Richard Shinn Brian Hudgens 20240410 1.0 vector digital data https://doi.org/10.5066/P9SS9GD9 Matthew Kauffman Blake Lowrey Chloe Beaupre Scott Bergen Stefanie Bergh Kevin Blecha Samantha Bundick Hunter Burkett James W. Cain III Peyton Carl David Casady Corey Class Alyson Courtemanch Michelle Cowardin Jennifer Diamond Katie Dugger Orrin Duvuvuei Joanna Ennis Michelle Flenner Jessica Fort Gary Fralick Ian Freeman Jeff Gagnon David Garcelon Kyle Garrison Emily Gelzer Evan Greenspan Valerie Hinojoza-Rood Pat Hnilicka Andy Holland Brian Hudgens Bart Kroger Art Lawson Cody McKee Jennifer L. McKee Jerod Merkle Tony W. Mong Haley Nelson Brendan Oates Marie-Pier Poulin Craig Reddell Robert Ritson Hall Sawyer Cody Schroeder Jessie Shapiro Scott Sprague Erik Steiner Alethea Steingisser Sam Stephens Blair Stringham Patrick Ryan Swazo-Hinds Nicole Tatman Cody F. Wallace Don Whittaker Benjamin Wise Heiko U. Wittmer Erin Wood 2024 publication Reston, VA U.S. Geological Survey The Likely Tables herd contains migrants, but this herd does not migrate between traditional summer and winter seasonal ranges. Instead, much of the herd displays a nomadic tendency, slowly migrating north for the summer using various high use areas as they move. Therefore, annual ranges were modeled using year-round data to demarcate high use areas in lieu modeling specific winter ranges. A high use area being used during winter by many of the collared animals is west of the Warner Mountains, east of U.S. Highway 395, and north of Moon Lake. Some animals live in the agricultural fields west of U.S. Highway 395. There appears to be little if any movement across the highway, which is fenced on both sides in this area. Summer ranges are spread out, with some individuals moving as far north as Goose Lake. A few outliers in the herd moved long distances south toward the Lassen herd or east to Nevada. Drought, increasing fire frequency, invasive annual grasses, and juniper encroachment negatively affect pronghorn habitat. Recent population surveys indicate a declining population (Trausch and others, 2020). Juniper removal on public and private lands have potential to improve habitat quality and potentially reduce predation (Ewanyk, 2020). Fences on public and private lands affect movement corridors and increase crossing and/or migration times. Recent fence modifications on BLM lands have shown potential to ease pronghorn movements (Hudgens, 2022). These mapping layers show the location of the annual range for pronghorn (Antilocapra americana) in the Likely Tables population in California. They were developed from 25 sequences collected from a sample size of 20 animals comprising GPS locations collected every 1-4 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, energy 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. The second volume described an additional 65 migrations mapped within nine western states and select tribal lands and was published in April, 2022. The third volume described an additional 45 migrations mapped across most western states and select tribal lands. This volume, the forth in the report series, details migrations and seasonal ranges from an additional 31 new herds throughout nine western states. 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, federal and Tribal stakeholders to reduce barriers to migration caused by fences, roads, and other development. 2014 2020 observed Complete As needed Modoc County, California -121.0396 -119.6254 42.1975 40.9530 ISO 19115 Topic Category biota USGS Thesaurus migration (organisms) migratory species animal behavior USGS Metadata Identifier USGS:6584b4bed34eff134d42d9d9 Common geographic areas Alturas California United States USGS Biocomplexity Thesaurus Ungulates Integrated Taxonomic Information System (ITIS) 2023 ONLINE_REFERENCE Washington, D.C. Integrated Taxonomic Information System (ITIS) http://itis.gov expert knowledge Kingdom Animalia animals Subkingdom Bilateria triploblasts 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 Antilocapridae pronghorns Genus Antilocapra Species Antilocapra americana pronghorn Pronghorn 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. Richard Shinn mailing and physical

702 East 8th St

Alturas CA 96101 USA 1 (530) 233-3581 richard.shinn@wildlife.ca.gov 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. 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 three-step process to calculate population-level corridors and to identify stopovers, which generally followed the approach outlined by Sawyer et al. (2009). First, we averaged the UDs (estimated using the Brownian bridge movement model) for a given individual’s spring and fall migration sequences across all years 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 20,000 m2. As an alternative to using UDs estimated from the Brownian bridge movement model, some corridors were delineated using the line buffer method (Merkle and others, 2023). In the line buffer approach, analysts simply buffered the straight line connecting successive GPS locations by a consistent width, often 250 to 300 m. Like with the UD approach mentioned above, we then defined different levels of corridor use based on the number of individuals using a given pixel. Seasonal ranges: We applied a three-step process to calculate population-level seasonal ranges (summer, winter, or annual), which generally followed the approach outlined by Sawyer et al. (2009). First, we isolated seasonal sequences, defined as movements between fall and spring migrations. For each year, we calculated a standard date for start and end of each season and applied one of two options to calculate seasonal range dates based on preference of individual States: (1) for each year, we calculated the start of the seasonal periods using the quantiles or means of the migration start and end dates, or (2) defined a fixed date range based on local expert knowledge for a given herd (e.g., Dec.15 - Mar. 15). We discarded seasonal sequences that spanned less than 30 days. Following the methods for migration corridors, we calculated a population-level UD of winter, summer, or annual use and identified the core range using the 50% isopleth. 2023 Vector G-polygon 1 Albers Conical Equal Area 29.5 45.5 -96.0 23.0 0.0 0.0 coordinate pair 0.6096 0.6096 meters NAD83_National_Spatial_Reference_System_2007 GRS_1980 6378137.0 298.257222101 CA_Pronghorn_LikelyTables_AnnualRange.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 Shape type State State where tracked herd lives Producer Defined CA California Producer defined Species Species that was tracked Producer Defined Pronghorn Pronghorn Producer defined Herd Herd name Producer Defined LikelyTables Likely Tables pronghorn Producer defined DataType Annual range Producer Defined AnnualRange Annual range used by Likely Tables pronghorn Producer defined Contour Annual range is defined by the top 50% of the values (area) during the year. Producer Defined 50.0 50% isopleth of the population-level UD annual range. 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 user accepts sole responsibility for the correct interpretation of this report and the correct use of its accompanying dataset. Prior to using this dataset, please contact Richard Shinn, Kristin Denryter, or Christine Found-Jackson to ensure correct interpretation of the data. The data is best interpreted at a scale of 1:100,000 or larger. Given the small sample size used to construct home range utilization distributions and migration corridors from this population, the home range of these pronghorn likely extends beyond the borders of what is considered high-use home range in our analysis, and likely does not represent the true extent of the home range for this population. Moreover, our sample only represents a fraction of the possible population of pronghorn migrating in this area; therefore, other corridors may have gone undetected in our analysis. This analysis represents migration corridors, stopovers, and home range from one pronghorn population, and is one of a suite of datasets being developed for California’s ungulate herds by CDFW. CDFW makes no warranty of any kind regarding these data, express or implied. By downloading these datasets, the user understands that these data are subject to change at any time as new information becomes available. The user will not seek to hold the State or the Department liable under any circumstances for any damages with respect to any claim by the user or any third party on account of or arising from the use of data or maps. CDFW reserves the right to modify or replace these datasets without notification. No statement or dataset shall by itself be considered an official response from a state agency regarding impacts to wildlife resulting from a management action subject to the California Environmental Quality Act (CEQA). The State makes no claims, promises, or guarantees about the accuracy, completeness, reliability, or adequacy of these data and expressly disclaims liability for errors and omissions in these data. No warranty of any kind, implied, expressed, or statutory, including but not limited to the warranties of non-infringement of third party rights, title, merchantability, fitness for a particular purpose, and freedom from computer virus, is given with respect to these data. Digital Data https://doi.org/10.5066/P9SS9GD9 None 20240410 GS-NOROCK Data Steward U.S. Geological Survey Data Steward mailing

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Bozeman MT 59715 United States 406-994-5034 406-994-6556 norock_data_steward@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999