Mule Deer Migration Corridors - East Tehama - 2010-2017 [ds2931]

<div style='text-align:Left;'><div><div><p style='margin:0 0 11 0;'><span><span>The project leads for the collection of most of this data were Scott Hill and Henry Lomeli. Mule deer (38 adult females and 7 adult males) from the East Tehama herd were captured and equipped with store-onboard GPS collar (G2110B, Advanced Telemetry Systems) and iridium satellite GPS collars (Siritrack/Lotek), transmitting data from 2010-2018. The Eastern Tehama herd migrates from a lower elevation winter range in the eastern foothills of the Sacramento Valley to upper elevation summer ranges in the southern Cascade and northern Sierra Nevada mountains (Hill and Figura 2020). A small percentage of the herd are residents, particularly along the Sacramento River and in areas of irrigated agriculture. GPS locations were fixed between 1-13 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. </span></span></p><p style='margin:0 0 11 0;'><span><span>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 35 migrating deer, including 63 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. Collars placed on males malfunctioned, likely leading to irregular behavior, and were therefore not considered for this analysis. The average migration time and average migration distance for deer was 25.68 days and 59.96 km, respectively. 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 33 individual deer and 36 wintering sequences using a fixed motion variance of 1000. 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. Large water bodies were clipped from the final outputs.</span></span></p><p style='margin:0 0 11 0;'><span><span>Corridors are visualized based on deer use per cell, with greater than or equal to 1 deer, greater than or equal to 4 deer (10% of the sample), and greater than or equal to 7 deer (20% of the sample) representing migration corridors, medium 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 m</span></span><span><span>2</span></span><span><span> 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 50</span></span><span><span>th</span></span><span><span> percentile contour of the winter range utilization distribution.</span></span></p></div></div></div>

Tags: Auth_CDFW, Brownian bridge movement model, CAOpenData, CDFW, California Department of Fish And Wildlife, California Natural Resources Agency, DS2931_20210601_wm, GPS, Odocoileus hemionus, connectivity, migration mapper, mule deer, stopover, telemetry, winter range
Organization: California Department of Fish and Wildlife