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Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences

Cerrado is the second largest biome in South America and accounted for the second largest contribution to carbon emissions in Brazil for the last 10 years, mainly due to land-use changes. It comprises approximately 2 million km(2) and is divided into 22 ecoregions, based on environmental conditions...

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Autores principales: Roitman, Iris, Bustamante, Mercedes M. C., Haidar, Ricardo F., Shimbo, Julia Z., Abdala, Guilherme C., Eiten, George, Fagg, Christopher W., Felfili, Maria Cristina, Felfili, Jeanine Maria, Jacobson, Tamiel K. B., Lindoso, Galiana S., Keller, Michael, Lenza, Eddie, Miranda, Sabrina C., Pinto, José Roberto R., Rodrigues, Ariane A., Delitti, Wellington B. C., Roitman, Pedro, Sampaio, Jhames M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070178/
https://www.ncbi.nlm.nih.gov/pubmed/30067735
http://dx.doi.org/10.1371/journal.pone.0196742
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author Roitman, Iris
Bustamante, Mercedes M. C.
Haidar, Ricardo F.
Shimbo, Julia Z.
Abdala, Guilherme C.
Eiten, George
Fagg, Christopher W.
Felfili, Maria Cristina
Felfili, Jeanine Maria
Jacobson, Tamiel K. B.
Lindoso, Galiana S.
Keller, Michael
Lenza, Eddie
Miranda, Sabrina C.
Pinto, José Roberto R.
Rodrigues, Ariane A.
Delitti, Wellington B. C.
Roitman, Pedro
Sampaio, Jhames M.
author_facet Roitman, Iris
Bustamante, Mercedes M. C.
Haidar, Ricardo F.
Shimbo, Julia Z.
Abdala, Guilherme C.
Eiten, George
Fagg, Christopher W.
Felfili, Maria Cristina
Felfili, Jeanine Maria
Jacobson, Tamiel K. B.
Lindoso, Galiana S.
Keller, Michael
Lenza, Eddie
Miranda, Sabrina C.
Pinto, José Roberto R.
Rodrigues, Ariane A.
Delitti, Wellington B. C.
Roitman, Pedro
Sampaio, Jhames M.
author_sort Roitman, Iris
collection PubMed
description Cerrado is the second largest biome in South America and accounted for the second largest contribution to carbon emissions in Brazil for the last 10 years, mainly due to land-use changes. It comprises approximately 2 million km(2) and is divided into 22 ecoregions, based on environmental conditions and vegetation. The most dominant vegetation type is cerrado sensu stricto (cerrado ss), a savanna woodland. Quantifying variation of biomass density of this vegetation is crucial for climate change mitigation policies. Integrating remote sensing data with adequate allometric equations and field-based data sets can provide large-scale estimates of biomass. We developed individual-tree aboveground biomass (AGB) allometric models to compare different regression techniques and explanatory variables. We applied the model with the strongest fit to a comprehensive ground-based data set (77 sites, 893 plots, and 95,484 trees) to describe AGB density variation of cerrado ss. We also investigated the influence of physiographic and climatological variables on AGB density; this analysis was restricted to 68 sites because eight sites could not be classified into a specific ecoregion, and one site had no soil texture data. In addition, we developed two models to estimate plot AGB density based on plot basal area. Our data show that for individual-tree AGB models a) log-log linear models provided better estimates than nonlinear power models; b) including species as a random effect improved model fit; c) diameter at 30 cm above ground was a reliable predictor for individual-tree AGB, and although height significantly improved model fit, species wood density did not. Mean tree AGB density in cerrado ss was 22.9 tons ha(-1) (95% confidence interval = ± 2.2) and varied widely between ecoregions (8.8 to 42.2 tons ha(-1)), within ecoregions (e.g. 4.8 to 39.5 tons ha(-1)), and even within sites (24.3 to 69.9 tons ha(-1)). Biomass density tended to be higher in sites close to the Amazon. Ecoregion explained 42% of biomass variation between the 68 sites (P < 0.01) and shows strong potential as a parameter for classifying regional biomass variation in the Cerrado.
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spelling pubmed-60701782018-08-09 Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences Roitman, Iris Bustamante, Mercedes M. C. Haidar, Ricardo F. Shimbo, Julia Z. Abdala, Guilherme C. Eiten, George Fagg, Christopher W. Felfili, Maria Cristina Felfili, Jeanine Maria Jacobson, Tamiel K. B. Lindoso, Galiana S. Keller, Michael Lenza, Eddie Miranda, Sabrina C. Pinto, José Roberto R. Rodrigues, Ariane A. Delitti, Wellington B. C. Roitman, Pedro Sampaio, Jhames M. PLoS One Research Article Cerrado is the second largest biome in South America and accounted for the second largest contribution to carbon emissions in Brazil for the last 10 years, mainly due to land-use changes. It comprises approximately 2 million km(2) and is divided into 22 ecoregions, based on environmental conditions and vegetation. The most dominant vegetation type is cerrado sensu stricto (cerrado ss), a savanna woodland. Quantifying variation of biomass density of this vegetation is crucial for climate change mitigation policies. Integrating remote sensing data with adequate allometric equations and field-based data sets can provide large-scale estimates of biomass. We developed individual-tree aboveground biomass (AGB) allometric models to compare different regression techniques and explanatory variables. We applied the model with the strongest fit to a comprehensive ground-based data set (77 sites, 893 plots, and 95,484 trees) to describe AGB density variation of cerrado ss. We also investigated the influence of physiographic and climatological variables on AGB density; this analysis was restricted to 68 sites because eight sites could not be classified into a specific ecoregion, and one site had no soil texture data. In addition, we developed two models to estimate plot AGB density based on plot basal area. Our data show that for individual-tree AGB models a) log-log linear models provided better estimates than nonlinear power models; b) including species as a random effect improved model fit; c) diameter at 30 cm above ground was a reliable predictor for individual-tree AGB, and although height significantly improved model fit, species wood density did not. Mean tree AGB density in cerrado ss was 22.9 tons ha(-1) (95% confidence interval = ± 2.2) and varied widely between ecoregions (8.8 to 42.2 tons ha(-1)), within ecoregions (e.g. 4.8 to 39.5 tons ha(-1)), and even within sites (24.3 to 69.9 tons ha(-1)). Biomass density tended to be higher in sites close to the Amazon. Ecoregion explained 42% of biomass variation between the 68 sites (P < 0.01) and shows strong potential as a parameter for classifying regional biomass variation in the Cerrado. Public Library of Science 2018-08-01 /pmc/articles/PMC6070178/ /pubmed/30067735 http://dx.doi.org/10.1371/journal.pone.0196742 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Roitman, Iris
Bustamante, Mercedes M. C.
Haidar, Ricardo F.
Shimbo, Julia Z.
Abdala, Guilherme C.
Eiten, George
Fagg, Christopher W.
Felfili, Maria Cristina
Felfili, Jeanine Maria
Jacobson, Tamiel K. B.
Lindoso, Galiana S.
Keller, Michael
Lenza, Eddie
Miranda, Sabrina C.
Pinto, José Roberto R.
Rodrigues, Ariane A.
Delitti, Wellington B. C.
Roitman, Pedro
Sampaio, Jhames M.
Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title_full Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title_fullStr Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title_full_unstemmed Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title_short Optimizing biomass estimates of savanna woodland at different spatial scales in the Brazilian Cerrado: Re-evaluating allometric equations and environmental influences
title_sort optimizing biomass estimates of savanna woodland at different spatial scales in the brazilian cerrado: re-evaluating allometric equations and environmental influences
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6070178/
https://www.ncbi.nlm.nih.gov/pubmed/30067735
http://dx.doi.org/10.1371/journal.pone.0196742
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