Mass and energy fluxes in an intensively managed tropical pasture in Southeastern Brazil - Bianchini, Vitor de Jesus Martins (2025)
Pastures are Brazil\'s dominant land use form and support national livestock production. The Brazilian livestock sector contributes approximately 17 % of the country\'s total greenhouse gas (GHG) emissions, underscoring critical role of its production and the state of its pastures, predominantly in varying stages of degradation. Pastures are also highly susceptible to severe and prolonged droughts, conditions expected to intensify due to climate change. Therefore, integrating livestock intensification strategies with practices to reduce GHG emissions, improving the climate resilience of pasture-based systems, and improve their efficiency in utilizing natural resources is a significant challenge for Brazil. However, Brazil still faces a shortage of studies focused on tropical pastures examining how enhanced management practices influence GHG flux dynamics and water usage in these agroecosystems. An experiment was carried out in an elephant grass (Pennisetum purpureum Schum. cv. Cameroon) pasture subjected to intermittent stocking management strategies in Southeastern Brazil. Seasonal variations in net ecosystem CO2 exchange (NEE), actual evapotranspiration (ETa), and water use efficiency were analyzed using eddy covariance measurements. Meteorological variables and plant measurements were used to identify the critical drivers for the CO2 fluxes through statistical modeling. Results showed that the pasture acted as a net source of CO2 to the atmosphere in both years studied. The annual NEE was 34 ± 14 g CO2-C m-2 yr-1 in 2021-2022 and 21 ± 12 g CO2-C m-2 yr-1 in 2022-2023. Ecosystem respiration, driven by increased air and soil temperatures, heightened rainfall, and higher incoming solar radiation levels, especially during spring and summer, played a crucial role in this result. The pasture absorbed more CO2, showed higher ETa, and produced more leaves in the rainy periods when the pasture structure was kept close to the management targets. CO2 losses to the atmosphere prevailed in the dry periods and in wet periods where the pasture structure deviated significantly from the optimal limits for elephant grass. Understanding the dynamics of ETa and its relationship to the overall water balance of the agroecosystem is crucial for assessing how pastures respond to rainfall variability and drought events and evaluating crop water productivity. To further investigate this relationship, a satellite-based remote sensing method was used to estimate pasture ETa from reflectance-based basal crop coefficients (Kcbrf) derived from a linear relationship between basal crop coefficients (Kcb) and a spectral vegetation index (VI). The Kcb-VI relationship developed in this study showed a strong positive correlation between the soil-adjusted vegetation index (SAVI) and Kcb, with ϱ and R2 values of 0.89 and 0.79, respectively. Comparisons between observed and simulated ETa indicated good agreement for daily values (RMSE of 0.59 mm d-1, D of 0.86) and for average weekly values (RMSE of 0.38 mm d-1, D of 0.93). Biases of -5% and 3% were obtained for modeled cumulative ETa in the years 2021-2022 and 2022-2023, respectively. The average crop water productivity values were comparable between the two years, 2.2 kg m-3 in 2021-2022 and 1.8 kg m-3 in 2022-2023.