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Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes

Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were...

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Autores principales: Galaiduk, Ronen, Radford, Ben T., Wilson, Shaun K., Harvey, Euan S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732166/
https://www.ncbi.nlm.nih.gov/pubmed/29247193
http://dx.doi.org/10.1038/s41598-017-17946-2
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author Galaiduk, Ronen
Radford, Ben T.
Wilson, Shaun K.
Harvey, Euan S.
author_facet Galaiduk, Ronen
Radford, Ben T.
Wilson, Shaun K.
Harvey, Euan S.
author_sort Galaiduk, Ronen
collection PubMed
description Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were used to model the probability of occurrence of six focal species after surveys that utilised two remote underwater video sampling methods (i.e. baited and towed video). Models developed for the towed video method had consistently better predictive performance for all but one study species although only three models had a good to fair fit, and the rest were poor fits, highlighting the challenges associated with modelling habitat associations of marine species in highly homogenous, low relief environments. Models based on baited video dataset regularly included large-scale measures of structural complexity, suggesting fish attraction to a single focus point by bait. Conversely, models based on the towed video data often incorporated small-scale measures of habitat complexity and were more likely to reflect true species-habitat relationships. The cost associated with use of the towed video systems for surveying low-relief seascapes was also relatively low providing additional support for considering this method for marine spatial ecological modelling.
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spelling pubmed-57321662017-12-21 Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes Galaiduk, Ronen Radford, Ben T. Wilson, Shaun K. Harvey, Euan S. Sci Rep Article Information on habitat associations from survey data, combined with spatial modelling, allow the development of more refined species distribution modelling which may identify areas of high conservation/fisheries value and consequentially improve conservation efforts. Generalised additive models were used to model the probability of occurrence of six focal species after surveys that utilised two remote underwater video sampling methods (i.e. baited and towed video). Models developed for the towed video method had consistently better predictive performance for all but one study species although only three models had a good to fair fit, and the rest were poor fits, highlighting the challenges associated with modelling habitat associations of marine species in highly homogenous, low relief environments. Models based on baited video dataset regularly included large-scale measures of structural complexity, suggesting fish attraction to a single focus point by bait. Conversely, models based on the towed video data often incorporated small-scale measures of habitat complexity and were more likely to reflect true species-habitat relationships. The cost associated with use of the towed video systems for surveying low-relief seascapes was also relatively low providing additional support for considering this method for marine spatial ecological modelling. Nature Publishing Group UK 2017-12-15 /pmc/articles/PMC5732166/ /pubmed/29247193 http://dx.doi.org/10.1038/s41598-017-17946-2 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Galaiduk, Ronen
Radford, Ben T.
Wilson, Shaun K.
Harvey, Euan S.
Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title_full Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title_fullStr Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title_full_unstemmed Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title_short Comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
title_sort comparing two remote video survey methods for spatial predictions of the distribution and environmental niche suitability of demersal fishes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732166/
https://www.ncbi.nlm.nih.gov/pubmed/29247193
http://dx.doi.org/10.1038/s41598-017-17946-2
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