Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models
Abstract Open‐population spatial capture–recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate not only occasion‐specific density, but also demographic parameters. OPSCR models can also estimate spatial varia...
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Online Access: | http://dx.doi.org/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecy.3934 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 |
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crwiley:10.1002/ecy.3934 2024-03-17T08:58:15+00:00 Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models Milleret, Cyril Dey, Soumen Dupont, Pierre Brøseth, Henrik Turek, Daniel de Valpine, Perry Bischof, Richard Miljødirektoratet Naturvårdsverket Norges Forskningsråd 2023 http://dx.doi.org/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecy.3934 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Ecology volume 104, issue 2 ISSN 0012-9658 1939-9170 Ecology, Evolution, Behavior and Systematics journal-article 2023 crwiley https://doi.org/10.1002/ecy.3934 2024-02-22T01:04:03Z Abstract Open‐population spatial capture–recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate not only occasion‐specific density, but also demographic parameters. OPSCR models can also estimate spatial variation in vital rates, but such models are neither widely used nor thoroughly tested. We developed a Bayesian OPSCR model that not only accounts for spatial variation in survival using spatial covariates but also estimates local density‐dependent effects on survival within a unified framework. Using simulations, we show that OPSCR models provide sound inferences on the effect of spatial covariates on survival, including multiple competing sources of mortality, each with potentially different spatial determinants. Estimation of local density‐dependent survival was possible but required more data due to the greater complexity of the model. Not accounting for spatial heterogeneity in survival led to up to 10% positive bias in abundance estimates. We provide an empirical demonstration of the model by estimating the effect of country and density on cause‐specific mortality of female wolverines ( Gulo gulo ) in central Sweden and Norway. The ability to make population‐level inferences on spatial variation in survival is an essential step toward a fully spatially explicit OPSCR model capable of disentangling the role of multiple spatial drivers of population dynamics. Article in Journal/Newspaper Gulo gulo Wiley Online Library Norway Ecology 104 2 |
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Open Polar |
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Wiley Online Library |
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crwiley |
language |
English |
topic |
Ecology, Evolution, Behavior and Systematics |
spellingShingle |
Ecology, Evolution, Behavior and Systematics Milleret, Cyril Dey, Soumen Dupont, Pierre Brøseth, Henrik Turek, Daniel de Valpine, Perry Bischof, Richard Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
topic_facet |
Ecology, Evolution, Behavior and Systematics |
description |
Abstract Open‐population spatial capture–recapture (OPSCR) models use the spatial information contained in individual detections collected over multiple consecutive occasions to estimate not only occasion‐specific density, but also demographic parameters. OPSCR models can also estimate spatial variation in vital rates, but such models are neither widely used nor thoroughly tested. We developed a Bayesian OPSCR model that not only accounts for spatial variation in survival using spatial covariates but also estimates local density‐dependent effects on survival within a unified framework. Using simulations, we show that OPSCR models provide sound inferences on the effect of spatial covariates on survival, including multiple competing sources of mortality, each with potentially different spatial determinants. Estimation of local density‐dependent survival was possible but required more data due to the greater complexity of the model. Not accounting for spatial heterogeneity in survival led to up to 10% positive bias in abundance estimates. We provide an empirical demonstration of the model by estimating the effect of country and density on cause‐specific mortality of female wolverines ( Gulo gulo ) in central Sweden and Norway. The ability to make population‐level inferences on spatial variation in survival is an essential step toward a fully spatially explicit OPSCR model capable of disentangling the role of multiple spatial drivers of population dynamics. |
author2 |
Miljødirektoratet Naturvårdsverket Norges Forskningsråd |
format |
Article in Journal/Newspaper |
author |
Milleret, Cyril Dey, Soumen Dupont, Pierre Brøseth, Henrik Turek, Daniel de Valpine, Perry Bischof, Richard |
author_facet |
Milleret, Cyril Dey, Soumen Dupont, Pierre Brøseth, Henrik Turek, Daniel de Valpine, Perry Bischof, Richard |
author_sort |
Milleret, Cyril |
title |
Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
title_short |
Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
title_full |
Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
title_fullStr |
Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
title_full_unstemmed |
Estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
title_sort |
estimating spatially variable and density‐dependent survival using open‐population spatial capture–recapture models |
publisher |
Wiley |
publishDate |
2023 |
url |
http://dx.doi.org/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecy.3934 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.3934 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Gulo gulo |
genre_facet |
Gulo gulo |
op_source |
Ecology volume 104, issue 2 ISSN 0012-9658 1939-9170 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1002/ecy.3934 |
container_title |
Ecology |
container_volume |
104 |
container_issue |
2 |
_version_ |
1793767774007328768 |