Parish's Phacelia - Species Distribution Model, DRECP

Apr 26, 2013 (Last modified Mar 11, 2014)
Description:
These data are statistical model outputs for Parish's phacelia (Phacelia parishii) species distribution, completed by CBI. Predictions of habitat occupancy were generated from Maxent models for the DRECP.

This species distribution model was produced for a limited extent within the DRECP region, defined as a union of a 10km buffer of occurrences, USDA ecoregion subsections with occurrences, and 5 adjacent subsections, at 270 m resolution with 19 detections points obtained March 2013 from CNDDB (California Department of Fish and Wildlife, Biogeographic Data Branch) and Consortium of California Herbaria (http://ucjeps.berkeley.edu/consortium/).
The model was built with the following 9 environmental predictors (provided to CBI by Frank Davis’ Biogeography Lab at UC Santa Barbara, created for the CA Energy Commission’s project “Cumulative Biological Impacts Framework for Solar Energy in the CA Desert”, 500-10-021) in order of importance:

Topographic relief in the 270m cell estimated as the standard deviation of elevations from 30m digital elevation model;
Precipitation of warmest quarter (mm);
Aridity index (annual precipitation (mm)/ potential evapotranspiration (mm/annual), x100);
Minimum temperature of coldest period (°C, x10);
Soil thickness, produced by A. &. L. Flint;
Soil pH (pH scale) from 0-50cm, derived from SSURGO or STATSGO where SSURGO was unavailable.  The mapunit area weighted average of the soil component percent area weighted average of the soil component horizon depth weighted average of ph1to1h2o_r in table chorizon;
Playas, as the union of USGS NHD feature code 36100 and those features delineated by VegCAMP and GAP.  Categorical presence/absence;
Soil available water storage (cm) from 0-50cm, derived from SSURGO or STATSGO where SSURGO was unavailable.  The mapunit-area-weighted average of aws050wta in table muaggatt;
Temperature seasonality (C of V, x100).

This model has a 10-fold cross validated AUC score of 0.912 (standard deviation 0.094). The binary layer depicting predicted suitable habitat was derived using the maximum training sensitivity and specificity threshold (0.165).
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Conservation Biology Institute
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Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 3.0 License.
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