Publicación Artículo científico (article).

Modelling seabirds biodiversity through Bayesian Spatial Beta regression models: A proxy to inform marine protected areas in the Mediterranean Sea

Digital.CSIC. Repositorio Institucional del CSIC
Digital.CSIC. Repositorio Institucional del CSIC
  • Sarzo, Blanca
  • Martínez-Minaya, Joaquín
  • Pennino, Maria Grazia
  • Conesa, David
  • Coll, Marta
10 pages, 6 figures, 4 tables.-- Data availability: The code is available in the github repository of the first author as stated in the manuscript, Seabirds are bioindicators of marine ecosystems health and one of the world's most endangered avian groups. The creation of marine protected areas plays an important role in the conservation of marine environment and its biodiversity. The distributions of top predators, as seabirds, have been commonly used for the management and creation of these figures of protection. The main objective of this study is to investigate seabirds biodiversity distribution in the Mediterranean Sea through the use of Bayesian spatial Beta regression models. We used an extensive historical database of at-sea locations of 19 different seabird species as well as geophysical, climatology variables and cumulative anthropogenic threats to model species biodiversity. We found negative associations between seabirds biodiversity and distance to the coast as well as concavity of the seabed, and positive with chlorophyll and slope. Further, a positive association was found between seabirds biodiversity and coastal impact. In this study we define as hot spot of seabird biodiversity those areas with a posterior predictive mean over 0.50. We found potential hot spots in the Mediterranean Sea which do not overlap with the existing MPASs and marine IBAs. Specifically, our hot spots areas do not overlap with the 52.04% and 16.87% of the current MPAs and marine IBAs, respectively. Overall, our study highlights the need for the extension of spatial prioritization of conservation areas to seabirds biodiversity, addressing the challenges of establishing transboundary governance, BS was supported by Margarita Salas fellowship from Ministry of Universities-University of Valencia (MS21-013). JM-M would like to thank for the support by the Basque Government through the BERC 2018–2021 program and by the Ministry of Science, Innovation and Universities: BCAM Severo Ochoa accreditation SEV-2017-0718 and PID2020-115882RB-I00 research project. DC would like to thank the Spanish Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación for grant PID2019-106341 GB-I00 (jointly financed by the European Regional Development Fund, FEDER). MC acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869300 (FutureMares project) and No 101059407 (MarinePlan), and the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), Peer reviewed

Digital.CSIC. Repositorio Institucional del CSIC

Digital.CSIC. Repositorio Institucional del CSIC
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Digital.CSIC. Repositorio Institucional del CSIC