Leafing patterns and drivers across seasonally dry tropical communities

Detalhes bibliográficos
Autor(a) principal: Alberton, Bruna [UNESP]
Data de Publicação: 2019
Outros Autores: Torres, Ricardo da Silva, Silva, Thiago Sanna Freire, da Rocha, Humberto R., Moura, Magna S.B., Morellato, Leonor Patricia Cerdeira [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/rs11192267
http://hdl.handle.net/11449/201233
Resumo: Investigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees.
id UNSP_e91b0ceb80da6a7c68b044f8a9c608ab
oai_identifier_str oai:repositorio.unesp.br:11449/201233
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Leafing patterns and drivers across seasonally dry tropical communitiesCaatingaCerradoClimate driversDeciduousnessGreennessNear-surface remote phenologySavannaSeasonalityTime seriesVegetative phenologyInvestigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees.Laborat'rio de Fenologia Instituto de Bioci'ncias Universidade Estadual Paulista (Unesp)Institute of Computing University of CampinasBiological and Environmental Sciences University of StirlingInstituto de Astronomia Geof'sica e Ci'ncias Atmosf'ricas Universidade de S'o PauloEmpresa Brasileira de Pesquisa Agropecu'ria Embrapa Semi'ridoLaborat'rio de Fenologia Instituto de Bioci'ncias Universidade Estadual Paulista (Unesp)Universidade Estadual Paulista (Unesp)Universidade Estadual de Campinas (UNICAMP)University of StirlingUniversidade de S'o PauloEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)Alberton, Bruna [UNESP]Torres, Ricardo da SilvaSilva, Thiago Sanna Freireda Rocha, Humberto R.Moura, Magna S.B.Morellato, Leonor Patricia Cerdeira [UNESP]2020-12-12T02:27:25Z2020-12-12T02:27:25Z2019-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/rs11192267Remote Sensing, v. 11, n. 19, 2019.2072-4292http://hdl.handle.net/11449/20123310.3390/rs111922672-s2.0-85073408575Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensinginfo:eu-repo/semantics/openAccess2021-10-22T13:21:49Zoai:repositorio.unesp.br:11449/201233Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:07:12.976889Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Leafing patterns and drivers across seasonally dry tropical communities
title Leafing patterns and drivers across seasonally dry tropical communities
spellingShingle Leafing patterns and drivers across seasonally dry tropical communities
Alberton, Bruna [UNESP]
Caatinga
Cerrado
Climate drivers
Deciduousness
Greenness
Near-surface remote phenology
Savanna
Seasonality
Time series
Vegetative phenology
title_short Leafing patterns and drivers across seasonally dry tropical communities
title_full Leafing patterns and drivers across seasonally dry tropical communities
title_fullStr Leafing patterns and drivers across seasonally dry tropical communities
title_full_unstemmed Leafing patterns and drivers across seasonally dry tropical communities
title_sort Leafing patterns and drivers across seasonally dry tropical communities
author Alberton, Bruna [UNESP]
author_facet Alberton, Bruna [UNESP]
Torres, Ricardo da Silva
Silva, Thiago Sanna Freire
da Rocha, Humberto R.
Moura, Magna S.B.
Morellato, Leonor Patricia Cerdeira [UNESP]
author_role author
author2 Torres, Ricardo da Silva
Silva, Thiago Sanna Freire
da Rocha, Humberto R.
Moura, Magna S.B.
Morellato, Leonor Patricia Cerdeira [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Universidade Estadual de Campinas (UNICAMP)
University of Stirling
Universidade de S'o Paulo
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)
dc.contributor.author.fl_str_mv Alberton, Bruna [UNESP]
Torres, Ricardo da Silva
Silva, Thiago Sanna Freire
da Rocha, Humberto R.
Moura, Magna S.B.
Morellato, Leonor Patricia Cerdeira [UNESP]
dc.subject.por.fl_str_mv Caatinga
Cerrado
Climate drivers
Deciduousness
Greenness
Near-surface remote phenology
Savanna
Seasonality
Time series
Vegetative phenology
topic Caatinga
Cerrado
Climate drivers
Deciduousness
Greenness
Near-surface remote phenology
Savanna
Seasonality
Time series
Vegetative phenology
description Investigating the timing of key phenological events across environments with variable seasonality is crucial to understand the drivers of ecosystem dynamics. Leaf production in the tropics is mainly constrained by water and light availability. Identifying the factors regulating leaf phenology patterns allows efficiently forecasting of climate change impacts. We conducted a novel phenological monitoring study across four Neotropical vegetation sites using leaf phenology time series obtained from digital repeated photographs (phenocameras). Seasonality differed among sites, from very seasonally dry climate in the caatinga dry scrubland with an eight-month long dry season to the less restrictive Cerrado vegetation with a six-month dry season. To unravel the main drivers of leaf phenology and understand how they influence seasonal dynamics (represented by the green color channel (Gcc) vegetation index), we applied Generalized Additive Mixed Models (GAMMs) to estimate the growing seasons, using water deficit and day length as covariates. Our results indicated that plant-water relationships are more important in the caatinga, while light (measured as day-length) was more relevant in explaining leafing patterns in Cerrado communities. Leafing behaviors and predictor-response relationships (distinct smooth functions) were more variable at the less seasonal Cerrado sites, suggesting that different life-forms (grasses, herbs, shrubs, and trees) are capable of overcoming drought through specific phenological strategies and associated functional traits, such as deep root systems in trees.
publishDate 2019
dc.date.none.fl_str_mv 2019-10-01
2020-12-12T02:27:25Z
2020-12-12T02:27:25Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3390/rs11192267
Remote Sensing, v. 11, n. 19, 2019.
2072-4292
http://hdl.handle.net/11449/201233
10.3390/rs11192267
2-s2.0-85073408575
url http://dx.doi.org/10.3390/rs11192267
http://hdl.handle.net/11449/201233
identifier_str_mv Remote Sensing, v. 11, n. 19, 2019.
2072-4292
10.3390/rs11192267
2-s2.0-85073408575
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Remote Sensing
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129286816661504