Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass
Main Author: | |
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Publication Date: | 2014 |
Other Authors: | , , |
Format: | Article |
Language: | eng |
Source: | Repositório Institucional do INPA |
Download full: | https://repositorio.inpa.gov.br/handle/1/16011 |
Summary: | Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address 'why' by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies. © 2014 IOP Publishing Ltd. |
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Di Vittorio, Alan V.Negrón-Juárez, Robinson I.Higuchi, NiroChambers, Jeffrey Quintin2020-05-21T21:56:29Z2020-05-21T21:56:29Z2014https://repositorio.inpa.gov.br/handle/1/1601110.1088/1748-9326/9/3/034010Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address 'why' by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies. © 2014 IOP Publishing Ltd.Volume 9, Número 3Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessBiomassStochastic ModelsAmazonForestFrequency DistributionsMortalityPower LawPower Law DistributionSpatial ClusteringTree Growth ModelingForestryBiomassCanopy ArchitectureCanopy GapCarbon BudgetEnvironmental DisturbanceGrowth ModelingLandscape EcologyLongevityMortalityPower LawSatellite ImagerySize DistributionTropical ForestBiomassForestsMortalityAmazoniaTropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomassinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleEnvironmental Research Lettersengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALartigo-inpa.pdfartigo-inpa.pdfapplication/pdf636148https://repositorio.inpa.gov.br/bitstream/1/16011/1/artigo-inpa.pdf451d661b2e1b8c644acae3318b385ab1MD511/160112020-05-21 18:40:00.054oai:repositorio:1/16011Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-05-21T22:40Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.en.fl_str_mv |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
title |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
spellingShingle |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass Di Vittorio, Alan V. Biomass Stochastic Models Amazon Forest Frequency Distributions Mortality Power Law Power Law Distribution Spatial Clustering Tree Growth Modeling Forestry Biomass Canopy Architecture Canopy Gap Carbon Budget Environmental Disturbance Growth Modeling Landscape Ecology Longevity Mortality Power Law Satellite Imagery Size Distribution Tropical Forest Biomass Forests Mortality Amazonia |
title_short |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
title_full |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
title_fullStr |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
title_full_unstemmed |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
title_sort |
Tropical forest carbon balance: Effects of field- and satellite-based mortality regimes on the dynamics and the spatial structure of Central Amazon forest biomass |
author |
Di Vittorio, Alan V. |
author_facet |
Di Vittorio, Alan V. Negrón-Juárez, Robinson I. Higuchi, Niro Chambers, Jeffrey Quintin |
author_role |
author |
author2 |
Negrón-Juárez, Robinson I. Higuchi, Niro Chambers, Jeffrey Quintin |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Di Vittorio, Alan V. Negrón-Juárez, Robinson I. Higuchi, Niro Chambers, Jeffrey Quintin |
dc.subject.eng.fl_str_mv |
Biomass Stochastic Models Amazon Forest Frequency Distributions Mortality Power Law Power Law Distribution Spatial Clustering Tree Growth Modeling Forestry Biomass Canopy Architecture Canopy Gap Carbon Budget Environmental Disturbance Growth Modeling Landscape Ecology Longevity Mortality Power Law Satellite Imagery Size Distribution Tropical Forest Biomass Forests Mortality Amazonia |
topic |
Biomass Stochastic Models Amazon Forest Frequency Distributions Mortality Power Law Power Law Distribution Spatial Clustering Tree Growth Modeling Forestry Biomass Canopy Architecture Canopy Gap Carbon Budget Environmental Disturbance Growth Modeling Landscape Ecology Longevity Mortality Power Law Satellite Imagery Size Distribution Tropical Forest Biomass Forests Mortality Amazonia |
description |
Debate continues over the adequacy of existing field plots to sufficiently capture Amazon forest dynamics to estimate regional forest carbon balance. Tree mortality dynamics are particularly uncertain due to the difficulty of observing large, infrequent disturbances. A recent paper (Chambers et al 2013 Proc. Natl Acad. Sci. 110 3949-54) reported that Central Amazon plots missed 9-17% of tree mortality, and here we address 'why' by elucidating two distinct mortality components: (1) variation in annual landscape-scale average mortality and (2) the frequency distribution of the size of clustered mortality events. Using a stochastic-empirical tree growth model we show that a power law distribution of event size (based on merged plot and satellite data) is required to generate spatial clustering of mortality that is consistent with forest gap observations. We conclude that existing plots do not sufficiently capture losses because their placement, size, and longevity assume spatially random mortality, while mortality is actually distributed among differently sized events (clusters of dead trees) that determine the spatial structure of forest canopies. © 2014 IOP Publishing Ltd. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2020-05-21T21:56:29Z |
dc.date.available.fl_str_mv |
2020-05-21T21:56:29Z |
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/1/16011 |
dc.identifier.doi.none.fl_str_mv |
10.1088/1748-9326/9/3/034010 |
url |
https://repositorio.inpa.gov.br/handle/1/16011 |
identifier_str_mv |
10.1088/1748-9326/9/3/034010 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Volume 9, 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 |
Environmental Research Letters |
publisher.none.fl_str_mv |
Environmental Research Letters |
dc.source.none.fl_str_mv |
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Repositório Institucional do INPA |
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