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Predicting fine-scale distributions of peripheral aquatic species in headwater streams

Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The sou...

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Autores principales: DeRolph, Christopher R, Nelson, Stacy A C, Kwak, Thomas J, Hain, Ernie F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298442/
https://www.ncbi.nlm.nih.gov/pubmed/25628872
http://dx.doi.org/10.1002/ece3.1331
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author DeRolph, Christopher R
Nelson, Stacy A C
Kwak, Thomas J
Hain, Ernie F
author_facet DeRolph, Christopher R
Nelson, Stacy A C
Kwak, Thomas J
Hain, Ernie F
author_sort DeRolph, Christopher R
collection PubMed
description Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients.
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spelling pubmed-42984422015-01-27 Predicting fine-scale distributions of peripheral aquatic species in headwater streams DeRolph, Christopher R Nelson, Stacy A C Kwak, Thomas J Hain, Ernie F Ecol Evol Original Research Headwater species and peripheral populations that occupy habitat at the edge of a species range may hold an increased conservation value to managers due to their potential to maximize intraspecies diversity and species' adaptive capabilities in the context of rapid environmental change. The southern Appalachian Mountains are the southern extent of the geographic range of native Salvelinus fontinalis and naturalized Oncorhynchus mykiss and Salmo trutta in eastern North America. We predicted distributions of these peripheral, headwater wild trout populations at a fine scale to serve as a planning and management tool for resource managers to maximize resistance and resilience of these populations in the face of anthropogenic stressors. We developed correlative logistic regression models to predict occurrence of brook trout, rainbow trout, and brown trout for every interconfluence stream reach in the study area. A stream network was generated to capture a more consistent representation of headwater streams. Each of the final models had four significant metrics in common: stream order, fragmentation, precipitation, and land cover. Strahler stream order was found to be the most influential variable in two of the three final models and the second most influential variable in the other model. Greater than 70% presence accuracy was achieved for all three models. The underrepresentation of headwater streams in commonly used hydrography datasets is an important consideration that warrants close examination when forecasting headwater species distributions and range estimates. Additionally, it appears that a relative watershed position metric (e.g., stream order) is an important surrogate variable (even when elevation is included) for biotic interactions across the landscape in areas where headwater species distributions are influenced by topographical gradients. BlackWell Publishing Ltd 2015-01 2014-12-09 /pmc/articles/PMC4298442/ /pubmed/25628872 http://dx.doi.org/10.1002/ece3.1331 Text en © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
spellingShingle Original Research
DeRolph, Christopher R
Nelson, Stacy A C
Kwak, Thomas J
Hain, Ernie F
Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title_full Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title_fullStr Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title_full_unstemmed Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title_short Predicting fine-scale distributions of peripheral aquatic species in headwater streams
title_sort predicting fine-scale distributions of peripheral aquatic species in headwater streams
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298442/
https://www.ncbi.nlm.nih.gov/pubmed/25628872
http://dx.doi.org/10.1002/ece3.1331
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