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These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

These data were compiled to provide a quantitative, spatially explicit estimate of ecological resilience and resistance (R&R) under ambient and projected future climate conditions. Objective of our study was to understand where and why climate change will alter the distribution of ecological resilience and resistance in the sagebrush biome throughout the 21st century. To accomplish this, we pursued four specific objectives: we estimated the new R&R indicators under future climate conditions and quantified changes from historical conditions; we developed a continuous R&R index that integrates probability information from the underlying predictive R&R models; we assessed the robustness of projected changes in R&R to uncertainty in future climate conditions. These data represent spatially-explicit estimates of ecological resilience and resistance (R&R; categorical indicators, probabilities, continuous indices) under ambient and downscaled projected historical and future climate conditions (historical, RCP 4.5, and RCP 8.5 CMIP5 scenarios). These data were created in rangelands and open woodlands across the sagebrush biome in 2023. These data were created by a collaboration between Northern Arizona University and the U.S. Geological Survey, Southwest Biological Science Center based on modeling which utilized predictive R&R models utilizing ecological and climate metrics which were based on soil properties (NRCS), ambient climate data (gridMET), and downscaled climate projections (MACAv2-METDATA). These data can be used to assess geographic patterns in resilience and resistance under ambient and projected future climate conditions.

These data were compiled as a part of a landscape conservation design effort for the sagebrush biome and are the result of applying a spatially explicit model that assessed geographic patterns in Sagebrush Ecological Integrity and, a new quantitative measure of the intactness of sagebrush plant communities, used these results to identify Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas (ORAs). Our overall objective in this study was to characterize geographic patterns in ecological integrity of sagebrush ecosystems. These data represent the estimated integrity of sagebrush ecosystems, estimated from a spatial model that assigns high integrity in areas with abundant big sagebrush and perennial grass/forb cover and with minimal annual grass/forb cover, minimal conifers, and minimal human modification. This spatial model was applied over the entire sagebrush and was estimated for 5 historical time periods between 1998 and 2020, and for one future time period (2030-2060). For each time period, input data were derived from satellite imagery, and the spatial model used those input values to estimate Sagebrush Ecological Integrity. This approach to estimating ecological integrity was developed by consultation with experts from across the biome, allowing for the relationship between integrity and plant cover to vary among regions, as described in Doherty et al (2022). These data can be used to inform and prioritize conservation and restoration efforts across the sagebrush biome.

These data were compiled as a part of a landscape conservation design effort for the sagebrush biome and are the result of applying a spatially explicit model that assessed geographic patterns in Sagebrush Ecological Integrity and, a new quantitative measure of the intactness of sagebrush plant communities, used these results to identify Core Sagebrush Areas (CSAs), Growth Opportunity Areas (GOAs), and Other Rangeland Areas (ORAs). Our overall objective in this study was to characterize geographic patterns in ecological integrity of sagebrush ecosystems. These data represent the estimated integrity of sagebrush ecosystems, estimated from a spatial model that assigns high integrity in areas with abundant big sagebrush and perennial grass/forb cover and with minimal annual grass/forb cover, minimal conifers, and minimal human modification. This spatial model was applied over the entire sagebrush and was estimated for 5 historical time periods between 1998 and 2020, and for one future time period (2030-2060). For each time period, input data were derived from satellite imagery, and the spatial model used those input values to estimate Sagebrush Ecological Integrity. This approach to estimating ecological integrity was developed by consultation with experts from across the biome, allowing for the relationship between integrity and plant cover to vary among regions, as described in Doherty et al (2022). These data can be used to inform and prioritize conservation and restoration efforts across the sagebrush biome.

A 30 meter integer grid derived from USGS GAP data published in 2010 of sagebrush land cover within 120 meters of conifer land cover. It is one of several inputs used in the BLM FIAT analysis completed March 2015. FIAT was developed using a process designed to identify strategies that ameliorate threats to Greater Sage-Grouse (GRSG; Centrocercus urophasianus) and their habitats. While the assessment is applicable across the range of sage-grouse, the analysis is limited to Western Association of Fish and Wildlife Management Agencies’(WAFWA) Management Zones III, IV, and V (roughly the Great Basin region) because of the significant issues associated with invasive annual grasses and the high level of wildfires in this region. It incorporates emerging science, regional findings, and local data in identifying management opportunities that counter detrimental ecological trends in wildfire, invasive annual grasses, and conifer expansion. The purpose of the assessment is to identify potential project areas and management strategies in highly valued greater sage-grouse habitats which, if implemented, would reduce the threats to greater sage-grouse.

A 30 meter integer grid derived from USGS GAP data published in 2010 of sagebrush land cover within 120 meters of conifer land cover. It is one of several inputs used in the BLM FIAT analysis completed March 2015. FIAT was developed using a process designed to identify strategies that ameliorate threats to Greater Sage-Grouse (GRSG; Centrocercus urophasianus) and their habitats. While the assessment is applicable across the range of sage-grouse, the analysis is limited to Western Association of Fish and Wildlife Management Agencies’(WAFWA) Management Zones III, IV, and V (roughly the Great Basin region) because of the significant issues associated with invasive annual grasses and the high level of wildfires in this region. It incorporates emerging science, regional findings, and local data in identifying management opportunities that counter detrimental ecological trends in wildfire, invasive annual grasses, and conifer expansion. The purpose of the assessment is to identify potential project areas and management strategies in highly valued greater sage-grouse habitats which, if implemented, would reduce the threats to greater sage-grouse.

This data release contains a formatted dataset compiled from multiple databases on restoration treatments and environmental conditions from across the sagebrush (Artemisia spp.) biome. With these data, we modeled the influence of environmental conditions and restoration treatments on trends in sagebrush cover using generalized additive models. We then used these models to create maps of projected sagebrush cover 30 years following wildfire (no treatment, and aerial or drill seeding of sagebrush). We also provide maps for the probability of recovery after 30 years without treatment, with aerial seeding of sagebrush, or with drill seeding of sagebrush. Widespread degradation of ecosystem function and biodiversity loss has led to calls for massive investments in ecological restoration across the globe, but limited resources necessitate targeted application of restoration efforts. In western North America, disturbances such as wildfire, drought, and invasive species are increasingly altering the sagebrush biome, degrading habitat for species of conservation concern such as greater sage-grouse (Centrocercus urophasianus). Effective restoration is needed to address these challenges, but understanding the conditions determining when, where, and at what rate sagebrush recovery will occur is a pressing research need across the vast and heterogeneous sagebrush landscape. Files included in this data release: sage_dat_release.csv – compiled and formatted multiple treatment and environmental datasets spanning broad spatio-temporal extents sagebrush_notreat.tif – projected sagebrush cover 30 years following wildfire given local environmental conditions, without treatment sagebrush_notreat_sd.tif – error (summarized across simulations) in projected sagebrush cover 30 years following wildfire given local environmental conditions, without treatment perc_change_sage_aerial_artemisia.tif – projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with aerial seeding Artemisia spp. perc_change_sage_aerial_artemisia_sd.tif – error (summarized across simulations) in projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with aerial seeding Artemisia spp. perc_change_sage_drill_artemisia.tif – projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with drill seeding Artemisia spp. perc_change_sage_drill_artemisia_sd.tif – error (summarized across simulations) in projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with drill seeding Artemisia spp. prob_recovery_notreat.tif – probability of recovery 30 years after wildfire, without treatment prob_recovery_aerial_artemisia.tif – probability of recovery 30 years after wildfire, with aerial seeding Artemisia spp. prob_recovery_drill_artemisia.tif – probability of recovery 30 years after wildfire, with drill seeding Artemisia spp.

This data release contains a formatted dataset compiled from multiple databases on restoration treatments and environmental conditions from across the sagebrush (Artemisia spp.) biome. With these data, we modeled the influence of environmental conditions and restoration treatments on trends in sagebrush cover using generalized additive models. We then used these models to create maps of projected sagebrush cover 30 years following wildfire (no treatment, and aerial or drill seeding of sagebrush). We also provide maps for the probability of recovery after 30 years without treatment, with aerial seeding of sagebrush, or with drill seeding of sagebrush. Widespread degradation of ecosystem function and biodiversity loss has led to calls for massive investments in ecological restoration across the globe, but limited resources necessitate targeted application of restoration efforts. In western North America, disturbances such as wildfire, drought, and invasive species are increasingly altering the sagebrush biome, degrading habitat for species of conservation concern such as greater sage-grouse (Centrocercus urophasianus). Effective restoration is needed to address these challenges, but understanding the conditions determining when, where, and at what rate sagebrush recovery will occur is a pressing research need across the vast and heterogeneous sagebrush landscape. Files included in this data release: sage_dat_release.csv – compiled and formatted multiple treatment and environmental datasets spanning broad spatio-temporal extents sagebrush_notreat.tif – projected sagebrush cover 30 years following wildfire given local environmental conditions, without treatment sagebrush_notreat_sd.tif – error (summarized across simulations) in projected sagebrush cover 30 years following wildfire given local environmental conditions, without treatment perc_change_sage_aerial_artemisia.tif – projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with aerial seeding Artemisia spp. perc_change_sage_aerial_artemisia_sd.tif – error (summarized across simulations) in projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with aerial seeding Artemisia spp. perc_change_sage_drill_artemisia.tif – projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with drill seeding Artemisia spp. perc_change_sage_drill_artemisia_sd.tif – error (summarized across simulations) in projected change in sagebrush cover (relative to no treatment) 30 years following wildfire given local environmental conditions, with drill seeding Artemisia spp. prob_recovery_notreat.tif – probability of recovery 30 years after wildfire, without treatment prob_recovery_aerial_artemisia.tif – probability of recovery 30 years after wildfire, with aerial seeding Artemisia spp. prob_recovery_drill_artemisia.tif – probability of recovery 30 years after wildfire, with drill seeding Artemisia spp.

A 30 meter integer grid derived from USGS GAP data published in 2010 of sagebrush land cover within 120 meters of conifer land cover. It is one of several inputs used in the BLM FIAT analysis completed March 2015. FIAT was developed using a process designed to identify strategies that ameliorate threats to Greater Sage-Grouse (GRSG; Centrocercus urophasianus) and their habitats. While the assessment is applicable across the range of sage-grouse, the analysis is limited to Western Association of Fish and Wildlife Management Agencies’(WAFWA) Management Zones III, IV, and V (roughly the Great Basin region) because of the significant issues associated with invasive annual grasses and the high level of wildfires in this region. It incorporates emerging science, regional findings, and local data in identifying management opportunities that counter detrimental ecological trends in wildfire, invasive annual grasses, and conifer expansion. The purpose of the assessment is to identify potential project areas and management strategies in highly valued greater sage-grouse habitats which, if implemented, would reduce the threats to greater sage-grouse.