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Highlights • The SPoRT-LIS surface soil moisture estimate was validated across the U.S. Great Plains region. • Validation performance was evaluated across varying soil types, land cover, depth, slope, aspect, and pixel heterogeneity. • Results demonstrate that SPoRT-LIS surface soil moisture is suitable for water resources applications. Abstract Evaluation of surface soil moisture is necessary to understand spatiotemporal soil moisture trends and their implications on water resources management. This research evaluated a real-time instantiation of NASA's Land Information System (LIS) for water resources management applications at a higher spatial and temporal resolution than is currently available with remotely-sensed satellite estimates or in situ measurements of the same product. Managed by NASA's Short-term Prediction Research and Transition (SPoRT) Center, the "SPoRT-LIS" is an observation-driven, real-time simulation of the Noah land surface model at a 3-km resolution over the full continental United States. Surface soil moisture estimates from SPoRT-LIS (0–10 cm layer) were validated against in situ soil moisture from the International Soil Moisture Network in the Missouri and Arkansas-Red-White River Basins. Validation was conducted at in situ measurement depths of 5-cm and 10-cm, and performance was evaluated across varying soil types, land cover, depth, slope, aspect, and pixel heterogeneity to determine conditions under which SPoRT-LIS surface soil moisture had excellent estimation capability. Results demonstrate that 53% of data at a depth of 5-cm and 51% of the data at a depth of 10-cm were significantly correlated with a Spearman's ρ greater than 0.5 on a daily basis. Based upon validation results, it is evident that the SPoRT-LIS surface soil moisture estimate is satisfactory for research and operational water resources management applications. [ABSTRACT FROM AUTHOR]

For millennia grasslands have provided a myriad of ecosystem services and have been coupled with human resource use. The loss of 46% of grasslands worldwide necessitates the need for conservation that is spatially, temporally, and socioeconomically strategic. In the Southern Great Plains of the United States, conversion of native grasslands to cropland, woody encroachment, and establishment of vertical anthropogenic features have made large intact grasslands rare for lesser prairie-chickens (Tympanuchus pallidicinctus). However, it remains unclear how the spatial distribution of grasslands and anthropogenic features constrain populations and influence conservation. We estimated the distribution of lesser prairie-chickens using data from individuals marked with GPS transmitters in Kansas and Colorado, USA, and empirically derived relationships with anthropogenic structure densities and grassland composition. Our model suggested decreased probability of use in 2-km radius (12.6 km2) landscapes that had greater than two vertical features, two oil wells, 8 km of county roads, and 0.15 km of major roads or transmission lines. Predicted probability of use was greatest in 5-km radius landscapes that were 77% grassland. Based on our model predictions, ~10% of the current expected lesser prairie-chicken distribution was available as habitat. We used our estimated species distribution to provide spatially explicit prescriptions for CRP enrollment and tree removal in locations most likely to benefit lesser prairie-chickens. Spatially incentivized CRP sign up has the potential to provide 4189 km2 of additional habitat and strategic application of tree removal has the potential to restore 1154 km2. Tree removal and CRP enrollment are conservation tools that can align with landowner goals and are much more likely to be effective on privately owned working lands. [ABSTRACT FROM AUTHOR]