Description: BaldEagleActiveNestSites_QtrMile is an ESRI SDE Feature Class showing a 0.25 mile buffer zone around active Bald Eagle (Haliaeetus leucocephalus) nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BatWinterHibernacula is an ESRI SDE Feature Class showing a 350 foot buffer zone winter hibernacula for Townsend’s big-eared bat, Mexican free-tailed bat, and myotis in Colorado.
Description: BighornProductionArea is an ESRI SDE Feature Class showing production (lambing) areas for bighorn sheep in Colorado. Production areas are defined as that part of the overall range occupied by pregnant females during a specific time period in the spring. This time period is May 1 to June 30 for Rocky Mtn bighorn sheep, and February 28 to May 1 for desert bighorn sheep. Only known production areas are mapped. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: CSTGrouseLekSites is an ESRI SDE Feature Class of Lek Sites for Columbian sharp-tailed grouse (Tympanuchus phasianellus columbianus) in Colorado. Lek Sites are defined as usually an open area or area of low vegetative cover, usually on a ridge or knoll where sharp-tailed grouse traditionally display and breed. Buffered from all lek points (Active, Inactive, Potential), except "Historic" and "Historic-R" in the Feature Class CSTGrouseLeks at 0.6 miles. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: CPW State Wildlife Areas And State Parks HPHC
Display Field: PropName
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: This data set is maintained by the CPW GIS Unit. These data include all public access designated parcels (Restricted, Seasonal, or Public Access) of SWA's included in Chapter 9, and State Parks.
Copyright Text: CPW GIS Unit, CPW Real Estate Unit, Colorado Parks and Wildlife, Colorado Department of Natural Resources
Description: FerruginousHawkActiveNestSite is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Ferruginous Hawk nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: GoldenEagleActiveNestSite_QtrMile is an ESRI SDE Feature Class showing a 0.25 mile buffer zone around active Golden Eagle nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: GPChickenLekSites is an ESRI SDE Feature Class showing a 0.6 mile buffer around all lek points (Active), except 'Unknown' leks in the SDE Feature Class GPChickenLeks.This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: GrSageGrouseLekSites is an ESRI SDE Feature Class showing those areas known to be used by sage grouse within the last 10 years from the date of mapping. "Use" is defined as 1) radio telemetry locations, 2) confirmed observations of birds or sign by reliable sources, 3) documented use reported in unpublished reports or publications (mapped by field biologists). Mapped as a buffer zone of 1.0 miles around all lek points (Active, Inactive), except 'Unknown' in the feature class GrSageGrouseLeks. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: GunnSageGrouseLekSites is an ESRI SDE Feature Class that shows Lek Sites for Gunnison's Sage Grouse (Centrocercus minimus) in Colorado. Lek Sites are defined as an open area usually located in low sagebrush where sage grouse traditionally display and breed. These are mapped as a 1.0 mile buffer zone around all lek polygons (Active, Inactive), except 'Unknown' in GunnSageGrouseLeks.This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: LeastTernProductionArea is an ESRI SDE Feature Class showing an area that includes nesting habitat and contains one or more active or previously active and aggressively defended territories. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: LPChickenLekSites is an ESRI SDE Feature Class showing areas where lesser prairie chickens are known to have displayed and bred in the past 10 years. Lek sites typically, although not always, are located on open ridges, grass knolls, or slight rises in topography where vegetation is sparse. Buffered 1.25 miles around all lek points (Active, Inactive), except 'Unknown', in the SDE Feature Class LPChickenLeks. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: CPW BIOLOGISTS, DISTRICT WILDLIFE MANAGERS AND RESEARCHERS
Description: NorthernGoshawkActiveNestSite is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Northern Goshawk nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PeregrineFalconActiveNestSite is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Peregrine Falcon nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PipingPloverProductionArea is an ESRI SDE Feature Class showing Production Area, an area that includes nesting habitat and contains one or more active or previously active and aggressively defended territories. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PSTGrouseLekSites is an ESRI SDE Feature Class of Lek Sites for Plains sharp-tailed grouse (Tympanuchus phasianellus) in Colorado. Lek Sites are defined as usually an open area or area of low vegetative cover, usually on a ridge or knoll where sharp-tailed grouse traditionally display and breed. Buffered from all lek points (Active, Inactive), except 'Unknown' in the Feature Class PSTGrouseLeks at 0.4 miles. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PrairieFalconActiveNestSite is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Prairie Falcon nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BighornMigrationCorridors is an ESRI SDE Feature Class showing a specific, mappable site through which large numbers of animals migrate, and the loss of which would change migration routes. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BighornWinterRange is an ESRI SDE Feature Class showing that part of the overall range where 90% of the individuals are located during the average five winters out of ten, from the first heavy snowfall to spring green-up, or as a specific period which may defined for each unit. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Columbian Sharp-tailed Grouse Production Area HPHD
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: CSTGrouseProductionArea is an ESRI SDE Feature Class showing production areas for Columbian Sharp-tailed Grouse (Tympanuchus phasianellus columbianus) in Colorado. Production Areas are defined as areas that include 90% of sharp-tailed grouse nesting or brood rearing habitat. This is mapped as a buffer zone of 1.25 miles around active dancing grounds in CSTGrouseLeks and clipped to CSTGrouseOverallRange. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: ElkMigrationCorridors is an ESRI SDE Feature Class depicting Migration Corridors for Elk in Colorado. Migration Corridors is defined as a specific mappable site through which large numbers of animals migrate and loss of which would change migration routes. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: ElkProductionArea is an ESRI SDE Feature Class showing elk production areas. This dataset represents that part of the overall range of elk occupied by the females from May 15 to June 15 for calving. Only known areas are mapped and this does not include all production areas for the Data Analysis Unit. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: ElkSevereWinterRange is an ESRI SDE Feature Class that shows severe winter range for elk in the state of Colorado. This dataset represents that part of the overall range of elk where 90% of the individuals are located when the annual snowpack is at its maximum and/or temperatures are at a minimum in the two worst winters out of ten. The winter of 1983-1984 is a good example of a severe winter. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: ElkWinterConcentrationArea is an ESRI SDE Feature Class that shows winter concentration areas for elk in the state of Colorado. This dataset represents that part of the winter range of elk where densities are at least 200% greater than the surrounding winter range density during the average five winters out of ten from the first heavy snowfall to spring green-up, or during a site specific period of winter as defined for each Data Analysis Unit. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Greater Prairie Chicken Production Area HPHD
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: GPChickenProductionArea is an ESRI SDE Feature Class showing areas which includes all nesting and brood rearing habitat of the greater prairie chicken. Currently defined as a 2.2 mile buffer zone around each active lek point in the SDE Feature Class GPChickenLeks and clipped to GPChickenOverallRange. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Greater Sage Grouse Priority Habitat Management Area HPHD
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: The data set was created by preparing fine-scale population-specific Species Distribution Models (SDMs) to map revised PHMA and GHMA areas for each of the six greater sage-grouse populations within the current occupied range of Colorado. First, known presence locations of marked greater sage-grouse were used to train Random Forest and Resource Selection Function (RSF) models to estimate seasonal (e.g., breeding, summer-fall and winter) habitat suitability. Secondly, the seasonal model results were classified into high or low habitat suitability categories and subsequently compiled to produce a year-round habitat suitability map. Third, the resulting year-round habitat suitability maps were used to develop revised PHMA and GHMA areas for each population. Finally, the current occupied range for each population were modified to 1) exclude areas identified as unsuitable habitats and 2) include areas outside of current occupied range where evidence of sage-grouse occupancy exists.Data inputs into the RSF and Random Forest Models included presence data from GPS and VHF collar data provided to Olsson from CPW biologists, which was used to refine the models. A combination of vegetative and topographic predictors were employed at multiple scales in assessing the probability of habitat selection for the populations analyzed in this study. The predictors were analyzed at multiple spatial scales, as the literature demonstrates that habitat selection by a species occurs at some scales and not others (Mayor et al. 2009, Acker et al. 2017). The predictors were measured at five scales: 100 meters (m), 400 m, 1000 m, 1600 m, and 3200 m. These were selected to assess a range of local- to landscape-level scales that may influence habitat selection. Furthermore, these scales are comparable to scales assessed in other contemporary studies concerning habitat selection of greater sage-grouse (Doherty et al. 2010; Rice et al. 2016; Walker et al. 2016).Populations were also analyzed to assess utilization of smaller mapped aspen stands as compared to larger continuous forested stands of aspen and/or mixed-conifer. While greater-sage grouse tend to avoid larger forested areas, they will utilize smaller aspen stands (T. Apa pers. comm. 2016-2018). All presence locations for each population were sampled against mapped aspen stands to calculate 1) the rate of selection for aspen stands by the population, and 2) the acreage of each aspen stand utilized. The sampled stand acreages were subsequently graphed and examined to identify natural breaks in the data. Stands with acreages less than the natural break value and not directly adjacent to other forested stands were classified and analyzed separately as isolated aspen polygons which were included as potentially suitable habitat; the remaining aspen stands were classified as forested and integrated with mixed-conifer forests, which were assumed to be non-suitable habitat.Finally, the distance to forested areas was measured as a vegetative predictor using the Euclidean Distance tool in ArcGIS 10.4, excluding all isolated aspen patches and mixed-conifer patches less than 0.5 acres (and see previous paragraph).Vegetation types were derived from the Colorado Vegetation Classification Project (CVCP), a 25 m resolution raster dataset developed by CPW, which mapped landcover conditions through the periods from 1993to 1997. In addition, vegetation types were also derived from the 2001 LANDFIRE Existing Vegetation Type (EVT) layer for areas adjacent to the study area in Utah and Wyoming to provide complete and continuous vegetation cover for populations abutting the state boundary. The LANDFIRE EVT is a 30 m resolution raster dataset developed by the United States Geological Survey (USGS) mapping landcover conditions from 2001 (LANDFIRE 2001). Vegetative types were classified into biologically relevant classes and subsequently measured as percent-proportion by dividing the number of cells for the particular class by the total number of cells within the radii of the five defined scales using ArcGIS 10.4. The assigned classes of vegetative types varied by population and are detailed in the population-specific reports provided to BLM.Topographic predictors were derived from the 10 m resolution National Elevation Dataset (NED) Digital Elevation Model (DEM) developed and maintained by the USGS. Key topographic predictors include aspect, Compound Topographic Index (CTI), elevation, percent slope, slope position and surface roughness. Aspect and percent slope were calculated in ArcGIS 10.4. CTI, slope position and surface roughness were calculated using the Geomorphology and Gradient Metrics toolbox (Evans et al. 2014). In addition, aspect was subsequently transformed using the TRASP method in the Geomorphology and Gradient Metrics toolbox. To develop the multi-scale predictors, CTI and percent slope were measured as the mean of all values within the radii of the five defined scales; slope position and surface roughness were calculated using the radii of the five defined scales.The following summary of the step-wise procedure was developed to convert the Random Forest and RSF continuous surface model results into revised Habitat Management Area Prescriptions. Details of these methods follow this list:1. Classify all seasonal Random Forest and RSF model results into high and low habitat suitability layers.2. Ensemble all Random Forest and RSF classified seasonal layers to form a single year-round annual habitat layer designating locations as either high or low habitat suitability.3. Convert all highly suitable locations to Priority Habitat Management Areas (PHMA) and all locations designated as low habitat suitability to General Habitat Management Areas (GHMA).4. Classify all areas within a 0.6-mile radius from lek locations having an active or unknown status designation as PHMA, regardless of habitat suitability classification.5. Identify all irrigated agricultural lands and designate interiors as Undesignated Habitat (UDH).6. Review and apply site-specific manual conversions of initial management prescription designations based on CPW biologist and stakeholder input.7. Remove identified non-habitat areas from Current Occupied Range (COR). Expand COR in areas beyond the current population boundary where evidence exists to demonstrate occupation by greater sage-grouse.The previous habitat layer generated by CPW, only two habitat designations prescribed by the BLM ARMPA exist for assigning management approaches for conservation of the Colorado greater sage-grouse populations; PHMA and GHMA. PHMA have the highest conservation value based on a combination of habitat and sage-grouse population characteristics and are managed to minimize disturbance activities through No Surface Occupancy (NSO) stipulations and implementing capped disturbance allowances. GHMA represent areas with lower greater sage-grouse occupancy and generally have marginal habitat conditions with fewer management restrictions that provide greater flexibility in land use activities.The initial step to applying PHMA and GHMA habitat management prescriptions involves converting all areas classified as highly suitable habitat in the population’s year-round classified habitat layer to PHMA, while the remaining low habitat suitability areas are converted to GHMA. Secondly, all lek locations with a CPW-prescribed active or unknown status designation are buffered with a 0.6-mile radius and the entirety of the interior of the buffer area is converted to PHMA. Third, the most recent mapped irrigated agricultural lands data was acquired from the Colorado Division of Water Resources for all applicable populations, then the following procedure described below were implemented to apply the Undesignated Habitat prescription to the interior of all irrigated agricultural lands.Undesignated HabitatThrough the course of this study, an additional management prescription was established by AGNC to address concerns regarding habitat management on privately held irrigated agricultural lands.An Undesignated Habitat(UDH) management prescription was developed to address concerns surrounding the management of privately held irrigated agricultural lands. The UDH prescription is applicable to all populations, excluding the Parachute-Piceance-Roan population (due to a lack of irrigated agricultural lands). UDH are areas of seasonally irrigated and harvested hay fields. These areas are utilized seasonally by sage-grouse, primarily in the late summer and fall, near edges where irrigated fields are adjacent and abutting sagebrush habitats. UDH is considered effective habitat, but it is the long-term irrigation and haying practices which have created and maintain this habitat type, and thus the unimpeded irrigation, haying operations and maintenance are not considered to be a negative impact to sage-grouse. While utilization of the edges of irrigated agricultural lands by sage-grouse is known to vary from population to population, studying grouse utilization on a population-specific basis proved problematic as most populations lacked adequate telemetry locations within irrigated agricultural lands to yield results with any level of confidence. For this reason, the North Park population was selected to analyze in detail due to the high number of telemetry points located within irrigated agricultural lands. Approximately 20 percent of all summer-fall telemetry locations for the North Park population occur within irrigated agricultural lands, compared to less than 1 percent to 3 percent utilization demonstrated in the remaining populations.All summer-fall telemetry locations occurring within irrigated agricultural lands were sampled to calculate the distance each point occurred from the edges of irrigated fields. The distances for each location were plotted in a histogram and subsequently reviewed by CPW and AGNC team consultants, revealing a natural break occurring in the data at approximately 83 m. As a result, all interior irrigated agricultural lands lying beyond 83 m from the edge of sagebrush habitats are designated as UDH, while the zone occurring from the 83 meters up to the edges of sagebrush habitats retained the PHMA or GHMA designations as determined by the Random Forest and RSF model results.Final Review.Finally, the resulting revised management prescription layer was manually reviewed by AGNC and by CPW biologists and researchers to identify areas that may warrant conversion from PHMA to GHMA, or vice versa, based on biological considerations, habitat characteristics or the potential for impacting critical future economic development activities.Each population model was slightly different based on the data and nature of the populations. Below is a brief summary of the models by population along with reference to the specific population model documentation that describes each model in much more detail.Northwest Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Northwest population follows the procedures outlined in section5.0 Methodsof the Methods Report. However, as described further below, the telemetry data acquired for analyzing the population were highly clustered. Employing these data in models to predict habitat suitability across a vast, variable landscape resulted in spurious and unreliable predictions in areas further removed from known presence locations. For this reason, we also developed a fourth model for the Northwest population to predict habitat suitability based on known lek locations to enhance predictions in areas lacking available telemetry data (see section 3.4.2 Random Forestbelow). Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NW_Population_Report.pdfParachute-Piceance-Roan (PPR) Population Model: The approach to analyzing greater sage-grouse habitat suitability for the PPR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. RSF models were not developed for the PPR population as part of this study, rather, this project employed RSF models previously developed by CPW in a separate study performed in 2015 to analyze sage-grouse habitat conditions within the PPR area (Walker et al. 2015). CPW’s analysis in their 2015 study implemented the same procedure in developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this project. The 2015 PPR habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW considered two additional scales for analyses, 800 m and 2400 m in their 2015 study, as compared to the scales analyzed in this study. To ensure consistency with CPW’s RSF models, the Random Forest models developed for this study also include these same scales of analyses. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2015 PRR study was defined as occurring between March 14thto 14 days beyond the date on which approximately 90 percent of females finished nesting for that year (Walker et al. 2015). In addition, the summer-fall season was defined as ending on November 30thin CPW’s 2015 study, as compared to November 15thin this study. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the PPR population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2015 report, titled “Mapping and Prioritizing Seasonal Habitats for Greater Sage-Grouse in Northwestern Colorado”, and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_PPR_Population_Report.pdf.North Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NP population follows the procedures outlined in section 5.0 Methods of the Methods Report. RSF models were not developed for the NP population as part of this study. Rather, this project employed RSF models developed by CPW in a separate study performed in 2016 to analyze sage-grouse habitat conditions for the NP range (Rice et al. 2016; Appendix I). CPW’s analysis in their 2016 study implemented similar methods to developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this study. The 2016 North Park habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW developed their seasonal RSF models for the NP population as single-scale models. The scales analyzed were derived from Average Daily Movement (ADM) distances calculated from the available telemetry data for each season. The scales employed for each seasonal analysis were 150.8 m, 83.1 m and 203.6 m for the breeding, summer-fall and winter seasons, respectively. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2016 North Park study was defined as occurring between April 1st to July 15th; the summer-fall season was defined as July 16th to September 1st; the winter season was defined as starting October 1st and ending March 1st. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the NP population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2016 report, titled “Mapping and Prioritizing Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development”and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NP_Population_Report.pdf.Middle Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Middle Park population follows the procedures outlined in Section 5.0of the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MP_Population_Report.pdf.North Eagle-South Routt Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NESR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NESR_Population_Report.pdf.Meeker White River Population Model: The approach to mapping greater sage-grouse habitat suitability for the MWR population differed from the procedures outlined in Section 5.0of the Methods Report. The population contained 97 total marked locations of greater sage-grouse across all seasons, resulting in insufficient data to adequately train habitat models to yield credible and defensible results. For this reason, this project relied on the expertise and knowledge of CPW Wildlife Managers, Moffat County officials and local landowners to manually digitize revised areas of PHMA and GHMA for the MWR population. On October 25th, 2018, CPW and AGNC representatives, as well as AGNC consultants, met with Moffat County officials and local landowners to discuss the current state of the population’s greater sage-grouse and habitat conditions, as well as the ongoing modeling efforts attempted to date. AGNC consultants and CPW informed participants that the population lacked an adequate pool of telemetry locations to perform the same modeling methods implemented on other Colorado populations in assessing habitat conditions and developing revised areas of PHMA and GHMA. For this reason, it was conveyed that the approach for revising management areas in the MWR population would rely on the local officials and landowners, as well as the input provided by the experience and expertise of CPW staff, to identify areas having the highest habitat quality evidence of utilization by greater sage-grouse. The identified areas would subsequently be digitized in a GIS and managed as PHMA, while all remaining areas would be managed according to GHMA guidelines and stipulations.In recent decades, the MWR population has seen considerable areas of lands converted from sagebrush to agricultural uses, thereby reducing the amount of suitable habitats available to the region’s sage-grouse. The conversion of these lands is most pronounced in the north-eastern lobe of the MWR population, as well as the northern portion of the western lobe of the population; the two smaller lobes in the southeast remain unaffected by agricultural operations and are predominately sagebrush habitats with smaller components of mixed-mountain shrubs.The vast majority of the lower elevations occurring in the northern portion of the western lobe of the MWR population are currently utilized in agricultural operations and host little, to no, sagebrush cover. Moving south to the higher elevations in this area of the range, the vegetation transitions to broader expanses of sagebrush intermixed with a moderate component of mixed-mountains shrubs and smaller stands of pinyon-juniper and aspen. While a considerable portion of these lands are currently protected under an assortment of Conservation Easements, these habitat conditions are nevertheless considered marginal in the ability to support greater sage-grouse occupancy. In addition, no sightings of greater sage-grouse have occurred within this region according to recent records or the available telemetry data. Finally, while three historic leks are located within this area, no evidence exists to suggest active lekking occurs within this region. In the prior decade, CPW attempted to establish two leks in this area, but the locations were not utilized and subsequently established as active lekking grounds. For these reasons, all parties agreed the western lobe of the MWR population should be managed in accordance with GHMA guidelines.The two smaller lobes located in the southeast portion of the MWR occupied range exhibit similar vegetation characteristics, though sagebrush cover is more dominant with less intermixed mixed-mountain shrubs, pinyon-juniper and aspen components. While agricultural operations are absent in these areas, there is no evidence to suggest occupancy by greater sage-grouse. There is no record of recent sightings in either area nor any marked locations of sage-grouse in the available telemetry data. Furthermore, there are no records of active, inactive or historic leks that have occurred in either lobe. Consequently, all parties concurred that both areas should be managed in accordance with GHMA guidelines.The northeastern lobe of the MWR population, located directly west of the Town of Meeker, contains the highest quality habitat within the population’s current occupied range. Despite substantial conversion of historic sagebrush lands to agricultural operations in recent decades, evidence suggests continued utilization of the surrounding habitats by greater sage-grouse, though to a far lesser degree as compared to other State populations. All 97 telemetry locations that exist for the MWR population occur in this region, consisting of three individuals collected in 2010. The population’s only active lek occurs in this area, in addition to three historic leks located on the surrounding landscape. In addition, both County officials and local landowners relayed sightings of a single individual within this area in recent years.Based on this evidence, all parties agreed that the northeastern lobe of the MWR population should be managed as both GHMA and PHMA. The northeastern lobe is bisected east to west by County Road 6. Sagebrush habitats north of County Road 6 are of lesser quality and are highly fragmented by agricultural activities, and to a lesser extent, natural gas extraction operations. Accordingly, all areas north of County Road 6 were agreed to be managed consistent with GHMA guidelines. By contrast, lands south of County Road 6 exhibit improved habitat conditions and less fragmentation. Not surprisingly, the majority of available telemetry locations occur within this region, as well as the population’s only known active lek. Therefor, it was collectively decided this region be managed in accordance with PHMA guidelines and stipulation. Furthermore, local officials and landowners indicated sightings of greater sage-grouse in this region beyond the eastern perimeter of the occupied range boundary. For this reason, the MWR boundary was expanded further east to protect additional habitats within the population’s occupied range. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MWR_Population_Report.pdf.Additional BLM and CPW Edits:The final product from Olsson was a vectorized version of the ensembled models, this resulted in a data set with a number of GIS related issues. 1) The were small grid cell sized (25 meters squared) of a particular habitat type, in a sea of another habitat type. This biologically did not make sense and was at a scale smaller than the BLM minimum mapping unit. The BLM GIS shop ran a process to remove these outlier habitat categorizations to get a more uniform layer. 2) The data were not snapped to the boundary of Colorado, the data set was intended to include range for the entire state of Colorado, however there was a sliver of non-habitat along the Wyoming and Utah border that was missing in the final version from Olsson. The CPW GIS Unit fixed this issue and snapped the Habitat layer to boundary of the state of Colorado, using the official state boundary from the State GIS data warehouse. 3) The data set was converted from a raster without the smooth option resulting in a data set with squared off boundaries at every 25 meters. This cause a large number of vertices in the data making the loading of the data set for staff very difficult. To deal with these issues the Simplify tool was used with the retain critical bends method and a simplification tolerance of 25 meters. 4) Finally, since the data was converted from a raster it no longer matched up with the boundary of the GrSG Occupied Range Layer, also there were a few omissions of occupied range that needed to be added to the final habitat layer. To rectify this the habitat layer, minus the linkage polygons was intersected with the GrSG occupied range layer and all the pieces that were not in common were saved. The pieces of the habitat layer that were outside occupied range were deleted and the pieces that were missing to complete the boundary of occupied range were added and classified as the habitat type of the adjacent polygons. These pieces were small, just triangles that caused the raster converted habitat layer to to be squared off versus the smooth occupied range layer boundary. Then small bits of occupied range that had been noticed as an omission were added.
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Description: Gunnison sage grouse GIS data set identifying occupied habitats in Colorado. The data set was created by mapping efforts of the Colorado Division of Wildlife biologist and district officers during the spring of 2004 and updated as recently as summer of 2009. Occupied Habitat: Areas of suitable habitat known to be used by sage-grouse within the last 10 years from the date of mapping. Areas of suitable habitat contiguous with areas of known use, which do not have effective barriers to sage-grouse movement from known use areas, are mapped as occupied habitat unless specific information exists that documents the lack of sage-grouse use. Mapped from any combination of telemetry locations, sightings of sage grouse or sage grouse sign, local biological expertise, GIS analysis, or other data sources.
Description: GunnSageGrouseProductionArea is an ESRI SDE Feature Class that shows production areas for Gunnison's Sage Grouse (Centrocercus minimus) in Colorado. Production Areas are defined as areas that would include the majority of important Gunnison's Sage Grouse nesting habitat. These are mapped as a four-mile buffer zone around active leks in GunnSageGrouseLeks. As of 9/8/2016 these buffer zones are no longer clipped to GunnSageGrouseOverallRange per directive from Jon Holst, CPW Energy Resource Specialist - SW Region. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: The Lesser Prairie Chicken Priority Areas are mapped polygons designating high priority habitat, both focal areas (CHAT 1) and connectivity areas (CHAT 2) as defined in the Lesser Prairie Chicken Rangewide Plan. These were mapped with the Colorado Parks and Wildlife (CPW) Bird Conservation Coordinator and the Area 12 Wildlife Biologist (only area in the state that the bird is present). Current lek location data, soil type, vegetation and CPR data were used to aide in the mapping effort.As a component of the 5-Year Review of the Range-wide Conservation Plan (Van Pelt et al. 2013), the Interstate Working Group (IWG) evaluated and re-mapped (as necessary) the Estimated Occupied Range (EOR) along with the Focal Areas (CHAT 1) and Connectivity Zones (CHAT 2) across lesser prairie-chicken (LPC) range in Colorado, Kansas, Oklahoma, Texas, and New Mexico. The IWG used the criteria below to adjust the EOR and Focal Area and Connectivity Zone delineations. The proposed mapping revisions are based on best available science and local knowledge. The IWG presented the initial proposed mapping changes to the LPC State Implementation Teams for review in late 2019 and early 2020. Recommended changes to the range-wide EOR boundary will be included in the 10-year review of the RWP. The current 5-year Review will only recommend changes to Focal Areas (CHAT 1) and Connectivity Areas (CHAT 2) such that there is no change to the EOR+10 in the RWP (Van Pelt et. al 2013) and associated area of coverage for the LPC Candidate Conservation Agreement with Assurances (CCAA) (USFWS 2014). However, individual states may decide to use the updated EOR mapping for land-use recommendations and targeting habitat conservation and restoration. Colorado Parks and Wildlife (CPW) will use current biologically-based mapping for LPC conservation in Colorado. IWG Criteria for Changes to the Focal Area Zones (CHAT 1) and Connectivity Zones (CHAT 2):Additions were based on:1) Newly documented leks2) Newly created or restored habitat conditions3) Restoration opportunitiesDeletions were based on:1) New and cumulative anthropogenic developmentsColorado Parks and Wildlife revised LPC mapping was completed by Liza Rossi (Bird Conservation Coordinator), Jonathan Reitz (Lamar Terrestrial Biologist), and Michelle Flenner (GIS Specialist) in July 2019. The proposed changes were presented at the Colorado LPC State Implementation Team Meeting in Lamar on November 14, 2019. The group there was supportive of the changes and thought we should reflect our biological understanding of LPC distribution rather than being confined by the 2013 RWP covered area. CPW is proposing these changes to reflect current distribution of LPC in Colorado. CPW updates Species Activity Mapping (SAM) every four years across Colorado. SAM mapping will be updated for the CPW SE Region in 2020 and the updated Colorado EOR as well as proposed CHAT 1 and CHAT 2 will be incorporated in CPW mapping. The proposed changes were reviewed and agreed to by CPW Area 12 personnel at an Area Meeting on February 5, 2020. Although CPW will move forward with this mapping for Colorado conservation efforts, formal changes to the covered area of the RWP (2013 EOR +10, Van Pelt et al. 2013) or the Range-wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (CCAA, USFWS 2014) will be evaluated through the 10-Year Review of the RWP or an update to the CCAA). Changes to the CHAT mapping will be presented as part of the 5-year Review to the Lesser Prairie-Chicken Initiative Council. USFWS. 2014. Range-Wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in Colorado Kansas, New Mexico, Oklahoma, and Texas. 78 FR 76639.Van Pelt, W.E., S. Kyle, J. Pitman, D. Klute, G. Beauprez, D. Schoeling, A. Janus, J. Haufler. 2013. The Lesser Prairie-Chicken Range-wide Conservation Plan. Western Association of Fish and Wildlife Agencies. Cheyenne, Wyoming. Pp.367.Interstate Working Group Members include: Kent Fricke, chair (Kansas Department of Wildlife, Parks and Tourism), Liza Rossi (Colorado Parks and Wildlife), Brett Cooper (Oklahoma Department of Wildlife Conservation), Grant Beauprez (New Mexico Department of Game and Fish), and Russell Martin (Texas Parks and Wildlife Department).
Description: MuleDeerMigrationCorridors is an ESRI SDE Feature Class showing a specific mappable site through which large numbers of animals migrate and loss of which would change migration routes. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: MuleDeerSevereWinterRange is an ESRI SDE Feature Class showing that part of the overall range where 90% of the individuals are located when the annual snowpack is at its maximum and/or temperatures are at a minimum in the two worst winters out of ten. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: MuleDeerWinterConcentrationArea is an ESRI SDE Feature Class showing that part of the winter range where densities are at least 200% greater than the surrounding winter range density during the same period used to define winter range in the average five winters out of ten. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Plains Sharp-tailed Grouse Production Area HPHD
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: PSTGrouseProductionArea is an ESRI SDE Feature Class showing production areas for Plains Sharp-tailed Grouse (Tympanuchus phasianellus) in Colorado. Production Areas are defined as areas that include 90% of sharp-tailed grouse nesting or brood rearing habitat. This is mapped as a buffer zone of 1.25 miles around active dancing grounds in PSTGrouseLeks and clipped to PSTGrouseOverallRange. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PronghornMigrationCorridors is an ESRI SDE Feature Class showing Migration Corridors of Pronghorn. Migration Corridors is defined as a specific mappable site through which large numbers of animals migrate and the loss of which would change migration routes. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: PronghornWinterConcentrationArea is an ESRI SDE Feature Class showing Winter Concentration Areas of Pronghorn. Winter Concentration Area is defined as that part of the winter range where animal densities are at least 200% greater than the surrounding winter range density during the same period used to define winter range in the average five winters out of ten. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BaldEagleActiveNestSites_HalfMile is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Bald Eagle (Haliaeetus leucocephalus) nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BaldEagleRoostSite is an ESRI SDE Feature Class showing roost sites and communal roost sites for Bald Eagle (Haliaeetus leucocephalus) in Colorado. Roost sites are defined as a 0.25 mile buffer zone aroundgroups of or individual trees that provide diurnal and/or nocturnal perches for less than 15 wintering bald eagles in Colorado; these trees are usually the tallest available trees in the wintering area and are primarily located in riparian habitats.Communal Roost Sites are defined as groups of or individual trees that provide diurnal and/or nocturnal perches for more than 15 wintering bald eagles; these trees are usually the tallest available trees in the wintering area. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: BurrowingOwlActiveNestSite is an ESRI SDE Feature Class showing a 0.25 mile buffer zone around active Burrowing Owl nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Columbian Sharp-tailed Grouse Winter Range HPHE1
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: CSTGrouseWinterRange is an ESRI SDE Feature Class showing winter range for Columbian Sharp-tailed Grouse (Tympanuchus phasianellus columbianus) in Colorado. Winter Range is defined as the observed winter range, usually in a tall shrub vegetative type, within 5 km of a lek site. Shrub height should be sufficient to allow feeding on buds by birds above normal snow depths. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Description: GoldenEagleActiveNestSite_HalfMile is an ESRI SDE Feature Class showing a 0.5 mile buffer zone around active Golden Eagle nests in Colorado. This information was derived from field personnel. A variety of data capture techniques were used including drawing on mylar overlays at 1:50,000 scale USGS county mapsheets and implementation of the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).
Copyright Text: Colorado Parks and Wildlife Biologists, District Wildlife Managers, and Researchers.
Name: Greater Sage Grouse General Habitat Management Area HPHE1
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: The data set was created by preparing fine-scale population-specific Species Distribution Models (SDMs) to map revised PHMA and GHMA areas for each of the six greater sage-grouse populations within the current occupied range of Colorado. First, known presence locations of marked greater sage-grouse were used to train Random Forest and Resource Selection Function (RSF) models to estimate seasonal (e.g., breeding, summer-fall and winter) habitat suitability. Secondly, the seasonal model results were classified into high or low habitat suitability categories and subsequently compiled to produce a year-round habitat suitability map. Third, the resulting year-round habitat suitability maps were used to develop revised PHMA and GHMA areas for each population. Finally, the current occupied range for each population were modified to 1) exclude areas identified as unsuitable habitats and 2) include areas outside of current occupied range where evidence of sage-grouse occupancy exists.Data inputs into the RSF and Random Forest Models included presence data from GPS and VHF collar data provided to Olsson from CPW biologists, which was used to refine the models. A combination of vegetative and topographic predictors were employed at multiple scales in assessing the probability of habitat selection for the populations analyzed in this study. The predictors were analyzed at multiple spatial scales, as the literature demonstrates that habitat selection by a species occurs at some scales and not others (Mayor et al. 2009, Acker et al. 2017). The predictors were measured at five scales: 100 meters (m), 400 m, 1000 m, 1600 m, and 3200 m. These were selected to assess a range of local- to landscape-level scales that may influence habitat selection. Furthermore, these scales are comparable to scales assessed in other contemporary studies concerning habitat selection of greater sage-grouse (Doherty et al. 2010; Rice et al. 2016; Walker et al. 2016).Populations were also analyzed to assess utilization of smaller mapped aspen stands as compared to larger continuous forested stands of aspen and/or mixed-conifer. While greater-sage grouse tend to avoid larger forested areas, they will utilize smaller aspen stands (T. Apa pers. comm. 2016-2018). All presence locations for each population were sampled against mapped aspen stands to calculate 1) the rate of selection for aspen stands by the population, and 2) the acreage of each aspen stand utilized. The sampled stand acreages were subsequently graphed and examined to identify natural breaks in the data. Stands with acreages less than the natural break value and not directly adjacent to other forested stands were classified and analyzed separately as isolated aspen polygons which were included as potentially suitable habitat; the remaining aspen stands were classified as forested and integrated with mixed-conifer forests, which were assumed to be non-suitable habitat.Finally, the distance to forested areas was measured as a vegetative predictor using the Euclidean Distance tool in ArcGIS 10.4, excluding all isolated aspen patches and mixed-conifer patches less than 0.5 acres (and see previous paragraph).Vegetation types were derived from the Colorado Vegetation Classification Project (CVCP), a 25 m resolution raster dataset developed by CPW, which mapped landcover conditions through the periods from 1993to 1997. In addition, vegetation types were also derived from the 2001 LANDFIRE Existing Vegetation Type (EVT) layer for areas adjacent to the study area in Utah and Wyoming to provide complete and continuous vegetation cover for populations abutting the state boundary. The LANDFIRE EVT is a 30 m resolution raster dataset developed by the United States Geological Survey (USGS) mapping landcover conditions from 2001 (LANDFIRE 2001). Vegetative types were classified into biologically relevant classes and subsequently measured as percent-proportion by dividing the number of cells for the particular class by the total number of cells within the radii of the five defined scales using ArcGIS 10.4. The assigned classes of vegetative types varied by population and are detailed in the population-specific reports provided to BLM.Topographic predictors were derived from the 10 m resolution National Elevation Dataset (NED) Digital Elevation Model (DEM) developed and maintained by the USGS. Key topographic predictors include aspect, Compound Topographic Index (CTI), elevation, percent slope, slope position and surface roughness. Aspect and percent slope were calculated in ArcGIS 10.4. CTI, slope position and surface roughness were calculated using the Geomorphology and Gradient Metrics toolbox (Evans et al. 2014). In addition, aspect was subsequently transformed using the TRASP method in the Geomorphology and Gradient Metrics toolbox. To develop the multi-scale predictors, CTI and percent slope were measured as the mean of all values within the radii of the five defined scales; slope position and surface roughness were calculated using the radii of the five defined scales.The following summary of the step-wise procedure was developed to convert the Random Forest and RSF continuous surface model results into revised Habitat Management Area Prescriptions. Details of these methods follow this list:1. Classify all seasonal Random Forest and RSF model results into high and low habitat suitability layers.2. Ensemble all Random Forest and RSF classified seasonal layers to form a single year-round annual habitat layer designating locations as either high or low habitat suitability.3. Convert all highly suitable locations to Priority Habitat Management Areas (PHMA) and all locations designated as low habitat suitability to General Habitat Management Areas (GHMA).4. Classify all areas within a 0.6-mile radius from lek locations having an active or unknown status designation as PHMA, regardless of habitat suitability classification.5. Identify all irrigated agricultural lands and designate interiors as Undesignated Habitat (UDH).6. Review and apply site-specific manual conversions of initial management prescription designations based on CPW biologist and stakeholder input.7. Remove identified non-habitat areas from Current Occupied Range (COR). Expand COR in areas beyond the current population boundary where evidence exists to demonstrate occupation by greater sage-grouse.The previous habitat layer generated by CPW, only two habitat designations prescribed by the BLM ARMPA exist for assigning management approaches for conservation of the Colorado greater sage-grouse populations; PHMA and GHMA. PHMA have the highest conservation value based on a combination of habitat and sage-grouse population characteristics and are managed to minimize disturbance activities through No Surface Occupancy (NSO) stipulations and implementing capped disturbance allowances. GHMA represent areas with lower greater sage-grouse occupancy and generally have marginal habitat conditions with fewer management restrictions that provide greater flexibility in land use activities.The initial step to applying PHMA and GHMA habitat management prescriptions involves converting all areas classified as highly suitable habitat in the population’s year-round classified habitat layer to PHMA, while the remaining low habitat suitability areas are converted to GHMA. Secondly, all lek locations with a CPW-prescribed active or unknown status designation are buffered with a 0.6-mile radius and the entirety of the interior of the buffer area is converted to PHMA. Third, the most recent mapped irrigated agricultural lands data was acquired from the Colorado Division of Water Resources for all applicable populations, then the following procedure described below were implemented to apply the Undesignated Habitat prescription to the interior of all irrigated agricultural lands.Undesignated HabitatThrough the course of this study, an additional management prescription was established by AGNC to address concerns regarding habitat management on privately held irrigated agricultural lands.An Undesignated Habitat(UDH) management prescription was developed to address concerns surrounding the management of privately held irrigated agricultural lands. The UDH prescription is applicable to all populations, excluding the Parachute-Piceance-Roan population (due to a lack of irrigated agricultural lands). UDH are areas of seasonally irrigated and harvested hay fields. These areas are utilized seasonally by sage-grouse, primarily in the late summer and fall, near edges where irrigated fields are adjacent and abutting sagebrush habitats. UDH is considered effective habitat, but it is the long-term irrigation and haying practices which have created and maintain this habitat type, and thus the unimpeded irrigation, haying operations and maintenance are not considered to be a negative impact to sage-grouse. While utilization of the edges of irrigated agricultural lands by sage-grouse is known to vary from population to population, studying grouse utilization on a population-specific basis proved problematic as most populations lacked adequate telemetry locations within irrigated agricultural lands to yield results with any level of confidence. For this reason, the North Park population was selected to analyze in detail due to the high number of telemetry points located within irrigated agricultural lands. Approximately 20 percent of all summer-fall telemetry locations for the North Park population occur within irrigated agricultural lands, compared to less than 1 percent to 3 percent utilization demonstrated in the remaining populations.All summer-fall telemetry locations occurring within irrigated agricultural lands were sampled to calculate the distance each point occurred from the edges of irrigated fields. The distances for each location were plotted in a histogram and subsequently reviewed by CPW and AGNC team consultants, revealing a natural break occurring in the data at approximately 83 m. As a result, all interior irrigated agricultural lands lying beyond 83 m from the edge of sagebrush habitats are designated as UDH, while the zone occurring from the 83 meters up to the edges of sagebrush habitats retained the PHMA or GHMA designations as determined by the Random Forest and RSF model results.Final Review.Finally, the resulting revised management prescription layer was manually reviewed by AGNC and by CPW biologists and researchers to identify areas that may warrant conversion from PHMA to GHMA, or vice versa, based on biological considerations, habitat characteristics or the potential for impacting critical future economic development activities.Each population model was slightly different based on the data and nature of the populations. Below is a brief summary of the models by population along with reference to the specific population model documentation that describes each model in much more detail.Northwest Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Northwest population follows the procedures outlined in section5.0 Methodsof the Methods Report. However, as described further below, the telemetry data acquired for analyzing the population were highly clustered. Employing these data in models to predict habitat suitability across a vast, variable landscape resulted in spurious and unreliable predictions in areas further removed from known presence locations. For this reason, we also developed a fourth model for the Northwest population to predict habitat suitability based on known lek locations to enhance predictions in areas lacking available telemetry data (see section 3.4.2 Random Forestbelow). Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NW_Population_Report.pdfParachute-Piceance-Roan (PPR) Population Model: The approach to analyzing greater sage-grouse habitat suitability for the PPR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. RSF models were not developed for the PPR population as part of this study, rather, this project employed RSF models previously developed by CPW in a separate study performed in 2015 to analyze sage-grouse habitat conditions within the PPR area (Walker et al. 2015). CPW’s analysis in their 2015 study implemented the same procedure in developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this project. The 2015 PPR habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW considered two additional scales for analyses, 800 m and 2400 m in their 2015 study, as compared to the scales analyzed in this study. To ensure consistency with CPW’s RSF models, the Random Forest models developed for this study also include these same scales of analyses. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2015 PRR study was defined as occurring between March 14thto 14 days beyond the date on which approximately 90 percent of females finished nesting for that year (Walker et al. 2015). In addition, the summer-fall season was defined as ending on November 30thin CPW’s 2015 study, as compared to November 15thin this study. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the PPR population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2015 report, titled “Mapping and Prioritizing Seasonal Habitats for Greater Sage-Grouse in Northwestern Colorado”, and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_PPR_Population_Report.pdf.North Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NP population follows the procedures outlined in section 5.0 Methods of the Methods Report. RSF models were not developed for the NP population as part of this study. Rather, this project employed RSF models developed by CPW in a separate study performed in 2016 to analyze sage-grouse habitat conditions for the NP range (Rice et al. 2016; Appendix I). CPW’s analysis in their 2016 study implemented similar methods to developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this study. The 2016 North Park habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW developed their seasonal RSF models for the NP population as single-scale models. The scales analyzed were derived from Average Daily Movement (ADM) distances calculated from the available telemetry data for each season. The scales employed for each seasonal analysis were 150.8 m, 83.1 m and 203.6 m for the breeding, summer-fall and winter seasons, respectively. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2016 North Park study was defined as occurring between April 1st to July 15th; the summer-fall season was defined as July 16th to September 1st; the winter season was defined as starting October 1st and ending March 1st. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the NP population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2016 report, titled “Mapping and Prioritizing Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development”and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NP_Population_Report.pdf.Middle Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Middle Park population follows the procedures outlined in Section 5.0of the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MP_Population_Report.pdf.North Eagle-South Routt Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NESR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NESR_Population_Report.pdf.Meeker White River Population Model: The approach to mapping greater sage-grouse habitat suitability for the MWR population differed from the procedures outlined in Section 5.0of the Methods Report. The population contained 97 total marked locations of greater sage-grouse across all seasons, resulting in insufficient data to adequately train habitat models to yield credible and defensible results. For this reason, this project relied on the expertise and knowledge of CPW Wildlife Managers, Moffat County officials and local landowners to manually digitize revised areas of PHMA and GHMA for the MWR population. On October 25th, 2018, CPW and AGNC representatives, as well as AGNC consultants, met with Moffat County officials and local landowners to discuss the current state of the population’s greater sage-grouse and habitat conditions, as well as the ongoing modeling efforts attempted to date. AGNC consultants and CPW informed participants that the population lacked an adequate pool of telemetry locations to perform the same modeling methods implemented on other Colorado populations in assessing habitat conditions and developing revised areas of PHMA and GHMA. For this reason, it was conveyed that the approach for revising management areas in the MWR population would rely on the local officials and landowners, as well as the input provided by the experience and expertise of CPW staff, to identify areas having the highest habitat quality evidence of utilization by greater sage-grouse. The identified areas would subsequently be digitized in a GIS and managed as PHMA, while all remaining areas would be managed according to GHMA guidelines and stipulations.In recent decades, the MWR population has seen considerable areas of lands converted from sagebrush to agricultural uses, thereby reducing the amount of suitable habitats available to the region’s sage-grouse. The conversion of these lands is most pronounced in the north-eastern lobe of the MWR population, as well as the northern portion of the western lobe of the population; the two smaller lobes in the southeast remain unaffected by agricultural operations and are predominately sagebrush habitats with smaller components of mixed-mountain shrubs.The vast majority of the lower elevations occurring in the northern portion of the western lobe of the MWR population are currently utilized in agricultural operations and host little, to no, sagebrush cover. Moving south to the higher elevations in this area of the range, the vegetation transitions to broader expanses of sagebrush intermixed with a moderate component of mixed-mountains shrubs and smaller stands of pinyon-juniper and aspen. While a considerable portion of these lands are currently protected under an assortment of Conservation Easements, these habitat conditions are nevertheless considered marginal in the ability to support greater sage-grouse occupancy. In addition, no sightings of greater sage-grouse have occurred within this region according to recent records or the available telemetry data. Finally, while three historic leks are located within this area, no evidence exists to suggest active lekking occurs within this region. In the prior decade, CPW attempted to establish two leks in this area, but the locations were not utilized and subsequently established as active lekking grounds. For these reasons, all parties agreed the western lobe of the MWR population should be managed in accordance with GHMA guidelines.The two smaller lobes located in the southeast portion of the MWR occupied range exhibit similar vegetation characteristics, though sagebrush cover is more dominant with less intermixed mixed-mountain shrubs, pinyon-juniper and aspen components. While agricultural operations are absent in these areas, there is no evidence to suggest occupancy by greater sage-grouse. There is no record of recent sightings in either area nor any marked locations of sage-grouse in the available telemetry data. Furthermore, there are no records of active, inactive or historic leks that have occurred in either lobe. Consequently, all parties concurred that both areas should be managed in accordance with GHMA guidelines.The northeastern lobe of the MWR population, located directly west of the Town of Meeker, contains the highest quality habitat within the population’s current occupied range. Despite substantial conversion of historic sagebrush lands to agricultural operations in recent decades, evidence suggests continued utilization of the surrounding habitats by greater sage-grouse, though to a far lesser degree as compared to other State populations. All 97 telemetry locations that exist for the MWR population occur in this region, consisting of three individuals collected in 2010. The population’s only active lek occurs in this area, in addition to three historic leks located on the surrounding landscape. In addition, both County officials and local landowners relayed sightings of a single individual within this area in recent years.Based on this evidence, all parties agreed that the northeastern lobe of the MWR population should be managed as both GHMA and PHMA. The northeastern lobe is bisected east to west by County Road 6. Sagebrush habitats north of County Road 6 are of lesser quality and are highly fragmented by agricultural activities, and to a lesser extent, natural gas extraction operations. Accordingly, all areas north of County Road 6 were agreed to be managed consistent with GHMA guidelines. By contrast, lands south of County Road 6 exhibit improved habitat conditions and less fragmentation. Not surprisingly, the majority of available telemetry locations occur within this region, as well as the population’s only known active lek. Therefor, it was collectively decided this region be managed in accordance with PHMA guidelines and stipulation. Furthermore, local officials and landowners indicated sightings of greater sage-grouse in this region beyond the eastern perimeter of the occupied range boundary. For this reason, the MWR boundary was expanded further east to protect additional habitats within the population’s occupied range. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MWR_Population_Report.pdf.Additional BLM and CPW Edits:The final product from Olsson was a vectorized version of the ensembled models, this resulted in a data set with a number of GIS related issues. 1) The were small grid cell sized (25 meters squared) of a particular habitat type, in a sea of another habitat type. This biologically did not make sense and was at a scale smaller than the BLM minimum mapping unit. The BLM GIS shop ran a process to remove these outlier habitat categorizations to get a more uniform layer. 2) The data were not snapped to the boundary of Colorado, the data set was intended to include range for the entire state of Colorado, however there was a sliver of non-habitat along the Wyoming and Utah border that was missing in the final version from Olsson. The CPW GIS Unit fixed this issue and snapped the Habitat layer to boundary of the state of Colorado, using the official state boundary from the State GIS data warehouse. 3) The data set was converted from a raster without the smooth option resulting in a data set with squared off boundaries at every 25 meters. This cause a large number of vertices in the data making the loading of the data set for staff very difficult. To deal with these issues the Simplify tool was used with the retain critical bends method and a simplification tolerance of 25 meters. 4) Finally, since the data was converted from a raster it no longer matched up with the boundary of the GrSG Occupied Range Layer, also there were a few omissions of occupied range that needed to be added to the final habitat layer. To rectify this the habitat layer, minus the linkage polygons was intersected with the GrSG occupied range layer and all the pieces that were not in common were saved. The pieces of the habitat layer that were outside occupied range were deleted and the pieces that were missing to complete the boundary of occupied range were added and classified as the habitat type of the adjacent polygons. These pieces were small, just triangles that caused the raster converted habitat layer to to be squared off versus the smooth occupied range layer boundary. Then small bits of occupied range that had been noticed as an omission were added.
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Description: The data set was created by preparing fine-scale population-specific Species Distribution Models (SDMs) to map revised PHMA and GHMA areas for each of the six greater sage-grouse populations within the current occupied range of Colorado. First, known presence locations of marked greater sage-grouse were used to train Random Forest and Resource Selection Function (RSF) models to estimate seasonal (e.g., breeding, summer-fall and winter) habitat suitability. Secondly, the seasonal model results were classified into high or low habitat suitability categories and subsequently compiled to produce a year-round habitat suitability map. Third, the resulting year-round habitat suitability maps were used to develop revised PHMA and GHMA areas for each population. Finally, the current occupied range for each population were modified to 1) exclude areas identified as unsuitable habitats and 2) include areas outside of current occupied range where evidence of sage-grouse occupancy exists.Data inputs into the RSF and Random Forest Models included presence data from GPS and VHF collar data provided to Olsson from CPW biologists, which was used to refine the models. A combination of vegetative and topographic predictors were employed at multiple scales in assessing the probability of habitat selection for the populations analyzed in this study. The predictors were analyzed at multiple spatial scales, as the literature demonstrates that habitat selection by a species occurs at some scales and not others (Mayor et al. 2009, Acker et al. 2017). The predictors were measured at five scales: 100 meters (m), 400 m, 1000 m, 1600 m, and 3200 m. These were selected to assess a range of local- to landscape-level scales that may influence habitat selection. Furthermore, these scales are comparable to scales assessed in other contemporary studies concerning habitat selection of greater sage-grouse (Doherty et al. 2010; Rice et al. 2016; Walker et al. 2016).Populations were also analyzed to assess utilization of smaller mapped aspen stands as compared to larger continuous forested stands of aspen and/or mixed-conifer. While greater-sage grouse tend to avoid larger forested areas, they will utilize smaller aspen stands (T. Apa pers. comm. 2016-2018). All presence locations for each population were sampled against mapped aspen stands to calculate 1) the rate of selection for aspen stands by the population, and 2) the acreage of each aspen stand utilized. The sampled stand acreages were subsequently graphed and examined to identify natural breaks in the data. Stands with acreages less than the natural break value and not directly adjacent to other forested stands were classified and analyzed separately as isolated aspen polygons which were included as potentially suitable habitat; the remaining aspen stands were classified as forested and integrated with mixed-conifer forests, which were assumed to be non-suitable habitat.Finally, the distance to forested areas was measured as a vegetative predictor using the Euclidean Distance tool in ArcGIS 10.4, excluding all isolated aspen patches and mixed-conifer patches less than 0.5 acres (and see previous paragraph).Vegetation types were derived from the Colorado Vegetation Classification Project (CVCP), a 25 m resolution raster dataset developed by CPW, which mapped landcover conditions through the periods from 1993to 1997. In addition, vegetation types were also derived from the 2001 LANDFIRE Existing Vegetation Type (EVT) layer for areas adjacent to the study area in Utah and Wyoming to provide complete and continuous vegetation cover for populations abutting the state boundary. The LANDFIRE EVT is a 30 m resolution raster dataset developed by the United States Geological Survey (USGS) mapping landcover conditions from 2001 (LANDFIRE 2001). Vegetative types were classified into biologically relevant classes and subsequently measured as percent-proportion by dividing the number of cells for the particular class by the total number of cells within the radii of the five defined scales using ArcGIS 10.4. The assigned classes of vegetative types varied by population and are detailed in the population-specific reports provided to BLM.Topographic predictors were derived from the 10 m resolution National Elevation Dataset (NED) Digital Elevation Model (DEM) developed and maintained by the USGS. Key topographic predictors include aspect, Compound Topographic Index (CTI), elevation, percent slope, slope position and surface roughness. Aspect and percent slope were calculated in ArcGIS 10.4. CTI, slope position and surface roughness were calculated using the Geomorphology and Gradient Metrics toolbox (Evans et al. 2014). In addition, aspect was subsequently transformed using the TRASP method in the Geomorphology and Gradient Metrics toolbox. To develop the multi-scale predictors, CTI and percent slope were measured as the mean of all values within the radii of the five defined scales; slope position and surface roughness were calculated using the radii of the five defined scales.The following summary of the step-wise procedure was developed to convert the Random Forest and RSF continuous surface model results into revised Habitat Management Area Prescriptions. Details of these methods follow this list:1. Classify all seasonal Random Forest and RSF model results into high and low habitat suitability layers.2. Ensemble all Random Forest and RSF classified seasonal layers to form a single year-round annual habitat layer designating locations as either high or low habitat suitability.3. Convert all highly suitable locations to Priority Habitat Management Areas (PHMA) and all locations designated as low habitat suitability to General Habitat Management Areas (GHMA).4. Classify all areas within a 0.6-mile radius from lek locations having an active or unknown status designation as PHMA, regardless of habitat suitability classification.5. Identify all irrigated agricultural lands and designate interiors as Undesignated Habitat (UDH).6. Review and apply site-specific manual conversions of initial management prescription designations based on CPW biologist and stakeholder input.7. Remove identified non-habitat areas from Current Occupied Range (COR). Expand COR in areas beyond the current population boundary where evidence exists to demonstrate occupation by greater sage-grouse.The previous habitat layer generated by CPW, only two habitat designations prescribed by the BLM ARMPA exist for assigning management approaches for conservation of the Colorado greater sage-grouse populations; PHMA and GHMA. PHMA have the highest conservation value based on a combination of habitat and sage-grouse population characteristics and are managed to minimize disturbance activities through No Surface Occupancy (NSO) stipulations and implementing capped disturbance allowances. GHMA represent areas with lower greater sage-grouse occupancy and generally have marginal habitat conditions with fewer management restrictions that provide greater flexibility in land use activities.The initial step to applying PHMA and GHMA habitat management prescriptions involves converting all areas classified as highly suitable habitat in the population’s year-round classified habitat layer to PHMA, while the remaining low habitat suitability areas are converted to GHMA. Secondly, all lek locations with a CPW-prescribed active or unknown status designation are buffered with a 0.6-mile radius and the entirety of the interior of the buffer area is converted to PHMA. Third, the most recent mapped irrigated agricultural lands data was acquired from the Colorado Division of Water Resources for all applicable populations, then the following procedure described below were implemented to apply the Undesignated Habitat prescription to the interior of all irrigated agricultural lands.Undesignated HabitatThrough the course of this study, an additional management prescription was established by AGNC to address concerns regarding habitat management on privately held irrigated agricultural lands.An Undesignated Habitat(UDH) management prescription was developed to address concerns surrounding the management of privately held irrigated agricultural lands. The UDH prescription is applicable to all populations, excluding the Parachute-Piceance-Roan population (due to a lack of irrigated agricultural lands). UDH are areas of seasonally irrigated and harvested hay fields. These areas are utilized seasonally by sage-grouse, primarily in the late summer and fall, near edges where irrigated fields are adjacent and abutting sagebrush habitats. UDH is considered effective habitat, but it is the long-term irrigation and haying practices which have created and maintain this habitat type, and thus the unimpeded irrigation, haying operations and maintenance are not considered to be a negative impact to sage-grouse. While utilization of the edges of irrigated agricultural lands by sage-grouse is known to vary from population to population, studying grouse utilization on a population-specific basis proved problematic as most populations lacked adequate telemetry locations within irrigated agricultural lands to yield results with any level of confidence. For this reason, the North Park population was selected to analyze in detail due to the high number of telemetry points located within irrigated agricultural lands. Approximately 20 percent of all summer-fall telemetry locations for the North Park population occur within irrigated agricultural lands, compared to less than 1 percent to 3 percent utilization demonstrated in the remaining populations.All summer-fall telemetry locations occurring within irrigated agricultural lands were sampled to calculate the distance each point occurred from the edges of irrigated fields. The distances for each location were plotted in a histogram and subsequently reviewed by CPW and AGNC team consultants, revealing a natural break occurring in the data at approximately 83 m. As a result, all interior irrigated agricultural lands lying beyond 83 m from the edge of sagebrush habitats are designated as UDH, while the zone occurring from the 83 meters up to the edges of sagebrush habitats retained the PHMA or GHMA designations as determined by the Random Forest and RSF model results.Final Review.Finally, the resulting revised management prescription layer was manually reviewed by AGNC and by CPW biologists and researchers to identify areas that may warrant conversion from PHMA to GHMA, or vice versa, based on biological considerations, habitat characteristics or the potential for impacting critical future economic development activities.Each population model was slightly different based on the data and nature of the populations. Below is a brief summary of the models by population along with reference to the specific population model documentation that describes each model in much more detail.Northwest Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Northwest population follows the procedures outlined in section5.0 Methodsof the Methods Report. However, as described further below, the telemetry data acquired for analyzing the population were highly clustered. Employing these data in models to predict habitat suitability across a vast, variable landscape resulted in spurious and unreliable predictions in areas further removed from known presence locations. For this reason, we also developed a fourth model for the Northwest population to predict habitat suitability based on known lek locations to enhance predictions in areas lacking available telemetry data (see section 3.4.2 Random Forestbelow). Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NW_Population_Report.pdfParachute-Piceance-Roan (PPR) Population Model: The approach to analyzing greater sage-grouse habitat suitability for the PPR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. RSF models were not developed for the PPR population as part of this study, rather, this project employed RSF models previously developed by CPW in a separate study performed in 2015 to analyze sage-grouse habitat conditions within the PPR area (Walker et al. 2015). CPW’s analysis in their 2015 study implemented the same procedure in developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this project. The 2015 PPR habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW considered two additional scales for analyses, 800 m and 2400 m in their 2015 study, as compared to the scales analyzed in this study. To ensure consistency with CPW’s RSF models, the Random Forest models developed for this study also include these same scales of analyses. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2015 PRR study was defined as occurring between March 14thto 14 days beyond the date on which approximately 90 percent of females finished nesting for that year (Walker et al. 2015). In addition, the summer-fall season was defined as ending on November 30thin CPW’s 2015 study, as compared to November 15thin this study. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the PPR population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2015 report, titled “Mapping and Prioritizing Seasonal Habitats for Greater Sage-Grouse in Northwestern Colorado”, and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_PPR_Population_Report.pdf.North Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NP population follows the procedures outlined in section 5.0 Methods of the Methods Report. RSF models were not developed for the NP population as part of this study. Rather, this project employed RSF models developed by CPW in a separate study performed in 2016 to analyze sage-grouse habitat conditions for the NP range (Rice et al. 2016; Appendix I). CPW’s analysis in their 2016 study implemented similar methods to developing RSF models to assess habitat conditions and were therefore considered appropriate for inclusion in this study. The 2016 North Park habitat study performed by CPW differed in two respects concerning 1) scales of analyses, and 2) seasonal cut-off dates. First, CPW developed their seasonal RSF models for the NP population as single-scale models. The scales analyzed were derived from Average Daily Movement (ADM) distances calculated from the available telemetry data for each season. The scales employed for each seasonal analysis were 150.8 m, 83.1 m and 203.6 m for the breeding, summer-fall and winter seasons, respectively. Secondly, CPW utilized marginally different cut-off dates to define seasonal date ranges. The breeding season in the 2016 North Park study was defined as occurring between April 1st to July 15th; the summer-fall season was defined as July 16th to September 1st; the winter season was defined as starting October 1st and ending March 1st. The telemetry data employed in Random Forest models analyzing seasonal habitat conditions in the NP population for this study utilize the same seasonal date ranges as defined above to ensure consistency between Random Forest and RSF model analyses. CPW’s complete 2016 report, titled “Mapping and Prioritizing Seasonal Habitat Use by Greater Sage-Grouse (Centrocercus urophasianus) on a Landscape with Low Density Oil and Gas Development”and supplemental information are included as Appendix I of this report. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NP_Population_Report.pdf.Middle Park Population Model: The approach to analyzing greater sage-grouse habitat suitability for the Middle Park population follows the procedures outlined in Section 5.0of the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MP_Population_Report.pdf.North Eagle-South Routt Population Model: The approach to analyzing greater sage-grouse habitat suitability for the NESR population follows the procedures outlined in section 5.0 Methodsof the Methods Report. The breeding season was defined as March 15th to June 15th, the summer-fall season was defined as June 16th to November 15th, and the winter season was defined as November 16th to March 14th. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_NESR_Population_Report.pdf.Meeker White River Population Model: The approach to mapping greater sage-grouse habitat suitability for the MWR population differed from the procedures outlined in Section 5.0of the Methods Report. The population contained 97 total marked locations of greater sage-grouse across all seasons, resulting in insufficient data to adequately train habitat models to yield credible and defensible results. For this reason, this project relied on the expertise and knowledge of CPW Wildlife Managers, Moffat County officials and local landowners to manually digitize revised areas of PHMA and GHMA for the MWR population. On October 25th, 2018, CPW and AGNC representatives, as well as AGNC consultants, met with Moffat County officials and local landowners to discuss the current state of the population’s greater sage-grouse and habitat conditions, as well as the ongoing modeling efforts attempted to date. AGNC consultants and CPW informed participants that the population lacked an adequate pool of telemetry locations to perform the same modeling methods implemented on other Colorado populations in assessing habitat conditions and developing revised areas of PHMA and GHMA. For this reason, it was conveyed that the approach for revising management areas in the MWR population would rely on the local officials and landowners, as well as the input provided by the experience and expertise of CPW staff, to identify areas having the highest habitat quality evidence of utilization by greater sage-grouse. The identified areas would subsequently be digitized in a GIS and managed as PHMA, while all remaining areas would be managed according to GHMA guidelines and stipulations.In recent decades, the MWR population has seen considerable areas of lands converted from sagebrush to agricultural uses, thereby reducing the amount of suitable habitats available to the region’s sage-grouse. The conversion of these lands is most pronounced in the north-eastern lobe of the MWR population, as well as the northern portion of the western lobe of the population; the two smaller lobes in the southeast remain unaffected by agricultural operations and are predominately sagebrush habitats with smaller components of mixed-mountain shrubs.The vast majority of the lower elevations occurring in the northern portion of the western lobe of the MWR population are currently utilized in agricultural operations and host little, to no, sagebrush cover. Moving south to the higher elevations in this area of the range, the vegetation transitions to broader expanses of sagebrush intermixed with a moderate component of mixed-mountains shrubs and smaller stands of pinyon-juniper and aspen. While a considerable portion of these lands are currently protected under an assortment of Conservation Easements, these habitat conditions are nevertheless considered marginal in the ability to support greater sage-grouse occupancy. In addition, no sightings of greater sage-grouse have occurred within this region according to recent records or the available telemetry data. Finally, while three historic leks are located within this area, no evidence exists to suggest active lekking occurs within this region. In the prior decade, CPW attempted to establish two leks in this area, but the locations were not utilized and subsequently established as active lekking grounds. For these reasons, all parties agreed the western lobe of the MWR population should be managed in accordance with GHMA guidelines.The two smaller lobes located in the southeast portion of the MWR occupied range exhibit similar vegetation characteristics, though sagebrush cover is more dominant with less intermixed mixed-mountain shrubs, pinyon-juniper and aspen components. While agricultural operations are absent in these areas, there is no evidence to suggest occupancy by greater sage-grouse. There is no record of recent sightings in either area nor any marked locations of sage-grouse in the available telemetry data. Furthermore, there are no records of active, inactive or historic leks that have occurred in either lobe. Consequently, all parties concurred that both areas should be managed in accordance with GHMA guidelines.The northeastern lobe of the MWR population, located directly west of the Town of Meeker, contains the highest quality habitat within the population’s current occupied range. Despite substantial conversion of historic sagebrush lands to agricultural operations in recent decades, evidence suggests continued utilization of the surrounding habitats by greater sage-grouse, though to a far lesser degree as compared to other State populations. All 97 telemetry locations that exist for the MWR population occur in this region, consisting of three individuals collected in 2010. The population’s only active lek occurs in this area, in addition to three historic leks located on the surrounding landscape. In addition, both County officials and local landowners relayed sightings of a single individual within this area in recent years.Based on this evidence, all parties agreed that the northeastern lobe of the MWR population should be managed as both GHMA and PHMA. The northeastern lobe is bisected east to west by County Road 6. Sagebrush habitats north of County Road 6 are of lesser quality and are highly fragmented by agricultural activities, and to a lesser extent, natural gas extraction operations. Accordingly, all areas north of County Road 6 were agreed to be managed consistent with GHMA guidelines. By contrast, lands south of County Road 6 exhibit improved habitat conditions and less fragmentation. Not surprisingly, the majority of available telemetry locations occur within this region, as well as the population’s only known active lek. Therefor, it was collectively decided this region be managed in accordance with PHMA guidelines and stipulation. Furthermore, local officials and landowners indicated sightings of greater sage-grouse in this region beyond the eastern perimeter of the occupied range boundary. For this reason, the MWR boundary was expanded further east to protect additional habitats within the population’s occupied range. Detail documentation for this model is in the Olsson Report: AGNC_GRSG_MWR_Population_Report.pdf.Additional BLM and CPW Edits:The final product from Olsson was a vectorized version of the ensembled models, this resulted in a data set with a number of GIS related issues. 1) The were small grid cell sized (25 meters squared) of a particular habitat type, in a sea of another habitat type. This biologically did not make sense and was at a scale smaller than the BLM minimum mapping unit. The BLM GIS shop ran a process to remove these outlier habitat categorizations to get a more uniform layer. 2) The data were not snapped to the boundary of Colorado, the data set was intended to include range for the entire state of Colorado, however there was a sliver of non-habitat along the Wyoming and Utah border that was missing in the final version from Olsson. The CPW GIS Unit fixed this issue and snapped the Habitat layer to boundary of the state of Colorado, using the official state boundary from the State GIS data warehouse. 3) The data set was converted from a raster without the smooth option resulting in a data set with squared off boundaries at every 25 meters. This cause a large number of vertices in the data making the loading of the data set for staff very difficult. To deal with these issues the Simplify tool was used with the retain critical bends method and a simplification tolerance of 25 meters. 4) Finally, since the data was converted from a raster it no longer matched up with the boundary of the GrSG Occupied Range Layer, also there were a few omissions of occupied range that needed to be added to the final habitat layer. To rectify this the habitat layer, minus the linkage polygons was intersected with the GrSG occupied range layer and all the pieces that were not in common were saved. The pieces of the habitat layer that were outside occupied range were deleted and the pieces that were missing to complete the boundary of occupied range were added and classified as the habitat type of the adjacent polygons. These pieces were small, just triangles that caused the raster converted habitat layer to to be squared off versus the smooth occupied range layer boundary. Then small bits of occupied range that had been noticed as an omission were added.
Copyright Text: Olsson Consultants
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Suite 200
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olsson.com
Name: Lesser Prairie Chicken Connectivity Area HPHE1
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: The Lesser Prairie Chicken Priority Areas are mapped polygons designating high priority habitat, both focal areas (CHAT 1) and connectivity areas (CHAT 2) as defined in the Lesser Prairie Chicken Rangewide Plan. These were mapped with the Colorado Parks and Wildlife (CPW) Bird Conservation Coordinator and the Area 12 Wildlife Biologist (only area in the state that the bird is present). Current lek location data, soil type, vegetation and CPR data were used to aide in the mapping effort.As a component of the 5-Year Review of the Range-wide Conservation Plan (Van Pelt et al. 2013), the Interstate Working Group (IWG) evaluated and re-mapped (as necessary) the Estimated Occupied Range (EOR) along with the Focal Areas (CHAT 1) and Connectivity Zones (CHAT 2) across lesser prairie-chicken (LPC) range in Colorado, Kansas, Oklahoma, Texas, and New Mexico. The IWG used the criteria below to adjust the EOR and Focal Area and Connectivity Zone delineations. The proposed mapping revisions are based on best available science and local knowledge. The IWG presented the initial proposed mapping changes to the LPC State Implementation Teams for review in late 2019 and early 2020. Recommended changes to the range-wide EOR boundary will be included in the 10-year review of the RWP. The current 5-year Review will only recommend changes to Focal Areas (CHAT 1) and Connectivity Areas (CHAT 2) such that there is no change to the EOR+10 in the RWP (Van Pelt et. al 2013) and associated area of coverage for the LPC Candidate Conservation Agreement with Assurances (CCAA) (USFWS 2014). However, individual states may decide to use the updated EOR mapping for land-use recommendations and targeting habitat conservation and restoration. Colorado Parks and Wildlife (CPW) will use current biologically-based mapping for LPC conservation in Colorado. IWG Criteria for Changes to the Focal Area Zones (CHAT 1) and Connectivity Zones (CHAT 2):Additions were based on:1) Newly documented leks2) Newly created or restored habitat conditions3) Restoration opportunitiesDeletions were based on:1) New and cumulative anthropogenic developmentsColorado Parks and Wildlife revised LPC mapping was completed by Liza Rossi (Bird Conservation Coordinator), Jonathan Reitz (Lamar Terrestrial Biologist), and Michelle Flenner (GIS Specialist) in July 2019. The proposed changes were presented at the Colorado LPC State Implementation Team Meeting in Lamar on November 14, 2019. The group there was supportive of the changes and thought we should reflect our biological understanding of LPC distribution rather than being confined by the 2013 RWP covered area. CPW is proposing these changes to reflect current distribution of LPC in Colorado. CPW updates Species Activity Mapping (SAM) every four years across Colorado. SAM mapping will be updated for the CPW SE Region in 2020 and the updated Colorado EOR as well as proposed CHAT 1 and CHAT 2 will be incorporated in CPW mapping. The proposed changes were reviewed and agreed to by CPW Area 12 personnel at an Area Meeting on February 5, 2020. Although CPW will move forward with this mapping for Colorado conservation efforts, formal changes to the covered area of the RWP (2013 EOR +10, Van Pelt et al. 2013) or the Range-wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (CCAA, USFWS 2014) will be evaluated through the 10-Year Review of the RWP or an update to the CCAA). Changes to the CHAT mapping will be presented as part of the 5-year Review to the Lesser Prairie-Chicken Initiative Council. USFWS. 2014. Range-Wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in Colorado Kansas, New Mexico, Oklahoma, and Texas. 78 FR 76639.Van Pelt, W.E., S. Kyle, J. Pitman, D. Klute, G. Beauprez, D. Schoeling, A. Janus, J. Haufler. 2013. The Lesser Prairie-Chicken Range-wide Conservation Plan. Western Association of Fish and Wildlife Agencies. Cheyenne, Wyoming. Pp.367.Interstate Working Group Members include: Kent Fricke, chair (Kansas Department of Wildlife, Parks and Tourism), Liza Rossi (Colorado Parks and Wildlife), Brett Cooper (Oklahoma Department of Wildlife Conservation), Grant Beauprez (New Mexico Department of Game and Fish), and Russell Martin (Texas Parks and Wildlife Department).
Name: Lesser Prairie Chicken Estimated Occupied Range HPHE1
Display Field: Activity_C
Type: Feature Layer
Geometry Type: esriGeometryPolygon
Description: The Colorado Lesser Prairie Chicken EOR isan area which encompasses all known seasonal activities within the observed range of the lesser prairie chicken. The range was mapped and edited by the Colorado Parks and Wildlife (CPW) Bird Conservation Coordinator, CPW Area 12 Wildlife Biologist (where the bird range is located) and the CPW GIS Unit. The purpose of this layer is to indicate suitable range within Colorado for the Lesser Prairie Chicken based on suitable habitat present. Data used to help map the range include area soil data, CRP property and location of known Lesser Prairie Chicken leks.The range was separated into two Ecoregions Sandsage and Shortgrass to indicate the habitat type the range falls in.As a component of the 5-Year Review of the Range-wide Conservation Plan (Van Pelt et al. 2013), the Interstate Working Group (IWG) evaluated and re-mapped (as necessary) the Estimated Occupied Range (EOR) along with the Focal Areas (CHAT 1) and Connectivity Zones (CHAT 2) across lesser prairie-chicken (LPC) range in Colorado, Kansas, Oklahoma, Texas, and New Mexico. The IWG used the criteria below to adjust the EOR and Focal Area and Connectivity Zone delineations. The proposed mapping revisions are based on best available science and local knowledge. The IWG presented the initial proposed mapping changes to the LPC State Implementation Teams for review in late 2019 and early 2020. Recommended changes to the range-wide EOR boundary will be included in the 10-year review of the RWP. The current 5-year Review will only recommend changes to Focal Areas (CHAT 1) and Connectivity Areas (CHAT 2) such that there is no change to the EOR+10 in the RWP (Van Pelt et. al 2013) and associated area of coverage for the LPC Candidate Conservation Agreement with Assurances (CCAA) (USFWS 2014). However, individual states may decide to use the updated EOR mapping for land-use recommendations and targeting habitat conservation and restoration. Colorado Parks and Wildlife (CPW) will use current biologically-based mapping for LPC conservation in Colorado. Colorado Parks and Wildlife revised LPC mapping was completed by Liza Rossi (Bird Conservation Coordinator), Jonathan Reitz (Lamar Terrestrial Biologist), and Michelle Flenner (GIS Specialist) in July 2019. CPW made adjustments to the EOR as well as Focal Areas (CHAT 1) and Connectivity Zones (CHAT 2). Mapping adjustments were based on the information below.The EOR was expanded to include the majority of documented leks, including areas in Cheyenne County not included in 2013. The northern portion of the proposed EOR would connect to Kansas and be included in the Shortgrass/CRP Mosaic Ecoregion rather than the Sand Sagebrush Ecoregion. Jonathan Reitz increased CPW lek searching effort in spring 2019 in order to help inform CHAT (Focal Area and Connectivity Zones) mapping and EOR review and revisions. He increased efforts in anticipation that the IWG would be reviewing and proposing changes to the CHAT layers and potentially EOR as part of the 5-year RWP review. During 2019 intensified lek searches, Jonathan identified multiple new leks in Cheyenne County. However, a lek in eastern and northern Cheyenne County near the Kansas state line, but outside mapped EOR, has been documented since 2015. For proposed changes in Cheyenne County, we used lek data to include areas outside of the current EOR, but which now clearly have lesser prairie-chickens. LPC leks (many of which are mixed LPC and greater prairie-chicken leks) in this area have also been located by consultants surveying for wind companies. For the proposed changes in Baca County, it is important to note that we used locations from translocated LPC, which have changed our understanding of LPC habitat use in southeastern Colorado. The translocated LPC are using CRP grasslands and portions of shortgrass and mid-grass prairie that were not originally included in the sand sagebrush prairie CHAT mapping. 2013 CHAT mapping focused largely on sandy soils and excluded many of the soils associated with shortgrass and mid-grass areas. We are proposing to reduce the EOR in Prowers County based on local knowledge of LPC use in the area. Although there is a single historic lek identified in this area, this lek was only documented during a single year and had only three birds on it.The proposed changes were presented at the Colorado LPC State Implementation Team Meeting in Lamar on November 14, 2019. The group there was supportive of the changes and thought we should reflect our biological understanding of LPC distribution rather than being confined by the 2013 RWP covered area. CPW is proposing these changes to reflect current distribution of LPC in Colorado. CPW updates Species Activity Mapping (SAM) every four years across Colorado. SAM mapping will be updated for the CPW SE Region in 2020 and the updated Colorado EOR as well as proposed CHAT 1 and CHAT 2 will be incorporated in CPW mapping. The proposed changes were reviewed and agreed to by CPW Area 12 personnel at an Area Meeting on February 5, 2020. Although CPW will move forward with this mapping for Colorado conservation efforts, formal changes to the covered area of the RWP (2013 EOR +10, Van Pelt et al. 2013) or the Range-wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (CCAA, USFWS 2014) will be evaluated through the 10-Year Review of the RWP or an update to the CCAA). Changes to the CHAT mapping will be presented as part of the 5-year Review to the Lesser Prairie-Chicken Initiative Council. USFWS. 2014. Range-Wide Oil and Gas Candidate Conservation Agreement with Assurances for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in Colorado Kansas, New Mexico, Oklahoma, and Texas. 78 FR 76639.Van Pelt, W.E., S. Kyle, J. Pitman, D. Klute, G. Beauprez, D. Schoeling, A. Janus, J. Haufler. 2013. The Lesser Prairie-Chicken Range-wide Conservation Plan. Western Association of Fish and Wildlife Agencies. Cheyenne, Wyoming. Pp.367.Interstate Working Group Members include: Kent Fricke, chair (Kansas Department of Wildlife, Parks and Tourism), Liza Rossi (Colorado Parks and Wildlife), Brett Cooper (Oklahoma Department of Wildlife Conservation), Grant Beauprez (New Mexico Department of Game and Fish), and Russell Martin (Texas Parks and Wildlife Department).
Copyright Text: Colorado Parks and Wildlife Biologists