Wildfires are increasingly modifying wildlife habitat in the western United States and managers need ways to scope the pace and degree to which post-fire restoration actions can re-create habitat in dynamic landscapes. We simulated post-fire revegetation and greater sage-grouse (Centrocercus urophasianus) habitat restoration using a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. The STSM represented the vegetation dynamics of the sagebrush ecosystem and included annual fires, annual grass invasion, conifer encroachment, and sagebrush revegetation restoration. We compared simulated vegetation output with sage-grouse perennial grass and sagebrush cover habitat needs and evaluated trajectories of potential habitat for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin. This data release is organized into two general datasets: the ST-Sim library and the associated projections of potential sage-grouse habitat (organized by population). Habitat layers illustrate a time series of potential habitat and 50-year potential change in habitat classification for sage-grouse across space and time. The structure of these data follow: A) STSM Model – contains the ST-Sim library, input, and output files; SagebrushSteppeRestoration.ssim, B) KLAM Habitat Data – contains habitat data for the Klamath Oregon/California PAC (located in the northwestern region of the Great Basin), C) NWINV Habitat Data – contains habitat data for the NW Interior Nevada PAC (located in the central region of the Great Basin), and D) STRAW Habitat Data – contains habitat data for the Strawberry Utah PAC (located along the eastern edge of the Great Basin). The STSM was built using the Syncrosim ST-Sim platform with the software's integrated stock-flow submodel to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (average, double, maximum), and two durations (single-year, multi-year) were simulated for each PAC landscape. Seeding and planting effort levels were based on historic treatment area polygon data (median size) for sagebrush seeding (6 km2) and planting (4 km2). Area was used as a measure of effort that represented an annual fire response equivalent to average effort, double effort (2x area median), and maximum effort (45 km2). The ‘maximum effort’ scenario represented a hypothetical management response 7-11 times larger than average post-fire revegetation treatment area sizes. Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). A combination seeding-planting scenario representing single-year gains from seeding and multi-year gains from HD planting (two additional years of sagebrush cover gains) and a passive no restoration scenario equivalent to ‘no effort’ were simulated to compare with single- and multi-year seeding or planting scenarios. Habitat layers were generated at 10-year intervals using the simulated vegetation outputs from the five best restoration scenarios of each type (no restoration, seeding, LD planting, HD planting, multi-year) for each PAC landscape. Sagebrush and perennial grass cover from projected continuous component cover values tracked in the STSM stock-flow (SF) submodel were used to characterize potential habitat based on sage-grouse seasonal life stage cover requirements. Habitat distinctions were based on a given pixel meeting minimum cover amounts and classified pixels as suitable, marginally suitable, and unsuitable relative to seasonal spring (i.e., breeding period), summer (i.e., brood-rearing period), and winter sagebrush

This is a spatially-explicit state-and-transition simulation model (STSM) of sagebrush-steppe vegetation dynamics for greater sage-grouse (Centrocercus urophasianus) Priority Areas for Conservation (PACs) in the Great Basin. The STSM was built using the ST-Sim platform and uses an integrated stock-flow submodel (STSM-SF) to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Spatially explicit models were built for three sage-grouse PACs (Klamath Oregon/California [KLAM], NW Interior Nevada [NWINV], Strawberry Utah [STRAW]) that differed in historic wildfire patterns and the amounts of various component vegetation cover present (sagebrush, annual grass, pinyon-juniper percent cover), and represented a range of possible variation in annual area burned (fire size, frequency), annual grass invasion, conifer encroachment and simulated potential for habitat restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (post-fire treatment area), and two durations (single-year, multi-year) were simulated for each PAC landscape. Seeding and planting effort levels were based on historic treatment area polygon data (median size) for sagebrush seeding (6 km2) and planting (4 km2). Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). A combination seeding-planting scenario representing single-year gains from seeding and multi-year gains from HD planting was also simulated to compare with single- and multi-year seeding or planting scenarios.

This is a spatially-explicit state-and-transition simulation model (STSM) of sagebrush-steppe vegetation dynamics for greater sage-grouse (Centrocercus urophasianus) Priority Areas for Conservation (PACs) in the Great Basin. The STSM was built using the ST-Sim platform and uses an integrated stock-flow submodel (STSM-SF) to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Spatially explicit models were built for three sage-grouse PACs (Klamath Oregon/California [KLAM], NW Interior Nevada [NWINV], Strawberry Utah [STRAW]) that differed in historic wildfire patterns and the amounts of various component vegetation cover present (sagebrush, annual grass, pinyon-juniper percent cover), and represented a range of possible variation in annual area burned (fire size, frequency), annual grass invasion, conifer encroachment and simulated potential for habitat restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (post-fire treatment area), and two durations (single-year, multi-year) were simulated for each PAC landscape. Seeding and planting effort levels were based on historic treatment area polygon data (median size) for sagebrush seeding (6 km2) and planting (4 km2). Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). A combination seeding-planting scenario representing single-year gains from seeding and multi-year gains from HD planting was also simulated to compare with single- and multi-year seeding or planting scenarios.

Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the NW-Interior Nevada, USA (NWINV) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years of five different post-fire sagebrush revegetation restoration actions. The habitat layers generated illustrate spatial and temporal variation in potential future habitat, and the potential for change from revegetation actions aimed at restoration of sagebrush and perennial grass cover conditions across the NWINV landscape. These layers identify areas of potential future habitat (suitable, marginally suitable, unsuitable) and change in habitat condition classification (improvement, deterioration, no change) following post-fire revegetation actions (seeding, planting). The STSM represented the vegetation dynamics of sagebrush-steppe systems and included annual fires, annual grass invasion, conifer encroachment, and sagebrush revegetation restoration. The STSM was built using the Syncrosim software ST-Sim (stsim) platform with use of the stock-flow (stsimsf) submodel to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (average, double, maximum), and two durations (single-year, multi-year) were simulated for each PAC landscape. Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). The NW-Interior Nevada PAC represented an at-risk of increased annual-grass invasion landscape with high amounts of annual grass invaded sagebrush shrubland (10% of landscape) and annual grasslands (7% of landscape). Simulated vegetation output was compared with sage-grouse perennial grass and sagebrush cover habitat needs to evaluate trajectories of potential habitat and potential for change in habitat classification after 50 years of recursive fire and the five best restoration scenarios of each type (no restoration, seeding, LD planting, HD planting, multi-year).

Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the NW-Interior Nevada, USA (NWINV) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years of five different post-fire sagebrush revegetation restoration actions. The habitat layers generated illustrate spatial and temporal variation in potential future habitat, and the potential for change from revegetation actions aimed at restoration of sagebrush and perennial grass cover conditions across the NWINV landscape. These layers identify areas of potential future habitat (suitable, marginally suitable, unsuitable) and change in habitat condition classification (improvement, deterioration, no change) following post-fire revegetation actions (seeding, planting). The STSM represented the vegetation dynamics of sagebrush-steppe systems and included annual fires, annual grass invasion, conifer encroachment, and sagebrush revegetation restoration. The STSM was built using the Syncrosim software ST-Sim (stsim) platform with use of the stock-flow (stsimsf) submodel to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (average, double, maximum), and two durations (single-year, multi-year) were simulated for each PAC landscape. Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). The NW-Interior Nevada PAC represented an at-risk of increased annual-grass invasion landscape with high amounts of annual grass invaded sagebrush shrubland (10% of landscape) and annual grasslands (7% of landscape). Simulated vegetation output was compared with sage-grouse perennial grass and sagebrush cover habitat needs to evaluate trajectories of potential habitat and potential for change in habitat classification after 50 years of recursive fire and the five best restoration scenarios of each type (no restoration, seeding, LD planting, HD planting, multi-year).

Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the Klamath Oregon/California, USA (KLAM) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years of five different post-fire sagebrush revegetation restoration actions. The habitat layers generated illustrate spatial and temporal variation in potential future habitat, and the potential for change from revegetation actions aimed at restoration of sagebrush and perennial grass cover conditions across the KLAM landscape. These layers identify areas of potential future habitat (suitable, marginally suitable, unsuitable) and change in habitat condition classification (improvement, deterioration, no change) following post-fire revegetation actions (seeding, planting). The STSM represented the vegetation dynamics of sagebrush-steppe systems and included annual fires, annual grass invasion, conifer encroachment, and sagebrush revegetation restoration. The STSM was built using the Syncrosim software ST-Sim (stsim) platform with use of the stock-flow (stsimsf) submodel to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (average, double, maximum), and two durations (single-year, multi-year) were simulated for each PAC landscape. Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). The Klamath Oregon/California PAC represented a degraded sagebrush landscape with high amounts of annual grass invaded sagebrush shrubland (47% of landscape). Simulated vegetation output was compared with sage-grouse perennial grass and sagebrush cover habitat needs to evaluate trajectories of potential habitat and potential for change in habitat classification after 50 years of recursive fire and the five best restoration scenarios of each type (no restoration, seeding, LD planting, HD planting, multi-year).

Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the Klamath Oregon/California, USA (KLAM) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years of five different post-fire sagebrush revegetation restoration actions. The habitat layers generated illustrate spatial and temporal variation in potential future habitat, and the potential for change from revegetation actions aimed at restoration of sagebrush and perennial grass cover conditions across the KLAM landscape. These layers identify areas of potential future habitat (suitable, marginally suitable, unsuitable) and change in habitat condition classification (improvement, deterioration, no change) following post-fire revegetation actions (seeding, planting). The STSM represented the vegetation dynamics of sagebrush-steppe systems and included annual fires, annual grass invasion, conifer encroachment, and sagebrush revegetation restoration. The STSM was built using the Syncrosim software ST-Sim (stsim) platform with use of the stock-flow (stsimsf) submodel to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Thirteen restoration scenarios representing a combination of three revegetation alternatives (no restoration, seeding, planting) under three effort levels (average, double, maximum), and two durations (single-year, multi-year) were simulated for each PAC landscape. Planting scenarios represented the sagebrush cover gains of planting 4 plants/m2 (low-density; LD planting) and 8 plants/m2 (high-density; HD planting). The Klamath Oregon/California PAC represented a degraded sagebrush landscape with high amounts of annual grass invaded sagebrush shrubland (47% of landscape). Simulated vegetation output was compared with sage-grouse perennial grass and sagebrush cover habitat needs to evaluate trajectories of potential habitat and potential for change in habitat classification after 50 years of recursive fire and the five best restoration scenarios of each type (no restoration, seeding, LD planting, HD planting, multi-year).

A raster identifying previously burned areas as being 1) recovered (to sagebrush-dominant ecosystem), 2) recovering, or 3) transitioned to annual grass-dominated.

A raster identifying previously burned areas as being 1) recovered (to sagebrush-dominant ecosystem), 2) recovering, or 3) transitioned to annual grass-dominated.

Here, we present changes in greater sage-grouse nesting habitat suitability that represents habitat before a simulated fire event and post-fire event after simulating the planting of sagebrush. The planting design used here reflects 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. 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 the change of nesting habitat conditions 15-years after a simulated fire and sagebrush revegetation. Here, we provide the habitat recovery results for one of many different planting designs assessed for this project.