The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do INPA |
Texto Completo: | https://repositorio.inpa.gov.br/handle/1/15453 |
Resumo: | There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2 increases. Hence, we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven with CO2 forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present-day predictions. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present-day biomass accumulation. Notably, the two vegetation demographic models (VDMs) (ED2 and ELM-FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15-year period, and while high interannual variation existed, biomass change was near neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha−1 year−1). ELMv1-ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density-dependent mortality. The VDM's performance was similar or better than the BGC models run in carbon-only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to nondemographic (i.e., “big-leaf”) models but also include finer scale demography and competition that can be evaluated against field observations. ©2020. The Authors. |
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Holm, Jennifer A.G, Knox, RyanZhu, QingFisher, Rosie A.Koven, Charles D.Nogueira Lima, Adriano J.Riley, William J.Longo, MarcosNegrón-Juárez, Robinson I.Araüjo, Alessandro Carioca deKueppers, Lara M.Moorcroft, Paul R.Higuchi, NiroChambers, Jeffrey Quintin2020-05-14T14:27:39Z2020-05-14T14:27:39Z2020https://repositorio.inpa.gov.br/handle/1/1545310.1029/2019JG005500There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2 increases. Hence, we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven with CO2 forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present-day predictions. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present-day biomass accumulation. Notably, the two vegetation demographic models (VDMs) (ED2 and ELM-FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15-year period, and while high interannual variation existed, biomass change was near neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha−1 year−1). ELMv1-ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density-dependent mortality. The VDM's performance was similar or better than the BGC models run in carbon-only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to nondemographic (i.e., “big-leaf”) models but also include finer scale demography and competition that can be evaluated against field observations. ©2020. The Authors.Volume 125, Número 3Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessAnnual VariationBiogeochemical CycleBiomassBiomass AllocationCarbon SinkDensity DependenceEddy CovariancePhosphorusTropical ForestVegetation StructureThe Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Modelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleJournal of Geophysical Research: Biogeosciencesengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALCentral.pdfCentral.pdfapplication/pdf3685232https://repositorio.inpa.gov.br/bitstream/1/15453/1/Central.pdfe1c4b9c5c2eb1bc5766e15bc0209d307MD511/154532020-07-14 11:07:34.749oai:repositorio:1/15453Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T15:07:34Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.en.fl_str_mv |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
title |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
spellingShingle |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models Holm, Jennifer A. Annual Variation Biogeochemical Cycle Biomass Biomass Allocation Carbon Sink Density Dependence Eddy Covariance Phosphorus Tropical Forest Vegetation Structure |
title_short |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
title_full |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
title_fullStr |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
title_full_unstemmed |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
title_sort |
The Central Amazon Biomass Sink Under Current and Future Atmospheric CO2: Predictions From Big-Leaf and Demographic Vegetation Models |
author |
Holm, Jennifer A. |
author_facet |
Holm, Jennifer A. G, Knox, Ryan Zhu, Qing Fisher, Rosie A. Koven, Charles D. Nogueira Lima, Adriano J. Riley, William J. Longo, Marcos Negrón-Juárez, Robinson I. Araüjo, Alessandro Carioca de Kueppers, Lara M. Moorcroft, Paul R. Higuchi, Niro Chambers, Jeffrey Quintin |
author_role |
author |
author2 |
G, Knox, Ryan Zhu, Qing Fisher, Rosie A. Koven, Charles D. Nogueira Lima, Adriano J. Riley, William J. Longo, Marcos Negrón-Juárez, Robinson I. Araüjo, Alessandro Carioca de Kueppers, Lara M. Moorcroft, Paul R. Higuchi, Niro Chambers, Jeffrey Quintin |
author2_role |
author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Holm, Jennifer A. G, Knox, Ryan Zhu, Qing Fisher, Rosie A. Koven, Charles D. Nogueira Lima, Adriano J. Riley, William J. Longo, Marcos Negrón-Juárez, Robinson I. Araüjo, Alessandro Carioca de Kueppers, Lara M. Moorcroft, Paul R. Higuchi, Niro Chambers, Jeffrey Quintin |
dc.subject.eng.fl_str_mv |
Annual Variation Biogeochemical Cycle Biomass Biomass Allocation Carbon Sink Density Dependence Eddy Covariance Phosphorus Tropical Forest Vegetation Structure |
topic |
Annual Variation Biogeochemical Cycle Biomass Biomass Allocation Carbon Sink Density Dependence Eddy Covariance Phosphorus Tropical Forest Vegetation Structure |
description |
There is large uncertainty whether Amazon forests will remain a carbon sink as atmospheric CO2 increases. Hence, we simulated an old-growth tropical forest using six versions of four terrestrial models differing in scale of vegetation structure and representation of biogeochemical (BGC) cycling, all driven with CO2 forcing from the preindustrial period to 2100. The models were benchmarked against tree inventory and eddy covariance data from a Brazilian site for present-day predictions. All models predicted positive vegetation growth that outpaced mortality, leading to continual increases in present-day biomass accumulation. Notably, the two vegetation demographic models (VDMs) (ED2 and ELM-FATES) always predicted positive stem diameter growth in all size classes. The field data, however, indicated that a quarter of canopy trees didn't grow over the 15-year period, and while high interannual variation existed, biomass change was near neutral. With a doubling of CO2, three of the four models predicted an appreciable biomass sink (0.77 to 1.24 Mg ha−1 year−1). ELMv1-ECA, the only model used here that includes phosphorus constraints, predicted the lowest biomass sink relative to initial biomass stocks (+21%), lower than the other BGC model, CLM5 (+48%). Models projections differed primarily through variations in nutrient constraints, then carbon allocation, initial biomass, and density-dependent mortality. The VDM's performance was similar or better than the BGC models run in carbon-only mode, suggesting that nutrient competition in VDMs will improve predictions. We demonstrate that VDMs are comparable to nondemographic (i.e., “big-leaf”) models but also include finer scale demography and competition that can be evaluated against field observations. ©2020. The Authors. |
publishDate |
2020 |
dc.date.accessioned.fl_str_mv |
2020-05-14T14:27:39Z |
dc.date.available.fl_str_mv |
2020-05-14T14:27:39Z |
dc.date.issued.fl_str_mv |
2020 |
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/1/15453 |
dc.identifier.doi.none.fl_str_mv |
10.1029/2019JG005500 |
url |
https://repositorio.inpa.gov.br/handle/1/15453 |
identifier_str_mv |
10.1029/2019JG005500 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Volume 125, Número 3 |
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 |
Journal of Geophysical Research: Biogeosciences |
publisher.none.fl_str_mv |
Journal of Geophysical Research: Biogeosciences |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do INPA instname:Instituto Nacional de Pesquisas da Amazônia (INPA) instacron:INPA |
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Repositório Institucional do INPA |
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