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Predicting presence and absence of trout (Salmo trutta) in Iran

Species distribution modelling, as a central issue in freshwater ecology, is an important tool for conservation and management of aquatic ecosystems. The brown trout (Salmo trutta) is a sensitive species which reacts to habitat changes induced by human impacts. Therefore, the identification of suita...

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Autores principales: Mostafavi, Hossein, Pletterbauer, Florian, Coad, Brian W., Mahini, Abdolrassoul Salman, Schinegger, Rafaela, Unfer, Günther, Trautwein, Clemens, Schmutz, Stefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Urban and Fischer 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974070/
https://www.ncbi.nlm.nih.gov/pubmed/24707064
http://dx.doi.org/10.1016/j.limno.2013.12.001
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author Mostafavi, Hossein
Pletterbauer, Florian
Coad, Brian W.
Mahini, Abdolrassoul Salman
Schinegger, Rafaela
Unfer, Günther
Trautwein, Clemens
Schmutz, Stefan
author_facet Mostafavi, Hossein
Pletterbauer, Florian
Coad, Brian W.
Mahini, Abdolrassoul Salman
Schinegger, Rafaela
Unfer, Günther
Trautwein, Clemens
Schmutz, Stefan
author_sort Mostafavi, Hossein
collection PubMed
description Species distribution modelling, as a central issue in freshwater ecology, is an important tool for conservation and management of aquatic ecosystems. The brown trout (Salmo trutta) is a sensitive species which reacts to habitat changes induced by human impacts. Therefore, the identification of suitable habitats is essential. This study explores the potential distribution of brown trout by a species distribution modelling approach for Iran. Furthermore, modelling results are compared to the distribution described in the literature. Areas outside the currently known distribution which may offer potential habitats for brown trout are identified. The species distribution modelling was based on five different modelling techniques: Generalised Linear Model, Generalised Additive Model, Generalised Boosting Model, Classification Tree Analysis and Random Forests, which are finally summarised in an ensemble forecasting approach. We considered four environmental descriptors at the local scale (slope, bankfull width, wetted width, and elevation) and three climatic parameters (mean air temperature, range of air temperature and annual precipitation) which were extracted on three different spatial extents (1/5/10 km). The performance of all models was excellent (≥0.8) according to the TSS (True Skill Statistic) criterion. Slope, mean and range of air temperature were the most important variables in predicting brown trout occurrence. Presented results deepen the knowledge about distribution patterns of brown trout in Iran. Moreover, this study gives a basic background for the future development of assessment methods for riverine ecosystems in Iran.
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spelling pubmed-39740702014-04-03 Predicting presence and absence of trout (Salmo trutta) in Iran Mostafavi, Hossein Pletterbauer, Florian Coad, Brian W. Mahini, Abdolrassoul Salman Schinegger, Rafaela Unfer, Günther Trautwein, Clemens Schmutz, Stefan Limnologica Article Species distribution modelling, as a central issue in freshwater ecology, is an important tool for conservation and management of aquatic ecosystems. The brown trout (Salmo trutta) is a sensitive species which reacts to habitat changes induced by human impacts. Therefore, the identification of suitable habitats is essential. This study explores the potential distribution of brown trout by a species distribution modelling approach for Iran. Furthermore, modelling results are compared to the distribution described in the literature. Areas outside the currently known distribution which may offer potential habitats for brown trout are identified. The species distribution modelling was based on five different modelling techniques: Generalised Linear Model, Generalised Additive Model, Generalised Boosting Model, Classification Tree Analysis and Random Forests, which are finally summarised in an ensemble forecasting approach. We considered four environmental descriptors at the local scale (slope, bankfull width, wetted width, and elevation) and three climatic parameters (mean air temperature, range of air temperature and annual precipitation) which were extracted on three different spatial extents (1/5/10 km). The performance of all models was excellent (≥0.8) according to the TSS (True Skill Statistic) criterion. Slope, mean and range of air temperature were the most important variables in predicting brown trout occurrence. Presented results deepen the knowledge about distribution patterns of brown trout in Iran. Moreover, this study gives a basic background for the future development of assessment methods for riverine ecosystems in Iran. Urban and Fischer 2014-03 /pmc/articles/PMC3974070/ /pubmed/24707064 http://dx.doi.org/10.1016/j.limno.2013.12.001 Text en © 2013 Elsevier GmbH. All rights reserved. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Mostafavi, Hossein
Pletterbauer, Florian
Coad, Brian W.
Mahini, Abdolrassoul Salman
Schinegger, Rafaela
Unfer, Günther
Trautwein, Clemens
Schmutz, Stefan
Predicting presence and absence of trout (Salmo trutta) in Iran
title Predicting presence and absence of trout (Salmo trutta) in Iran
title_full Predicting presence and absence of trout (Salmo trutta) in Iran
title_fullStr Predicting presence and absence of trout (Salmo trutta) in Iran
title_full_unstemmed Predicting presence and absence of trout (Salmo trutta) in Iran
title_short Predicting presence and absence of trout (Salmo trutta) in Iran
title_sort predicting presence and absence of trout (salmo trutta) in iran
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974070/
https://www.ncbi.nlm.nih.gov/pubmed/24707064
http://dx.doi.org/10.1016/j.limno.2013.12.001
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