Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Potentially suitable land cover on serpentine soils (resistance surface post-processing component) - A landscape connectivity analysis for the coastal marten (Martes caurina humboldtensis)

Metadata Updated: January 14, 2026

The resistance surface that formed the basis of our coastal marten connectivity model is comprised of several data layers that represent forested and non-forested land cover, waterbodies, rivers, roads, and serpentine soils.

This dataset contains the potentially suitable land cover on serpentine soils used to modify the resistance surface after it was initially compiled.

In addition to late seral forests, coastal martens have at times been found utilizing shrub-dominated habitats on serpentine soils in areas influenced by coastal fog (within 30 km of the coast) (Slauson 2003, Slauson et al. 2019a). These sites often have sparse tree cover (Jimerson et al. 1995), but support a dense layer of the ericaceous shrubs preferred by the species. Many of these areas would be mapped as having relatively low OGSI values in the GNN model and thus as having lower habitat value and connectivity potential for coastal martens in an OGSI-based model. While these habitats make up a relatively small percentage of the overall landscape, some occur on ridgetops that could potentially act as movement pathways for martens, and including these soils may help define habitat cores more realistically. While there is only a limited amount of data available on coastal marten use of serpentine habitats, several lines of evidence in the led us to treat these areas as sub-optimal but usable habitat in our model. Home range sizes appear to be larger in areas with a higher proportion of serpentine habitat based on the larger scale at which it influenced occupancy in Slauson et al.’s (2019a, b) habitat model relative to late seral forest. Furthermore, Slauson et al. (2009b) reported that populations appeared to be male-biased and had more transitory occupancy than in habitat dominated by late successional forest.

Overview of the Development Process

To develop this dataset of potentially suitable land cover on serpentine soils, we first obtained a dataset of serpentine soils in the Klamath-Siskiyou Ecoregion that was assembled by Noss et al. (1999) for an earlier conservation planning effort by merging data from USGS geology maps of the region and STATSGO soils data from the U.S. Natural Resource Conservation Service. We clipped these serpentine soil polygons to a distance of 30 km from the coast to obtain a map of serpentine polygons that could potentially support coastal marten habitat.

We then obtained the complete GAP/LANDFIRE Terrestrial Ecosystems 2011 data (USGS 2011) for OR and CA that was used in the GNN Structure forest model (LEMMA 2014a) as a mask for non-forested pixels (in the GNN model data, these are represented by the ESLF_CODE and ESLF_NAME attributes). From these GAP/LANDFIRE data, we extracted the ESLF categories for all pixels that overlapped with the footprint of our 30km-clipped serpentine soil polygons.

We then assessed the ESLF categories found within the serpentine footprint to identify and remove habitat types that did not seem likely to support the type of shrub-dominated habitats the martens use in serpentine sites based on their lack of suitable ericaceous shrub species in the community descriptions (NatureServe 2017). The remaining 32 ESLF categories (see attribute table) were used to modify the resistance surface as described below.

The associated spatial metadata record contains additional information, including: A more specific treatment of the development process for this dataset (see Lineage section). A thorough description of how this data layer was incorporated into the post-processing of the resistance surface.

This is an abbreviated and incomplete description of the dataset. Please refer to the spatial metadata for a more thorough description of the methods used to produce this dataset, and a discussion of any assumptions or caveats that should be taken into consideration.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date January 14, 2026
Metadata Updated Date January 14, 2026

Metadata Source

Harvested from DOI FWS DCAT-US

Additional Metadata

Resource Type Dataset
Metadata Created Date January 14, 2026
Metadata Updated Date January 14, 2026
Publisher U.S. Fish and Wildlife Service
Maintainer
Identifier http://datainventory.doi.gov/id/dataset/FWS_ServCat_146364
Data First Published 2020-05-01T00:00:00Z
Data Last Modified 2020-05-01T00:00:00Z
Category geospatial
Public Access Level public
Bureau Code 010:18
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://ddi.doi.gov/fws-data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 3dbd435d-a0fc-48f6-9116-57fe8bf381a7
Harvest Source Id f51f1f6c-4e4a-4e0a-b4e3-a5577c6dcc19
Harvest Source Title DOI FWS DCAT-US
Homepage URL https://iris.fws.gov/APPS/ServCat/Reference/Profile/146364
Metadata Type geospatial
Old Spatial -124.58,38.38,-122.06,46.43
Program Code 010:028, 010:094
Source Datajson Identifier True
Source Hash bdb5701201673893180d18cbfb53921292afbfb7e68e06b259661d1a9d579cbf
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -124.58, 38.38, -124.58, 46.43, -122.06, 46.43, -122.06, 38.38, -124.58, 38.38}

Didn't find what you're looking for? Suggest a dataset here.