The California Natural and Workings Lands Carbon and Greenhouse Gas Model (CALAND) v3 estimates the effects of more than 16 specific land management activities on California’s landscape carbon budget. The model is based on field data from California and includes interactions among land management activities, wildfire, land use and cover change, and climate. Outputs include annual estimates of carbon stocks and fluxes, carbon dioxide and methane emissions, wood product storage and decay, and potential bioenergy feedstock. A map of the initial (2010) spatial delineation of land categories used by CALAND is included.

This dataset consists of modeled projections of land use and land cover for the State of California for the period 2001-2101. The Land Use and Carbon Scenario Simulator (LUCAS) model was initialized in 2001 and run forward on an annual time step to 2100. In total 9 simulations were run with 10 Monte Carlo replications of each simulation. Two base scenarios were selected from Sleeter et al., 2017 (http://onlinelibrary.wiley.com/doi/10.1002/2017EF000560/full) for analysis, including a "business-as-usual" (BAU) land use scenario and a scenario based on "medium" population projections. For each base scenario we ran three alternative conservation scenarios where we simulated conversion of lands into conservation easements. The three conservation easement scenarios simulated conversion of 1) 120 km2/yr for 15 years, 2) 120 km2/yr for 30 years, and 3) 240 km2/yr for 30 years. All easement conversions were set to begin in 2020 and extend for their stated duration. In addition to the conservation easement scenarios, we also ran a variant of the BAU land use scenario where current Williamson Act lands were removed from the simulation of future conditions.

This dataset consists of modeled projections of land use and land cover for the State of California for the period 2001-2101. The Land Use and Carbon Scenario Simulator (LUCAS) model was initialized in 2001 and run forward on an annual time step to 2100. In total 9 simulations were run with 10 Monte Carlo replications of each simulation. Two base scenarios were selected from Sleeter et al., 2017 (http://onlinelibrary.wiley.com/doi/10.1002/2017EF000560/full) for analysis, including a "business-as-usual" (BAU) land use scenario and a scenario based on "medium" population projections. For each base scenario we ran three alternative conservation scenarios where we simulated conversion of lands into conservation easements. The three conservation easement scenarios simulated conversion of 1) 120 km2/yr for 15 years, 2) 120 km2/yr for 30 years, and 3) 240 km2/yr for 30 years. All easement conversions were set to begin in 2020 and extend for their stated duration. In addition to the conservation easement scenarios, we also ran a variant of the BAU land use scenario where current Williamson Act lands were removed from the simulation of future conditions.

Scenario-based simulation model projections of land use change, ecosystem carbon stocks, and ecosystem carbon fluxes for the State of California from 2001-2101 using the SyncroSim software framework, see http://doc.syncrosim.com/index.php?title=Reference_Guide for software documentation. We explored four land-use scenarios and two radiative forcing scenarios (e.g. Representative Concentration Pathways; RCPs) as simulated by four earth system models (i.e. climate models). Results can be used to understand the drivers of change in ecosystem carbon storage over short, medium, and long (e.g. 100 year) time intervals. See Sleeter et al. (2019) Global Change Biology (doi: 10.1111/gcb.14677) for detailed descriptions of scenarios.

Scenario-based simulation model projections of land use change, ecosystem carbon stocks, and ecosystem carbon fluxes for the State of California from 2001-2101 using the SyncroSim software framework, see http://doc.syncrosim.com/index.php?title=Reference_Guide for software documentation. We explored four land-use scenarios and two radiative forcing scenarios (e.g. Representative Concentration Pathways; RCPs) as simulated by four earth system models (i.e. climate models). Results can be used to understand the drivers of change in ecosystem carbon storage over short, medium, and long (e.g. 100 year) time intervals. See Sleeter et al. (2019) Global Change Biology (doi: 10.1111/gcb.14677) for detailed descriptions of scenarios.

This data series provides tabular output from a series of modeling simulations for the State of California. The methods and results of this research are described in detail in Sleeter et al. (2019). We used the LUCAS model to project changes in ecosystem carbon balance resulting from land use and land use change, climate change, and ecosystem disturbances such as wildfire and drought. The model was run at a 1-km spatial resolution on an annual timestep. We simulated 32 unique scenarios, consisting of 4 land-use scenarios and 2 radiative forcing scenarios as simulated by 4 global climate models. For each scenario, we ran 100 Monte Carlo realizations of the model. Additional details describing the modeling effort can be found in the *Global Change Biology* paper. Results presented here have been aggregated from the individual cell level to either ecoregion or state-wide summaries.

This data series provides tabular output from a series of modeling simulations for the State of California. The methods and results of this research are described in detail in Sleeter et al. (2019). We used the LUCAS model to project changes in ecosystem carbon balance resulting from land use and land use change, climate change, and ecosystem disturbances such as wildfire and drought. The model was run at a 1-km spatial resolution on an annual timestep. We simulated 32 unique scenarios, consisting of 4 land-use scenarios and 2 radiative forcing scenarios as simulated by 4 global climate models. For each scenario, we ran 100 Monte Carlo realizations of the model. Additional details describing the modeling effort can be found in the *Global Change Biology* paper. Results presented here have been aggregated from the individual cell level to either ecoregion or state-wide summaries.

This data series provides tabular output from a series of modeling simulations for the State of California. The methods and results of this research are described in detail in Sleeter et al. (2019). We used the LUCAS model to project changes in ecosystem carbon balance resulting from land use and land use change, climate change, and ecosystem disturbances such as wildfire and drought. The model was run at a 1-km spatial resolution on an annual timestep. We simulated 32 unique scenarios, consisting of 4 land-use scenarios and 2 radiative forcing scenarios as simulated by 4 global climate models. For each scenario, we ran 100 Monte Carlo realizations of the model. Additional details describing the modeling effort can be found in the *Global Change Biology* paper. Results presented here have been aggregated from the individual cell level to either ecoregion or state-wide summaries.

This dataset provides tabular data output from a series of modeling simulations for forest ecosystems of the U.S. state of California under different initial conditions scenarios. We used the LUCAS state and transition simulation model with carbon stocks and fluxes based on the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to simulate changes in forest ecosystem carbon balance resulting from historical land use and land cover change, annual climate variability, and disturbance from wildfire and drought-induced forest die-off. The model was run at a 1-km spatial resolution on an annual timestep for the years 1985 to 2020. We simulated 36 initial conditions scenarios based on unique combinations of spatial datasets used to define forest extent, forest composition and forest age at the beginning of the simulation period. Results presented here have been aggregated from the individual grid cell level and summarized for the entire state of California.

This dataset consists of modeled projections of land use and land cover and population for the State of California for the period 1970-2101. For the 1970-2001 period, we used the USGS's LUCAS model to "backcast" LULC, beginning with the 2001 initial conditions and ending with 1970. For future projections, the model was initialized in 2001 and run forward on an annual time step to 2100. In total 5 simulations were run with 10 Monte Carlo replications of each simulation. The simulations include: 1) Historical backcast from 2001-1970, 2) Business-as-usual (BAU) projection from 2001-2101, and 3) three modified BAU projections based on California Department of Finance population projections based on high, medium, and low growth rates.