The project leads for the collection of this data were Julie Garcia and Richard Shinn. Female mule deer were captured in February 2017 and equipped with satellite collars manufactured by Lotek. Location fixes were collected from these collars between 2017 and 2020. Additional GPS data was collected between 1999-2001 from deer captured in 1999. The earlier dataset was included in the analysis to supplement the small sample size of the 2017-2020 dataset. The data was collected from deer throughout Modoc County with a priority to ascertain general distributions, survival, and home range, and not to model migration routes, hence the low sample sizes. Deer with overlapping winter ranges were defined as from the same herd. The Modoc Interstate deer herd migrates from a winter range near Clear Lake Reservoir in Modoc County, California north into Oregon in Klamath and Lake counties for the summer. GPS locations were fixed at 12-hour intervals in the 2017-2020 dataset and 8-hour intervals in the 1999-2001 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 21 migrating deer, including 52 migration sequences. Resident deer with winter ranges overlapping those of migrant deer were removed from the analysis; only migrants were used in the mapping of corridors, stopovers, and winter ranges. GPS locations, date, time, and average location error were used as inputs in Migration Mapper. Sixteen migration sequences from 12 deer, with an average migration time of 23.89 days and an average migration distance of 69.71 km, were used from the 1999-2001 dataset. Thirty-six migration sequences from 9 deer, with an average migration time of 19.53 days and an average migration distance of 87.57 km, were used from the 2017-2020 dataset. 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 and a fixed motion variance of 1000. Winter range analyses were based on data from 20 individual deer and 32 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 5 deer (20% of the sample) 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 m2were 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 50thpercentile contour of the winter range utilization distribution.
