https://cpw.cvlcollections.org/files/original/df7aa12fafa6ca63b360bff47fcd1ba9.pdf 580ca9936db9d919b08af2d1af3a0ff9 PDF Text Text Colorado Division of Parks and Wildlife September 2014-September 2015 WILDLIFE RESEARCH REPORT State of: Cost Center: Work Package: Task No.: Colorado 3420 0663 N/A Federal Aid Project No. N/A : : : : Division of Parks and Wildlife Avian Research Terrestrial Species Conservation Development of landscape scale resource selection models using interpolated layers from micro-scale vegetation measurements in North Park, Colorado Period Covered: September 1, 2014 – August 31, 2015 Author: M. Rice All information in this report is preliminary and subject to further evaluation. Information MAY NOT BE PUBLISHED OR QUOTED without permission of the author. Manipulation of these data beyond that contained in this report is discouraged. EXTENDED ABSTRACT State agencies have long used micro-scale vegetation measurements to assess relationships between species and how they chose their habitat. Often species select small scale habitat based on vegetation structure, the height and density of certain vegetation, and the availability of forage species. With the onset of remote sensing and the ability to predict species’ distributions based on relatively easy and inexpensive methods, micro-scale measurements have had reduced value when describing a species’ habitat selection. There is also the problem of how to translate micro-scale measurements at a small scale to landscape level resource selection models. There is a long history of using interpolation methods to predict vegetation characteristics across space, but these predictive surfaces have rarely been applied to spatial models of species habitat. We tested the ability of micro-scale vegetation measurements predictive layers to be incorporated into landscape scale models related to the North Park population of greater sage-grouse in Colorado. The greater sage-grouse (Centrocercus urophasianus) (GRSG) is a species of conservation concern due to historical population declines and range contraction. For species that use large areas including GRSG, there is value in evaluating habitat selection at multiple spatial scales as species may respond differently at larger or smaller scales. Finer scale models based on detailed species and landscape information have shown great potential to detect crucial habitat not obvious at broader scales. How we incorporate this information may be critical to how we manage GRSG on the ground. As part of a radio-telemetry study conducted in 2010-2012, vegetation measurements were taken at all located nest sites as well as a sample of brood, broodless female, and winter sites. We created a grid layer of 1-km2 cells across North park (figure 1) and selected individual grid cells based on a spatially balanced random sample in which we would search for GRSG use or non-use. The same vegetation measurements were taken at approximately the same number of non-use sites as use sites. At all vegetation measurement sites, two 20-m transects were placed in the cardinal directions with the 10-m mark of each transect intersecting at the nest bowl or UTM location for other use and non-use points. Canopy cover, shrub intercept species, percent of forbs, percent grass cover, percent soil cover, and percent litter cover, height of grass, forb plant height, and height of nearest sagebrush were measured at �each location. At winter locations snow depth and height of nearest sagebrush above snow were also measured. These original vegetation measurements will be used to create a kriging interpolation for canopy cover, sagebrush height, grass height, forb height, and percent cover across the North Park study area. In the summer of 2015, we selected additional points to sample within the same 1-km2 grid created for the original project. These points would then be used to validate the original vegetation measurements by taking the same vegetation measurements. These locations were not based on any GRSG locations or nests. Figure 2 displays the locations of the original vegetation measurements and the validation locations along with the private and public land access across North Park. We will compare the original vegetation measurements to remote sensing layers to determine if there is agreement between the two scales. In addition, we will validate the interpolated spatial layers using the validation vegetation measurements. If both of these comparisons prove to be in agreement and the error associated with the interpolation layers is low, we will re-do our resource selection seasonal models including these additional, more detailed vegetation variables to determine a) if they improve the habitat selection models based on lower AIC values and b) refine the amount of area considered high priority habitat within North Park. All models will follow the same methods as defined in the original North Park assessment. All vegetation measurements have been measured including 232 original vegetation locations (2010-2012) and 169 validation locations (2015). The interpolation models and possible resource selection models are to be completed by the end of 2016 along with a final report and publication regardless of the success or lack thereof using interpolation models. �Figure 1: North Park study area and 1-km2 grid cells used to randomly select locations for vegetation measurements both in the original dataset and the validation dataset. �Figure 2: Sample locations in 2010-2012 and in 2015 in North Park used for interpolation or validation of interpolation layers to use in landscape resource selection models. � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Reports Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Development of landscape scale resource selection models using interpolated layers from micro-scale vegetation measurements in North Park, Colorado Description An account of the resource State agencies have long used micro-scale vegetation measurements to assess relationships between species and how they chose their habitat. Often species select small scale habitat based on vegetation structure, the height and density of certain vegetation, and the availability of forage species. With the onset of remote sensing and the ability to predict species’ distributions based on relatively easy and inexpensive methods, micro-scale measurements have had reduced value when describing a species’ habitat selection. There is also the problem of how to translate micro-scale measurements at a small scale to landscape level resource selection models. There is a long history of using interpolation methods to predict vegetation characteristics across space, but these predictive surfaces have rarely been applied to spatial models of species habitat. Creator An entity primarily responsible for making the resource Rice, Mindy B. Subject The topic of the resource Wildlife management Wildlife habitat improvement Extent The size or duration of the resource. 4 pages Date Created Date of creation of the resource. 2015 Rights Information about rights held in and over the resource <a href="http://rightsstatements.org/vocab/NoC-NC/1.0/">No Copyright - Non-Commercial Use Only</a> Type The nature or genre of the resource Text Format The file format, physical medium, or dimensions of the resource application/pdf Language A language of the resource English Is Part Of A related resource in which the described resource is physically or logically included. Cost Center 3420 Avian Research. Work Package 0663 Terrestrial species conservation