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

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

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...

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Détails bibliographiques
Auteurs principaux: Pos, E, de Souza Coelho, L, de Andrade Lima Filho, D, Salomão, RP, Amaral, IL, de Almeida Matos, FD, Castilho, CV, Phillips, OL, Guevara, JE, de Jesus Veiga Carim, M, López, DC, Magnusson, WE, Wittmann, F, Irume, MV, Martins, MP, Sabatier, D, da Silva Guimarães, JR, Molino, J-F, Bánki, OS, Piedade, MTF, Pitman, NCA, Mendoza, AM, Ramos, JF, Hawes, JE, Almeida, EJ, Barbosa, LF, Cavalheiro, L, Dos Santos, MCV, Luize, BG, de Leão Novo, EMM, Vargas, PN, Silva, TSF, Venticinque, EM, Manzatto, AG, Reis, NFC, Terborgh, J, Casula, KR, Coronado, ENH, Montero, JC, Marimon, BS, Marimon-Junior, BH, Feldpausch, TR, Duque, A, Baraloto, C, Arboleda, NC, Engel, J, Petronelli, P, Zartman, CE, Killeen, TJ, Vasquez, R, Malhi, Y
Format: Journal article
Langue:English
Publié: Springer Nature 2023

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