DOI: 10.6084/m9.figshare.29925071.v1
title: Geodatabase of ultramafic substrates in South Coast Ranges, California, USA.docx

description: Geodatabase of ultramafic substrates in South Coast Ranges, California, USA Ryan O’Dell Natural Resource Specialist Bureau of Land Management Central Coast Field Office Marina, California, USA rodell@blm.gov August 2025 Background and Goals Rock type and soil type have a strong influence on plant species distribution. There are about 250 plant taxa endemic to ultramafic substrate in California (Miller and Safford 2020). Many have small ranges (local endemics) and are rare or endangered. Plant ecologists and conservationists wish to develop Species Distribution Models (SDMs) for ultramafic endemic plant species in GIS. However, there is no existing, continuous, high accuracy geodatabase of ultramafic substrates for most of California. Most ultramafic Species Distribution Models (SDMs) produced in the past 15 years have used the Geologic Map of California (USGS 2010; 1:750,000 scale) and/or Gridded Soil Survey Geographic Database (gSSURGO; NRCS; 1:6,000 scale). Neither of these data sources delineate ultramafic substrates with high enough accuracy for satisfactory SDMs. Polygon lines often do not closely match ultramafic geologic boundaries clearly visible in the high-resolution satellite imagery. Additionally, smaller ultramafic masses, ultramafic landslides, and ultramafic alluvial deposits are either not mapped, or not identified by rock type (e.g. Qls or Qa, only). The goal is to produce a continuous, fine scale (4,000 m2 MMU), high accuracy (± 20 m) geodatabase of ultramafic substrates for most of California. The first stage (2020 – 2025) will be to delineate polygons of ultramafic masses, ultramafic landslides, and ultramafic alluvium as accurately as possible. The second stage (2025 - 2030) will be to divide the polygons further and assign attributes based on field observations including - rock_type · serpentinite, 75-100% · peridotite, serpentinized 25 - 75% · peridotite, serpentinized 0 - 25% shear_strength · block, pulverized matrix · block, sheared matrix · block, no matrix soil_series soil_depth · &lt; 10 cm · 10 - 30 cm · 30 cm+ soil_texture · clay · clay-loam · loam · sandy-loam · sand Data sources 1) High resolution satellite imagery from Google Earth – portable basemap server. Airbus; Landsat/Copernicus. https://mt1.google.com/vt/lyrs=s&x={col}&y={row}&z={level} 2) National Geologic Map Database (NGMD). https://ngmdb.usgs.gov/ngmdb/ngmdb_home.html Dibblee Maps (1:24,000 scale) are generally the most detailed and highest accuracy for South Coast Ranges. https://store.aapg.org/ATSResources/product-splash/dibblee.aspx 3) Gridded Soil Survey Geographic Database (gSSURGO). gSSURGO_CA.gdb https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database Extracting and drawing the polygons 1) Trace ultramafic rock polygons from geologic maps. The National Geologic Map Database (NGMD). I examined the digitized maps to identify those with highest accuracy. For the South Coast Ranges, these tended to be the Dibblee Maps, which are not available for download on NGMD - viewing only. For the Dibblee Maps, I collected screen capture images (JPEG) from the NGMD map viewer, then manually georeferenced them in ArcGIS Pro (GIS). All other maps in NGMD (GeoTiff) were downloaded and opened in GIS. I then manually traced all polygons mapped as ultramafic rock types. 2) Extract ultramafic soil polygons from gSSURGO. I carefully identified all of the map unit key (MUKEY) codes corresponding to soils derived from ultramafic rock and extracted the polygons from gSSURGO. A spreadsheet of these can be found in Figshare – “Ultramafic soils NRCS – CA, OR, WA.” SQLs to extract the polygons from gSSURGO is in “Extract all ultramafic soil polygons from gSSURGO for California, Oregon, and Washington, USA.” 3) Compare ultramafic rock polygon lines to ultramafic soil polygons and high-resolution satellite imagery, and adjust the lines. Ultramafic soil polygons and high-resolution satellite imagery were used to adjust the ultramafic rock polygon lines through consensus of data and visual indicators. Ultramafic rock and soil has a distinctive color, compared to adjacent non-ultramafic rock types. Serpentinite rock has a blue hue. Weathered ultramafic rock (especially peridotite) and soil typically has a substantially redder hue (oxidized iron), than adjacent non-ultramafic rock types. Vegetative cover on ultramafic rock is typically much lower than the adjacent non-ultramafic rock, so both the color of the rock and soil is visible in satellite imagery. The vegetation type (color and patterns) on ultramafic rock also typically contrasts sharply with the surrounding non-ultramafic rock. In South Coast Ranges, the strict ultramafic endemic large woody shrub Quercus durata var. durata appears as a distinctive gray-green color. I used my 20+ years of field observations and knowledge of ultramafic areas from throughout California to manually adjust the ultramafic polygons based on rock, soil, and vegetation color patterns in the high resolution satellite imagery. I also carefully examined the satellite imagery and delineated small ultramafic masses, ultramafic landslides, and ultramafic alluvial deposits not mapped (represented) in the geologic maps or soil surveys. 4) Follow-up field observations and reexamination of polygons in GIS. Most of the ultramafic polygons for South Coast Ranges were drawn in 2020 and 2021. I conducted additional field work 2021 – 2025 (as checks), reexamined polygons in GIS, and continued to improve polygon line accuracy.