This data set contains output from the dynamic vegetation model MC1, as modified to simulate future woody encroachment in the northern Great Plains. Simulations were done for the historical period (1895-2005) and the future period (2006-2100). Separate simulations were done for eastern and western portions of the region, with the eastern simulations using model parameters appropriate for Juniperus virginiana as the major evergreen needle-leaf life form, and the western simulations using model parameters appropriate for Pinus ponderosa as the major evergreen needle-leaf life form. Simulations in each portion were run for two A2 emissions scenario climate projections (CSIRO, representing moderate temperature increases and wetter conditions, and MIROC, representing very hot and dry conditions) crossed with 8 (eastern portion) or 6 (western portion) fire x grazing x tree regeneration capacity (eastern only) scenarios. Output variables provided on a yearly basis are potential evapotranspiration, live aboveground tree carbon and aboveground grass net primary production. Output variables provided as decadal averages are live aboveground tree carbon, tree leaf area index, soil available water for plant survival, surface runoff, potential evapotranspiration, streamflow, and actual evapotranspiration. Child records contain command files for running the model, model parameters, model input, and output from model runs for the equilibrium and spinup stages of model runs (precursors to running historical and future simulations).

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions.We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Great Plains (corresponding to the area represented by the Great Plains Landscape Conservation Cooperative). The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains

A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Great Plains (corresponding to the area represented by the Great Plains Landscape Conservation Cooperative). The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains

A new version of USGS’s FORE-SCE model was used to produce unprecedented landscape projections for four ecoregions in the Great Plains (corresponding to the area represented by the Great Plains Landscape Conservation Cooperative). The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains

These data provide current and future projected post-fire invasion risk by non-native short-lived grasses and forbs based on vegetation cover data from 26,729 plots in the western United States that burned prior to being sampled. Projected post-fire invasion risk was calculated using random forests with gridded climate, soil, and topographic predictor variables following Prevéy et al. (2024). Projections cover the western United States west of -100 longitude over the current time period (1981-2010), mid-century (2041–2070) and the end of the century (2071–2100) under medium (SSP245) and high (SSP585) greenhouse gas emission scenarios for non-native C3 short-lived grasses and non-native short-lived forbs. Each raster file represents the projected post-fire invasion risk for each non-native functional group ('sl_grass' = short-lived C3 grass, 'sl_forb' = short-lived forb), then the time period (current = 1981-2010, mid = 2041-2071, and late = 2071-2100), and lastly, the emissions scenario (none for current, '245' for SSP245, and '585' for SSP585). For example, 'sl_grass_mid_245.tif' is a raster file showing projected post-fire invasion risk for non-native short-lived C3 grasses for mid-century (2041-2070) under the SSP245 emissions scenario.

These data provide current and future projected post-fire invasion risk by non-native short-lived grasses and forbs based on vegetation cover data from 26,729 plots in the western United States that burned prior to being sampled. Projected post-fire invasion risk was calculated using random forests with gridded climate, soil, and topographic predictor variables following Prevéy et al. (2024). Projections cover the western United States west of -100 longitude over the current time period (1981-2010), mid-century (2041–2070) and the end of the century (2071–2100) under medium (SSP245) and high (SSP585) greenhouse gas emission scenarios for non-native C3 short-lived grasses and non-native short-lived forbs. Each raster file represents the projected post-fire invasion risk for each non-native functional group ('sl_grass' = short-lived C3 grass, 'sl_forb' = short-lived forb), then the time period (current = 1981-2010, mid = 2041-2071, and late = 2071-2100), and lastly, the emissions scenario (none for current, '245' for SSP245, and '585' for SSP585). For example, 'sl_grass_mid_245.tif' is a raster file showing projected post-fire invasion risk for non-native short-lived C3 grasses for mid-century (2041-2070) under the SSP245 emissions scenario.

The USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Prairie Potholes region of the northern Great Plains of the United States. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland

The USGS’s FORE-SCE model was used to produce unprecedented landscape projections for the Prairie Potholes region of the northern Great Plains of the United States. The projections are characterized by 1) high spatial resolution (30-meter cells), 2) high thematic resolution (29 land use and land cover classes), 3) broad spatial extent (covering much of the Great Plains), 4) use of real land ownership boundaries to ensure realistic representation of landscape patterns, and 5) representation of both anthropogenic land use and natural vegetation change. A variety of scenarios were modeled from 2014 to 2100, with decadal timesteps (i.e., 2014, 2020, 2030, etc.). Modeled land use and natural vegetation classes were responsive to projected future changes in environmental conditions, including changes in groundwater and water access. Eleven primary land-use scenarios were modeled, from four different scenario families. The land-use scenarios focused on socioeconomic impacts on anthropogenic land use (demographics, energy use, agricultural economics, and other socioeconomic considerations). The following provides a brief summary of the 11 major land-use scenarios. 1) Business-as-usual - Based on an extrapolation of recent land-cover trends as derived from remote-sensing data. Overall trends were provided by 2001 to 2011 change in the National Land Cover Database, while change in crop types were extrapolated from 2008 to 2014 change in the Cropland Data Layer. Overall the scenario is marked by expansion of high-value traditional crops (corn, soybeans, cotton), with a concurrent decline in dryland wheat and some other lower-value crops. 2) Billion Ton Update scenario ($40 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update (BTU). The $40 scenario represents likely agricultural conditions under an assumed farmgate price of $40 per dry ton of biomass (for the production of biofuel). This is the least aggressive BTU scenario for placing "perennial grass" (for biofuel feedstock) on the landscape. 3) Billion Ton Update scenario ($60 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $60 scenario represents likely agricultural conditions under an assumed farmgate price of $60 per dry ton of biomass (for the production of biofuel). At the higher farmgate price, the perennial grass class expands dramatically. 4) Billion Ton Update scenario ($80 farmgate price) - This scenario is based on US Department of Energy biofuel scenarios from the Billion Ton Update. The $80 scenario represents likely agricultural conditions under an assumed farmgate price of $80 per dry ton of biomass (for the production of biofuel). With the high farmgate price, this scenario shows the highest expansion of perennial grass among the 11 modeled scenarios. 5) GCAM Reference scenario - Based on global-scale scenarios from the GCAM model, the "reference" scenario provides a likely landscape under a world without specific carbon or climate mitigation efforts. As such, it's another form of a "business-as-usual" scenario. 6) GCAM 4.5 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 4.5 model represents a mid-level mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of ~4.5 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland (including perennial grass used as feedstock for cellulosic biofuel production). 7) GCAM 2.6 scenario - Based on global-scale scenarios from the GCAM model, the GCAM 2.6 model represents a very aggressive mitigation scenario, where carbon payments and other mitigation efforts result in a net radiative forcing of only ~2.6 W/m2 by 2100. Agriculture becomes even more concentrated in the Great Plains and Midwestern US, resulting in substantial increases in cropland

This data release provides inputs needed to run the LANDIS PRO forest landscape model and the LINKAGES 3.0 ecosystem process model for the temperate-boreal ecotone Great Xing’an Mountains of northeastern China, and simulation results that underlie figures and analysis in the accompanying publication. The study compared the impacts of small and large fires on vegetation dynamics. The data release includes input data for LINKAGES including soils, landtype, and climate data; initial conditions of stands in the study area for LANDIS PRO; and maps of LANDIS PRO output for each model grid cell including total trees, total biomass (Mg/ha), and tree density (trees/ha) in ten-year timesteps. Output for four climate and fire scenarios are included for a 115-year simulation period (i.e., 1985 – 2100). A baseline scenario that applied observed climate and the historical fire regime from (1967 – 2006) was used for model calibration and evaluation. Three climate-change scenarios evaluated interactions between fire size and projected future climate under the GFDL-CM3 model with the RCP8.5 emissions scenario: (1) climate change and no fire, (2) climate change and small, frequent fires, and (3) climate change and large, infrequent fires.