Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters

Bibliographic Details
Main Author: Castanho, Andrea Dde Almeida
Publication Date: 2013
Other Authors: Coe, Michael T., Costa, Marcos Heil, Malhi, Yadvinder Singh, Galbraith, David R., Quesada, Carlos Alberto
Format: Article
Language: eng
Source: Repositório Institucional do INPA
Download full: https://repositorio.inpa.gov.br/handle/1/14897
Summary: Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy. © 2013 Author(s).
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spelling Castanho, Andrea Dde AlmeidaCoe, Michael T.Costa, Marcos HeilMalhi, Yadvinder SinghGalbraith, David R.Quesada, Carlos Alberto2020-05-07T13:47:16Z2020-05-07T13:47:16Z2013https://repositorio.inpa.gov.br/handle/1/1489710.5194/bg-10-2255-2013Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy. © 2013 Author(s).Volume 10, Número 4, Pags. 2255-2272Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessAboveground BiomassBiomeEcological ModelingForest EcosystemHomogeneityNet Primary ProductionNumerical ModelPhysicochemical PropertySpatial VariationTropical ForestAmazoniaImproving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parametersinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBiogeosciencesengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALartigo-inpa.pdfapplication/pdf9688252https://repositorio.inpa.gov.br/bitstream/1/14897/1/artigo-inpa.pdfbf6be4b98b6370943dcf36d71cb366c6MD51CC-LICENSElicense_rdfapplication/octet-stream914https://repositorio.inpa.gov.br/bitstream/1/14897/2/license_rdf4d2950bda3d176f570a9f8b328dfbbefMD521/148972020-07-14 10:28:10.214oai:repositorio:1/14897Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T14:28:10Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false
dc.title.en.fl_str_mv Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
title Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
spellingShingle Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
Castanho, Andrea Dde Almeida
Aboveground Biomass
Biome
Ecological Modeling
Forest Ecosystem
Homogeneity
Net Primary Production
Numerical Model
Physicochemical Property
Spatial Variation
Tropical Forest
Amazonia
title_short Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
title_full Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
title_fullStr Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
title_full_unstemmed Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
title_sort Improving simulated Amazon forest biomass and productivity by including spatial variation in biophysical parameters
author Castanho, Andrea Dde Almeida
author_facet Castanho, Andrea Dde Almeida
Coe, Michael T.
Costa, Marcos Heil
Malhi, Yadvinder Singh
Galbraith, David R.
Quesada, Carlos Alberto
author_role author
author2 Coe, Michael T.
Costa, Marcos Heil
Malhi, Yadvinder Singh
Galbraith, David R.
Quesada, Carlos Alberto
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Castanho, Andrea Dde Almeida
Coe, Michael T.
Costa, Marcos Heil
Malhi, Yadvinder Singh
Galbraith, David R.
Quesada, Carlos Alberto
dc.subject.eng.fl_str_mv Aboveground Biomass
Biome
Ecological Modeling
Forest Ecosystem
Homogeneity
Net Primary Production
Numerical Model
Physicochemical Property
Spatial Variation
Tropical Forest
Amazonia
topic Aboveground Biomass
Biome
Ecological Modeling
Forest Ecosystem
Homogeneity
Net Primary Production
Numerical Model
Physicochemical Property
Spatial Variation
Tropical Forest
Amazonia
description Dynamic vegetation models forced with spatially homogeneous biophysical parameters are capable of producing average productivity and biomass values for the Amazon basin forest biome that are close to the observed estimates, but these models are unable to reproduce observed spatial variability. Recent observational studies have shown substantial regional spatial variability of above-ground productivity and biomass across the Amazon basin, which is believed to be primarily driven by a combination of soil physical and chemical properties. In this study, spatial heterogeneity of vegetation properties is added to the Integrated Biosphere Simulator (IBIS) land surface model, and the simulated productivity and biomass of the Amazon basin are compared to observations from undisturbed forest. The maximum RuBiCo carboxylation capacity (Vcmax) and the woody biomass residence time (τw) were found to be the most important properties determining the modeled spatial variation of above-ground woody net primary productivity and biomass, respectively. Spatial heterogeneity of these properties may lead to simulated spatial variability of 1.8 times in the woody net primary productivity (NPPw) and 2.8 times in the woody above-ground biomass (AGBw). The coefficient of correlation between the modeled and observed woody productivity improved from 0.10 with homogeneous parameters to 0.73 with spatially heterogeneous parameters, while the coefficient of correlation between the simulated and observed woody above-ground biomass improved from 0.33 to 0.88. The results from our analyses with the IBIS dynamic vegetation model demonstrated that using single values for key ecological parameters in the tropical forest biome severely limits simulation accuracy. Clearer understanding of the biophysical mechanisms that drive the spatial variability of carbon allocation, τw and Vcmax is necessary to achieve further improvements to simulation accuracy. © 2013 Author(s).
publishDate 2013
dc.date.issued.fl_str_mv 2013
dc.date.accessioned.fl_str_mv 2020-05-07T13:47:16Z
dc.date.available.fl_str_mv 2020-05-07T13:47:16Z
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dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv https://repositorio.inpa.gov.br/handle/1/14897
dc.identifier.doi.none.fl_str_mv 10.5194/bg-10-2255-2013
url https://repositorio.inpa.gov.br/handle/1/14897
identifier_str_mv 10.5194/bg-10-2255-2013
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Volume 10, Número 4, Pags. 2255-2272
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 Biogeosciences
publisher.none.fl_str_mv Biogeosciences
dc.source.none.fl_str_mv reponame:Repositório Institucional do INPA
instname:Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron:INPA
instname_str Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron_str INPA
institution INPA
reponame_str Repositório Institucional do INPA
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