Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling

Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and c...

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Main Authors: G. R. van der Werf, D. C. Morton, R. S. DeFries, L. Giglio, J. T. Randerson, G. J. Collatz, P. S. Kasibhatla
Format: Article
Language:English
Published: Copernicus Publications 2009-02-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/6/235/2009/bg-6-235-2009.pdf
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spelling doaj-864102c8a35d481eadbc48d60757a5052020-11-24T21:04:46ZengCopernicus PublicationsBiogeosciences1726-41701726-41892009-02-0162235249Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modellingG. R. van der WerfD. C. MortonR. S. DeFriesL. GiglioJ. T. RandersonG. J. CollatzP. S. KasibhatlaTropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year<sup>−1</sup>, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth. http://www.biogeosciences.net/6/235/2009/bg-6-235-2009.pdf
collection DOAJ
language English
format Article
sources DOAJ
author G. R. van der Werf
D. C. Morton
R. S. DeFries
L. Giglio
J. T. Randerson
G. J. Collatz
P. S. Kasibhatla
spellingShingle G. R. van der Werf
D. C. Morton
R. S. DeFries
L. Giglio
J. T. Randerson
G. J. Collatz
P. S. Kasibhatla
Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
Biogeosciences
author_facet G. R. van der Werf
D. C. Morton
R. S. DeFries
L. Giglio
J. T. Randerson
G. J. Collatz
P. S. Kasibhatla
author_sort G. R. van der Werf
title Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
title_short Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
title_full Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
title_fullStr Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
title_full_unstemmed Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling
title_sort estimates of fire emissions from an active deforestation region in the southern amazon based on satellite data and biogeochemical modelling
publisher Copernicus Publications
series Biogeosciences
issn 1726-4170
1726-4189
publishDate 2009-02-01
description Tropical deforestation contributes to the build-up of atmospheric carbon dioxide in the atmosphere. Within the deforestation process, fire is frequently used to eliminate biomass in preparation for agricultural use. Quantifying these deforestation-induced fire emissions represents a challenge, and current estimates are only available at coarse spatial resolution with large uncertainty. Here we developed a biogeochemical model using remote sensing observations of plant productivity, fire activity, and deforestation rates to estimate emissions for the Brazilian state of Mato Grosso during 2001–2005. Our model of DEforestation CArbon Fluxes (DECAF) runs at 250-m spatial resolution with a monthly time step to capture spatial and temporal heterogeneity in fire dynamics in our study area within the ''arc of deforestation'', the southern and eastern fringe of the Amazon tropical forest where agricultural expansion is most concentrated. Fire emissions estimates from our modelling framework were on average 90 Tg C year<sup>−1</sup>, mostly stemming from fires associated with deforestation (74%) with smaller contributions from fires from conversions of Cerrado or pastures to cropland (19%) and pasture fires (7%). In terms of carbon dynamics, about 80% of the aboveground living biomass and litter was combusted when forests were converted to pasture, and 89% when converted to cropland because of the highly mechanized nature of the deforestation process in Mato Grosso. The trajectory of land use change from forest to other land uses often takes more than one year, and part of the biomass that was not burned in the dry season following deforestation burned in consecutive years. This led to a partial decoupling of annual deforestation rates and fire emissions, and lowered interannual variability in fire emissions. Interannual variability in the region was somewhat dampened as well because annual emissions from fires following deforestation and from maintenance fires did not covary, although the effect was small due to the minor contribution of maintenance fires. Our results demonstrate how the DECAF model can be used to model deforestation fire emissions at relatively high spatial and temporal resolutions. Detailed model output is suitable for policy applications concerned with annual emissions estimates distributed among post-clearing land uses and science applications in combination with atmospheric emissions modelling to provide constrained global deforestation fire emissions estimates. DECAF currently estimates emissions from fire; future efforts can incorporate other aspects of net carbon emissions from deforestation including soil respiration and regrowth.
url http://www.biogeosciences.net/6/235/2009/bg-6-235-2009.pdf
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