These data are statistical model outputs for Cushenbury
buckwheat (
Eriogonum ovalifolium var.
vineum
) 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 by the Carbonate Habitat Management
Area extent (Todd G. Olson, Carbonate Habitat Management Strategy, 2003, http://www.dmg.gov/documents/WMP_Volumes/Appendix%20S%20-%20CHMS.pdf), at 270 m resolution with 194 detections points
obtained in 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 eight 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; except for
the carbonate habitat types, which was provided to CBI by Dudek) in order of
importance:
Carbonate habitat types (for
description, see http://www.dmg.gov/documents/WMP_Volumes/Appendix%20S%20-%20CHMS.pdf), categorical presence/absence, indicating the
presence of critical, suitable, and occupied carbonate plant habitat types, each
270m pixel.
Maximum temperature of warmest period
(°C, x10);
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;
Soil water content at wilting
point, produced by A. & L. Flint;
Soil thickness, produced by A.
&. L. Flint;
Topographic relief in the 270m cell
estimated as the standard deviation of
elevations from 30m digital elevation model;
Flow accumulation (ESRI Spatial
Analyst Flow Accumulation), calculated from 90m HydroSHEDS flow direction
rasters. 90m model data were log(x+1)
transformed. Maximum of the transformed
values in each 270m pixel;
Precipitation of warmest quarter
(mm)
This model has a 10-fold cross validated AUC score of 0.919
(standard deviation 0.020). Both continuous probability surfaces and binary
layers are available. The binary layer depicting predicted suitable habitat was
derived using the maximum training sensitivity and specificity threshold (0.219).