Arizona Game and Fish Department Lucas Olson Jeff Gagnon Scott Sprague 20220407 Version 2.0 vector digital data https://doi.org/10.5066/P9TKA3L8 Matthew Kauffman Blake Lowrey Jeffrey Beck Jodi Berg Scott Bergen Joel Berger James Cain Sarah Dewey Jennifer Diamond Orrin Duvuvuei Julien Fattebert Jeff Gagnon Julie Garcia Evan Greenspan Embere Hall Glenn Harper Stan Harter Kent Hersey Pat Hnilicka Mark Hurley Lee Knox Art Lawson Eric Maichak James Meacham Jerod Merkle Arthur Middleton Daniel Olson Lucas Olson Craig Reddell Benjamin Robb Gabe Rozman Hall Sawyer Cody Schroeder Brandon Scurlock Jeff Short Scott Sprague Alethea Steingisser Nicole Tatman 2022 publication Mule deer (Odocoileus hemionus) of the Kaibab Plateau in Arizona had a population estimate of 10,200 individuals in 2019. The herd is relatively isolated; limited in range to the east, south, and west sides by the Grand Canyon. Annually the Kaibab herd migrates an average of 27 mi (43 km) between summer and winter range. Winter range is along the west, east, and northern extents of the plateau; consisting of pinyon-juniper woodlands mixed with sagebrush, cliffrose, bitterbrush, and various grasses. Some of the Kaibab herd winters in Utah, sharing winter range with Utah’s Paunsaugunt Plateau herd. During migration mule deer pass through mid-elevation transitional range containing Gambel oak, pinyon pine, and Utah juniper. Summer range is dominated by a mix of ponderosa pine, spruce, fir, and aspen, interspersed with open meadows. There are currently few impediments to mule deer migration on the Kaibab Plateau. These data provide the location of migration routes for Mule Deer from the Kaibab Herd in Arizona. They were developed using 123 migration sequences collected from a sample size of 48 adult mule deer comprising GPS locations collected every 0.5-7 hours. Migration is widespread across taxonomic groups and increasingly recognized as fundamental to maintaining abundant wildlife populations and communities. Many ungulate herds migrate across the western United States to access food and avoid harsh environmental conditions. With the advent of global positioning system (GPS) collars, researchers can describe and map the year-round movements of ungulates at both large and small spatial scales. The migrations can traverse landscapes that are a mix of different jurisdictional ownership and management. Today, the landscapes that migrating herds traverse are increasingly threatened by fencing, high-traffic roads, oil and gas development, and other types of permanent development. Over the last decade, a model of science-based conservation has emerged in which migration corridors, stopovers, and winter ranges can be mapped in detail, thereby allowing threats and conservation opportunities to be identified and remedied. In 2018, the U.S. Geological Survey (USGS) assembled a Corridor Mapping Team (CMT) to work collaboratively with western states to map migrations of mule deer, elk, and pronghorn. Led by the USGS Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of federal scientists, university researchers, and biologists and analysts from participating state and tribal agencies. The first set of maps described a total of 42 migrations across five western states and was published in 2020 as the first volume of this report series. This second volume describes an additional 65 migrations mapped within nine western states and select tribal lands. As the American West continues to grow, this report series and the associated map files released on USGS’s ScienceBase will allow for migration maps to be used for conservation planning by a wide array of state and federal stakeholders to reduce barriers to migration caused by fences, roads, and other development. 20120101 20210618 observed Complete As needed Kaibab Plateau -112.6805 -111.9382 37.0859 36.0780 ISO 19115 Topic Category environment economy USGS Thesaurus migration migratory species animal behavior migration (organisms) USGS Metadata Identifier USGS:620e4ac4d34e6c7e83baa36c Common geographic areas Arizona United States Kaibab Plateau None Odocoileus hemionus Kingdom Animalia animals Subkingdom Bilateria Infrakingdom Deuterostomia Phylum Chordata chordates Subphylum Vertebrata vertebrates Infraphylum Gnathostomata Superclass Tetrapoda Class Mammalia mammals Subclass Theria Infraclass Eutheria Order Artiodactyla artiodactyls cloven-hoofed ungulates even-toed ungulates Family Cervidae cervids caribou deer moose wapiti Subfamily Capreolinae Genus Odocoileus mule deer white-tailed deer Species Odocoileus hemionus mule deer Mule Deer TSN: 180698 None. Please see 'Distribution Info' for details. The Arizona Game and Fish Department will retain ownership of the data provided and must approve of any additional use before other analyses, research, or publications are initiated. The burden for determining fitness for use lies entirely with the user. For purposes of publication or dissemination, citations, or credit should be given to the Arizona Game and Fish Department. Jeff Gagnon Arizona Game and Fish Department Wildlife Specialist Regional Supervisor mailing

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Phoenix AZ 85086 United States 19288148925 jgagnon@azgfd.gov Kirby D. Bristow Larisa E. Harding Richard W. Lucas Thomas C. McCall 2020 publication Animal Production Science vol. 60, issue 10 n/a CSIRO Publishing ppg. 1292 https://doi.org/10.1071/AN19373 Carrel, W.K. Ockenfels, R.A. Sweinsburg, R.E. 1999 publication Arizona Game and Fish Department, Phoenix, AZ. Russo, J.P. 1964 publication Arizona Game and Fish Department, Phoenix, Arizona No formal attribute accuracy tests were conducted We checked to ensure values were in expected ranges (e.g. locations of corridors were as expected, and dates of GPS observations were consistent with the project time period). Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. No formal positional accuracy tests were conducted No formal positional accuracy tests were conducted Methods varied by data type (i.e., migration routes, migration corridors, stopovers or winter ranges). Routes: To identify migration routes, we first extracted migration sequences for each individual-year. To identify spring and fall migration start and end dates for a given individual in a given year, we visually inspected the Net Squared Displacement (NSD) curve (Bunnefeld et al. 2011, Bastille-Rousseau et al. 2016) alongside digital maps of the animal’s movement trajectory (Merkle and others, 2017). The NSD represents the square of the straight-line distance between any GPS location of an animal’s movement trajectory and a point within the animal’s winter range. When an animal stays within a defined home range, the NSD varies relatively little over time as the animal travels. However, when an animal migrates away from its winter range, the NSD of each successive location increases until it settles in its summer range (Fig. 1). The days with clear breakpoints in the NSD curves represent the start and end dates for migration and were used to define migration sequences for spring and fall migration. Migration routes were mapped by joining successive GPS locations within each given migration sequence. Corridors and stopovers: We applied a multi-step process to calculate population-level corridors and to identify stopovers, which generally followed the approach outlined by Sawyer et al. (2009). First, we used Brownian bridge movement models (BBMM) (Horne and others, 2007) to estimate an occurrence distribution (in other words, the probability of where the animal could have traveled during its migration, hereafter, utilization distribution [UD]) for each individual spring and fall migration sequence using a 50-meter (164-foot) resolution. The UDs were then averaged across years for each individual to produce a single, individual-level migration UD. We rescaled this averaged UD to sum to one. We then defined a migration footprint for each individual as the 99% isopleth of this UD. We stacked up all the individual footprints for a given population, and defined different levels of corridor use based on the number of individuals using a given pixel. We defined low-use corridors as areas traversed by ≥1 individual during migration, medium-use corridors were used by ≥10% of individuals within the population, and high-use corridors were used by ≥20% individuals within the population. We then converted these corridors from a grid-based format to a polygon format, while removing isolated use polygons of less than 20,000 m2 (i.e., less than approximately 5 acres). Finally, for the stopover calculation, instead of calculating footprints from each individual-level UD, we averaged all the individual-level UDs to produce a single population-level UD, rescaled to sum to one. We defined stopovers as the top 10% of the area of use from the population-averaged UD values. As with the corridors, we then converted stopovers from a grid-based format to a polygon format, and then removed isolated polygons of less than five acres. Winter ranges: We applied a three-step process to calculate population-level winter ranges, which generally followed the approach outlined by Sawyer et al. (2009). First, we isolated winter sequences, defined as movements between fall and spring migrations. For each year, we calculated a standard date for start and end of winter and applied one of two options to calculate winter range dates based on preference of individual States: (1) for each year, we calculated the start of winter as the 95% quantile of the end dates of all fall migrations, and the end of winter as the 5% quantile of the start dates of all spring migrations, or (2) we defined a fixed date range based on local expert knowledge for a given herd (e.g., Dec.15 - Mar. 15). We discarded winter sequences that spanned less than 30 days. Following the methods for migration corridors, we calculated a population-level UD of winter use and identified the core winter range using the 50% isopleth. Citations -Bunnefeld, N., Borger, L., van Moorter, B., Rolandsen, C.M., Dettki, H., Solberg, E.J., and Ericsson, G., 2011, A model‐driven approach to quantify migration patterns—Individual, regional and yearly differences: Journal of Animal Ecology, v. 80, no. 2, p. 466–476. [Also available at https://doi.org/10.1111/ j.1365-2656.2010.01776.x.] -Bastille-Rousseau, G., Potts, J.R., Yackulic, C.B., Frair, J.L., Ellington, E.H., and Blake, S., 2016, Flexible characterization of animal movement pattern using net squared displacement and a latent state model: Movement Ecology, v. 4, no. 15, 12 p. [Also available at https://doi.org/10.1186/s40462-016-0080-y.] -Merkle, J.A., Gage, J., and Kauffman, M.J., 2017, Migration mapper: Laramie, Wyo., University of Wyoming, Department of Zoology and Physiology, Migration Initiative, accessed June 1, 2020, at https://migrationinitiative.org/content/migration-mapper. -Sawyer, H., Kauffman, M.J., Nielson, R.M., and Horne, J.S., 2009, Identifying and prioritizing ungulate migration routes for landscape-level conservation: Ecological Applications, v. 19, no. 8, p. 2016–2025. [Also available at https://doi.org/10.1890/08-2034.1.] 2021 Vector String 123 Albers Conical Equal Area 29.5 45.5 -96.0 23.0 0.0 0.0 coordinate pair 0.6096 0.6096 meters North_American_Datum_1983 GRS_1980 6378137.0 298.257222101 MD_AZ_Kaibab_Routes_Ver2_2021.shp Attribute Table These data provide the location of migration routes for Mule Deer (Odocoileus hemionus) from the Kaibab Herd in Arizona. They were developed using 123 migration sequences collected from a sample size of 48 adult mule deer comprising GPS locations collected every 0.5-7 hours. Producer defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. mig Unique route ID Producer defined Unique identifier for route merging animal ID, season, and year firstdate Beginning date of migration Producer defined Beginning date of migration lastdate Ending date of migration Producer defined Ending date of migration id Animal ID Producer defined Unique Animal ID season Season of migration route Producer defined sp spring migration Producer defined fa fall migration Producer defined year Year of migration route Producer defined 2012.0 2020.0 U.S. Geological Survey GS ScienceBase mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Digital Data https://doi.org/10.5066/P9TKA3L8 None 20220407 Lucas Olson Mule Deer Foundation/Arizona Game and Fish Department Cooperative Mule Deer Biologist mailing

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Phoenix AZ 85086 United States 7152187056 lolson@azgfd.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999