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

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.

Metadata

Item Type:	Article
Authors/Creators:	Pos, E de Souza Coelho, L de Andrade Lima Filho, D Salomão, RP Amaral, IL de Almeida Matos, FD Castilho, CV Phillips, OL https://orcid.org/0000-0002-8993-6168 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 Mostacedo, B Assis, RL Schöngart, J Castellanos, H de Medeiros, MB Simon, MF Andrade, A Camargo, JL Demarchi, LO Laurance, WF Laurance, SGW de Sousa Farias, E Lopes, MA Magalhães, JLL Nascimento, HEM de Queiroz, HL Aymard, GAC Brienen, R Revilla, JDC Costa, FRC Quaresma, A Vieira, ICG Cintra, BBL Stevenson, PR Feitosa, YO Duivenvoorden, JF Mogollón, HF Ferreira, LV Comiskey, JA Draper, F de Toledo, JJ Damasco, G Dávila, N García-Villacorta, R Lopes, A Vicentini, A Noronha, JC Barbosa, FR de Sá Carpanedo, R Emilio, T Levis, C de Jesus Rodrigues, D Schietti, J Souza, P Alonso, A Dallmeier, F Gomes, VHF Lloyd, J Neill, D de Aguiar, DPP Araujo-Murakami, A Arroyo, L Carvalho, FA de Souza, FC do Amaral, DD Feeley, KJ Gribel, R Pansonato, MP Barlow, J Berenguer, E Ferreira, J Fine, PVA Guedes, MC Jimenez, EM Licona, JC Mora, MCP Peres, CA Zegarra, BEV Cerón, C Henkel, TW Maas, P Silveira, M Stropp, J Thomas-Caesar, R Baker, TR https://orcid.org/0000-0002-3251-1679 Daly, D Dexter, KG Householder, JE Huamantupa-Chuquimaco, I Pennington, T Paredes, MR Fuentes, A Pena, JLM Silman, MR Tello, JS Chave, J Valverde, FC Di Fiore, A Hilário, RR Phillips, JF Rivas-Torres, G van Andel, TR von Hildebrand, P Barbosa, EM de Matos Bonates, LC Doza, HPD Fonty, É Gómez, RZ Gonzales, T Gonzales, GPG Guillaumet, J-L Hoffman, B Junqueira, AB Malhi, Y de Andrade Miranda, IP Pinto, LFM Prieto, A Rudas, A Ruschel, AR Silva, N Vela, CIA Vos, VA Zent, EL Zent, S Albuquerque, BW Cano, A Correa, DF Costa, JBP Flores, BM Holmgren, M Nascimento, MT Oliveira, AA Ramirez-Angulo, H Rocha, M Scudeller, VV Sierra, R Tirado, M Umaña, MN van der Heijden, G Torre, EV Vriesendorp, C Wang, O Young, KR Reategui, MAA Baider, C Balslev, H Cárdenas, S Casas, LF Farfan-Rios, W Ferreira, C Linares-Palomino, R Mendoza, C Mesones, I Torres-Lezama, A Giraldo, LEU Villarroel, D Zagt, R Alexiades, MN Garcia-Cabrera, K Hernandez, L Milliken, W Cuenca, WP Pansini, S Pauletto, D Arevalo, FR Sampaio, AF Sandoval, EHV Gamarra, LV Boenisch, G Kattge, J Kraft, N Levesley, A Melgaço, K Pickavance, G Poorter, L Ter Steege, H
Copyright, Publisher and Additional Information:	© The Author(s) 2023. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.
Keywords:	Ecosystem; Entropy; Biodiversity; Forests; Plants; Ecology; Tropical Climate
Dates:	Published: 17 February 2023 Published (online): 17 February 2023 Accepted: 13 January 2023
Institution:	The University of Leeds
Academic Units:	The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > Ecology & Global Change (Leeds)
Funding Information:	Funder Grant number Leverhulme Trust RF/2/RFG/2004/0457 EU - European Union EXT 448221 Gordon & Betty Moore Foundation N/A EU - European Union 291585 (ERC 2011 ADG) NERC (Natural Environment Research Council) NER/A/S/2003/00609
Depositing User:	Symplectic Publications
Date Deposited:	28 Feb 2023 12:15
Last Modified:	28 Feb 2023 12:16
Status:	Published
Publisher:	Nature Research
Identification Number:	10.1038/s41598-023-28132-y
Related URLs:	PubMed URL
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:196819

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

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