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Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic

Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are i...

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Detalles Bibliográficos
Autores principales: Roberts, Sarah M., Halpin, Patrick N., Clark, James S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742080/
https://www.ncbi.nlm.nih.gov/pubmed/34997068
http://dx.doi.org/10.1038/s41598-021-04110-0
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author Roberts, Sarah M.
Halpin, Patrick N.
Clark, James S.
author_facet Roberts, Sarah M.
Halpin, Patrick N.
Clark, James S.
author_sort Roberts, Sarah M.
collection PubMed
description Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic dependencies such as interspecific competition and predation. When species interact, a joint species distribution model (JSDM) will allow for valid inference of environmental effects. We built a joint species distribution model of marine fish and invertebrates of the Northeast US Continental Shelf, providing evidence on species relationships with the environment as well as the likelihood of species to covary. Predictive performance is similar to SSDMs but the Bayesian joint modeling approach provides two main advantages over single species modeling: (1) the JSDM directly estimates the significance of environmental effects; and (2) predicted species richness accounts for species dependencies. An additional value of JSDMs is that the conditional prediction of species distributions can use not only the environmental associations of species, but also the presence and abundance of other species when forecasting future climatic associations.
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spelling pubmed-87420802022-01-11 Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic Roberts, Sarah M. Halpin, Patrick N. Clark, James S. Sci Rep Article Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic dependencies such as interspecific competition and predation. When species interact, a joint species distribution model (JSDM) will allow for valid inference of environmental effects. We built a joint species distribution model of marine fish and invertebrates of the Northeast US Continental Shelf, providing evidence on species relationships with the environment as well as the likelihood of species to covary. Predictive performance is similar to SSDMs but the Bayesian joint modeling approach provides two main advantages over single species modeling: (1) the JSDM directly estimates the significance of environmental effects; and (2) predicted species richness accounts for species dependencies. An additional value of JSDMs is that the conditional prediction of species distributions can use not only the environmental associations of species, but also the presence and abundance of other species when forecasting future climatic associations. Nature Publishing Group UK 2022-01-07 /pmc/articles/PMC8742080/ /pubmed/34997068 http://dx.doi.org/10.1038/s41598-021-04110-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Roberts, Sarah M.
Halpin, Patrick N.
Clark, James S.
Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title_full Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title_fullStr Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title_full_unstemmed Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title_short Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
title_sort jointly modeling marine species to inform the effects of environmental change on an ecological community in the northwest atlantic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8742080/
https://www.ncbi.nlm.nih.gov/pubmed/34997068
http://dx.doi.org/10.1038/s41598-021-04110-0
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