Mule Deer Migration Corridors - Loyalton - 2006-2017 [ds2914]

The project leads for the collection of this data were Sara Holm with California Department of Fish and Wildlife and Mike Cox with Nevada Department of Wildlife. Carl Lackey and Cody Schroeder of the Nevada Department of Wildlife and Julie Garcia of California Department of Fish and Wildlife also contributed to the completion of the mapping and project. The Loyalton mule deer herd winters west and northwest of Reno, Nevada along the California-Nevada border. Winter ranges for this herd are distributed across the Sierra Nevada foothills near Loyalton, California, extending into the Peterson Mountains, east of Highway 395 in Nevada. A portion of the herd also winters north of Interstate 80 on Peavine Mountain in Nevada. This population segment represents part of an interstate migratory herd but also has some non-migratory deer that are year-round residents in both states. From their winter ranges, deer generally migrate southwest into the Sierra Nevada Mountains of California, staying north of I-80 and into the Tahoe National Forest. The summer range for this herd is distributed in the mid to higher elevations of the Sierra on both sides of Highway 89 from Truckee to Sierraville, California. Significant challenges include urban development, vehicle collisions on both Highway 89 and 395, and large-scale wildfires that have burned a major portion of winter ranges in both California (2007 Balls Canyon, 2009 Mart, 2020 Loyalton Fire) and Nevada (2008 Peterson, 2013 Red Rock Fires). A large wildlife crossing structure was installed by California Department of Transportation and CDFW on Highway 89 to mitigate some of the impacts from vehicle collisions for this herd. Thirty-six mule deer were captured from 2006 to 2017. Between 8 and 24 location fixes were recorded per day. To improve the quality of the data set as per Bjørneraas et al. (2010), the GPS data were filtered prior to analysis to remove locations which were: i) further from either the previous point or subsequent point than an individual deer is able to travel in the elapsed time, ii) forming spikes in the movement trajectory based on outgoing and incoming speeds and turning angles sharper than a predefined threshold , or iii) fixed in 2D space and visually assessed as a bad fix by the analyst. The methodology used for this migration analysis allowed for the mapping of winter ranges and the identification and prioritization of migration corridors in a single deer population. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data, including location, date, time, and average location error as inputs in Migration Mapper. Thirty-one deer contributing 76 migration sequences were used in the modeling analysis. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. BBMMs were produced at a spatial resolution of 50 m using a sequential fix interval of less than 27 hours. Winter range analyses were based on data from 31 individual deer and 62 wintering sequences using a fixed motion variance of 1000. Winter range designations for this herd would likely expand with a larger sample, filling in some of the gaps between winter range polygons in the map. Large water bodies were clipped from the final outputs. Corridors are visualized based on deer use per cell, with greater than or equal to 1 deer, greater than or equal to 3 deer (10% of the sample), and greater than or equal to 6 deer (20% of the sample) from the Loyalton dataset representing migration corridors, moderate use, and high use corridors, respectively. Stopovers were calculated as the top 10 percent of the population level utilization distribution during migrations and can be interpreted as high use areas. Stopover polygon areas less than 20,000 m2 were removed, but remaining small stopovers may be interpreted as short-term resting sites, likely based on a small concentration of points from an individual animal. Winter range is visualized as the 50th percentile contour of the winter range utilization distribution.