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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Urban and Fischer
2014
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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. |
format | Online Article Text |
id | pubmed-3974070 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Urban and Fischer |
record_format | MEDLINE/PubMed |
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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