Projected climate change and urbanization impacts on the distribution of Ceanothus verrucosus
This dataset is based on the output from a project funded by the California Landscape Conservation Cooperative: “Decision support for climate change adaptation and fire management strategies for at risk species in southern California”.
The potential distribution of Ceanothus verrucosus was modeled using a MaxEnt species distribution model using recent and future climate data with presence records from the San Diego Natural History Museum. Species distributions were modeled only for the South Coast Ecoregion in California, USA as this is where management options and climate change adaptation possibilities are currently being examined for the species. Recent climate data were based on the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) at 800 m resolution downscaled to 90 m. We modeled climate change impacts using the A2 emissions scenario and two global change models; the Department of Energy’s Parallel Climate Model (PCM) the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL) which were also downscaled. Projected data from 2070-2099 was used to create a future endpoint and interpolated with averaged conditions of the recent climate (1970-1999) to create a time series of distribution changes: 2000, 2050 and 2100 are presented here.
A projected urbanization scenario from 2000-2050 based on the SLEUTH cellular autumaton model was overlaid onto the Ceanothus species distribution model (publicly owned land and conservation reserves were excluded from development in this implementation). After 2050 no further urbanization occurs in this model due to significant uncertainty in projections of urbanization past 50 years. The model assumed that where urbanization occurred Ceanothus would not. Projections were run under climate change conditions (PCM and GFDL) and without (urbanization only) to provide a range of possibilities for the species under global change.
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