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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.

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.

This dataset provides the plot-level data of the relative cover of ten different plant associations derived from a structural topic model and resistance and resilience metrics for predicting their abundances. Data comes from four different fires across the Great Basin: the 2007 Murphy Fire, 2012 Rush Fire, 2012 Holloway Fire, and the 2015 Soda Fire. Additional data utilized in the cross referenced paper from the Orchard Combat Training Center was redacted due to military rules but can be requested through the Idaho National Guard Environmental Management Office. Bureau of Land Management data (Murphy, Holloway, and Rush) species cover data was collected using line-point intercept methods on plots with between one and three transects of 25m or 50m in length. An additional small set of data (<1%) was collected by the Idaho Fish and Game using Daubenmire cover grids. Soda fire species cover data was collected with overhead photos and a grid-point intercept technique using Samplepoint software (Booth et al. 2006). Structural topic modelling was run to get the relative cover of ten different plant associations at each plot (Applestein et al. 2024).

This dataset provides the plot-level data of the relative cover of ten different plant associations derived from a structural topic model and resistance and resilience metrics for predicting their abundances. Data comes from four different fires across the Great Basin: the 2007 Murphy Fire, 2012 Rush Fire, 2012 Holloway Fire, and the 2015 Soda Fire. Additional data utilized in the cross referenced paper from the Orchard Combat Training Center was redacted due to military rules but can be requested through the Idaho National Guard Environmental Management Office. Bureau of Land Management data (Murphy, Holloway, and Rush) species cover data was collected using line-point intercept methods on plots with between one and three transects of 25m or 50m in length. An additional small set of data (<1%) was collected by the Idaho Fish and Game using Daubenmire cover grids. Soda fire species cover data was collected with overhead photos and a grid-point intercept technique using Samplepoint software (Booth et al. 2006). Structural topic modelling was run to get the relative cover of ten different plant associations at each plot (Applestein et al. 2024).

These NetCDF data were compiled to investigate how two complementary models can contribute to our understanding of contemporary and future big sagebrush regeneration across the historical and potential future sagebrush region. Objective of our study was to apply both models to address three specific objectives: (i) examine the geographic patterns of big sagebrush regeneration probabilities that the two different models project under historical conditions and future climate scenarios; (ii) quantify the robustness of model projections, e.g., the consistency among climate models in projected changes in regeneration for future time periods; and (iii) identify how model predictions for regeneration potential relate to environmental site characteristics like climate, soil moisture, and soils. Big sagebrush regeneration was modeled based on daily meteorological and ecohydrological variables across the historical and potential future geographic range of big sagebrush distribution in the western United States. These data represent the simulated potential of big sagebrush regeneration representing (i) range-wide big sagebrush regeneration responses in natural vegetation (process-based model, Schlaepfer et al. 2014) and (ii) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model, Shriver et al. 2018) as well as soil moisture and climatic variables for recent climate 1980-2010, and for future projected climate represented by all available climate models under two representative concentration pathways (RCP4.5 and RCP8.5) at two time periods during the 21st century (2020-2050 and 2070-2099) at 10-km resolution based on a simulation experiment described in Bradford et al. 2019 using the SOILWAT2 ecosystem water balance model (Schlaepfer et al. 2021). These data were created by a collaborative research project between the U.S. Geological Survey and Yale University.

These NetCDF data were compiled to investigate how two complementary models can contribute to our understanding of contemporary and future big sagebrush regeneration across the historical and potential future sagebrush region. Objective of our study was to apply both models to address three specific objectives: (i) examine the geographic patterns of big sagebrush regeneration probabilities that the two different models project under historical conditions and future climate scenarios; (ii) quantify the robustness of model projections, e.g., the consistency among climate models in projected changes in regeneration for future time periods; and (iii) identify how model predictions for regeneration potential relate to environmental site characteristics like climate, soil moisture, and soils. Big sagebrush regeneration was modeled based on daily meteorological and ecohydrological variables across the historical and potential future geographic range of big sagebrush distribution in the western United States. These data represent the simulated potential of big sagebrush regeneration representing (i) range-wide big sagebrush regeneration responses in natural vegetation (process-based model, Schlaepfer et al. 2014) and (ii) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model, Shriver et al. 2018) as well as soil moisture and climatic variables for recent climate 1980-2010, and for future projected climate represented by all available climate models under two representative concentration pathways (RCP4.5 and RCP8.5) at two time periods during the 21st century (2020-2050 and 2070-2099) at 10-km resolution based on a simulation experiment described in Bradford et al. 2019 using the SOILWAT2 ecosystem water balance model (Schlaepfer et al. 2021). These data were created by a collaborative research project between the U.S. Geological Survey and Yale University.