What does this data set describe?

Title: ODFWSageGrouseCoreAreas_20110629



Local Implementation Teams assisted in refining Core Area boundaries is to identify those areas that are not sage-grouse habitat and made recommendations to adjust the map boundaries accordingly.  Adjustments considered included adding occupied leks that were no more than 0.5 miles from the edge of a Core Area, and excluded areas of “non-habitat,” see detailed list below, that intersect the boundary of Core.  Exclusion areas may have begun at the boundary and extended more than 0.5 miles into the interior of a Core Area.


More specifically, high resolution National Agricultural Inventory Program (NAIP) imagery, Northwest GAP Landcover, and other GIS information Local Teams were used to make recommendations at a scale of 1:50,000 ft (2 times that of a topographic map) or greater.  Because Core Area Maps are a coarse filter, the goal was to identify landscape level changes in habitat, and not focus on individual parcels of land.

Each Local Implementation Team evaluated Core Area maps and refined boundaries within the following framework:

1. Adjustments were made ONLY to boundaries of Core Areas.


2. A 0.5 mile area outside of Core Areas was considered the standard area for adjustments to the perimeters. (Clarification: these are the outlined areas on the maps where potential habitat within core extends beyond the current core area boundary where leks are <3 miles to these boundaries. These areas can be considered for core status if suitable habitat is present and activities described in #3-7 below are not present.)


3. Excluded areas of existing industrial activity or permitted at greater levels than those recommended in the Conservation Strategy. This included mining, wind, solar, geothermal and other uses.


4. Excluded existing municipalities and subdivisions.


5. Excluded existing tilled agricultural lands.


6. Excluded areas where habitat is inconsistent with greater sage-grouse life-history (e.g., woodlands, badlands, “roughness” areas where terrain is unusable, etc.).


7. Excluded other areas where local information indicates there is no reason to be in Core.


8. Existing transmission lines and roads remained in the coarse level maps, but were recognized as areas to cluster developments when such proposals come forward.


9. Applied these rules to Low Density Area polygons as well, to ensure those polygons shared similar boundaries as Core Areas.



Core Area Approach to Habitat Mitigation for Greater Sage-Grouse in Oregon: The goal of these recommendations is to protect essential habitats to meet habitat and population objectives identified in this Plan. The objective of these recommendations is to avoid, minimize, or mitigate for impacts on sage-grouse habitats from energy development, its associated infrastructure or other industrial/commercial developments.
The rapid increase in energy development across the West in recent years has initiated a landscape approach to wildlife conservation, referred to as core areas (Doherty et al. in press). The landscape approach prioritizes habitats based on measures that assess sage-grouse population and habitat relative abundance, and provides protection for a minimum of 75% of the population. The remaining 25% of the population area would be available for development with some level of stipulations and regulations, but likely at a reduced level. The strength of this approach is that it uses biological information to identify core areas with the objective of protecting the most important breeding areas. It also enables managers, at the landscape scale, to map and analyze the risks and necessary conservation measures for each core area. The limitation of this approach is that it focuses on breeding abundances. For sage-grouse the relative abundance data is drawn from spring lek counts of males. Thus, habitat conservation measures may be biased towards breeding and nesting only. Lek data have limitations as well including: variable sampling effort both spatially and temporally and detection probabilities have not been estimated for ground or aerial counts. Notwithstanding, these are the best data available for mapping sage-grouse distributions.
Because the method outlined by Doherty et al. (in press) focuses on breeding habitats and ODFWs lek data is prone to variable sampling, an additional and complementary method was used to approximate seasonal use ranges, referred to as connectivity corridors. Using a home range estimator local and seasonal connectivity corridors were estimated. Thus, it is important to clarify some definitions about the mapping approach in Oregon. This document refers to Doherty's "core areas" (i.e., 25, 50, 75, 100%) as lek density strata. Lek density 25-75% polygons and the intersection of 100% strata and local connectivity polygons collectively define a "core area."


Purpose: The Core Area maps and data were developed as one component of the Conservation Strategy for sage-grouse in Oregon. Specifically, these data provide a tool in planning and identifying appropriate mitigation in the event of human development in sage-grouse habitats. These maps depict Core Areas and Low Density Habitat Areas that generally correspond with recommendations for Habitat Category 1 and Habitat Category 2 as defined in ODFW Mitigation Policy (OAR 635-415-0000), respectively, where impacts to sage-grouse habitat from a specific project are likely to occur .



1.      How should this data set be cited?

Hagen, Christian, 29 June 2011, 20110302_ODFWSageGrouseCoreAreas.

2.      What geographic area does the data set cover?

West_Bounding_Coordinate: -121.254974

East_Bounding_Coordinate: -116.921701

North_Bounding_Coordinate: 45.094273

South_Bounding_Coordinate: 41.854391

3.      What does it look like?

4.      Does the data set describe conditions during a particular time period?

Currentness_Reference: publication date

5.      What is the general form of this data set?

Geospatial_Data_Presentation_Form: vector digital data

6.      How does the data set represent geographic features?

 .a.       How are geographic features stored in the data set?

This is a Vector data set. It contains the following vector data types (SDTS terminology):

§  G-polygon (68)

a.b.      What coordinate system is used to represent geographic features?

Grid_Coordinate_System_Name: Universal Transverse Mercator


UTM_Zone_Number: 11


Scale_Factor_at_Central_Meridian: 0.999600

Longitude_of_Central_Meridian: -117.000000

Latitude_of_Projection_Origin: 0.000000

False_Easting: 500000.000000

False_Northing: 0.000000

Planar coordinates are encoded using coordinate pair
Abscissae (x-coordinates) are specified to the nearest 0.000000
Ordinates (y-coordinates) are specified to the nearest 0.000000
Planar coordinates are specified in meters

The horizontal datum used is North American Datum of 1983.
The ellipsoid used is Geodetic Reference System 80.
The semi-major axis of the ellipsoid used is 6378137.000000.
The flattening of the ellipsoid used is 1/298.257222.

7.      How does the data set describe geographic features?


Additional notes not covered by other fields



The Implmentation Meeting place that corresponds to the core area



Core Area or Low Density on April 1, 2011 before the Implementation Team Meetings.



Change or no-change to core based on the suggestions of the Implementation Team meetings.



Change or no-change to core based on the suggestions of the Implementation Team meetings and considered by the Statewide Team.

Coding for Apr1_core, Jun2_core, Jun29_core:

Core Area = No change to Core Area

Add2_core = New polygon of Core Area added

Change2_core = Existing polygon of Low Density changed to Core Area

Delete_core = Polygon of Core Area deleted entirely


Low Density = No change to Low Density

Add2_low = New polygon of Low Density added

Change2_low = Existsing polygon of Core Area changed to Low Density

Delete_low = Polygon of Low Density deleted entirely.



Recommendations made at the Implementation Team meetings.



Reasson(s) for the recommendations made at the Implementation Team meetings.


Who produced the data set?

1.      Who are the originators of the data set? (may include formal authors, digital compilers, and editors)

o    Christian Hagen

2.      Who also contributed to the data set?

3.      To whom should users address questions about the data?

Christian Hagen

541-388-6350 x1119 (voice)

Why was the data set created?

The Core Area maps and data were developed as one component of the Conservation Strategy for sage-grouse in Oregon. Specifically, these data provide a tool in planning and identifying appropriate mitigation in the event of human development in sage-grouse habitats.

How was the data set created?

1.      From what previous works were the data drawn?

(source 1 of 1)

2.      How were the data generated, processed, and modified?

(process 1 of 2)

Methods Data.-Using the Doherty et al. (in press) approach, average maximum counts of lekking male sage-grouse were used to identify high abundance areas. Additionally, a modification of Doherty et al. (in press) was used to delineate connectivity corridors between core regions. Lek count data (1980-2009) and the associated spatial coordinates provided the baseline information to map relative abundance of sage-grouse breeding areas. A total of 1,027 leks were analyzed to delineate lek density strata and connectivity corridors (Figure 22). Because sampling effort across leks is variable, 2 criteria were used to determine whether or not a lek was included in the mapping.
First, if a lek had >=1 male counted and recorded as the maximum male count over the last 8-yrs (2003-2010) that lek was included in the analysis. Second, those leks not counted during the 8-yr period, but that had males present at the last survey the percent change in males counted in a given year compared to 2010 to estimate lek size in 2010 was used. For example, a maximum count for a lek was 60 in 1987. Based on 88 leks (866 males) counted in 1987, 58 of those were counted again in 2009 (536 males), resulting in a 38% decrease in the number of males counted at all 58 leks surveyed in both years. Thus, the 2010 estimate for the lek would be 37 males (60 × {1+[-0.38]}). Otherwise the average maximum male count from 2003 to 2010 was used to estimate minimum male abundance.
Core Area Mapping.-Kernel density functions are often used in wildlife conservation to estimate home ranges of individual animals or to delineate concentrated use areas by populations (Worton 1989). A kernel is a mathematical density function that groups cells of concentrated use by attributing a grid placed over top of a study site with animal use or count data (Worton 1989). A 1-km2 grid of cells was populated with counts of sage-grouse males at leks across the range of the species in Oregon. This grid was used to select individual leks for core area strata designations. The kernel function was modified because choice of smoothing bandwidth is known to drastically affect area estimates and outer boundaries of concentrated use areas by populations (Horne and Garton 2006). Known distributions of nesting females around leks were used to delineate the outer boundaries of core regions and alleviated the choice of bandwidth issue (Holloran and Anderson 2005, ODFW 2009).
The value of each grid cell is a function of the number and proximity of leks in the surrounding landscape. Each cell was attributed with counts of males at leks within a radius of 6.4 km (4.0 mi). This distance was used because nesting females distribute their nests spatially in relation to lek location with >80% of nests located within a 6.4 km (4.0 mi) radius of lek sites (ODFW 2009). Once the grid was attributed, leks were classified relative to their abundance values and placed into 1 of 4 lek density groups, of which each strata contained 25 (very high density), 50 (high density), 75 (moderate density) and 100% (low density) of the known breeding population. These strata were then delineated by habitat areas of with a radii of 6.4-km (highest densities 25, and 50%) or 8.5-km (lower densities 75 and 100%) to delineate potential nesting areas.
The larger radius was used (5.3 mi; Holloran and Anderson 2005) to delineate lower lek density strata (75 and 100%), because Doherty et al. (in press) reported that increasing the radius in these strata provided more realistic estimates of the area needed to support breeding populations in low abundance or fragmented landscapes. Mapping output included a grouping of leks shaded by 4 colors that represent the smallest area necessary to contain 25, 50, 75, and 100% of nesting sage-grouse populations.
Connectivity mapping.- There is a need to support implementation of core regions with studies that document seasonal habitat use and migration patterns to ensure identified priority landscapes meet all seasonal habitat needs (Doherty et al. in press). Because lek surveys in Oregon are not uniformly distributed across the region nor have they been uniformly distributed over time, inferences about population density are limited. Additionally, the migratory status of many of Oregon's populations is unknown, and core area designations alone may not provide adequate habitat protection. As a result, connectivity areas were mapped to account for some of this uncertainty. Using a modified approach of the core area designations, connectivity corridors were mapped to link lek density strata and provide additional categorization of habitats.
As with lek density strata mapping, a kernel density function was used to delineate connectivity corridors. However, only the presence of leks was used to attribute each 1-km2 grid of cells, and the search radius was increased to 16 km. Such an approach only examines lek density. Using radiotelemetry data from Oregon, the center of seasonal use areas was estimated for 368 bird use seasons across 5 study areas. On average, sage-grouse moved 10.4, 10.5, and 9.4 km between breeding and summer, summer and winter, and breeding and winter ranges, respectively. Regionally, sage-grouse monitored in the Baker County study area moved an average of 15.9 km between breeding and summer ranges. Thus, 16 km was used to delineate the average maximum extent of connectivity between breeding and surrounding seasonal use areas. Two levels of connectivity were mapped: a 75% utilization distribution to delineate "local corridors," and a 90% utilization distribution to delineate "seasonal corridors." Polygons of both local and seasonal corridors were "clipped" to an occupied habitat data layer to approximate potential corridors as practical as possible. The clipped edges were smoothed out to 2 km to account for habitats difficult to map at the ecotone of juniper woodlands and forested types.
Winter habitat.- Previous analyses indicated that critical winter range occurred outside of lek density strata delineations, thus methods to include these important habitats are described here. Winter habitat use has been monitored with radiotelemetry (n = 1,659) near Jordan Valley, Baker City, Jack Creek, Hart Mountain, Beatys Butte, and GI Ranch (Eastern Crook County). Winter utilization distributions (90% use) were estimated for each study area. The resulting polygons were overlaid with lek density strata and connectivity layers and those areas of overlap were used to further define habitat categories.
Fragmentation.- Habitat loss and fragmentation are recognized as primary factors limiting sage-grouse populations (USFWS 2010), thus where kernel density polygons resulted in slivers (or "donut holes") of non-core or corridors that if not included in the core could lead to fragmentation of the core those slivers were connected to increase the likelihood that core would be retained.
Habitat Categorization.- A synthesis of the lek density strata and utilization corridors provides a framework for categorizing sagebrush habitat under the mitigation policy.
Core Areas were defined from 1 of the 3 following criteria: 1) All sagebrush types or other habitats that support sage-grouse that are encompassed by very high, high and moderate lek density strata. Collectively these groups represent 75% of the Oregon population but it only occupies 24% of the species range. 2) Where local connectivity corridors overlapped low lek density strata. 3) Where winter habitat use polygons overlapped with low lek density strata, either connectivity corridors or occupied habitat. Note, not all winter habitat use has been documented thus additional areas could be added to Category 1 as new information is acquired.
Low Density Areas were defined by the following criteria: 1) Where low density strata overlapped with seasonal connectivity corridors. 2) Where local corridors occurred outside of all lek density strata 3) Where low density strata occur outside of connectivity corridors, 4) Where seasonal connectivity corridors occur outside of all lek density strata.

Date: 12-Jul-2010 (process 2 of 2)

Dataset copied.

Data sources used in this process:

3.      What similar or related data should the user be aware of?

How reliable are the data; what problems remain in the data set?

1.      How well have the observations been checked?

Landscape level accuracy

2.      How accurate are the geographic locations?

Landscape level use

3.      How accurate are the heights or depths?

4.      Where are the gaps in the data? What is missing?

5.      How consistent are the relationships among the observations, including topology?

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?

Access_Constraints: Public information

Use_Constraints: DO NOT modify data.

1.      Who distributes the data set?[Distributor contact information not provided.]

2.      What's the catalog number I need to order this data set?

Downloadable Data

3.      What legal disclaimers am I supposed to read?

4.      How can I download or order the data?

o    Availability in digital form:

Data format:

Size: 3.039

o    Cost to order the data:

Who wrote the metadata?


Last modified: 12-Jul-2011

Metadata author:

Christian Hagen
Bend, OR 97702

541-388-6350 (voice)
541-388-6049 (FAX)

Metadata standard:

FGDC Content Standards for Digital Geospatial Metadata (FGDC-STD-001-1998)