SDE Feature Class
Tags
mule deer, Odocoileus hemionus, GPS, Brownian bridge movement model, migration mapper, stopover, winter range, telemetry, connectivity, Modoc, California, Oregon
Migration corridor, stopover, and winter range locations for mule deer (Odocoileus hemionus) developed by the California Department of Fish and Wildlife (CDFW) for the Modoc Interstate herd, Modoc County, California. Corridors, stopovers, and winter ranges were developed in Migration Mapper with Brownian Bridge Movement Models using GPS locations from collared deer. Migration corridors represent movement routes used by deer between winter and summer range habitats. Moderate use corridors were used by greater than or equal to 10% of the animals sampled, and high use corridors were used by greater than or equal to 20% of the animals sampled. Migration stopovers and winter range polygons also represent high use areas.
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 Bjrneraas 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 m 2 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 th percentile contour of the winter range utilization distribution.
Migration Mapper: https://migrationinitiative.org/content/migration-mapper Bjrneraas, K., Van Moorter, B., Rolandsen, C. M., and Herfindal, I. (2010). Screening global positioning system location data for errors using animal movement characteristics. The Journal of Wildlife Management, 74(6), 1361-1366. Sawyer, H., Kauffman, M. J., Nielson, R. M., and Horne, J. S. (2009). Identifying and prioritizing ungulate migration routes for landscapelevel conservation. Ecological Applications, 19(8), 2016-2025. California Department of Fish and Wildlife (CDFW)
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 Julie Garcia or Richard Shinn 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 winter range utilization distributions and migration corridors from this herd, winter range for mule deer likely extends beyond the borders of what is considered winter range in our analysis, and likely does not represent the true extent of the winter range for this herd. Moreover, our sample only represents a small fraction of the true population of mule deer migrating between CA and OR; therefore, many corridors may have gone undetected in our analysis. This analysis represents migration corridors, stopovers, and winter range from one deer herd, one study, and is one of a suite of datasets being developed for Californias 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).
License: This work is licensed under Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ ). Using the citation standards recommended for BIOS datasets ( https://www.wildlife.ca.gov/Data/BIOS/Citing-BIOS ) satisfies the attribution requirements of this license.
Disclaimer: 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.
Extent
West | -121.447946 | East | -120.706786 |
North | 42.791217 | South | 41.439635 |
Maximum (zoomed in) | 1:5,000 |
Minimum (zoomed out) | 1:150,000,000 |
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 Julie Garcia or Richard Shinn 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 winter range utilization distributions and migration corridors from this herd, winter range for mule deer likely extends beyond the borders of what is considered winter range in our analysis, and likely does not represent the true extent of the winter range for this herd. Moreover, our sample only represents a small fraction of the true population of mule deer migrating between CA and OR; therefore, many corridors may have gone undetected in our analysis. This analysis represents migration corridors, stopovers, and winter range from one deer herd, one study, and is one of a suite of datasets being developed for Californias 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).
License: This work is licensed under Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ ). Using the citation standards recommended for BIOS datasets ( https://www.wildlife.ca.gov/Data/BIOS/Citing-BIOS ) satisfies the attribution requirements of this license.
Disclaimer: 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.