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Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season

During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and c...

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Autores principales: Warwick-Evans, Victoria C., Atkinson, Philip W., Robinson, Leonie A., Green, Jonathan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816348/
https://www.ncbi.nlm.nih.gov/pubmed/27031616
http://dx.doi.org/10.1371/journal.pone.0150592
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author Warwick-Evans, Victoria C.
Atkinson, Philip W.
Robinson, Leonie A.
Green, Jonathan A.
author_facet Warwick-Evans, Victoria C.
Atkinson, Philip W.
Robinson, Leonie A.
Green, Jonathan A.
author_sort Warwick-Evans, Victoria C.
collection PubMed
description During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney’s coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney’s seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making.
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spelling pubmed-48163482016-04-14 Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season Warwick-Evans, Victoria C. Atkinson, Philip W. Robinson, Leonie A. Green, Jonathan A. PLoS One Research Article During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney’s coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney’s seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making. Public Library of Science 2016-03-31 /pmc/articles/PMC4816348/ /pubmed/27031616 http://dx.doi.org/10.1371/journal.pone.0150592 Text en © 2016 Warwick-Evans et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Warwick-Evans, Victoria C.
Atkinson, Philip W.
Robinson, Leonie A.
Green, Jonathan A.
Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title_full Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title_fullStr Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title_full_unstemmed Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title_short Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season
title_sort predictive modelling to identify near-shore, fine-scale seabird distributions during the breeding season
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816348/
https://www.ncbi.nlm.nih.gov/pubmed/27031616
http://dx.doi.org/10.1371/journal.pone.0150592
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