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Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition
Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505320/ https://www.ncbi.nlm.nih.gov/pubmed/34546495 http://dx.doi.org/10.1007/s00442-021-05025-3 |
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author | Nakadai, Ryosuke |
author_facet | Nakadai, Ryosuke |
author_sort | Nakadai, Ryosuke |
collection | PubMed |
description | Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00442-021-05025-3. |
format | Online Article Text |
id | pubmed-8505320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-85053202021-10-19 Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition Nakadai, Ryosuke Oecologia Methods Beta-diversity was originally defined spatially, i.e., as variation in community composition among sites in a region. However, the concept of beta-diversity has since been expanded to temporal contexts. This is referred to as “temporal beta-diversity”, and most approaches are simply an extension of spatial beta-diversity. The persistence and turnover of individuals over time is a unique feature of temporal beta-diversity. Nakadai (2020) introduced the “individual-based beta-diversity” concept, and provided novel indices to evaluate individual turnover and compositional shift by comparing individual turnover between two periods at a given site. However, the proposed individual-based indices are applicable only to pairwise dissimilarity, not to multiple-temporal (or more generally, multiple-unit) dissimilarity. Here, individual-based beta-diversity indices are extended to multiple-unit cases. In addition, a novel type of random permutation criterion related to these multiple-unit indices for detecting patterns of individual persistence is introduced in the present study. To demonstrate the usage the properties of these indices compared to average pairwise measures, I applied them to a dataset for a permanent 50-ha forest dynamics plot on Barro Colorado Island in Panama. Information regarding “individuals” is generally missing from community ecology and biodiversity studies of temporal dynamics. In this context, the methods proposed here are expected to be useful for addressing a wide range of research questions regarding temporal changes in biodiversity, especially studies using traditional individual-tracked forest monitoring data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00442-021-05025-3. Springer Berlin Heidelberg 2021-09-21 2021 /pmc/articles/PMC8505320/ /pubmed/34546495 http://dx.doi.org/10.1007/s00442-021-05025-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Methods Nakadai, Ryosuke Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title | Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title_full | Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title_fullStr | Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title_full_unstemmed | Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title_short | Individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
title_sort | individual-based multiple-unit dissimilarity: novel indices and null model for assessing temporal variability in community composition |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8505320/ https://www.ncbi.nlm.nih.gov/pubmed/34546495 http://dx.doi.org/10.1007/s00442-021-05025-3 |
work_keys_str_mv | AT nakadairyosuke individualbasedmultipleunitdissimilaritynovelindicesandnullmodelforassessingtemporalvariabilityincommunitycomposition |