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

Least-cost corridors classified as well-connected (≤15km) based on Euclidean distance - A landscape connectivity analysis for the coastal marten (Martes caurina humboldtensis)

Metadata Updated: September 14, 2025

This dataset contains an alternative representation of the least-cost corridors produced by our habitat connectivity model for the coastal marten, where a Maximum Euclidean Corridor Distance parameter of 15km has been set (i.e. corridors with a Euclidean distance greater than 15km have been excluded). This single parameter change was the only difference between the output from this model run, and the output from our Primary Model. This dataset was used in our report to make maps depicting corridors that are well-connected (≤15km), moderately-connected (≤45km), or poorly connected (>45km; i.e. all remaining corridors in the Primary Model that didn't fall into the first two categories) based on Euclidean distance. To construct these figures, you need two or three of the aforementioned datasets layered on top of one another. See Figures A6.1 and A6.2 in the report for symbology examples.

After developing the coastal marten landscape resistance surface (i.e. movement model) and mapping habitat cores, we used Linkage Mapper to identify Least-Cost Paths (LCPs) between cores and to map broader mosaicked corridors around these single-pixel width paths. Linkage Mapper proceeds through several steps to complete these tasks (McRae and Kavanagh 2016). First, it identifies and lists which habitat cores are nearest neighbors using both the Euclidean distance (the “as-the-crow-flies” straight-line distance between nearest points on the edges of a pair of cores regardless of the character of the intervening landscape) and the cost-weighted distance (CWD). Second, it creates a “stick map” using straight-line linkages to connect core area pairs that are candidates for corridor mapping. Third, it locates the LCPs through the resistance surface between these pairs of cores and calculates their cost-weighted distance. This LCP is a single 30m pixel wide. A single pixel’s cost-weighted distance is the cell’s resistance value multiplied by the size of the cell, and the cost-weighted distance of an LCP is the sum of the cost-weighted distances of the pixels it runs through.

Finally, Linkage Mapper creates least-cost corridors, which are wider swathes surrounding the LCPs that have only slightly higher movement costs and are more biologically realistic for conservation planning. It does this by calculating for each pixel on the landscape how much more costly a pathway passing through it between two cores would be than the LCP. Pixels closest to the LCP tend to be relatively close to it in CWD value, with the potential contribution of pixels to connectivity tending to decrease further away from the LCP. Linkage Mapper then creates a composite linkage map by assigning each pixel its minimum value relative to the nearest LCP (WHCWG 2010). Thus, the final map is a mosaic of normalized least-cost corridors around the LCPs. These corridors will vary in width depending on the resistance values surrounding the LCP.

We opted not to set a maximum Euclidean or cost-weighted distance for least-cost corridors between habitat cores in our primary model, but we did impose a 15km Maximum Euclidean Corridor Distance parameter for this alternative model run.

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 September 11, 2025
Metadata Updated Date September 14, 2025

Metadata Source

Harvested from DOI FWS DCAT-US

Additional Metadata

Resource Type Dataset
Metadata Created Date September 11, 2025
Metadata Updated Date September 14, 2025
Publisher U.S. Fish and Wildlife Service
Maintainer
Identifier http://datainventory.doi.gov/id/dataset/fws-servcat-146378
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 63e9093e-03c6-4f91-a01a-1dd3638bbac9
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/146378
Metadata Type geospatial
Old Spatial -124.58,38.38,-122.06,46.43
Program Code 010:094, 010:028
Source Datajson Identifier True
Source Hash 14f299dee7772259d3015600dfeb11082e0f79d0b2f24081340a2baebca7a20f
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.