Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives

Variance partitioning methods, which are built upon multivariate statistics, have been widely applied in different taxa and habitats in community ecology. Here, I performed a literature review on the development and application of the methods, and then discussed the limitation of available methods a...

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Main Author: Youhua Chen
Format: Article
Language:English
Published: International Academy of Ecology and Environmental Sciences 2015-06-01
Series:Computational Ecology and Software
Subjects:
Online Access:http://www.iaees.org/publications/journals/ces/articles/2015-5(2)/distinguishing-niche-and-neutral-processes.pdf
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spelling doaj-97d8c58e367b429888b2353824e956372020-11-25T01:50:56ZengInternational Academy of Ecology and Environmental SciencesComputational Ecology and Software2220-721X2220-721X2015-06-0152130138Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectivesYouhua Chen0Department of Renewable Resources, University of Alberta, Edmonton, T6G 2H1, CanadaVariance partitioning methods, which are built upon multivariate statistics, have been widely applied in different taxa and habitats in community ecology. Here, I performed a literature review on the development and application of the methods, and then discussed the limitation of available methods and the difficulties involved in sampling schemes. The central goal of the work is then to propose some potential practical methods that might help to overcome different issues of traditional least-square-based regression modeling. A variety of regression models has been considered for comparison. In initial simulations, I identified that generalized additive model (GAM) has the highest accuracy to predict variation components. Therefore, I argued that other advanced regression techniques, including the GAM and related models, could be utilized in variation partitioning for better quantifying the aggregation scenarios of species distribution.http://www.iaees.org/publications/journals/ces/articles/2015-5(2)/distinguishing-niche-and-neutral-processes.pdfmultivariate ordinationregression modelsgeneral additive modelsdispersal limitationenvironmental filtering
collection DOAJ
language English
format Article
sources DOAJ
author Youhua Chen
spellingShingle Youhua Chen
Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
Computational Ecology and Software
multivariate ordination
regression models
general additive models
dispersal limitation
environmental filtering
author_facet Youhua Chen
author_sort Youhua Chen
title Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
title_short Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
title_full Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
title_fullStr Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
title_full_unstemmed Distinguishing niche and neutral processes: Issues in variation partitioning statistical methods and further perspectives
title_sort distinguishing niche and neutral processes: issues in variation partitioning statistical methods and further perspectives
publisher International Academy of Ecology and Environmental Sciences
series Computational Ecology and Software
issn 2220-721X
2220-721X
publishDate 2015-06-01
description Variance partitioning methods, which are built upon multivariate statistics, have been widely applied in different taxa and habitats in community ecology. Here, I performed a literature review on the development and application of the methods, and then discussed the limitation of available methods and the difficulties involved in sampling schemes. The central goal of the work is then to propose some potential practical methods that might help to overcome different issues of traditional least-square-based regression modeling. A variety of regression models has been considered for comparison. In initial simulations, I identified that generalized additive model (GAM) has the highest accuracy to predict variation components. Therefore, I argued that other advanced regression techniques, including the GAM and related models, could be utilized in variation partitioning for better quantifying the aggregation scenarios of species distribution.
topic multivariate ordination
regression models
general additive models
dispersal limitation
environmental filtering
url http://www.iaees.org/publications/journals/ces/articles/2015-5(2)/distinguishing-niche-and-neutral-processes.pdf
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