Using GIS to Conserve the Greater Sage-Grouse

GIS Contributor


The Bureau of Land Management (BLM) manages a large portion of the sagebrush-strewn area of southeast Oregon, and is deeply involved in rigorous efforts to conserve the greater sage-grouse.

The greater sage-grouse is the largest grouse in North America, and relies on the sagebrush ecosystem for food, shelter, and breeding habitat. Development in southeast Oregon has led to a reduction in overall habitat, which, among other environmental factors, poses a threat to the continued prosperity of the species.

The BLM’s conservation efforts comprise a detailed set of plans and policies for which GIS is a linchpin technology.

The BLM’s overall guiding principles are multiple use and sustained yield, priorities that are defined in the Federal Land Policy and Management Act (FLPMA) of 1976.

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This requires BLM to look at competing interests when deciding how to manage vast amounts of land in the West. Over the past few decades, GIS has emerged as an essential analysis and communication tool for the Oregon BLM in general, and its sage-grouse conservation efforts in particular.

A male Greater Sage-Grouse (Image Credit: Pacific Southwest Region U.S. Fish and Wildlife Service)
A male Greater Sage-Grouse (Photo: Pacific Southwest Region U.S. Fish and Wildlife Service, public domain)

Tracking Sage-Grouse Habitat Disturbance with GIS

BLM’s sage-grouse plan require the use of spatial analysis to regulate surface disturbance in sensitive sage-grouse habitat.

The plan requires that the BLM track proposed surface-disturbing developments – broken down into over a dozen categories – within the Priority Areas of Conservation (PAC). The PACs are 20 key regions of sage-grouse breeding and habitat in southeast Oregon, delineated by the State of Oregon Department of Fish and Wildlife (ODFW). Combined, the PACs cover millions of acres, most of them managed by the BLM.

To track the surface-disturbing development in this sensitive habitat, BLM is using a United States Geological Survey (USGS)-hosted web application called the Surface Disturbance Analysis and Reclamation Tracking Tool (SDARTT)

This app allows BLM staff to evaluate the impact of a proposed development project on the overall percentage of disturbed land within a project analysis area using a geoprocessing workflow outlined in the BLM’s sage-grouse plan.

The denominator for the percentage is the total area of the project analysis area, which is created using the following logic:

  1. Buffering a proposed disturbance footprint by four miles;
  2. Merging the resulting polygon with a further four-mile buffer around any occupied or pending (likely recent or future occupation) sage-grouse breeding grounds, called “leks”, intersected by the first buffer; and
  3. Clipping the combined buffers to the PAC boundaries.

The sage-grouse plan also mandates that the combined acreage of projects deemed sage-grouse disturbances (numerator) not exceed a three percent disturbance cap on the total acreage of the project analysis area. Disturbances in SDARTT include features such as wind turbines, communication towers, roads, power lines, airports, and recreation sites.

A view of a line of white windmills going over a hill against a cloudless blue sky.
An example of the types of disturbances tracked by SDARTT. (Image Credit: Bureau of Land Management)

This may seem like a straightforward analysis exercise to a GIS professional. However, the tasks of coordinating data development, providing accurate updates, and ensuring a consistent approach to data management are not trivial.

Four BLM Districts intersect the sage-grouse planning boundary: Burns, Prineville, Lakeview, and Vale. The GIS and planning staff in these offices provide an impressive array of analytical, management, and regulatory services day in, day out.

This necessitates an approach centered on process efficiency, standardization, and automation that can only be perfected through the use of SDARTT.

Before project analysis polygons and disturbance layers can be uploaded and used in SDARTT, they must be translated into a specific SDARTT-compatible format. To help translate the disturbance and project analysis area data into the correct format, SDARTT provides authorized users a zipfile of several Esri file geodatabase templates for use in ArcGIS Desktop software.

It also provides a map-based view and project tracking interface for project analysis boundaries, proposed developments, and more than a dozen types of disturbances, each represented by a custom template feature class.

To assist local BLM District Office staff, GIS staff at the BLM’s regional office in Portland, Oregon prepare automated translations of corporate geospatial data into SDARTT format using Python, arcpy, and the ArcGIS geoprocessing framework.

These tools provide a baseline set of disturbance feature classes that staff can batch upload to SDARTT. This greatly reduces the burden of BLM District GIS staff to set up the SDARTT analysis while increasing consistency.

These SDARTT scripts leverage the in-memory workspace to avoid cluttering up the local user’s scratch geodatabase and reduce processing time.

The BLM’s regional office also provides a custom Python Addin toolbar that will streamline data management practices for local BLM District GIS specialists who use SDARTT on a more frequent basis.

BLM staff now have a menu of tools to quickly perform the following tasks:

  1. Generate the project analysis boundary according to the standardized process mentioned above, and create as-built disturbance layers for the project area where they are missing;
  2. Launch the SDARTT web application once they are ready to upload data;
  3. Launch Google Maps in a browser zoomed to the current extent and zoom level;
  4. View the existing disturbance layers through a web map service layer matching SDARTT;
  5. Launch the user guide for the toolbar;
  6. Create an empty disturbance feature class where the user can digitize or append proposed development polygons;
  7. Zip the output shapefiles (selected in the ArcCatalog window) with a single click; and
  8. Export the SDARTT file geodatabase feature classes to shapefile format.
The BLM – OR SDARTT Toolbar for ArcMap (Image Credit: Micah Babinski)
The BLM – OR SDARTT Toolbar for ArcMap (Image Credit: Micah Babinski)

The BLM’s GIS-based framework for quickly processing corporate geospatial data for SDARTT is nearing completion, and the BLM is well situated to meet the obligations of sage-grouse plan. These tools will benefit the planners, realty specialists, and GIS staff throughout Oregon.

An important source of surface disturbance that the BLM tracks with SDARTT in Sage-Grouse habitat is power lines.  Since GIS data depicting power lines is difficult to find and often of low quality, the Oregon Geospatial Enterprise Office’s Utilities Framework Implementation Team is currently employing a six-month Power Lines Work Group.

The work group will assess national standards for power line data in order to meet BLM and partner organizations’ (including the State of Oregon) mapping and analysis needs, and will create a system to dynamically update power line data in Oregon.

Without an effective GIS system, Oregon BLM would have a difficult time confronting the geospatial challenges of implementing the sage-grouse plan and simultaneously tracking potential surface disturbances.

The SDARTT data preparation and automation tools represent just one more example of GIS allowing government agencies to efficiently collaborate and serve the public’s interests.

About the Author:

Micah Babinski has worked in GIS seven years in the nonprofit, public, and private sectors. He is currently a GIS project manager for Elyon International, working under contract with the Bureau of Land Management in Portland, Oregon. Babinski graduated from the University of Washington Geography program. His particular interests in GIS include Python, data management, natural resources, and open data. He is a certified Geographic Information Systems Professional (GISP) and Esri-certified ArcGIS Desktop Professional. He hopes to continually improve his skills while helping others become more efficient GIS workers.

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