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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...
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...
This data release contains a shapefile of riparian vegetation communities attributed with information on trends in satellite-estimates of vegetation productivity for the period from 2000-2020. Cloud-masked Landsat data were processed from 2000 to 2020 to generate a 21-year growing season (June, July, and August) time series combining data from Landsat 5 (2000-2011), Landsat 7 (2012), and Landsat 8 (2013-2020). We computed the near-infrared reflectance of vegetation (NIRv) which is strongly correlated to vegetation Gross Primary Productivity (GPP). We analyzed growing season time series trends in NIRv by riparian vegetation type at the polygon-level using the Theil-Sen estimator (aka Sen's slope). In addition to...
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