The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean

Species distribution models (SDMs) have been used to predict potential distributions of habitats and to model the effects of environmental changes. Despite their usefulness, currently there is no standardized sampling strategy that provides suitable and sufficiently representative predictive models...

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Detalles Bibliográficos
Autores: Cefalì, Maria Elena, Ballesteros, Enric, Riera, Joan Lluís, Chappuis, Eglantine, Terradas, Marc, Mariani, Simone, Cebrián, Emma
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/320179
Acceso en línea:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197234&type=printable
http://hdl.handle.net/10261/320179
Access Level:acceso abierto
Palabra clave:Sede Central IEO
Medio Marino y Protección Ambiental
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spelling The optimal sampling design for littoral habitats modelling: A case study from the north-western MediterraneanCefalì, Maria ElenaBallesteros, EnricRiera, Joan LluísChappuis, EglantineTerradas, MarcMariani, SimoneCebrián, EmmaSede Central IEOMedio Marino y Protección AmbientalSpecies distribution models (SDMs) have been used to predict potential distributions of habitats and to model the effects of environmental changes. Despite their usefulness, currently there is no standardized sampling strategy that provides suitable and sufficiently representative predictive models for littoral marine benthic habitats. Here we aim to establish the best performing and most cost-effective sample design to predict the distribution of littoral habitats in unexplored areas. We also study how environmental variability, sample size, and habitat prevalence may influence the accuracy and performance of spatial predictions. For first time, a large database of littoral habitats (16,098 points over 562,895 km of coastline) is used to build up, evaluate, and validate logistic predictive models according to a variety of sampling strategies. A regularly interspaced strategy with a sample of 20% of the coastline provided the best compromise between usefulness (in terms of sampling cost and effort) and accuracy. However, model performance was strongly depen upon habitat characteristics. The proposed sampling strategy may help to predict the presence or absence of target species or habitats thus improving extensive cartographies, detect high biodiversity areas, and, lastly, develop (the best) environmental management plans, especially in littoral environments.Public Library of ScienceConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202320232018info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197234&type=printablehttp://hdl.handle.net/10261/320179reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésSede Central IEOSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3201792026-05-22T06:33:51Z
dc.title.none.fl_str_mv The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
title The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
spellingShingle The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
Cefalì, Maria Elena
Sede Central IEO
Medio Marino y Protección Ambiental
title_short The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
title_full The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
title_fullStr The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
title_full_unstemmed The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
title_sort The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
dc.creator.none.fl_str_mv Cefalì, Maria Elena
Ballesteros, Enric
Riera, Joan Lluís
Chappuis, Eglantine
Terradas, Marc
Mariani, Simone
Cebrián, Emma
author Cefalì, Maria Elena
author_facet Cefalì, Maria Elena
Ballesteros, Enric
Riera, Joan Lluís
Chappuis, Eglantine
Terradas, Marc
Mariani, Simone
Cebrián, Emma
author_role author
author2 Ballesteros, Enric
Riera, Joan Lluís
Chappuis, Eglantine
Terradas, Marc
Mariani, Simone
Cebrián, Emma
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Sede Central IEO
Medio Marino y Protección Ambiental
topic Sede Central IEO
Medio Marino y Protección Ambiental
description Species distribution models (SDMs) have been used to predict potential distributions of habitats and to model the effects of environmental changes. Despite their usefulness, currently there is no standardized sampling strategy that provides suitable and sufficiently representative predictive models for littoral marine benthic habitats. Here we aim to establish the best performing and most cost-effective sample design to predict the distribution of littoral habitats in unexplored areas. We also study how environmental variability, sample size, and habitat prevalence may influence the accuracy and performance of spatial predictions. For first time, a large database of littoral habitats (16,098 points over 562,895 km of coastline) is used to build up, evaluate, and validate logistic predictive models according to a variety of sampling strategies. A regularly interspaced strategy with a sample of 20% of the coastline provided the best compromise between usefulness (in terms of sampling cost and effort) and accuracy. However, model performance was strongly depen upon habitat characteristics. The proposed sampling strategy may help to predict the presence or absence of target species or habitats thus improving extensive cartographies, detect high biodiversity areas, and, lastly, develop (the best) environmental management plans, especially in littoral environments.
publishDate 2018
dc.date.none.fl_str_mv 2018
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197234&type=printable
http://hdl.handle.net/10261/320179
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0197234&type=printable
http://hdl.handle.net/10261/320179
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sede Central IEO
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Public Library of Science
publisher.none.fl_str_mv Public Library of Science
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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