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Abstract Winter wheat (Triticum aestivum L.) and tallgrass prairie are common land cover types in the Southern Plains of the United States. During the last century, agricultural expansion into native grasslands was extensive, particularly managed pasture or winter wheat. In this study, we measured carbon dioxide (CO 2) and water vapor (H 2 O) fluxes from winter wheat and tallgrass prairie sites in Central Oklahoma using the eddy covariance in 2015 and 2016. The objective of this study was to contrast CO 2 and H 2 O fluxes between these two ecosystems to provide insights on the impacts of conversion of tallgrass prairie to winter wheat on carbon and water budgets. Daily net ecosystem CO 2 exchange (NEE) reached seasonal peaks of −9.4 and −8.8 g C m−2 in 2015 and −6.2 and −7.5 g C m−2 in 2016 at winter wheat and tall grass prairie sites, respectively. Both sites were net sink of carbon during their growing seasons. At the annual scale, the winter wheat site was a net source of carbon (56 ± 13 and 33 ± 9 g C m−2 year−1 in 2015 and 2016, respectively). In contrast, the tallgrass prairie site was a net sink of carbon (−128 ± 69 and −119 ± 53 g C m−2 year−1 in 2015 and 2016, respectively). Daily ET reached seasonal maximums of 6.0 and 5.3 mm day−1 in 2015, and 7.2 and 8.2 mm day−1 in 2016 at the winter wheat and tallgrass prairie sites, respectively. Although ecosystem water use efficiency (EWUE) was higher in winter wheat than in tallgrass prairie at the seasonal scale, summer fallow contributed higher water loss from the wheat site per unit of carbon fixed, resulting into lower EWUE at the annual scale. Results indicate that the differences in magnitudes and patterns of fluxes between the two ecosystems can influence carbon and water budgets. Graphical abstract Unlabelled Image Highlights • Carbon and water fluxes measured in two ecosystems located at 2.7 km apart are compared. • Winter wheat and tallgrass prairie are both carbon sinks during the growing season. • Summer fallow caused the wheat ecosystem to be a source of carbon at annual scale. • Management practices caused changes in the fluxes of prairie and wheat ecosystems. [ABSTRACT FROM AUTHOR]

• Managed pasture showed higher sensitivity to drought than native pasture. • Spring temperature and fall rainfall were critical for managed pasture. • Management activities modulated the effects of environmental variables on productivity. Future weather and climates, especially rainfall, are expected to have larger variability in the Southern Plains of the United States. However, the degree and timing of environmental variability that affect productivity of pastures managed differently have not been well studied. We examined the impacts of environmental variability on grassland productivity using 17 years of gross primary productivity (GPP) data for co-located native and managed prairie pastures in Oklahoma. We also considered the interactive effects of management factors and environmental variability into the regression models and identified the critical temporal windows of environmental variables (CWE) that influence annual variability in GPP. Managed pasture (MP) showed greater variability of GPP than did native pasture (NP), particularly with reduced GPP in drought years. The resilience of native prairies under unfavorable climate extremes was evident by lower GPP anomalies in NP than MP during the 2011–2012 drought. Although both pastures experienced the same degree of environmental variability, the CWE affecting GPP was significantly different between NP and MP due to the modulating impact of management practices on the responses of GPP. Not only the range but also the timings of the CWE were different between NP and MP as MP was more responsive to the spring temperature and fall rainfall. Our findings warrant the incorporation of MP as a different commodity from NP when accounting for the ecosystem responses to environmental variability in global climate models. [ABSTRACT FROM AUTHOR]

• First study to evaluate the impacts of MODIS vs. LS2 on GPP VPM and T VTM estimates. • Combined Landsat/Sentinel-2 (LS2) tracked phenology of prairie, alfalfa, and wheat. • LS2-enhanced vegetation index accurately identified site level optimal temperature. • LS2 data produced better gross primary production (GPP) estimates than MODIS. • The vegetation transpiration model is a simpler approach to estimating transpiration (T). Although agroecosystems have a significant potential to offset carbon dioxide (CO 2), the amount of CO 2 captured can vary significantly depending on management practices. Accurate estimation of gross primary production (GPP) and transpiration (T) of agroecosystems at the field scale are essential for the study of food security and water resource management. To date, the carbon and water fluxes data products for commercial agroecosystems are limited, mostly at the moderate spatial resolution (MSR, hundreds of meters), which cannot be used to assess the temporal dynamics of GPP and T at the field scale. This study used the vegetation photosynthesis model (VPM) and vegetation transpiration model (VTM) to estimate field-level daily GPP (GPP VPM) and T (T VTM), respectively, in native prairie, alfalfa (Medicago sativa L.), and winter wheat (Triticum aestivum L.) in central Oklahoma, USA. We evaluated the reliability and advantages of vegetation indices (enhanced vegetation index, EVI and land surface water index, LSWI) in monitoring the land surface phenology using moderate spatial resolution data from Moderate Resolution Imaging Spectroradiometer (MODIS) and high spatial resolution (HSR, tens of meters) data from Landsat and Sentinel-2. The accuracy of GPP VPM and T VTM estimates at different spatial scales was evaluated using GPP (GPP EC) and evapotranspiration (ET EC) from the eddy flux tower sites, respectively. Results demonstrate the capacity of VPM and VTM to estimate the field-level carbon and water flux dynamics and their responses to weather conditions. The use of HSR vegetation indices helped to address certain challenges faced by MSR indices, especially in capturing the crop phenology in smaller areas with conservation measures or disturbances. The findings highlight the importance of using HSR GPP estimates to reduce uncertainty in quantifying CO 2 fluxes for croplands and grasslands. The findings also demonstrate the ability of the models to track field-level vegetation phenology, carbon uptake, and water use in agroecosystems under different management practices. [ABSTRACT FROM AUTHOR]