Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes

Estimations of Net Ecosystem Exchange (NEE) are crucial to assess the carbon sequestration/carbon source capacity of agricultural systems. Although several global models have been built to describe carbon flux patterns based on flux tower data, South American ecosystems (and croplands in particular)...

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Autores principales: Marconato, Ulises Mariano, Fernández, Roberto J., Posse Beaulieu, Gabriela
Formato: Artículo
Lenguaje:Inglés
Publicado: Frontiers Media 2022
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/12946
https://www.frontiersin.org/articles/10.3389/fsoil.2022.903544/full
https://doi.org/10.3389/fsoil.2022.903544
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author Marconato, Ulises Mariano
Fernández, Roberto J.
Posse Beaulieu, Gabriela
author_browse Fernández, Roberto J.
Marconato, Ulises Mariano
Posse Beaulieu, Gabriela
author_facet Marconato, Ulises Mariano
Fernández, Roberto J.
Posse Beaulieu, Gabriela
author_sort Marconato, Ulises Mariano
collection INTA Digital
description Estimations of Net Ecosystem Exchange (NEE) are crucial to assess the carbon sequestration/carbon source capacity of agricultural systems. Although several global models have been built to describe carbon flux patterns based on flux tower data, South American ecosystems (and croplands in particular) are underrepresented in the databases used to calibrate these models, leading to large uncertainties in regional and global NEE estimation. Despite the fact that almost half of the land surface is used worldwide for agricultural activities, these models still do not include variables related to cropland management. Using enhanced vegetation index (EVI) derived from MODIS imagery (250m) and monthly CO2 exchange from a 9-year record of an eddy covariance (EC) flux tower in a crop field in the Inland Pampas region, we developed regression models to predict monthly NEE. We tested whether including a term for crop identity/land cover as a categorical variable (maize, soybean, wheat, and fallow) could improve model capability in capturing monthly NEE dynamics. NEE measured at the flux tower site was scaled to croplands across the Inland Pampa using crop-type maps, from which annual NEE maps were generated for the 2018–2019, 2019–2020, and 2020–2021 agricultural campaigns. The model based solely on EVI showed to be a good predictor of monthly NEE for the study region (r2 = 0.78), but model adjustment was improved by including a term for crop identity (r2 = 0.83). A second set of maps was generated taking into account carbon exports during harvest to estimate Net Biome Productivity (NBP) at the county level. Crops across the region as a whole acted as a carbon sink during the three studied campaigns, although with highly heterogeneous spatial and temporal patterns. Between 60% and 80% of the carbon sequestered was exported during harvest, a large decrease from the carbon sequestration capacity estimated using just NEE, which further decreased if fossil carbon emissions from agricultural supplies are taken into account. Estimates presented in this study are a first step towards upscaling carbon fluxes at the regional scale in a South American cropland area, and could help to improve regional to global estimations of carbon fluxes and refine national greenhouse gas (GHG) inventories.
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spelling INTA129462022-09-23T10:36:23Z Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes Marconato, Ulises Mariano Fernández, Roberto J. Posse Beaulieu, Gabriela Agriculture Moderate Resolution Imaging Spectroradiometer Crops Farmland Agricultura Espectrorradiómetro de Imágenes de Resolución Moderada Cultivos Tierras Agrícolas Net Biome Productivity Upscaline Carbon Fluxes Crop Type Mapping Productividad Neta del Bioma Flujos de Carbono Mapeo de Tipos de Cultivos Estimations of Net Ecosystem Exchange (NEE) are crucial to assess the carbon sequestration/carbon source capacity of agricultural systems. Although several global models have been built to describe carbon flux patterns based on flux tower data, South American ecosystems (and croplands in particular) are underrepresented in the databases used to calibrate these models, leading to large uncertainties in regional and global NEE estimation. Despite the fact that almost half of the land surface is used worldwide for agricultural activities, these models still do not include variables related to cropland management. Using enhanced vegetation index (EVI) derived from MODIS imagery (250m) and monthly CO2 exchange from a 9-year record of an eddy covariance (EC) flux tower in a crop field in the Inland Pampas region, we developed regression models to predict monthly NEE. We tested whether including a term for crop identity/land cover as a categorical variable (maize, soybean, wheat, and fallow) could improve model capability in capturing monthly NEE dynamics. NEE measured at the flux tower site was scaled to croplands across the Inland Pampa using crop-type maps, from which annual NEE maps were generated for the 2018–2019, 2019–2020, and 2020–2021 agricultural campaigns. The model based solely on EVI showed to be a good predictor of monthly NEE for the study region (r2 = 0.78), but model adjustment was improved by including a term for crop identity (r2 = 0.83). A second set of maps was generated taking into account carbon exports during harvest to estimate Net Biome Productivity (NBP) at the county level. Crops across the region as a whole acted as a carbon sink during the three studied campaigns, although with highly heterogeneous spatial and temporal patterns. Between 60% and 80% of the carbon sequestered was exported during harvest, a large decrease from the carbon sequestration capacity estimated using just NEE, which further decreased if fossil carbon emissions from agricultural supplies are taken into account. Estimates presented in this study are a first step towards upscaling carbon fluxes at the regional scale in a South American cropland area, and could help to improve regional to global estimations of carbon fluxes and refine national greenhouse gas (GHG) inventories. Fil: Marconato, Ulises. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA); Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA); Argentina Fil: Fernandez, Roberto J. Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA),; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA); Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Ecología; Argentina Fil: Posse Beaulieu, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina 2022-09-23T10:23:42Z 2022-09-23T10:23:42Z 2022-06-23 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVesion http://hdl.handle.net/20.500.12123/12946 https://www.frontiersin.org/articles/10.3389/fsoil.2022.903544/full 2673-8619 https://doi.org/10.3389/fsoil.2022.903544 eng info:eu-repograntAgreement/INTA/PNNAT-1128023/AR./Emisiones de gases con efecto invernadero. info:eu-repograntAgreement/INTA/2019-PD-E3-I058-001/2019-PD-E3-I058-001/AR./EMISIONES (GEI) EN LOS SISTEMAS AGROPECUARIOS y FORESTALES. MEDIDAS DE MITIGACIÓN info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Frontiers Media Frontiers Soil Science 2 : 903544 (June 2022)
spellingShingle Agriculture
Moderate Resolution Imaging Spectroradiometer
Crops
Farmland
Agricultura
Espectrorradiómetro de Imágenes de Resolución Moderada
Cultivos
Tierras Agrícolas
Net Biome Productivity
Upscaline
Carbon Fluxes
Crop Type Mapping
Productividad Neta del Bioma
Flujos de Carbono
Mapeo de Tipos de Cultivos
Marconato, Ulises Mariano
Fernández, Roberto J.
Posse Beaulieu, Gabriela
Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title_full Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title_fullStr Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title_full_unstemmed Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title_short Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes
title_sort cropland net ecosystem exchange estimation for the inland pampas argentina using evi land cover maps and eddy covariance fluxes
topic Agriculture
Moderate Resolution Imaging Spectroradiometer
Crops
Farmland
Agricultura
Espectrorradiómetro de Imágenes de Resolución Moderada
Cultivos
Tierras Agrícolas
Net Biome Productivity
Upscaline
Carbon Fluxes
Crop Type Mapping
Productividad Neta del Bioma
Flujos de Carbono
Mapeo de Tipos de Cultivos
url http://hdl.handle.net/20.500.12123/12946
https://www.frontiersin.org/articles/10.3389/fsoil.2022.903544/full
https://doi.org/10.3389/fsoil.2022.903544
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