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We present high spatial-resolution trends of the Palmer drought severity index (PDSI), potential evapotranspiration (PET), and selected climate variables from 1979-2013 for the contiguous United States in order to gain an understanding of recent drought trends and their climatic forcings. Based on a spatial grouping analysis, four regions of increasing (upper Midwest, Louisiana, southeastern United States (US), and western US) and decreasing (New England, Pacific Northwest, upper Great Plains, and Ohio River Valley) drought trends based on Mann-Kendall Z values were found. Within these regions, partial correlation and multiple regression for trends in climate variables and PDSI were performed to examine potential climatic controls on these droughts. As expected, there was a US-wide concurrence on drought forcing by precipitation. However, there was correspondence of recent PET trends with recent drought trends in many regions. For regions with an increase in recent droughts, average air temperature was generally the second most important variable after precipitation in determining recent drought trends. Across the regions where recent drought trends are decreasing, there was no clear ranking of climate-variable importance, where trends in average temperature, specific humidity and net radiation all played significant regional roles in determining recent drought trends. Deconstructing the trends in drought show that, while there are regions in the US showing positive and negative trends in drought conditions, the climate forcings for these drought trends are regionally specific. The results of this study allow for the interpretation of the role of the changing hydroclimatic cycle in recent drought trends, which also have implications for the current and impending results of climate change.

While more and more studies are exploring the application of remote sensing in assessing biodiversity for different ecosystems, most consider biodiversity at one point in time. Using several remote-sensing-based metrics, we asked how well remote sensing can detect biodiversity (both aand b-diversity) in a prairie grassland across time using airborne hyperspectral data collected in two successive years (2017 and 2018) and at different periods in the growing season (2018). The ability to detect biodiversity using "spectral diversity" and "spectral species" types indeed varied significantly over a 2-yr timespan. Toward the end of the growing season in 2018, the relationship between field-and remote-sensing-based aand b-diversity weakened compared to data collected from the same season in the previous year. This contrasting pattern between the two years was likely influenced by prescribed fire, altered weather, and the resulting shifting species composition and phenology. These findings indicate that direct detection of aand b-diversity in grasslands should be multi-temporal when possible and should consider the effect of disturbances, climate variables, and phenology. We demonstrate an essential role for airborne platforms in developing a global biodiversity monitoring system involving forthcoming space-borne hyperspectral sensors.