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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स्वरूप: | article |
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2023
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ऑनलाइन पहुंच: | http://repositorio.ikiam.edu.ec/jspui/handle/RD_IKIAM/656 |
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_version_ | 1838788998018891776 |
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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. |
instacron_str | IKIAM |
institution | IKIAM |
instname_str | Universidad Regional Amazónica |
language_invalid_str_mv | en |
network_acronym_str | IKIAM |
network_name_str | Repositorio Universidad Regional Amazónica |
oai_identifier_str | oai:repositorio.ikiam.edu.ec:RD_IKIAM/656 |
publishDate | 2023 |
reponame_str | Repositorio Universidad Regional Amazónica |
repository.mail.fl_str_mv | . |
repository.name.fl_str_mv | Repositorio Universidad Regional Amazónica - Universidad Regional Amazónica |
repository_id_str | 0 |
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 |