These data represent simulated ecological drought conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) describe geographic patterns in ecological drought under historical climate conditions, 2) quantify the direction and magnitude of change in ecological drought, 3) identify areas and ecological drought metrics with projected changes that are robust across climate models, defined as drought metrics and locations where >90% of climate models agree in the direction of change.

Drylands cover 40% of the global terrestrial surface and provide important ecosystem services. While drylands as a whole are expected to increase in distribution and aridity in coming decades, temperature and precipitation forecasts vary by latitude and geographic region suggesting different trajectories for tropical, subtropical, and temperate drylands. Uncertainty in the future of tropical and subtropical drylands is well constrained, whereas soil moisture and ecological droughts, which drive vegetation productivity and composition, remain poorly understood in temperate drylands. Here we show that, over the 21st century, temperate drylands may contract by a third, primarily converting to subtropical drylands, and that deep soil layers will be increasingly dry during the growing season. These changes imply major shifts in vegetation and ecosystem service delivery. Our results illustrate the importance of appropriate drought measures and, as the first global study to focus on temperate drylands, highlight a distinct fate for these highly-populated areas. The data are outputs from the SOILWAT ecohydrological model, which was applied in a grid over 6 temperate drylands across the globe (South America, Southern Africa, Eastern Asia, Western and Central Asia, Western Mediterranean basin, and North America. Simulations were conducted for two time periods: 1980-2010 and 2069-2099.

This dataset provides the final report from the Adaptation and Response in Drylands (ARID) scoping study. ARID is one of the two scoping studies funded by NASA in 2023 to identify the scientific questions and develop the initial study design and implementation concept for a new NASA Terrestrial Ecology field campaign. This report emphasizes a prioritized research agenda and an initial implementation plan, focusing on the western U.S. to deepen our understanding of national dryland processes and resources. ARID is also leveraging an extensive network of international sites and collaborators in Africa, Australia, Mexico, and South America. This global approach facilitates the evaluation, monitoring, and forecasting of drylands worldwide, ensuring a coordinated effort to address and inform solutions for the challenges facing these critical ecosystems. ARID will use cutting-edge approaches to address four Science Themes: 1) Climate Variability and Drought, 2) Ecosystem Structure, Function, and Biodiversity, 3) Carbon Cycle Interannual Variability and Long-Term Trends, and 4) Social-Ecological Systems. The scoping study performed extensive outreach, conducting over 160 meetings and events with hundreds of scientists and decision-makers across six continents, which translated to the ARID science plan being co-created with a wide range of contributors and perspectives, including remote sensing, modeling, and dryland scientists; Tribal Nations; and a range of U.S. federal entities. This report outlines a targeted plan to deploy field and NASA airborne instruments to vastly augment data derived from satellite observations that, when joined, will substantially advance quantification of drylands' large and changing role in the U.S. and in the Earth system.

These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.

This dataset provides the final report from the Adaptation and Response in Drylands (ARID) scoping study. ARID is one of the two scoping studies funded by NASA in 2023 to identify the scientific questions and develop the initial study design and implementation concept for a new NASA Terrestrial Ecology field campaign. This report emphasizes a prioritized research agenda and an initial implementation plan, focusing on the western U.S. to deepen our understanding of national dryland processes and resources. ARID is also leveraging an extensive network of international sites and collaborators in Africa, Australia, Mexico, and South America. This global approach facilitates the evaluation, monitoring, and forecasting of drylands worldwide, ensuring a coordinated effort to address and inform solutions for the challenges facing these critical ecosystems. ARID will use cutting-edge approaches to address four Science Themes: 1) Climate Variability and Drought, 2) Ecosystem Structure, Function, and Biodiversity, 3) Carbon Cycle Interannual Variability and Long-Term Trends, and 4) Social-Ecological Systems. The scoping study performed extensive outreach, conducting over 160 meetings and events with hundreds of scientists and decision-makers across six continents, which translated to the ARID science plan being co-created with a wide range of contributors and perspectives, including remote sensing, modeling, and dryland scientists; Tribal Nations; and a range of U.S. federal entities. This report outlines a targeted plan to deploy field and NASA airborne instruments to vastly augment data derived from satellite observations that, when joined, will substantially advance quantification of drylands' large and changing role in the U.S. and in the Earth system.

These data were compiled as a supplement to a previously published journal article (Bradford et al., 2019), that employed a ecosystem water balance model to characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America. Also, these data are associated with a published USGS data release (Bradford and Schlaepfer, 2019). The objectives of our study were to (1) characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America, (2) evaluate the impact of these changes on estimation of resilience and resistance among a representative set of climate scenarios. These data represent geographic patterns in simulated soil temperature and soil moisture conditions and underlying variables based on SOILWAT2 simulations under climate conditions representing historical (current) time period (1980-2010) and two future projected time periods (2020-2050, d40yrs) and (2070-2100, d90yrs) for two representative concentration pathways (RCP4.5, RCP8.5) as medians across simulation runs based on output from each of the available downscaled global circulation models that participated in CMIP5 (RCP4.5, 37 GCMs; RCP8.5, 35 GCMs; Maurer et al. 2007). Additional information about the SOILWAT2 simulation experiments can be found in Bradford et al. 2019. These data were created in 2018, 2019, and 2021 for the area of the sagebrush region in the western North America. These data were created by a collaborative research project between the U.S. Geological Survey, Marshall University and Yale University. These data can be used with the high-resolution matching as defined by Renne et al. (in prep.), and within the scope of Bradford et al. 2019. These data may also be used to evaluate the potential impact of changing climate conditions on geographic patterns in simulated soil temperature and soil moisture conditions.

These data were compiled as a supplement to a previously published journal article (Bradford et al., 2019), that employed a ecosystem water balance model to characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America. Also, these data are associated with a published USGS data release (Bradford and Schlaepfer, 2019). The objectives of our study were to (1) characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America, (2) evaluate the impact of these changes on estimation of resilience and resistance among a representative set of climate scenarios. These data represent geographic patterns in simulated soil temperature and soil moisture conditions and underlying variables based on SOILWAT2 simulations under climate conditions representing historical (current) time period (1980-2010) and two future projected time periods (2020-2050, d40yrs) and (2070-2100, d90yrs) for two representative concentration pathways (RCP4.5, RCP8.5) as medians across simulation runs based on output from each of the available downscaled global circulation models that participated in CMIP5 (RCP4.5, 37 GCMs; RCP8.5, 35 GCMs; Maurer et al. 2007). Additional information about the SOILWAT2 simulation experiments can be found in Bradford et al. 2019. These data were created in 2018, 2019, and 2021 for the area of the sagebrush region in the western North America. These data were created by a collaborative research project between the U.S. Geological Survey, Marshall University and Yale University. These data can be used with the high-resolution matching as defined by Renne et al. (in prep.), and within the scope of Bradford et al. 2019. These data may also be used to evaluate the potential impact of changing climate conditions on geographic patterns in simulated soil temperature and soil moisture conditions.

These data were compiled using a new multivariate matching algorithm that transfers simulated soil moisture conditions (Bradford et al. 2020) from an original 10-km resolution to a 30-arcsec spatial resolution. Also, these data are a supplement to a previously published journal article (Bradford et al., 2020) and USGS data release (Bradford and Schlaepfer, 2020). The objectives of our study were to (1) characterize geographic patterns in ecological drought under historical climate, (2) quantify the direction and magnitude of projected responses in ecological drought under climate change, (3) identify areas and drought metrics with projected changes that are robust across climate models for a representative set of climate scenarios. These data represent geographic patterns in simulated ecological drought metrics based on SOILWAT2 simulations under climate conditions representing historical (current) time period (1980-2010) and two future projected time periods (2020-2050, d40yrs) and (2070-2100, d90yrs) for two representative concentration pathways (RCP4.5, RCP8.5) as medians across simulation runs based on output from each of the available downscaled global circulation models that participated in CMIP5 (RCP4.5, 37 GCMs; RCP8.5, 35 GCMs; Maurer et al. 2007). Additional information about the setup of SOILWAT2 simulation experiments can be found in Bradford et al. 2020. These data were created in 2020 and 2021 for the area of the sagebrush region in the western North America. These data were created by a collaborative research project between the U.S. Geological Survey and Yale University. These data can be used with the high-resolution matching algorithm (Renne et al., 202X), within the scope of Bradford et al. 2020, and as defined by the study. These data may also be used to evaluate the potential impact of changing climate conditions on robust ecological drought metrics within the scope defined by the study.

These data were compiled using a new multivariate matching algorithm that transfers simulated soil moisture conditions (Bradford et al. 2020) from an original 10-km resolution to a 30-arcsec spatial resolution. Also, these data are a supplement to a previously published journal article (Bradford et al., 2020) and USGS data release (Bradford and Schlaepfer, 2020). The objectives of our study were to (1) characterize geographic patterns in ecological drought under historical climate, (2) quantify the direction and magnitude of projected responses in ecological drought under climate change, (3) identify areas and drought metrics with projected changes that are robust across climate models for a representative set of climate scenarios. These data represent geographic patterns in simulated ecological drought metrics based on SOILWAT2 simulations under climate conditions representing historical (current) time period (1980-2010) and two future projected time periods (2020-2050, d40yrs) and (2070-2100, d90yrs) for two representative concentration pathways (RCP4.5, RCP8.5) as medians across simulation runs based on output from each of the available downscaled global circulation models that participated in CMIP5 (RCP4.5, 37 GCMs; RCP8.5, 35 GCMs; Maurer et al. 2007). Additional information about the setup of SOILWAT2 simulation experiments can be found in Bradford et al. 2020. These data were created in 2020 and 2021 for the area of the sagebrush region in the western North America. These data were created by a collaborative research project between the U.S. Geological Survey and Yale University. These data can be used with the high-resolution matching algorithm (Renne et al., 202X), within the scope of Bradford et al. 2020, and as defined by the study. These data may also be used to evaluate the potential impact of changing climate conditions on robust ecological drought metrics within the scope defined by the study.

The dryland ecosystems of the western United States have been invaded by exotic annual grasses, such as cheatgrass (Bromus tectorum L.), that has promoted increased fire activity and reduced biodiversity detrimental to socio-environmental systems. The use of remote sensing tools to monitor exotic annual grass cover and dynamics over large areas can support early detection and rapid response initiatives. This dataset was generated using in situ observations from Bureau of Land Management's (BLM) Assessment, Inventory, and Monitoring data (AIM) plots, weekly composites of harmonized Landsat and Sentinel-2 (HLS) data, relevant environmental, vegetation, remotely sensed, and geophysical factors and machine learning techniques to develop fractional estimates of exotic annual grass cover at a 30-m spatial resolution for 2016 to 2019. A total of 10,906 AIM plots from years 2016 - 2019 were used to train an ensemble of regression tree models (n=5). Besides cheatgrass (Bromus tectorum), other species such as Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus mardritensis L.,Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., Taeniatherum caput-medusae were included in the study. The geographic coverage includes rangelands in the Great Basin, the Snake River Plain, the state of Wyoming, and contiguous areas.