Spatiotemporal modeling of mature‐at‐length data using a sliding window approach
Abstract Assessing maturity status of fish and invertebrate species is important for understanding population dynamics with results (e.g., estimates of reproductive potential) often used to inform fisheries management strategies (e.g., the setting of minimum legal size requirements for fishing). Mat...
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crwiley:10.1002/env.2759 2024-06-02T08:02:26+00:00 Spatiotemporal modeling of mature‐at‐length data using a sliding window approach Yan, Yuan Cantoni, Eva Field, Chris Treble, Margaret Mills Flemming, Joanna 2022 http://dx.doi.org/10.1002/env.2759 https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2759 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/env.2759 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Environmetrics volume 34, issue 2 ISSN 1180-4009 1099-095X journal-article 2022 crwiley https://doi.org/10.1002/env.2759 2024-05-03T11:19:15Z Abstract Assessing maturity status of fish and invertebrate species is important for understanding population dynamics with results (e.g., estimates of reproductive potential) often used to inform fisheries management strategies (e.g., the setting of minimum legal size requirements for fishing). Maturity rates may vary substantially across a population's range, as well as between years. In addition, maturity data are typically obtained from fisheries‐independent surveys that may be incomplete (or missing) from year to year. Here we propose a spatial generalized linear mixed model (GLMM) framework for maturity data that includes spatially correlated random effects to address variations in space, and a sliding window approach to deal with unbalanced maturity data in both space and time. We demonstrate, with both real data and a simulation study, that this combined approach results in unbiased estimates of important growth parameters. Results of using our spatial GLMM framework with Greenland halibut ( Rheinhardtius hippoglossoides ) mature‐at‐length data from surveys of the eastern Canadian Arctic show that females mature at a much larger size than do males. The length at which 50% of the stock is mature () is found to be higher in Baffin Bay compared to Davis Strait, and a declining trend in the in recent years is revealed for both sexes. Our proposed methodology extends far beyond our current application in being useful for analyzing unbalanced spatiotemporal data from an array of diverse scientific fields. Article in Journal/Newspaper Arctic Baffin Bay Baffin Bay Baffin Davis Strait Greenland Wiley Online Library Arctic Baffin Bay Greenland Environmetrics 34 2 |
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English |
description |
Abstract Assessing maturity status of fish and invertebrate species is important for understanding population dynamics with results (e.g., estimates of reproductive potential) often used to inform fisheries management strategies (e.g., the setting of minimum legal size requirements for fishing). Maturity rates may vary substantially across a population's range, as well as between years. In addition, maturity data are typically obtained from fisheries‐independent surveys that may be incomplete (or missing) from year to year. Here we propose a spatial generalized linear mixed model (GLMM) framework for maturity data that includes spatially correlated random effects to address variations in space, and a sliding window approach to deal with unbalanced maturity data in both space and time. We demonstrate, with both real data and a simulation study, that this combined approach results in unbiased estimates of important growth parameters. Results of using our spatial GLMM framework with Greenland halibut ( Rheinhardtius hippoglossoides ) mature‐at‐length data from surveys of the eastern Canadian Arctic show that females mature at a much larger size than do males. The length at which 50% of the stock is mature () is found to be higher in Baffin Bay compared to Davis Strait, and a declining trend in the in recent years is revealed for both sexes. Our proposed methodology extends far beyond our current application in being useful for analyzing unbalanced spatiotemporal data from an array of diverse scientific fields. |
format |
Article in Journal/Newspaper |
author |
Yan, Yuan Cantoni, Eva Field, Chris Treble, Margaret Mills Flemming, Joanna |
spellingShingle |
Yan, Yuan Cantoni, Eva Field, Chris Treble, Margaret Mills Flemming, Joanna Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
author_facet |
Yan, Yuan Cantoni, Eva Field, Chris Treble, Margaret Mills Flemming, Joanna |
author_sort |
Yan, Yuan |
title |
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
title_short |
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
title_full |
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
title_fullStr |
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
title_full_unstemmed |
Spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
title_sort |
spatiotemporal modeling of mature‐at‐length data using a sliding window approach |
publisher |
Wiley |
publishDate |
2022 |
url |
http://dx.doi.org/10.1002/env.2759 https://onlinelibrary.wiley.com/doi/pdf/10.1002/env.2759 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/env.2759 |
geographic |
Arctic Baffin Bay Greenland |
geographic_facet |
Arctic Baffin Bay Greenland |
genre |
Arctic Baffin Bay Baffin Bay Baffin Davis Strait Greenland |
genre_facet |
Arctic Baffin Bay Baffin Bay Baffin Davis Strait Greenland |
op_source |
Environmetrics volume 34, issue 2 ISSN 1180-4009 1099-095X |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/env.2759 |
container_title |
Environmetrics |
container_volume |
34 |
container_issue |
2 |
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1800746931969851392 |