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

IF 2.1 Q3 SOIL SCIENCE
Ulises Marconato, R. J. Fernández, G. Posse
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引用次数: 3

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 (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.
利用EVI、土地覆盖图和涡协方差通量估算内陆潘帕斯(阿根廷)的农田净生态系统交换
生态系统净交换(NEE)的估计对于评估农业系统的固碳/碳源能力至关重要。尽管已经建立了几个基于通量塔数据描述碳通量模式的全球模型,但在用于校准这些模型的数据库中,南美生态系统(尤其是农田)的代表性不足,导致区域和全球净环境足迹估计存在很大的不确定性。尽管全世界几乎一半的地表用于农业活动,但这些模型仍然不包括与农田管理有关的变量。利用来自MODIS图像(250米)的增强植被指数(EVI)和来自内陆潘帕斯地区农田涡度协方差(EC)通量塔9年记录的每月CO2交换,我们开发了预测每月NEE的回归模型。我们测试了将作物特性/土地覆盖作为分类变量(玉米、大豆、小麦和休耕)是否可以提高模型捕捉月度NEE动态的能力。使用作物类型图,将通量塔现场测得的NEE按比例缩放为潘帕内陆的农田,根据作物类型图生成2018-2019年、2019-2020年和2020-2021年农业活动的年度NEE图。仅基于EVI的模型被证明是研究地区月度NEE的一个很好的预测指标(r2=0.78),但通过纳入作物特性术语(r2=0.83),模型调整得到了改进。第二组地图是在考虑收获期间碳出口的情况下生成的,以估计县一级的净生物多样性生产力(NBP)。在三次研究活动中,整个地区的作物作为一个碳汇,尽管具有高度异质的空间和时间模式。60%至80%的固碳在收获期间出口,与仅使用NEE估计的固碳能力相比大幅下降,如果考虑到农业供应的化石碳排放,固碳能力将进一步下降。本研究中提出的估计是在南美洲农田地区扩大区域范围内碳通量的第一步,有助于改进区域到全球的碳通量估计,并完善国家温室气体清单。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.90
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