Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches

16 pages, 9 figures, 3 tables, 1 appendix

Detalles Bibliográficos
Autores: Coll, Marta, Pennino, Maria Grazia, Steenbeek, Jeroen, Solé, Jordi, Bellido, José M.
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2019
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/189805
Acceso en línea:http://hdl.handle.net/10261/189805
Access Level:acceso abierto
Palabra clave:Mediterranean Sea
Commercial species
Ecospace
Bayesian models
Species distribution models
Spatial ecology
Food-web model
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spelling Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approachesColl, MartaPennino, Maria GraziaSteenbeek, JeroenSolé, JordiBellido, José M.Mediterranean SeaCommercial speciesEcospaceBayesian modelsSpecies distribution modelsSpatial ecologyFood-web model16 pages, 9 figures, 3 tables, 1 appendixThe spatial prediction of species distributions from survey data is a significant component of spatial planning and the ecosystem-based management approach to marine resources. Statistical analysis of species occurrences and their relationships with associated environmental factors is used to predict how likely a species is to occur in unsampled locations as well as future conditions. However, it is known that environmental factors alone may not be sufficient to account for species distribution. Other ecological processes including species interactions (such as competition and predation), and the impact of human activities, may affect the spatial arrangement of a species. Novel techniques have been developed to take a more holistic approach to estimating species distributions, such as Bayesian Hierarchical Species Distribution model (B-HSD model) and mechanistic food-web models using the new Ecospace Habitat Foraging Capacity model (E-HFC model). Here we used both species distribution and spatial food-web models to predict the distribution of European hake (Merluccius merluccius), anglerfishes (Lophius piscatorius and L. budegassa) and red mullets (Mullus barbatus and M. surmuletus) in an exploited marine ecosystem of the Northwestern Mediterranean Sea. We explored the complementarity of both approaches, comparing results of food-web models previously informed with species distribution modelling results, aside from their applicability as independent techniques. The study shows that both modelling results are positively and significantly correlated with observational data. Predicted spatial patterns of biomasses show positive and significant correlations between modelling approaches and are more similar when using both methodologies in a complementary way: when using the E-HFC model previously informed with the environmental envelopes obtained from the B-HSD model outputs, or directly using niche calculations from B-HSD models to drive the niche priors of E-HFC. We discuss advantages, limitations and future developments of both modelling techniquesMC was partially funded by the European Commission through the Marie Curie Career Integration Grant Fellowships – PCIG10-GA-2011-303534 - to the BIOWEB project. This study is a contribution to the project ECOTRANS (CTM2011-26333, Ministerio de Economía y Competitividad, Spain) and SafeNET (EU-DGMARE MARE/2014/41). MC and JS acknowledge financial support by the European Union´s Horizon research program grant agreement No 689518 for the MERCES projectPeer ReviewedElsevierMinisterio de Economía y Competitividad (España)European CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2019201920192019info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Preprintinfo:eu-repo/semantics/submittedVersionhttp://hdl.handle.net/10261/189805reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/689518https://doi.org/10.1016/j.ecolmodel.2019.05.005Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1898052026-05-22T06:33:51Z
dc.title.none.fl_str_mv Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
title Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
spellingShingle Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
Coll, Marta
Mediterranean Sea
Commercial species
Ecospace
Bayesian models
Species distribution models
Spatial ecology
Food-web model
title_short Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
title_full Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
title_fullStr Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
title_full_unstemmed Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
title_sort Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches
dc.creator.none.fl_str_mv Coll, Marta
Pennino, Maria Grazia
Steenbeek, Jeroen
Solé, Jordi
Bellido, José M.
author Coll, Marta
author_facet Coll, Marta
Pennino, Maria Grazia
Steenbeek, Jeroen
Solé, Jordi
Bellido, José M.
author_role author
author2 Pennino, Maria Grazia
Steenbeek, Jeroen
Solé, Jordi
Bellido, José M.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Economía y Competitividad (España)
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Mediterranean Sea
Commercial species
Ecospace
Bayesian models
Species distribution models
Spatial ecology
Food-web model
topic Mediterranean Sea
Commercial species
Ecospace
Bayesian models
Species distribution models
Spatial ecology
Food-web model
description 16 pages, 9 figures, 3 tables, 1 appendix
publishDate 2019
dc.date.none.fl_str_mv 2019
2019
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Preprint
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/189805
url http://hdl.handle.net/10261/189805
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/689518
https://doi.org/10.1016/j.ecolmodel.2019.05.005
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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