SDE Feature Class
Tags
mule deer, Odocoileus hemionus, GPS, Brownian bridge movement model, migration mapper, stopover, winter range, Mendocino, Glenn, Lake, telemetry, connectivity, California
Migration corridor, stopover, and winter range locations for black-tailed deer (Odocoileus hemionus columbianus) developed by the California Department of Fish and Wildlife (CDFW) for the Mendocino/ Clear Lake/ Alder Springs herd complex, Mendocino, Glenn, and Lake counties, 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 and high use corridors were used by greater than or equal to 10% and greater than or equal to 20% of the animals sampled, respectively. Migration stopovers and winter range polygons also represent high use areas.
The project leads for the collection of these data were David Casady (CDFW) and Heiko Wittmer (Victoria University of Wellington). Black-tailed deer (65 adult females) from the Mendocino/ Clear Lake/ Alder Springs herd complex (herafter: Mendocino herd) were captured and equipped with store-onboard GPS collars (Lotek Wireless models 3300 and 4400 M, Telonics model TGW-3500), transmitting data from 2004-2013. An additional 24 female black-tailed deer were captured from the Mendocino herd and fit with Lotek Iridiumtrack M GPS collars, transmitting data from 2017-2021. The project lead for this overlapping dataset was Josh Bush (CDFW). Mendocino mule deer exhibit variable movement patterns and strategies. This population includes traditional seasonal migrants, full-time residents, and multi-range migrants (i.e., deer with long-term spring and/or fall stopovers). Full-time residents were excluded from the analysis, but individual deer exhibiting any type of directed movement between high-use ranges were considered a migrant and included. Based on this analysis, the portion of the population that migrates between seasonal ranges does so from a multitude of lower elevation areas within the mountainous Mendocino National Forest in winter to higher elevation summer ranges. Migrants vary in their movements from shorter (2 km) to longer (25 km) distances. While this analysis clearly demonstrates certain movement corridor areas with higher concentrations of migrating deer, with a larger dataset, local biologists predict high-use winter ranges throughout valley bottoms in Mendocino National Forest, and possible high fidelity to summer range sites for individual deer in the area. Numerous black-tailed deer papers have been published as a result of this data collection effort (Casady and Allen 2013; Forrester et al. 2015; Lounsberry et al. 2015; Marescot et al. 2015; Bose et al. 2017; Bose et al. 2018; Forrester and Wittmer 2019).
GPS locations were fixed between 1-13 hour intervals in the 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 50 migrating deer, including 125 migration sequences, location, date, time, and average location error as inputs in Migration Mapper. The dataset was divided into four overlapping subgroups (i.e., north, central, south, east) and analyzed separately, but visualized together as a final product. The average migration time and average migration distance for deer was 7.43 days and 11.22 km, respectively. Corridors and stopovers were prioritized based on the number of animals moving through a particular area. Corridors were best visualized using a 200 m buffer around the lines due to large Brownian motion variance parameters per sequence. Winter ranges and stopovers 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 400. Winter range analyses were based on data from 45 individual deer and 65 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. 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 subgroup sample), and greater than or equal to 5 deer (20% of the subgroup 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 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. Bose, S., Forrester, T. D., Brazeal, J. L., Sacks, B. N., Casady, D. S. and Wittmer, H. U. (2017). Implications of fidelity and philopatry for the population structure of female black-tailed deer. Behavioral Ecology 28(4):983-990. Bose, S., Forrester, T. D., Casady, D. S. and Wittmer, H. U. (2018). Effect of activity states on habitat selection by black-tailed deer. Journal of Wildlife Management 82(8):1711-1724. Casady, D. S. and Allen, M. L. (2013). Handling adjustments to reduce chemical capture-related mortality in black-tailed deer. California Fish and Game 99(2):104-109. 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. Forrester, T. D., Casady, D. S. and Wittmer, H. U. (2015). Home sweet home: fitness consequences of site familiarity in female black-tailed deer. Behavioral Ecology and Sociobiology 69:603-612. Forrester, T. D. and Wittmer, H. U. (2019). Predator identity and forage availability affect predation risk of juvenile black-tailed deer. Wildlife Biology 2019(1):wlb.00510. Lounsberry, Z. T., Forrester, T. D., Olegario, M. T., Brazeal J. L., Wittmer, H. U. and Sacks, B. N. (2015). Estimating sex-specific abundance in fawning areas of a high-density Columbian black-tailed deer population using fecal DNA. Journal of Wildlife Management 79:39-49. Marescot, L., Forrester, T. D., Casady, D. S. and Wittmer, H. U. (2015). Using multistate capture-mark-recapture models to quantify effects of predation on age-specific survival and population growth in black-tailed deer. Population Ecology 57:185-197.
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.
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, Josh Bush, or Heiko Wittmer 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 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 possible population of deer migrating in this area; therefore, other 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 populations 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).
Extent
| West | -123.215772 | East | -122.557248 |
| North | 39.804623 | South | 39.397591 |
| Maximum (zoomed in) | 1:5,000 |
| Minimum (zoomed out) | 1:150,000,000 |
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.
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, Josh Bush, or Heiko Wittmer 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 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 possible population of deer migrating in this area; therefore, other 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 populations 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).