NDOW, CODY SCHROEDER USFWS, JOHN TULL ODFW, DON WHITTAKER 20220407 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 The Sheldon-Hart Mountain pronghorn (Antilocapra americana) herd is part of a large interstate metapopulation distributed across northwest Nevada, southeast Oregon, and portions of northeast California. Some animals travel up to 100 miles between summer and winter ranges and traverse multiple federal land jurisdictions, including the Sheldon National Wildlife Refuge, Hart Mountain National Wildlife Refuge, and surrounding Bureau of Land Management (BLM) lands. The herd can be characterized as conditionally or partially migratory with approximately 65% of collared animals exhibiting migratory tendencies. Major summer ranges include portions of the Hart Mountain Wildlife Refuge, Sheldon National Wildlife Refuge, and northern Black Rock Range in Nevada. Winter ranges are distributed across Hart Mountain and east to Catlow Valley, Sage Hen Flats in Oregon and portions of the Sheldon National Wildlife Refuge including Catnip Mountain, Gooch Table, Rock Springs Table, Summit Lake Indian Reservation, northern Calico Mountains. Challenges to this herd include invasive annual grasses and loss of native shrubs and grasslands, depletion of limited water resources due to severe droughts, and livestock fencing that prohibits efficient movements across the landscape. These data provide the location of Migration corridors for female Pronghorn in the Sheldon-Hart Mountain herd in Nevada and Oregon. They were developed from 79 migration sequences collected from a sample size of 30 animals comprising GPS locations collected every 5-6 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. 20110320 20131121 observed Complete As needed Northwestern Nevada and Southeastern Oregon -120.1938 -118.3359 43.0742 41.1380 USGS Thesaurus migration (organisms) migratory species animal behavior corridors USGS Metadata Identifier USGS:620e4b81d34e6c7e83baa3e0 Common geographic areas Lakeview Oregon United States None Antilocapra americana Kingdom Animalia Subkingdom Bilateria Infrakingdom Deuterostomia Phylum Chordata Subphylum Vertebrata Infraphylum Gnathostomata Superclass Tetrapoda Class Mammalia Subclass Theria Infraclass Eutheria Order Artiodactyla Family Antilocapridae Genus Antilocapra Species Antilocapra americana TSN: 180717 None. Please see 'Distribution Info' for details. Dataset authors will retain ownership of the data provided. 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 authors/originators listed herein. Cody Schroeder Nevada Department of Wildlife Mule Deer and Pronghorn Staff Specialist mailing and physical

6980 Sierra Center Pkwy

Reno NV 895009 USA 775-688-1659 cschroeder@ndow.org U.S. Fish and Wildlife Service and Nevada Department of Wildlife provided funding and capture support. 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), completeness, and there were no errors of omission. 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. We checked to ensure there were no locations outside of the expected regions. We checked to ensure there were no locations outside of the expected regions. 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. Annual Range: To estimate a population’s annual range, we generally followed the methods for calculating migration stopover sites or winter range with some exceptions. First, we isolated annual sequences for each individual. These were defined as movements consisting of > 275 days within a calendar year beginning at the time of collar deployment. Start dates were similar because GPS collars were deployed in batches around the same dates. End dates sometimes varied depending on mortalities. Following the methods for migration corridors, we calculated a population-level UD of annual use and identified the core annual range using isopleth values that were selected based on local expert knowledge for a given herd. 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 G-polygon 49 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 Pronghorn_NV_SheldonHartMtn_Corridors_Ver2_2020.shp Attribute Table Table containing attribute information associated with the data set. Producer Defined FID Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. ID Calculated ID Producer Defined 1 98 GRIDCODE We delineated low, medium and high level corridors from population level utilization distributions of animal movements. Producer Defined 1.0 This represents the low use corridor or the 99% population level footprint of the combined animal utilization distributions. Producer defined 10.0 This represents the medium use corridor or the combined animal UD for 10% or more of the population level corridor. Producer defined 20.0 This represents the high use corridor or the combined animal UD for 20% or more of the population level corridor. Producer defined 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 The Nevada Department of Wildlife 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 Nevada Department of Wildlife. Digital Data https://doi.org/10.5066/P9TKA3L8 None. 20220407 Cody Schroeder Nevada Department of Wildlife Mule deer and Pronghorn Staff Specialist mailing and physical

6980 Sierra Center Pkwy

Reno NV 89509 USA 775-688-1659 cschroeder@ndow.org FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999