate the implications on a 10‐year camera‐trap study of tigers in India. The results of our simulation study show that movement biases survival estimates in open SCR models when little is known about between‐primary‐period movements of animals. The size of the state‐space delineation can also bias the estimates of survival in certain cases.We found that both the state‐space definition and the between‐primary‐period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71 to 0.89). In general, we suggest that open SCR models can provide an efficient and flexible framework for long‐term monitoring of populations; however, in many cases, realistic modeling of between‐primary‐period movements is crucial for unbiased estimates of survival and density. |
format | Online Article Text |
id | pubmed-6206188 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62061882018-11-05 State space and movement specification in open population spatial capture–recapture models Gardner, Beth Sollmann, Rahel Kumar, N. Samba Jathanna, Devcharan Karanth, K. Ullas Ecol Evol Original Research With continued global changes, such as climate change, biodiversity loss, and habitat fragmentation, the need for assessment of long‐term population dynamics and population monitoring of threatened species is growing. One powerful way to estimate population size and dynamics is through capture–recapture methods. Spatial capture (SCR) models for open populations make efficient use of capture–recapture data, while being robust to design changes. Relatively few studies have implemented open SCR models, and to date, very few have explored potential issues in defining these models. We develop a series of simulation studies to examine the effects of the state‐space definition and between‐primary‐period movement models on demographic parameter estimation. We demonstrate the implications on a 10‐year camera‐trap study of tigers in India. The results of our simulation study show that movement biases survival estimates in open SCR models when little is known about between‐primary‐period movements of animals. The size of the state‐space delineation can also bias the estimates of survival in certain cases.We found that both the state‐space definition and the between‐primary‐period movement specification affected survival estimates in the analysis of the tiger dataset (posterior mean estimates of survival ranged from 0.71 to 0.89). In general, we suggest that open SCR models can provide an efficient and flexible framework for long‐term monitoring of populations; however, in many cases, realistic modeling of between‐primary‐period movements is crucial for unbiased estimates of survival and density. John Wiley and Sons Inc. 2018-09-27 /pmc/articles/PMC6206188/ /pubmed/30397470 http://dx.doi.org/10.1002/ece3.4509 Text en © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the 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 Gardner, Beth Sollmann, Rahel Kumar, N. Samba Jathanna, Devcharan Karanth, K. Ullas State space and movement specification in open population spatial capture–recapture models |
title | State space and movement specification in open population spatial capture–recapture models |
title_full | State space and movement specification in open population spatial capture–recapture models |
title_fullStr | State space and movement specification in open population spatial capture–recapture models |
title_full_unstemmed | State space and movement specification in open population spatial capture–recapture models |
title_short | State space and movement specification in open population spatial capture–recapture models |
title_sort | state space and movement specification in open population spatial capture–recapture models |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206188/ https://www.ncbi.nlm.nih.gov/pubmed/30397470 http://dx.doi.org/10.1002/ece3.4509 |
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