AUTHOR=Marconato Ulises , Fernández Roberto J. , Posse Gabriela TITLE=Cropland Net Ecosystem Exchange Estimation for the Inland Pampas (Argentina) Using EVI, Land Cover Maps, and Eddy Covariance Fluxes JOURNAL=Frontiers in Soil Science VOLUME=2 YEAR=2022 URL=https://www.frontiersin.org/journals/soil-science/articles/10.3389/fsoil.2022.903544 DOI=10.3389/fsoil.2022.903544 ISSN=2673-8619 ABSTRACT=
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 (250 m) 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 (