Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change

Detalhes bibliográficos
Autor(a) principal: Levine, Naomi Marcil
Data de Publicação: 2016
Outros Autores: Zhang, Ke, Longo, Marcos, Baccini, Alessandro, Phillips, Oliver L., Lewis, Simon L., Alvarez, Esteban, Andrade, Ana Cristina Segalin de, Brienen, Roel J.W., Erwin, Terry L., Feldpausch, Ted R., Mendoza, Abel Monteagudo, Vargas, Percy Núñez, Prieto, Adriana, Silva-Espejo, Javier Eduardo, Malhi, Yadvinder Singh, Moorcroft, Paul R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional do INPA
Texto Completo: https://repositorio.inpa.gov.br/handle/1/14852
Resumo: Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale dieback of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.
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spelling Levine, Naomi MarcilZhang, KeLongo, MarcosBaccini, AlessandroPhillips, Oliver L.Lewis, Simon L.Alvarez, EstebanAndrade, Ana Cristina Segalin deBrienen, Roel J.W.Erwin, Terry L.Feldpausch, Ted R.Mendoza, Abel MonteagudoVargas, Percy NúñezPrieto, AdrianaSilva-Espejo, Javier EduardoMalhi, Yadvinder SinghMoorcroft, Paul R.2020-05-07T13:41:00Z2020-05-07T13:41:00Z2016https://repositorio.inpa.gov.br/handle/1/1485210.1073/pnas.1511344112Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale dieback of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.Volume 113, Número 3, Pags. 793-797Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessBiomassClimate ChangeEcosystemEcosystem ResilienceForestPlant StressPriority JournalRemote SensingSavannaSensitivity AnalysisSoil MoistureSoil TextureSpatial Soil VariabilityWater StressBrasilDehydrationSeasonSoilSoilBiomassBrasilClimate ChangeDehydrationEcosystemRemote Sensing TechnologySeasonsSoilEcosystem heterogeneity determines the ecological resilience of the Amazon to climate changeinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleProceedings of the National Academy of Sciences of the United States of Americaengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALartigo-inpa.pdfapplication/pdf857721https://repositorio.inpa.gov.br/bitstream/1/14852/1/artigo-inpa.pdfdcc2693be454832628b9e9069a7339ceMD51CC-LICENSElicense_rdfapplication/octet-stream914https://repositorio.inpa.gov.br/bitstream/1/14852/2/license_rdf4d2950bda3d176f570a9f8b328dfbbefMD521/148522020-07-14 09:11:11.99oai:repositorio:1/14852Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T13:11:11Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false
dc.title.en.fl_str_mv Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
title Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
spellingShingle Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
Levine, Naomi Marcil
Biomass
Climate Change
Ecosystem
Ecosystem Resilience
Forest
Plant Stress
Priority Journal
Remote Sensing
Savanna
Sensitivity Analysis
Soil Moisture
Soil Texture
Spatial Soil Variability
Water Stress
Brasil
Dehydration
Season
Soil
Soil
Biomass
Brasil
Climate Change
Dehydration
Ecosystem
Remote Sensing Technology
Seasons
Soil
title_short Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
title_full Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
title_fullStr Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
title_full_unstemmed Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
title_sort Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
author Levine, Naomi Marcil
author_facet Levine, Naomi Marcil
Zhang, Ke
Longo, Marcos
Baccini, Alessandro
Phillips, Oliver L.
Lewis, Simon L.
Alvarez, Esteban
Andrade, Ana Cristina Segalin de
Brienen, Roel J.W.
Erwin, Terry L.
Feldpausch, Ted R.
Mendoza, Abel Monteagudo
Vargas, Percy Núñez
Prieto, Adriana
Silva-Espejo, Javier Eduardo
Malhi, Yadvinder Singh
Moorcroft, Paul R.
author_role author
author2 Zhang, Ke
Longo, Marcos
Baccini, Alessandro
Phillips, Oliver L.
Lewis, Simon L.
Alvarez, Esteban
Andrade, Ana Cristina Segalin de
Brienen, Roel J.W.
Erwin, Terry L.
Feldpausch, Ted R.
Mendoza, Abel Monteagudo
Vargas, Percy Núñez
Prieto, Adriana
Silva-Espejo, Javier Eduardo
Malhi, Yadvinder Singh
Moorcroft, Paul R.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Levine, Naomi Marcil
Zhang, Ke
Longo, Marcos
Baccini, Alessandro
Phillips, Oliver L.
Lewis, Simon L.
Alvarez, Esteban
Andrade, Ana Cristina Segalin de
Brienen, Roel J.W.
Erwin, Terry L.
Feldpausch, Ted R.
Mendoza, Abel Monteagudo
Vargas, Percy Núñez
Prieto, Adriana
Silva-Espejo, Javier Eduardo
Malhi, Yadvinder Singh
Moorcroft, Paul R.
dc.subject.eng.fl_str_mv Biomass
Climate Change
Ecosystem
Ecosystem Resilience
Forest
Plant Stress
Priority Journal
Remote Sensing
Savanna
Sensitivity Analysis
Soil Moisture
Soil Texture
Spatial Soil Variability
Water Stress
Brasil
Dehydration
Season
Soil
Soil
Biomass
Brasil
Climate Change
Dehydration
Ecosystem
Remote Sensing Technology
Seasons
Soil
topic Biomass
Climate Change
Ecosystem
Ecosystem Resilience
Forest
Plant Stress
Priority Journal
Remote Sensing
Savanna
Sensitivity Analysis
Soil Moisture
Soil Texture
Spatial Soil Variability
Water Stress
Brasil
Dehydration
Season
Soil
Soil
Biomass
Brasil
Climate Change
Dehydration
Ecosystem
Remote Sensing Technology
Seasons
Soil
description Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale dieback of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.
publishDate 2016
dc.date.issued.fl_str_mv 2016
dc.date.accessioned.fl_str_mv 2020-05-07T13:41:00Z
dc.date.available.fl_str_mv 2020-05-07T13:41:00Z
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 https://repositorio.inpa.gov.br/handle/1/14852
dc.identifier.doi.none.fl_str_mv 10.1073/pnas.1511344112
url https://repositorio.inpa.gov.br/handle/1/14852
identifier_str_mv 10.1073/pnas.1511344112
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Volume 113, Número 3, Pags. 793-797
dc.rights.driver.fl_str_mv Attribution-NonCommercial-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nc-nd/3.0/br/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivs 3.0 Brazil
http://creativecommons.org/licenses/by-nc-nd/3.0/br/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Proceedings of the National Academy of Sciences of the United States of America
publisher.none.fl_str_mv Proceedings of the National Academy of Sciences of the United States of America
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institution INPA
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