Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap
Understanding spatial physical habitat selection driven by competition and/or predator–prey interactions of mobile marine species is a fundamental goal of spatial ecology. However, spatial counts or density data for highly mobile animals often (1) include excess zeros, (2) have spatial correlation,...
Published in: | Ecology and Evolution |
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2017
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Online Access: | https://pure.qub.ac.uk/en/publications/ef76aca7-56cf-47d5-b031-5b01f750e872 https://doi.org/10.1002/ece3.3081 https://pureadmin.qub.ac.uk/ws/files/131093743/Sadykova_et_al_2017_Ecology_and_Evolution.pdf |
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ftqueensubelpubl:oai:pure.qub.ac.uk/portal:publications/ef76aca7-56cf-47d5-b031-5b01f750e872 2024-09-15T18:00:00+00:00 Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap Sadykova, Dinara Scott, Beth E. De Dominicis, Michela Wakelin, Sarah L. Sadykov, Alexander Wolf, Judith 2017-06-07 application/pdf https://pure.qub.ac.uk/en/publications/ef76aca7-56cf-47d5-b031-5b01f750e872 https://doi.org/10.1002/ece3.3081 https://pureadmin.qub.ac.uk/ws/files/131093743/Sadykova_et_al_2017_Ecology_and_Evolution.pdf eng eng https://pure.qub.ac.uk/en/publications/ef76aca7-56cf-47d5-b031-5b01f750e872 info:eu-repo/semantics/openAccess Sadykova , D , Scott , B E , De Dominicis , M , Wakelin , S L , Sadykov , A & Wolf , J 2017 , ' Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap ' , Ecology and Evolution . https://doi.org/10.1002/ece3.3081 /dk/atira/pure/sustainabledevelopmentgoals/climate_action name=SDG 13 - Climate Action /dk/atira/pure/sustainabledevelopmentgoals/life_below_water name=SDG 14 - Life Below Water article 2017 ftqueensubelpubl https://doi.org/10.1002/ece3.3081 2024-07-08T23:45:08Z Understanding spatial physical habitat selection driven by competition and/or predator–prey interactions of mobile marine species is a fundamental goal of spatial ecology. However, spatial counts or density data for highly mobile animals often (1) include excess zeros, (2) have spatial correlation, and (3) have highly nonlinear relationships with physical habitat variables, which results in the need for complex joint spatial models. In this paper, we test the use of Bayesian hierarchical hurdle and zero-inflated joint models with integrated nested Laplace approximation (INLA), to fit complex joint models to spatial patterns of eight mobile marine species (grey seal, harbor seal, harbor porpoise, common guillemot, black-legged kittiwake, northern gannet, herring, and sandeels). For each joint model, we specified nonlinear smoothed effect of physical habitat covariates and selected either competing species or predator–prey interactions. Out of a range of six ecologically important physical and biologic variables that are predicted to change with climate change and large-scale energy extraction, we identified the most important habitat variables for each species and present the relationships between these bio/physical variables and species distributions. In particular, we found that net primary production played a significant role in determining habitat preferences of all the selected mobile marine species. We have shown that the INLA method is well-suited for modeling spatially correlated data with excessive zeros and is an efficient approach to fit complex joint spatial models with nonlinear effects of covariates. Our approach has demonstrated its ability to define joint habitat selection for both competing and prey–predator species that can be relevant to numerous issues in the management and conservation of mobile marine species. Article in Journal/Newspaper Black-legged Kittiwake common guillemot harbor seal Queen's University Belfast Research Portal Ecology and Evolution 7 14 5212 5226 |
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Queen's University Belfast Research Portal |
op_collection_id |
ftqueensubelpubl |
language |
English |
topic |
/dk/atira/pure/sustainabledevelopmentgoals/climate_action name=SDG 13 - Climate Action /dk/atira/pure/sustainabledevelopmentgoals/life_below_water name=SDG 14 - Life Below Water |
spellingShingle |
/dk/atira/pure/sustainabledevelopmentgoals/climate_action name=SDG 13 - Climate Action /dk/atira/pure/sustainabledevelopmentgoals/life_below_water name=SDG 14 - Life Below Water Sadykova, Dinara Scott, Beth E. De Dominicis, Michela Wakelin, Sarah L. Sadykov, Alexander Wolf, Judith Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
topic_facet |
/dk/atira/pure/sustainabledevelopmentgoals/climate_action name=SDG 13 - Climate Action /dk/atira/pure/sustainabledevelopmentgoals/life_below_water name=SDG 14 - Life Below Water |
description |
Understanding spatial physical habitat selection driven by competition and/or predator–prey interactions of mobile marine species is a fundamental goal of spatial ecology. However, spatial counts or density data for highly mobile animals often (1) include excess zeros, (2) have spatial correlation, and (3) have highly nonlinear relationships with physical habitat variables, which results in the need for complex joint spatial models. In this paper, we test the use of Bayesian hierarchical hurdle and zero-inflated joint models with integrated nested Laplace approximation (INLA), to fit complex joint models to spatial patterns of eight mobile marine species (grey seal, harbor seal, harbor porpoise, common guillemot, black-legged kittiwake, northern gannet, herring, and sandeels). For each joint model, we specified nonlinear smoothed effect of physical habitat covariates and selected either competing species or predator–prey interactions. Out of a range of six ecologically important physical and biologic variables that are predicted to change with climate change and large-scale energy extraction, we identified the most important habitat variables for each species and present the relationships between these bio/physical variables and species distributions. In particular, we found that net primary production played a significant role in determining habitat preferences of all the selected mobile marine species. We have shown that the INLA method is well-suited for modeling spatially correlated data with excessive zeros and is an efficient approach to fit complex joint spatial models with nonlinear effects of covariates. Our approach has demonstrated its ability to define joint habitat selection for both competing and prey–predator species that can be relevant to numerous issues in the management and conservation of mobile marine species. |
format |
Article in Journal/Newspaper |
author |
Sadykova, Dinara Scott, Beth E. De Dominicis, Michela Wakelin, Sarah L. Sadykov, Alexander Wolf, Judith |
author_facet |
Sadykova, Dinara Scott, Beth E. De Dominicis, Michela Wakelin, Sarah L. Sadykov, Alexander Wolf, Judith |
author_sort |
Sadykova, Dinara |
title |
Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
title_short |
Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
title_full |
Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
title_fullStr |
Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
title_full_unstemmed |
Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap |
title_sort |
bayesian joint models with inla exploring marine mobile predator-prey and competitor species habitat overlap |
publishDate |
2017 |
url |
https://pure.qub.ac.uk/en/publications/ef76aca7-56cf-47d5-b031-5b01f750e872 https://doi.org/10.1002/ece3.3081 https://pureadmin.qub.ac.uk/ws/files/131093743/Sadykova_et_al_2017_Ecology_and_Evolution.pdf |
genre |
Black-legged Kittiwake common guillemot harbor seal |
genre_facet |
Black-legged Kittiwake common guillemot harbor seal |
op_source |
Sadykova , D , Scott , B E , De Dominicis , M , Wakelin , S L , Sadykov , A & Wolf , J 2017 , ' Bayesian joint models with INLA exploring marine mobile predator-prey and competitor species habitat overlap ' , Ecology and Evolution . https://doi.org/10.1002/ece3.3081 |
op_relation |
https://pure.qub.ac.uk/en/publications/ef76aca7-56cf-47d5-b031-5b01f750e872 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1002/ece3.3081 |
container_title |
Ecology and Evolution |
container_volume |
7 |
container_issue |
14 |
container_start_page |
5212 |
op_container_end_page |
5226 |
_version_ |
1810437117375938560 |