Historical and projected future land change and ecosystem carbon stocks for California
Dates
Publication Date
2024-09-06
Citation
Sleeter, B.M., and Selmants, P.C., 2024, Historical and projected future land change and ecosystem carbon stocks for California: U.S. Geological Survey data release, https://doi.org/10.5066/P1XMRMDC.
Summary
This dataset consists of annual raster maps of ecosystem carbon stocks, land use and land cover classes, and transition probabilities for the State of California during historical (1985-2020) and projected future (2021-2100) time periods. Data are simulation model output from the The Land Use and Carbon Simulator (LUCAS; Sleeter et al. 2022) run under different climate and land management scenarios. LUCAS model simulations were conducted on an annual timestep at 1-km spatial resolution with 40 Monte Carlo realizations per simulation. For the projected future time period, the model was run under all combinations of four climate scenarios, two urbanization scenarios, and two vegetation management scenarios. The climate scenarios were [...]
Summary
This dataset consists of annual raster maps of ecosystem carbon stocks, land use and land cover classes, and transition probabilities for the State of California during historical (1985-2020) and projected future (2021-2100) time periods. Data are simulation model output from the The Land Use and Carbon Simulator (LUCAS; Sleeter et al. 2022) run under different climate and land management scenarios. LUCAS model simulations were conducted on an annual timestep at 1-km spatial resolution with 40 Monte Carlo realizations per simulation. For the projected future time period, the model was run under all combinations of four climate scenarios, two urbanization scenarios, and two vegetation management scenarios. The climate scenarios were based on downscaled output from four CMIP6 Earth System Models (CESM, CNRM, EARTH3, and FGOALS) all run under Shared Socioeconomic Pathway 3 assuming additional radiative forcing of 7 W/m2 by the year 2100 (SSP370; see Tebaldi et al. 2021). Climate data were downscaled using the localized constructed analogs (LOCA) statistical method and are freely available to the public from the Analytics Engine Data Catalog (cal-adapt.org). The two urbanization scenarios sampled from historical rates of urban development on an annual basis, with one scenario restricting all new urban development to Wildland Urban Interface (WUI) areas while the other urbanization scenario excluded new urban development from WUI areas. The two land management scenarios consisted of a "business as usual" (Low) scenario based on historic rates of tree thinning and prescribed burning, while the second land management scenario (High) implemented forest management treatments to reduce wildfire hazard potential that match area targets from the 2021 California Wildfire and Forest Resilience Action Plan (Wildfire Task Force 2021). Historical land change was based on trends in the National Land Cover Database (NLCD) and historical climate was based on annual output data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM).
Tebaldi et al., 2021, Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6, Earth System Dynamics, 12: 253-293
Sleeter et al., 2022, Operational assessment tool for forest carbon dynamics for the United States: a new spatially explicit approach linking the LUCAS and CBM-CFS3 models, Carbon Balance and Management, 17:1
Data were generated as output of LUCAS model simulations designed to provide spatially explicit estimates of land use change and ecosystem carbon stocks for California under different climate and land management scenarios. This work was conducted in cooperation with University of California, Merced and funded by the California Energy Commission through a grant to the Pyregence Consortium (https://pyregence.org/).
Rights
This work is marked with Creative Commons Zero v1.0 Universal (https://creativecommons.org/publicdomain/zero/1.0/).