Carbon exchange of a dryland cotton field and its relationship with PlanetScope remote sensing data

Autor: Ronnie W. Schnell, Dorothy Menefee, Jason B. West, Nithya Rajan, Muthukumar V. Bagavathiannan, Song Cui
Rok vydání: 2020
Předmět:
Zdroj: Agricultural and Forest Meteorology. 294:108130
ISSN: 0168-1923
Popis: Agricultural systems experience numerous management-associated events during the growing season that can significantly influence seasonal and annual carbon balances. Measurements of carbon fluxes from agricultural fields using micrometeorological techniques such as eddy covariance can improve our understanding of management and weather-driven changes in carbon budgets. In-situ carbon flux data are also valuable in developing remote sensing-based models for extrapolation of biome-specific carbon budgets to higher spatial scales. In this study, net ecosystem carbon dioxide exchange (NEE) was continuously measured for two years (2017 and 2018) from a cotton (Gossypium hirsutum) field in College Station, Texas, USA. The measured NEE was partitioned into assimilatory (Gross Primary Production, GPP) and respiratory (Ecosystem respiration, Reco) fluxes. There were substantial differences in carbon fluxes between the two years, which were driven by variations in meteorological conditions and growth of weeds. Due to dry conditions, growing season carbon uptake in 2018 was reduced (883 g C m−2) compared to 2017 (947 g C m−2). While the growing season of 2018 was dry, the post-harvest off-season was remarkably wet with nearly 68% of the annual precipitation occurring after harvest (848 mm). This favored aggressive growth of weeds, resulting in substantial off-season carbon uptake in 2018 (374 g C m−2 in 2018 compared to 100 g C m−2 in 2017). Overall, the site was a net carbon source (175 g C m−2) in 2017, whereas it was a slight carbon sink (-5 g C m−2) in 2018. A significant correlation was found between satellite-derived normalized difference vegetation index (NDVI) and GPP (R2 0.78 in 2017 and 0.72 in 2018). Given that correlation, it would be possible to broaden these results to the wider region by estimating GPP with satellite data.
Databáze: OpenAIRE