Barstow woolly sunflower - Species Distribution Model, DRECP

May 6, 2013 (Last modified Dec 19, 2016)
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Description:
These data are statistical model outputs for Barstow woolly sunflower
(Eriophyllum mohavense) species distribution, completed by Frank Davis’ Biogeography Lab at UC Santa Barbara. 

The UCSB Biogeography Lab used Maxent to generate predictions of habitat occupancy for ~70 species for the CA Energy Commission’s project “Cumulative Biological Impacts Framework for Solar Energy in the CA Desert”, 500-10-021.

Species distribution models were produced at 270 m resolution using a subset of 22 environmental variables. Models were evaluated with 10-fold cross validated AUC scores. Binary layers depicting predicted suitable habitat were derived using the equal training sensitivity and specificity threshold. 

For more information on the environmental variables used, please refer to the supporting document “Frank Davis - Current Environmental Layer Descriptions”. For model diagnostics, please refer to the supporting document “Frank Davis - Maxent Model Summary (02/20/2013)”.
Data Provided By:
Frank Davis and Oliver Soong
Bren School of Environmental Science & Management
University of California
Santa Barbara, CA  93106-5131
Lab website: www.biogeog.ucsb.edu
Content date:
not specified
Citation:
Frank Davis and Oliver Soong
Bren School of Environmental Science & Management
University of California, Santa Barbara
Spatial Resolution:
270 m
Contact Organization:
Frank Davis and Oliver Soong
Bren School of Environmental Science & Management
University of California
Santa Barbara, CA  93106-5131
Lab website: www.biogeog.ucsb.edu
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Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 3.0 License.
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Tags:
drecp, statistical model, eriophyllum mohavense, maxent, barstow woolly sunflower, species distribution
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Conservation Biology Institute

The Conservation Biology Institute (CBI) provides scientific expertise to support the conservation and recovery of biological diversity in its natural state through applied research, education, planning, and community service.