The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean
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Título: | The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean |
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Autor/es: | Cefalì, Maria Elena | Ballesteros, Enric | Riera, Joan Lluís | Chappuis, Eglantine | Terradas, Marc | Mariani, Simone | Cebrian, Emma |
Grupo/s de investigación o GITE: | Fitopatología |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ciencias del Mar y Biología Aplicada |
Palabras clave: | Sampling design | Littoral habitats modelling | North-western Mediterranean |
Área/s de conocimiento: | Botánica |
Fecha de publicación: | 24-may-2018 |
Editor: | Public Library of Science (PLoS) |
Cita bibliográfica: | Cefalì ME, Ballesteros E, Riera JL, Chappuis E, Terradas M, Mariani S, et al. (2018) The optimal sampling design for littoral habitats modelling: A case study from the north-western Mediterranean. PLoS ONE 13(5): e0197234. https://doi.org/10.1371/journal.pone.0197234 |
Resumen: | 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. |
Patrocinador/es: | This study was supported by INTRAMURAL CSIC (0065) and the European Union’s Horizon 2020 (689518) MERCES. |
URI: | http://hdl.handle.net/10045/75989 |
ISSN: | 1932-6203 |
DOI: | 10.1371/journal.pone.0197234 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2018 Cefalì et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1371/journal.pone.0197234 |
Aparece en las colecciones: | INV - Fitopatología - Artículos de Revistas Investigaciones financiadas por la UE |
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