Monitoring of Carbon Stocks in Pastures in the Savannas of Brazil through Ecosystem Modeling on a Regional Scale

Claudinei Oliveira dos Santos (), Alexandre de Siqueira Pinto, Janete Rego da Silva, Leandro Leal Parente, Vinícius Vieira Mesquita, Maiara Pedral dos Santos and Laerte Guimaraes Ferreira
Additional contact information
Claudinei Oliveira dos Santos: Image Processing and GIS Laboratory (LAPIG), Institute of Socio-Environmental Studies (IESA), Federal University of Goiás (UFG), Goiânia 74001-970, GO, Brazil
Alexandre de Siqueira Pinto: Ecology Department, Federal University of Sergipe, Aracaju 49060-108, SE, Brazil
Janete Rego da Silva: Tourism and Patrimony, State University of Goiás, Goiás 76600-000, GO, Brazil
Leandro Leal Parente: Image Processing and GIS Laboratory (LAPIG), Institute of Socio-Environmental Studies (IESA), Federal University of Goiás (UFG), Goiânia 74001-970, GO, Brazil
Vinícius Vieira Mesquita: Image Processing and GIS Laboratory (LAPIG), Institute of Socio-Environmental Studies (IESA), Federal University of Goiás (UFG), Goiânia 74001-970, GO, Brazil
Maiara Pedral dos Santos: Ecology Department, Federal University of Sergipe, Aracaju 49060-108, SE, Brazil
Laerte Guimaraes Ferreira: Image Processing and GIS Laboratory (LAPIG), Institute of Socio-Environmental Studies (IESA), Federal University of Goiás (UFG), Goiânia 74001-970, GO, Brazil

Land, 2022, vol. 12, issue 1, 1-12

Abstract: In 2020, Brazil was the seventh largest emitter of GHG (greenhouse gases), releasing ~2.16 GtCO2e (gigatons of carbon dioxide equivalent) into the atmosphere. Activities related to land use contributed approximately 73% of national emissions in that year. Considering that pastures represent the primary land use in the country, occupying approximately 20% of the territory, the mapping and monitoring of C stocks in these areas is essential to determine their contribution to national emissions. In this study, based on the integrated use of the CENTURY model, georeferenced databases, and the R environment, we mapped and analyzed, for the first time, the C stocks dynamics associated with the pasture areas of the Cerrado biome between 2000 and 2019. The average C stocks in the soil (0–20 cm) and in the aboveground biomass estimated by modeling were ~31 MgC·ha −1 and ~4 MgC·ha −1 , respectively, values close to those observed in the literature for the region. Furthermore, the model results corresponded to the edaphic patterns of the region, with the highest average estimated C stocks in Cambisols (~34 MgC·ha −1 ) and the lowest in Neosols (~29 MgC·ha −1 ). The temporal dynamics of soil C stocks in these areas are directly related to the age of the pastures. In fact, stocks tend to be reduced in recently converted areas and stabilized in areas that have been under this land use for a longer time (≥30 years). As a result, a loss of ~103 MtC (millions of tons of carbon) was estimated in the Cerrado pasture soils in twenty years. The mapping and monitoring of C stocks in this land use type through approaches such as the one presented in this study is essential to support the Brazilian government’s efforts to mitigate C emissions.

Keywords: pastureland; soil organic carbon; ecosystem modeling; Brazilian savanna; CENTURY model; livestock; land use (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2073-445X/12/1/60/pdf (application/pdf)
https://www.mdpi.com/2073-445X/12/1/60/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:12:y:2022:i:1:p:60-:d:1014845

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().