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Beyond direct neighbourhood effects: higher-order interactions improve modelling and predicting tree survival and growth
Author(s) -
Yuanzhi Li,
Margaret M. Mayfield,
Bin Wang,
Junli Xiao,
Kamil Král,
David Janík,
Jan Holík,
Chengjin Chu
Publication year - 2020
Publication title -
national science review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.433
H-Index - 54
eISSN - 2095-5138
pISSN - 2053-714X
DOI - 10.1093/nsr/nwaa244
Subject(s) - pairwise comparison , tree (set theory) , temperate forest , neighbourhood (mathematics) , ecology , biology , temperate climate , statistics , mathematics , mathematical analysis
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.

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