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Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology

Pos, Edwin, de Souza Coelho, Luiz, de Andrade Lima Filho, Diogenes, Salomão, Rafael P, Amaral, Iêda Leão, de Almeida Matos, Francisca Dionízia, Castilho, Carolina V, Phillips, Oliver L, Guevara, Juan Ernesto, de Jesus Veiga Carim, Marcelo, and others. (2023) Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology. Scientific Reports, 13 (1). Article Number 2859. E-ISSN 2045-2322. (doi:10.1038/s41598-023-28132-y) (KAR id:100590)

Abstract

In a time of rapid global change, the question of what determines patterns in species abundance distribution remains a priority for understanding the complex dynamics of ecosystems. The constrained maximization of information entropy provides a framework for the understanding of such complex systems dynamics by a quantitative analysis of important constraints via predictions using least biased probability distributions. We apply it to over two thousand hectares of Amazonian tree inventories across seven forest types and thirteen functional traits, representing major global axes of plant strategies. Results show that constraints formed by regional relative abundances of genera explain eight times more of local relative abundances than constraints based on directional selection for specific functional traits, although the latter does show clear signals of environmental dependency. These results provide a quantitative insight by inference from large-scale data using cross-disciplinary methods, furthering our understanding of ecological dynamics.

Item Type: Article
DOI/Identification number: 10.1038/s41598-023-28132-y
Additional information: For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising
Uncontrolled keywords: Plants, Ecology, Ecosystem, Biodiversity, Tropical Climate, Entropy, Forests
Subjects: G Geography. Anthropology. Recreation > GN Anthropology
Divisions: Divisions > Division of Human and Social Sciences > School of Anthropology and Conservation
Funders: Agence Nationale de la Recherche (https://ror.org/00rbzpz17)
Natural Environment Research Council (https://ror.org/02b5d8509)
National Science Foundation (https://ror.org/021nxhr62)
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 13 Apr 2023 15:05 UTC
Last Modified: 05 Nov 2024 13:06 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/100590 (The current URI for this page, for reference purposes)

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