Tallgrass Prairie Responses to Weather Variability and Management: Analyses of Vegetation Dynamics and Water Use

Abstract

The tallgrass prairie of the Great Plains is an ecologically and economically important grassland ecosystem in the United States. Prairies face significant challenges from weather variability (such as changing precipitation patterns, increased droughts, and heat waves) and management-related disturbances (such as prescribed burns, hay production, and grazing). This study examines the responses of tallgrass prairie to weather variability and management practices using data from the long-term, multi-factor “integrated Grassland-Livestock and Burning Experiment (iGLOBE)” in central Oklahoma. The experiment includes a cluster of eddy covariance (EC) systems across five native tallgrass prairies managed with different grazing, hay production, and burning regimes. The major objectives were to 1) quantify the variations in EC-measured evapotranspiration (ET) at different temporal scales across differently managed prairies under varying environmental conditions, and 2) combine remotely sensed vegetation indices with ET to assess their potential for monitoring and examining ecosystem responses to variable weather and management. Interannual variations in precipitation patterns during the study period (2019–2024) influenced vegetation dynamics, forage production, and ET. Temperature variability also played a crucial role in modifying the impact of precipitation, particularly during the early and late growing seasons. The observed ranges of maximum daily, growing season (April-October), and annual ET were 4.9–8.64 mm d^-1, 468–716 mm, and 546–861 mm, respectively, across pastures. Annual ET: precipitation ratios ranged from 0.67 in wet years to 1.15 in dry years. This study provides a ground-truth ET dataset across different weather and management scenarios, enabling validation of ET estimates from models and satellite-derived products for tallgrass prairies, even where direct ET measurements are unavailable. A strong agreement (R² ≥ 0.70) between satellite-derived enhanced vegetation index (EVI) and EC-measured ET demonstrated the potential to combine these datasets for more precise quantification of how weather and management affect productivity and water use across native prairie landscapes.