Authors: Justin Bissell*, San Diego State University
Topics: Quantitative Methods, Physical Geography, Environmental Science
Keywords: GIScience, MaxEnt, geostatistics, spatial science, LiDAR, modeling
Session Type: Virtual Paper
Start / End Time: 11:10 AM / 12:25 PM
Room: Virtual 20
Presentation File: No File Uploaded
Restoration of anadromous salmonid habitat is of primary importance to the economic, historical, and cultural geography of the Pacific Northwest. Development and use of geospatial habitat models to pinpoint key areas where restoration funding can best be utilized is of great importance ; refinement of geostatistical modeling techniques using newly acquired high resolution data is ongoing. To this purpose, high resolution LiDAR DEM data was acquired for the Indian Creek and neighboring watersheds in Mendocino County, California, and used together with geomorphic stream data to statistically model stream widths, depths, and stream morphology. These geospatial covariates were in turn were used in conjunction with field surveyed habitat presence data and particle size to model potential anadromous salmonid species spawning habitat in a maximum entropy geostatistical modeling environment. Geospatially derived stream morphologic covariates were field-verified in selected locations and were successfully used to develop predictive geospatial models for spawning habitat for the species of interest in the Indian Creek watershed. Covariates of drainage area, slope within and areas proximate to the stream corridor, and particle size were all find to contribute significantly to final models. Probability models were field verified by engineering geologists and California Department of Fish and Wildlife biologists as highly reliable and applicable when utilized as guides for restoration project development and grant funded work.