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Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth
It is known that biotic interactions are the key to species coexistence and maintenance of species diversity. Traditional studies focus overwhelmingly on pairwise interactions between organisms, ignoring complex higher-order interactions (HOIs). In this study, we present a novel method of calculatin...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8288344/ https://www.ncbi.nlm.nih.gov/pubmed/34691640 http://dx.doi.org/10.1093/nsr/nwaa244 |
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author | Li, Yuanzhi Mayfield, Margaret M Wang, Bin Xiao, Junli Kral, Kamil Janik, David Holik, Jan Chu, Chengjin |
author_facet | Li, Yuanzhi Mayfield, Margaret M Wang, Bin Xiao, Junli Kral, Kamil Janik, David Holik, Jan Chu, Chengjin |
author_sort | Li, Yuanzhi |
collection | PubMed |
description | It is known that biotic interactions are the key to species coexistence and maintenance of species diversity. Traditional studies focus overwhelmingly on pairwise interactions between organisms, ignoring complex higher-order interactions (HOIs). In this study, we present a novel method of calculating individual-level HOIs for trees, and use this method to test the importance of size- and distance-dependent individual-level HOIs to tree performance in a 25-ha temperate forest dynamic plot. We found that full HOI-inclusive models improved our ability to model and predict the survival and growth of trees, providing empirical evidence that HOIs strongly influence tree performance in this temperate forest. Specifically, assessed HOIs mitigate the competitive direct effects of neighbours on survival and growth of focal trees. Our study lays a foundation for future investigations of the prevalence and relative importance of HOIs in global forests and their impact on species diversity. |
format | Online Article Text |
id | pubmed-8288344 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82883442021-10-21 Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth Li, Yuanzhi Mayfield, Margaret M Wang, Bin Xiao, Junli Kral, Kamil Janik, David Holik, Jan Chu, Chengjin Natl Sci Rev Environment/Ecology It is known that biotic interactions are the key to species coexistence and maintenance of species diversity. Traditional studies focus overwhelmingly on pairwise interactions between organisms, ignoring complex higher-order interactions (HOIs). In this study, we present a novel method of calculating individual-level HOIs for trees, and use this method to test the importance of size- and distance-dependent individual-level HOIs to tree performance in a 25-ha temperate forest dynamic plot. We found that full HOI-inclusive models improved our ability to model and predict the survival and growth of trees, providing empirical evidence that HOIs strongly influence tree performance in this temperate forest. Specifically, assessed HOIs mitigate the competitive direct effects of neighbours on survival and growth of focal trees. Our study lays a foundation for future investigations of the prevalence and relative importance of HOIs in global forests and their impact on species diversity. Oxford University Press 2020-09-23 /pmc/articles/PMC8288344/ /pubmed/34691640 http://dx.doi.org/10.1093/nsr/nwaa244 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Environment/Ecology Li, Yuanzhi Mayfield, Margaret M Wang, Bin Xiao, Junli Kral, Kamil Janik, David Holik, Jan Chu, Chengjin Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title | Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title_full | Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title_fullStr | Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title_full_unstemmed | Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title_short | Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
title_sort | beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth |
topic | Environment/Ecology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8288344/ https://www.ncbi.nlm.nih.gov/pubmed/34691640 http://dx.doi.org/10.1093/nsr/nwaa244 |
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