This dataset contains information on the survival of individual sagebrush seedlings, stands of seedlings and the vegetative and topographic conditions in which they were planted.

This dataset contains information on seedling survival, physiochemical, morphological, and eco-physiological characteristics of seedlings grown and planted from seed collected from different sagebrush populations as well as the climatic conditions of those seed source sites in relation to the common garden location in which they were planted.

This dataset contains information on seedling survival, physiochemical, morphological, and eco-physiological characteristics of seedlings grown and planted from seed collected from different sagebrush populations as well as the climatic conditions of those seed source sites in relation to the common garden location in which they were planted.

Evaluating factors that affect recovery of canopy-forming, foundational species is needed to guide effective treatment implementation aimed at mitigating their loss due to the changing fire regimes being experienced in semi-arid shrub-steppe of the Western USA. Most inferences on factors influencing recovery are based on one-time measurements taken as a snapshot in time, usually focused on the short-term initial establishment phase or outcomes observed decades after. We measured factors associated with the secondary establishment of big sagebrush in nearly 2000 plots across a heterogeneous landscape five years after a megafire (115,000 ha) and the diverse mosaic of restoration treatments implemented and compare these findings to previously published inferences on initial, first-year germination patterns observed on the same plots.

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.

To assess the degree to which transplanting sagebrush (Artemisia spp.) could quickly restore former sage-grouse habitat and the strategies by which greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) habitat restoration is best accomplished, we linked vegetation transitions with habitat selection models to evaluate habitat recovery. Within our modeling extent (Tuscarora, Nevada), we simulated the fire-induced loss of habitat, planting of sagebrush seedlings, and the regrowth of sagebrush and other vegetation over 15 years. We used sagebrush growth equations and vegetation state transitions to return and grow vegetation within the burned and planted areas. Every year, we updated seasonal sage-grouse habitat selection maps by re-applying pre-fire habitat selection equations to re-calculate the proportion of suitable habitat gained by sagebrush restoration efforts. We evaluated alternative planting designs to identify the key factors influencing habitat selection outcomes. Specifically, we varied the number of plants, patch sizes, densities, location of planting sites (i.e., random versus within sage-grouse nesting habitat), as well as post-transplant (30, 70, or 100%) survival. We assumed all planting occurred in a single year. We ranked the influence of these different planting factors on sage-grouse habitat recovery across restoration scenario. The following data reflect habitat conditions 15-years after a simulated fire and sagebrush revegetation. Here we provide the habitat recovery results of two different planting designs. We provide several example datasets from this project, including the following: tsf0tsf15_change_nontarg_me_ss_ld_bre10m.tif: Dataset representing a single-year (maximum-effort; me) habitat restoration effort where we used several small (ss) patches with low density (ld) planting of sagebrush. The planting was not targeted for nesting habitat, and the data reflects the change in simulated habitat conditions between 2015 and 2030. tsf0tsf15_change_targ_my_sm_hd_bre10m.tif: Dataset representing a multi-year (my) habitat restoration effort where we used several moderate (sm) patches with high density (hd) planting of sagebrush. The planting was targeted for nesting habitat, and the data reflects the change in simulated habitat conditions between 2015 and 2030. tsf15_nontarg_me_ss_ld_bre_hsi_10m_transf.tif: Dataset representing a single-year (maximum-effort; me) habitat restoration effort where we used several small (ss) patches with low density (ld) planting of sagebrush. The planting was not targeted for nesting habitat, and the data reflects simulated habitat conditions in 2030. tsf15_targ_my_sm_hd_bre_hsi_10m_transf.tif: Dataset representing a multi-year (my) habitat restoration effort where we used several moderate (sm) patches with high density (hd) planting of sagebrush. The planting was targeted for nesting habitat, and the data reflects simulated habitat conditions in 2030.

To assess the degree to which transplanting sagebrush (Artemisia spp.) could quickly restore former sage-grouse habitat and the strategies by which greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) habitat restoration is best accomplished, we linked vegetation transitions with habitat selection models to evaluate habitat recovery. Within our modeling extent (Tuscarora, Nevada), we simulated the fire-induced loss of habitat, planting of sagebrush seedlings, and the regrowth of sagebrush and other vegetation over 15 years. We used sagebrush growth equations and vegetation state transitions to return and grow vegetation within the burned and planted areas. Every year, we updated seasonal sage-grouse habitat selection maps by re-applying pre-fire habitat selection equations to re-calculate the proportion of suitable habitat gained by sagebrush restoration efforts. We evaluated alternative planting designs to identify the key factors influencing habitat selection outcomes. Specifically, we varied the number of plants, patch sizes, densities, location of planting sites (i.e., random versus within sage-grouse nesting habitat), as well as post-transplant (30, 70, or 100%) survival. We assumed all planting occurred in a single year. We ranked the influence of these different planting factors on sage-grouse habitat recovery across restoration scenario. The following data reflect habitat conditions 15-years after a simulated fire and sagebrush revegetation. Here we provide the habitat recovery results of two different planting designs. We provide several example datasets from this project, including the following: tsf0tsf15_change_nontarg_me_ss_ld_bre10m.tif: Dataset representing a single-year (maximum-effort; me) habitat restoration effort where we used several small (ss) patches with low density (ld) planting of sagebrush. The planting was not targeted for nesting habitat, and the data reflects the change in simulated habitat conditions between 2015 and 2030. tsf0tsf15_change_targ_my_sm_hd_bre10m.tif: Dataset representing a multi-year (my) habitat restoration effort where we used several moderate (sm) patches with high density (hd) planting of sagebrush. The planting was targeted for nesting habitat, and the data reflects the change in simulated habitat conditions between 2015 and 2030. tsf15_nontarg_me_ss_ld_bre_hsi_10m_transf.tif: Dataset representing a single-year (maximum-effort; me) habitat restoration effort where we used several small (ss) patches with low density (ld) planting of sagebrush. The planting was not targeted for nesting habitat, and the data reflects simulated habitat conditions in 2030. tsf15_targ_my_sm_hd_bre_hsi_10m_transf.tif: Dataset representing a multi-year (my) habitat restoration effort where we used several moderate (sm) patches with high density (hd) planting of sagebrush. The planting was targeted for nesting habitat, and the data reflects simulated habitat conditions in 2030.

This dataset contains observations used to better understand the initial establishment of sagebrush (Artemisia sp.), in the first 1-2 years post-wildfire. Field data come from 460 sagebrush populations sampled across the Great Basin and many GIS-derived co-variates are included as well.

This dataset contains observations used to better understand the initial establishment of sagebrush (Artemisia sp.), in the first 1-2 years post-wildfire. Field data come from 460 sagebrush populations sampled across the Great Basin and many GIS-derived co-variates are included as well.