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

Drivers of species distributions and their predictions have been a long-standing search in ecology, with approaches varying from deterministic to neutral (i.e. stochastic) and almost everything in between (e.g. near neutral, continuum or emergent-neutral1,2 ). Most models are based on prior assumpti...

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मुख्य लेखक: Pos, Edwin (author)
अन्य लेखक: de Souza Coelho, Luiz (author), de Andrade Lima Filho, Diogenes (author), Salomão, Rafael P. (author), Leão Amaral, Iêda (author), deAlmeida Matos, Francisca Dionízia (author), Castilho, CarolinaV. (author), Phillips, Oliver L. (author), Guevara, Juan Ernesto (author), Veiga Carim, Marcelo de Jesus (author), Cárdenas López, Dairon (author), Magnusson, William E. (author), Wittmann, Florian (author), Irume, Mariana Victória (author), Pires Martins, Maria (author), Sabatier, Daniel (author), da Silva Guimarães, José Renan (author), Molino, Jean François (author), Monteagudo Mendoza, Abel (author), Peñuela Mora, María Cristina (author)
स्वरूप: article
प्रकाशित: 2023
विषय:
ऑनलाइन पहुंच:http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/656
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_version_ 1838788998018891776
author Pos, Edwin
author2 de Souza Coelho, Luiz
de Andrade Lima Filho, Diogenes
Salomão, Rafael P.
Leão Amaral, Iêda
deAlmeida Matos, Francisca Dionízia
Castilho, CarolinaV.
Phillips, Oliver L.
Guevara, Juan Ernesto
Veiga Carim, Marcelo de Jesus
Cárdenas López, Dairon
Magnusson, William E.
Wittmann, Florian
Irume, Mariana Victória
Pires Martins, Maria
Sabatier, Daniel
da Silva Guimarães, José Renan
Molino, Jean François
Monteagudo Mendoza, Abel
Peñuela Mora, María Cristina
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author_facet Pos, Edwin
de Souza Coelho, Luiz
de Andrade Lima Filho, Diogenes
Salomão, Rafael P.
Leão Amaral, Iêda
deAlmeida Matos, Francisca Dionízia
Castilho, CarolinaV.
Phillips, Oliver L.
Guevara, Juan Ernesto
Veiga Carim, Marcelo de Jesus
Cárdenas López, Dairon
Magnusson, William E.
Wittmann, Florian
Irume, Mariana Victória
Pires Martins, Maria
Sabatier, Daniel
da Silva Guimarães, José Renan
Molino, Jean François
Monteagudo Mendoza, Abel
Peñuela Mora, María Cristina
author_role author
collection Repositorio Universidad Regional Amazónica
dc.creator.none.fl_str_mv Pos, Edwin
de Souza Coelho, Luiz
de Andrade Lima Filho, Diogenes
Salomão, Rafael P.
Leão Amaral, Iêda
deAlmeida Matos, Francisca Dionízia
Castilho, CarolinaV.
Phillips, Oliver L.
Guevara, Juan Ernesto
Veiga Carim, Marcelo de Jesus
Cárdenas López, Dairon
Magnusson, William E.
Wittmann, Florian
Irume, Mariana Victória
Pires Martins, Maria
Sabatier, Daniel
da Silva Guimarães, José Renan
Molino, Jean François
Monteagudo Mendoza, Abel
Peñuela Mora, María Cristina
dc.date.none.fl_str_mv 2023-03-31T19:13:41Z
2023-03-31T19:13:41Z
2023
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv Pos, Edwin & Coelho, Fernanda & Filho, Diogenes & Salomão, Rafael & Amaral, Iêda & Matos, Francisca & Castilho, Carolina & Phillips, Oliver & Guevara Andino, Juan & Carim, Marcelo & López, Dairon & Magnusson, William & Wittmann, F. & Irume, Mariana & Martins, Maria & Sabatier, Daniel & Guimarães, José & Molino, Jean-François & Bánki, Olaf & ter Steege, Hans. (2023). Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology. Scientific Reports. 13. 10.1038/s41598-023-28132-y.
http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/656
dc.language.none.fl_str_mv en
dc.relation.none.fl_str_mv PRODUCCIÓN CIENTÍFICA-ARTÍCULOS CIENTÍFICOS;A-IKIAM-000448
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:Repositorio Universidad Regional Amazónica
instname:Universidad Regional Amazónica
instacron:IKIAM
dc.subject.none.fl_str_mv Amazon tree
Amazónicos
Entropy
Tropical forest
Ecology
dc.title.none.fl_str_mv Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Drivers of species distributions and their predictions have been a long-standing search in ecology, with approaches varying from deterministic to neutral (i.e. stochastic) and almost everything in between (e.g. near neutral, continuum or emergent-neutral1,2 ). Most models are based on prior assumptions of processes that drive community dynamics. Te Maximum Entropy Formalism (hereafer called MEF) makes no such, potentially unjustifed, a-priori assumptions in generating predictions of species abundance distributions, as such it is a use ful construct to infer processes driving community dynamics given the constraints imposed by prior knowledge (e.g. functional traits or summed regional abundances)3 . Quantifying the relative importance of these distinct constraints can thus provide additional answers to understand the complexity of community dynamics (see Supporting Materials SM: boxes S1–S3). Tis is especially so because, although many diferent tests are available that link variation in taxon abundances to (1) trait variation, (2) taxon turnover between habitats or environ ments and (3) the distance decay of similarities between samples, none quantify the importance of these relative to each other. Te MEF as applied here, however, is capable of and designed to do exactly this by decomposing variation to separate information explained by each of these aspects in a four-step model (Fig. 1 and Box S2). Its application to an unprecedented large tree inventory database on genus level taxonomy consisting of>2,000 1-ha plots distributed over Amazonia4 and a genus trait database of 13 key functional traits representing global axes of plant strategies5 allows us to advance the study of Amazonian tree community dynamics from a new cross-disciplinary perspective.
eu_rights_str_mv openAccess
format article
id IKIAM_1d9f08d0368960738347dda2144b6d2f
identifier_str_mv Pos, Edwin & Coelho, Fernanda & Filho, Diogenes & Salomão, Rafael & Amaral, Iêda & Matos, Francisca & Castilho, Carolina & Phillips, Oliver & Guevara Andino, Juan & Carim, Marcelo & López, Dairon & Magnusson, William & Wittmann, F. & Irume, Mariana & Martins, Maria & Sabatier, Daniel & Guimarães, José & Molino, Jean-François & Bánki, Olaf & ter Steege, Hans. (2023). Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology. Scientific Reports. 13. 10.1038/s41598-023-28132-y.
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institution IKIAM
instname_str Universidad Regional Amazónica
language_invalid_str_mv en
network_acronym_str IKIAM
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publishDate 2023
reponame_str Repositorio Universidad Regional Amazónica
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repository.name.fl_str_mv Repositorio Universidad Regional Amazónica - Universidad Regional Amazónica
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spelling Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecologyPos, Edwinde Souza Coelho, Luizde Andrade Lima Filho, DiogenesSalomão, Rafael P.Leão Amaral, IêdadeAlmeida Matos, Francisca DioníziaCastilho, CarolinaV.Phillips, Oliver L.Guevara, Juan ErnestoVeiga Carim, Marcelo de JesusCárdenas López, DaironMagnusson, William E.Wittmann, FlorianIrume, Mariana VictóriaPires Martins, MariaSabatier, Danielda Silva Guimarães, José RenanMolino, Jean FrançoisMonteagudo Mendoza, AbelPeñuela Mora, María CristinaAmazon treeAmazónicosEntropyTropical forestEcologyDrivers of species distributions and their predictions have been a long-standing search in ecology, with approaches varying from deterministic to neutral (i.e. stochastic) and almost everything in between (e.g. near neutral, continuum or emergent-neutral1,2 ). Most models are based on prior assumptions of processes that drive community dynamics. Te Maximum Entropy Formalism (hereafer called MEF) makes no such, potentially unjustifed, a-priori assumptions in generating predictions of species abundance distributions, as such it is a use ful construct to infer processes driving community dynamics given the constraints imposed by prior knowledge (e.g. functional traits or summed regional abundances)3 . Quantifying the relative importance of these distinct constraints can thus provide additional answers to understand the complexity of community dynamics (see Supporting Materials SM: boxes S1–S3). Tis is especially so because, although many diferent tests are available that link variation in taxon abundances to (1) trait variation, (2) taxon turnover between habitats or environ ments and (3) the distance decay of similarities between samples, none quantify the importance of these relative to each other. Te MEF as applied here, however, is capable of and designed to do exactly this by decomposing variation to separate information explained by each of these aspects in a four-step model (Fig. 1 and Box S2). Its application to an unprecedented large tree inventory database on genus level taxonomy consisting of>2,000 1-ha plots distributed over Amazonia4 and a genus trait database of 13 key functional traits representing global axes of plant strategies5 allows us to advance the study of Amazonian tree community dynamics from a new cross-disciplinary perspective.2023-03-31T19:13:41Z2023-03-31T19:13:41Z2023info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfPos, Edwin & Coelho, Fernanda & Filho, Diogenes & Salomão, Rafael & Amaral, Iêda & Matos, Francisca & Castilho, Carolina & Phillips, Oliver & Guevara Andino, Juan & Carim, Marcelo & López, Dairon & Magnusson, William & Wittmann, F. & Irume, Mariana & Martins, Maria & Sabatier, Daniel & Guimarães, José & Molino, Jean-François & Bánki, Olaf & ter Steege, Hans. (2023). Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology. Scientific Reports. 13. 10.1038/s41598-023-28132-y.http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/656enPRODUCCIÓN CIENTÍFICA-ARTÍCULOS CIENTÍFICOS;A-IKIAM-000448info:eu-repo/semantics/openAccessreponame:Repositorio Universidad Regional Amazónicainstname:Universidad Regional Amazónicainstacron:IKIAM2023-04-01T08:00:37Zoai:repositorio.ikiam.edu.ec:RD_IKIAM/656Institucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oaiEcuador...opendoar:02025-07-27T07:51:28.914695trueInstitucionalhttps://repositorio.ikiam.edu.ec/Universidad públicahttps://www.ikiam.edu.ec/https://repositorio.ikiam.edu.ec/oai.Ecuador...opendoar:02025-07-27T07:51:28.914695Repositorio Universidad Regional Amazónica - Universidad Regional Amazónicatrue
spellingShingle Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
Pos, Edwin
Amazon tree
Amazónicos
Entropy
Tropical forest
Ecology
status_str publishedVersion
title Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
title_full Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
title_fullStr Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
title_full_unstemmed Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
title_short Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
title_sort Unraveling Amazon tree community assembly using Maximum Information Entropy: a quantitative analysis of tropical forest ecology
topic Amazon tree
Amazónicos
Entropy
Tropical forest
Ecology
url http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/656