The project lead for the collection of this data was Tom Stephenson. Mule deer (130 adult females) from the Casa Diablo herd were captured and equipped with store-onboard GPS collars (Lotek Pinnacle Pro and Vectronic Survey), transmitting data from 2014-2023. Casa Diablo mule deer are largely traditional migrants, with a winter range stretching between the Benton Range and eastern Inyo National Forest. For summer, individuals move west using a wide range of pathways; however, a concentrated movement corridor passes through Long Valley, across U.S. Highway 395, and into the high mountain Sierra Nevada range. Most deer do not cross into Yosemite National Park. Summer range exists on both sides of U.S. Highway 395, which is a known hotspot for deer-vehicle collisions. Migrants vary in their movements from shorter (4 km) to longer (80 km) distances.

GPS locations were fixed between 1-24 hour intervals in the dataset. 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. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data from 101 migrating deer, including 445 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. The dataset was divided into two overlapping subgroups based on winter range location (i.e., north, central) and analyzed separately, but visualized together as a final product. The average migration time and average migration distance for deer was 8.19 days and 40.22 km, respectively. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. Products were best visualized with a fixed motion variance of 500 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 84 individual deer and 162 wintering sequences. Winter range designations for this herd may expand with a larger sample, filling in some of the gaps between winter range polygons in the map.

Corridors are visualized based on deer use per cell, with greater than or equal to 1 deer, greater than or equal to 9 deer (10% of the sample), and greater than or equal to 18 deer (20% of the sample) representing migration corridors, moderate use corridors, 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.