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 ORCID: 0000-0002-2645-4380, de Almeida Matos, Francisca Dionízia, Castilho, Carolina V, Phillips, Oliver L, Guevara, Juan Ernesto, de Jesus Veiga Carim, Marcelo
et al (show 206 more authors) (2023) Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology. Scientific reports, 13 (1). 2859-.

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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
Uncontrolled Keywords: Plants, Ecology, Ecosystem, Biodiversity, Tropical Climate, Entropy, Forests
Divisions: Faculty of Science and Engineering > School of Environmental Sciences
Depositing User: Symplectic Admin
Date Deposited: 14 May 2023 15:50
Last Modified: 14 May 2023 15:50
DOI: 10.1038/s41598-023-28132-y
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3170338