The Selkirk White-tailed Deer Management Zone (WDMZ) is home to the largest population of white-tailed deer in the state and consists of seven Game Management Units (GMU; GMUs 105, 108, 111, 113, 117, 121, and 124) located in northeast Washington. Aside from the southern portion of GMU 124, dominated by the metropolitan area of Spokane, Washington, most of these GMUs have similar rural characteristics. Private landowners manage most of the Selkirk WDMZ (77 percent), primarily for commercial timber harvest. The U.S. Forest Service manages 16 percent of the land, and the U.S. Fish and Wildlife Service, Department of Natural Resources, and Bureau of Land Management manage the remaining 7 percent. White-tailed deer used in this analysis were captured on their winter range in GMUs 117 and 121, where the habitat consists of conifer forest (65 percent of the total land cover within the area) and shrub land. Grassland, pasture, and cultivated crops make up the next highest land cover types (altogether comprising nearly 21 percent of the Selkirk WDMZ). Agriculture in the valley supports high densities of deer adjacent to U.S. Highway 395, which bisects the Selkirk WDMZ from north to south. This white-tailed deer population experiences some of the highest rates of deer-vehicle collisions in the state (Myers and others 2008; G. Kalisz, Washington Department of Transportation, written commun.). Currently, there are no crossing mitigations in place along U.S. Highway 395 and State Route 20 to curtail collisions with wildlife. Other wildlife-human management challenges for this herd include mitigating crop damage complaints, maximizing hunting opportunity, and encroaching human development on the deer’s winter range. These mapping layers show the location of the migration stopovers for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 121 migration sequences collected from a sample size of 43 animals comprising GPS locations collected every 4 hours.

In the United States, the state with the highest number of paid hunting license holders in 2024 was Texas, with over 1.1 million. Second and third in the ranking were Pennsylvania and Tennessee.

White-tailed deer Odocoileus virginianus are the most popular big game animal in the United States. Recreational harvest of these animals is a critical tool in population management, as well as an important financial resource for state economies and wildlife agencies. Thus, herd health evaluations can provide information to wildlife managers tasked with developing sustainable harvest practices while monitoring for emergent problems. The purpose of our study was to document causes of illness and natural mortality in New York white-tailed deer submitted for post mortem evaluation. Animals were presented by members of the public and wildlife management personnel due to abnormal behavior or unexplained death. We describe demographic and seasonal associations among gross and histologic evaluation and diagnostic testing. Post mortem examinations were performed on 735 white-tailed deer submitted for necropsy in New York from January 2011 to November 2017. Causes of euthanasia or mortality were classified into nine categories. The most common findings were bacterial infections, trauma not evident at time of collection, and nutritional issues, primarily starvation. Using a multinomial logistic regression model, we looked for associations between the mortality categories and age, sex and season. Compared to the baseline of bacterial deaths, adults were less likely to have died from nutritional and parasitic causes, males were less likely to have died from other causes, and risk of death from nutritional reasons decreased from season to season, with lowest risk in winter. These methods can help wildlife biologists track changes in disease dynamics over time.

Methods Two of the highest priorities, also reflected in the New York State Interagency CWD Risk Minimization Plan, are to detect chronic wasting disease (CWD) in the deer population and document causes of death and disease in white-tailed deer. Standardized criteria for submission in the surveillance program are: 1) live deer behaving abnormally or in poor body condition necessitating humane euthanasia and; 2) deer found dead without an obvious cause of death or found to have some abnormality. DEC may be notified of deer meeting these criteria by members of the public or law enforcement and can submit the animal for necropsy and diagnostic testing. Because the surveillance program specifically excludes deer that died from obvious predation, hunting, and deer-vehicle collisions, animals collected do not represent the New York population as a whole; however, they are valuable for assessing the breadth of diseases affecting wild deer and establishing a standardized baseline for future assessment. A benefit of this program is that these animals can serve as sentinels for emerging diseases. This type of opportunistic surveillance is a widely used method for states to prioritize deer that could be infected by CWD (Joly et al. 2009). Providing a basis for comparison will allow states to refine their surveillance systems to be better informed about white-tailed deer diseases by demo- graphic categories and seasonality.

For the present study, records from deer presented for necropsy through the surveillance program from 2011 to 2017 were compiled to retrospectively evaluate disease occurrence in a subset of the New York deer population. A total of 534 deer out of 735 that died between January 2011 to November 2017 met the criteria for inclusion in the study. Deer that died from obvious, non-natural causes, including deer killed for diagnostic tests (9), forensic studies (102), research (21), hunter killed (49), obvious vehicular trauma and predation (20) were excluded. The study population consisted of 230 females, 169 males, and 135 animals of unknown sex. There were 227 adults, 157 juveniles, 17 neonates, and 133 deer of unknown age. Weight data was available for 215 cases in which full carcasses were submitted.

The Area 7 mule deer population is one of the state’s largest deer herds with an estimated population of about 11,000 in 2019. This deer herd is highly important to Nevada from an economic and ecological perspective. It’s one of the longest distance deer migrations in the state of Nevada with some animals known to migrate over 120 miles during a single migration. A subset of this population, known as the “Pequop” herd, crosses a major highway (US highway 93) and an interstate (Interstate-80) twice annually during their seasonal migration. Several million dollars in wildlife crossing structures have been constructed to help these deer during their migration, yet they still face challenges to connectivity between winter and summer ranges including miles of livestock fencing and a large-scale gold mine operation in close proximity a large stop-over site near Long Canyon. Winter range for this deer herd occurs primarily along the east side of the Pequop Mountains from Sixmile Creek to Ninemile Canyon. The largest stopovers occur along the west side of Snake Mountains near Tabor Creek, Antelope Peak and Bishop Creek areas, north and south of Interstate 80 near Pequop Summit, and the Sixmile Creek to Long Canyon area in the Pequop Mountains. Summer range for this herd primarily occurs between the Owyhee and Bruneau Rivers east of Wildhorse Reservoir. These data provide the _location of winter ranges for mule deer (Odocoileus hemionus) in the Pequop Mountains, Nevada. They were developed from Brownian bridge movement models (Sawyer et al. 2009) using 193 winter sequences collected from a sample size of 86 animals comprising GPS locations collected every 1-25 hours.

description: In a landscape dominated by urban development, the Rocky Mountain Arse:oal (RMA) is an especially important refuge for mule and white-tailed deer. RMA biologists estimate the current deer population exceeds 900 animals (approximately 250-300 white-tailed deer and 650-700 mule deer). The Comprehensive Management Plan for the RMA, completed in 1996, states that the Fish and Wildlife Service (Service) will manage deer populations between 325 and 550 total deer. These goals were generally based on habitat conditions from the early 1990' s and deer research conducted on the refuge in the late 1980's (Matiatos pers. comm. 1999). A specific study evaluating carrying capacity of the habitats on the RMA had never been conducted. The current management approach is a conservative one that attempts to suppress deer populations and minimize habitat degradation by culling females. Culling may have suppressed populations somewhat, but the estimated total population is much higher than the current management goal. The large numerical span between the population estimate and the management goal indicates that habitats on the RMA may be able to support a much higher population of deer than was originally thought. Recognizing this need to evaluate the available habitats and create a more scientifically based method to estimate carrying capacity, the Service initiated this study.; abstract: In a landscape dominated by urban development, the Rocky Mountain Arse:oal (RMA) is an especially important refuge for mule and white-tailed deer. RMA biologists estimate the current deer population exceeds 900 animals (approximately 250-300 white-tailed deer and 650-700 mule deer). The Comprehensive Management Plan for the RMA, completed in 1996, states that the Fish and Wildlife Service (Service) will manage deer populations between 325 and 550 total deer. These goals were generally based on habitat conditions from the early 1990' s and deer research conducted on the refuge in the late 1980's (Matiatos pers. comm. 1999). A specific study evaluating carrying capacity of the habitats on the RMA had never been conducted. The current management approach is a conservative one that attempts to suppress deer populations and minimize habitat degradation by culling females. Culling may have suppressed populations somewhat, but the estimated total population is much higher than the current management goal. The large numerical span between the population estimate and the management goal indicates that habitats on the RMA may be able to support a much higher population of deer than was originally thought. Recognizing this need to evaluate the available habitats and create a more scientifically based method to estimate carrying capacity, the Service initiated this study.

NJ Division of Fish & Wildlife (DFW) has created this grid data to represent Deer Management Units (DMU) in New Jersey. Each numbered grid is a 14.288 square mile projection. DMU's used in conjunction with Deer Management Zones (DMZ) by hunters identifying their location in the DMZ. The DMU is the most smallest and most detailed spatial reference used in deer management, i.e. monitoring disease outbreaks. Please note that initial data generation and creation procedures produced various missing grid numbers (222, 231, 244, 414, 550-559) and some grid order issues. Because of pre-existing use of that data in hunting and for data continuity, these have not been corrected. New Jersey's deer herd is a major component of the landscape throughout all but the most urbanized areas of the state. Deer affect our forests, farms, gardens, backyards and roadways. From a population reduced to a handful of deer in the early 1900s they rebounded during the 20th Century to a thriving herd today. A healthy deer herd, managed at levels that are compatible with current land use practices and the human population, has great value to the people of the state. Deer are photographed, watched and hunted by many in New Jersey and visitors from elsewhere. Deer hunters spend more than 100 million dollars each year as they enjoy approximately 1.5 million recreation-days hunting deer. Money spent in the course of deer hunting benefits a wide variety of New Jersey businesses. Please visit https://www.njfishandwildlife.com/ for more information and detailed instructions pertaining to permit/license issues.

The Manache mule deer herd contains both California mule deer (Odocoileus hemionus californicus) and Inyo mule deer (Odocoileus hemionus inyoensis). The herd predominantly covers the east slopes and crest of the Sierra Nevada. Elevation stretches from 3,200 ft on the Owens Valley winter range, to above 11,000 ft on the summer ranges in Sequoia National Park. The Manache herd migrates from winter ranges just west of U.S. Route 395 on the steep slopes and valleys of the Sierra Nevada near Dunmovin and Haiwee east to some of the highest elevations in the continental United States in Inyo and Sequoia National Forests. Deer numbers were very low by 1900, attributed largely to extreme overgrazing by domestic sheep and cattle, and the subsequent denuding of much of the herd’s summer range. Under the U.S. Forest Service’s jurisdiction, livestock allotments decreased and timber harvest improved range conditions with a resulting increase in deer numbers. Herd size peaked at approximately 7,000 animals in 1950. Following that peak, plant succession, more efficient fire suppression, and livestock competition contributed to a decline in herd size. The 1970s witnessed a reversal of this decline, with a dramatic increase to nearly 7,000 deer, but the current population size is unknown. These mapping layers show the location of the winter ranges for mule deer (Odocoileus hemionus) in the Manache population in California. They were developed from 96 sequences collected from a sample size of 42 animals comprising GPS locations collected every 2 hours.

Top models (Δ AICc < 8) predicting the average edge weight in seasonal networks of female white-tailed deer (Odocoileus virginianus) association ratea in Carbondale, Illinois (2002–2006).

The Area 7 mule deer population is one of the state’s largest deer herds with an estimated population of about 11,000 in 2019. This deer herd is highly important to Nevada from an economic and ecological perspective. It’s one of the longest distance deer migrations in the state of Nevada with some animals known to migrate over 120 miles during a single migration. A subset of this population, known as the “Pequop” herd, crosses a major highway (US highway 93) and an interstate (Interstate-80) twice annually during their seasonal migration. Several million dollars in wildlife crossing structures have been constructed to help these deer during their migration, yet they still face challenges to connectivity between winter and summer ranges including miles of livestock fencing and a large-scale gold mine operation in close proximity a large stop-over site near Long Canyon. Winter range for this deer herd occurs primarily along the east side of the Pequop Mountains from Sixmile Creek ...

NJ Division of Fish & Wildlife (DFW) manages deer herd in New Jersey through the use of deer management zones (DMZ). The Division, under authority of the Fish and Game Council designates these boundaries. Deer Management Zone boundaries are comprised of major and minor roads, waterways and geographic formations. Included for references are the county and township data. DMZs are updated on an as needed basis. New Jersey's deer herd is a major component of the landscape throughout all but the most urbanized areas of the state. Deer affect our forests, farms, gardens, backyards and roadways. From a population reduced to a handful of deer in the early 1900s they rebounded during the 20th Century to a thriving herd today. A healthy deer herd, managed at levels that are compatible with current land use practices and the human population, has great value to the people of the state. Deer are photographed, watched and hunted by many in New Jersey and visitors from elsewhere. Deer hunters spend more than 100 million dollars each year as they enjoy approximately 1.5 million recreation-days hunting deer. Money spent in the course of deer hunting benefits a wide variety of New Jersey businesses. Please visit http://www.njfishandwildlife.com/ for more information and detailed instructions pertaining to permit/license issues.

The Area 10 mule deer population is one of the largest deer herds in the state, accounting for roughly 20 percent of the statewide mule deer population. The Area 10 herd is comprised of several sub populations that occupy the majority of the Ruby Mountains, are highly migratory,and exhibit long distance migrations from summer to winter ranges. Several key stopovers occur within the migration corridor for the Area 10 deer migration. The largest stopovers are located along the Harrison Pass Road on both sides of Toyn Creek,the west side of Pearl Peak and Sherman Mountain, Little and Big Bald Mountains near the Bald Mountain Mine complex, and Bourne to Orchard Canyons west of Warm Spring Ranch. The winter range encompasses a very large area and is distributed along the lower elevations of the Ruby Mountains from Interstate 80 to US Highway 50, a span of approximately 120 miles. Some extended migrations have occurred even farther to the south near Highway 6 in extreme winter years. Several migratory pathways in Area 10 face challenges to permeability including livestock fences, impediments to the migration path from mineral extraction, competition from wild horses, and increasing highway traffic in some portions of the range. These data provide the location of winter ranges for mule deer (Odocoileus hemionus) in the Ruby Mountains, Elko County, Nevada. They were developed from Brownian bridge movement models (Sawyer et al. 2009) using 333 sequences collected from a sample size of 155 animals comprising GPS locations collected every 1-25 hours.

Analysis of ‘Mule Deer Migration Corridors - Loyalton - 2006-2017 [ds2914]’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/8ca60a93-6d2a-4549-a3c6-1d001bb32d20 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

The project leads for the collection of this data were Sara Holm with California Department of Fish and Wildlife and Mike Cox with Nevada Department of Wildlife. Carl Lackey and Cody Schroeder of the Nevada Department of Wildlife and Julie Garcia of California Department of Fish and Wildlife also contributed to the completion of the mapping and project. The Loyalton mule deer herd winters west and northwest of Reno, Nevada along the California-Nevada border. Winter ranges for this herd are distributed across the Sierra Nevada foothills near Loyalton, California, extending into the Peterson Mountains, east of Highway 395 in Nevada. A portion of the herd also winters north of Interstate 80 on Peavine Mountain in Nevada. This population segment represents part of an interstate migratory herd but also has some non-migratory deer that are year-round residents in both states. From their winter ranges, deer generally migrate southwest into the Sierra Nevada Mountains of California, staying north of I-80 and into the Tahoe National Forest. The summer range for this herd is distributed in the mid to higher elevations of the Sierra on both sides of Highway 89 from Truckee to Sierraville, California. Significant challenges include urban development, vehicle collisions on both Highway 89 and 395, and large-scale wildfires that have burned a major portion of winter ranges in both California (2007 Balls Canyon, 2009 Mart, 2020 Loyalton Fire) and Nevada (2008 Peterson, 2013 Red Rock Fires). A large wildlife crossing structure was installed by California Department of Transportation and CDFW on Highway 89 to mitigate some of the impacts from vehicle collisions for this herd. Thirty-six mule deer were captured from 2006 to 2017. Between 8 and 24 location fixes were recorded per day. 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 in a single deer population. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data, including location, date, time, and average location error as inputs in Migration Mapper. Thirty-one deer contributing 76 migration sequences were used in the modeling analysis. 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. Winter range analyses were based on data from 31 individual deer and 62 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 6 deer (20% of the sample) from the Loyalton dataset 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 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.

--- Original source retains full ownership of the source dataset ---

The project leads for the collection of this data were Sara Holm with California Department of Fish and Wildlife and Mike Cox with Nevada Department of Wildlife. Carl Lackey and Cody Schroeder of the Nevada Department of Wildlife and Julie Garcia of California Department of Fish and Wildlife also contributed to the completion of the mapping and project. The Loyalton mule deer herd winters west and northwest of Reno, Nevada along the California-Nevada border. Winter ranges for this herd are distributed across the Sierra Nevada foothills near Loyalton, California, extending into the Peterson Mountains, east of Highway 395 in Nevada. A portion of the herd also winters north of Interstate 80 on Peavine Mountain in Nevada. This population segment represents part of an interstate migratory herd but also has some non-migratory deer that are year-round residents in both states. From their winter ranges, deer generally migrate southwest into the Sierra Nevada Mountains of California, staying north of I-80 and into the Tahoe National Forest. The summer range for this herd is distributed in the mid to higher elevations of the Sierra on both sides of Highway 89 from Truckee to Sierraville, California. Significant challenges include urban development, vehicle collisions on both Highway 89 and 395, and large-scale wildfires that have burned a major portion of winter ranges in both California (2007 Balls Canyon, 2009 Mart, 2020 Loyalton Fire) and Nevada (2008 Peterson, 2013 Red Rock Fires). A large wildlife crossing structure was installed by California Department of Transportation and CDFW on Highway 89 to mitigate some of the impacts from vehicle collisions for this herd. Thirty-six mule deer were captured from 2006 to 2017. Between 8 and 24 _location fixes were recorded per day. 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 in a single deer population. Brownian Bridge Movement Models (BBMMs; Sawyer et al. 2009) were constructed with GPS collar data, including _location, date, time, and average _location error as inputs in Migration Mapper. Thirty-one deer contributing 76 migration sequences were used in the modeling analysis. 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. Winter range analyses were based on data from 31 individual deer and 62 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 6 deer (20% of the sample) from the Loyalton dataset 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 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.

The Wenatchee Mountains mule deer herd inhabits a matrix of private and public lands along the eastern slope of the Cascade Range in Chelan and Kittitas Counties in Washington (fig. 24). Historically, the Wenatchee Mountains mule deer herd was separated into two subherds, Chelan and Kittitas; however, recent GPS collar data indicated the mule deer south of U.S. Highway 2 and north of Interstate 90 represent one population. Their high-use winter range extends along the foothills west and south of Wenatchee, Washington and throughout the foothills of the Kittitas Valley near Ellensburg. Their low-use winter range occurs along the foothills west of the Columbia River north of Interstate 90. In the spring, migratory individuals travel west into the Wenatchee Mountains to their summer range, which includes regional wilderness areas. Between 2020 and 2021, collaring efforts focused on the foothills near Wenatchee and in the surrounding foothills near Ellensburg. Collar data analysis indicated the Wenatchee Mountains mule deer population is partially migratory. A high proportion of migratory individuals inhabit the northern winter range of the Wenatchee Mountains, and resident individuals more commonly inhabit the foothills of the Kittitas Valley. In 2022, collaring efforts of mule deer (n=25) in the northern winter range foothills near Wenatchee targeted the higher proportion of the migratory population, to more clearly identify the movement corridors intersecting U.S. Highway 97 near Blewett Pass. The herd has several challenges, including the increasing frequency of large-scale wildfires and residential developments, which continue to degrade and reduce available winter habitat. Disturbance from human recreation on the winter range continues to be a concern. Additionally, U.S. Highway 97 and State Route 970 receive high volumes of traffic in the region and present semipermeable barriers to spring and fall migration. These mapping layers show the location of the migration routes for mule deer (Odocoileus hemionus) in the Wenatchee population in Washington. They were developed from 184 migration sequences collected from a sample size of 59 animals comprising GPS locations collected every 4 hours.

The Methow mule deer (Odocoileus hemionus) sub-herd is part of the larger West Okanogan herd, the largest migratory mule deer herd in Washington State. Individuals travel as far as 65 miles twice annually between lowland winter range and higher elevation summer range (fig. 27). Mule deer wintering on the shrubsteppe dominated foothills in the lower half of the Methow valley undertake a roughly 3-week trek in mid-spring to the productive subalpine and alpine meadows of the Pasayten and Chelan Sawtooth Wilderness, and surrounding high country, with some animals traveling north into British Columbia. On summer range they mingle with deer moving up from the west side of the Okanogan valley forming an estimated summering population of between 15,000–25,000 animals. Currently, migrating deer in the Methow watershed do not have to contend with any known major barriers, but their movements are somewhat constrained in the lower portion of the watershed where the topography narrows the valley considerably. These data provide the _location of migration routes for mule deer in the Methow population in Washington. They were developed from 321 migration sequences collected from a sample size of 97 animals comprising GPS locations collected every 2 hours.

Ungulates are attracted to forest openings created by natural disturbance and timber harvesting due to the abundance of high quality browse in these openings. Despite the increased activity and browsing of ungulates in forest openings, the importance of browsing relative to abiotic factors such as light on forest regeneration is often unclear. In southern New England, medium-intensity harvesting is the predominant forest disturbance attracting white-tailed deer and moose. Oaks are the foundation hardwood taxon and predominant timber tree in the region and are in decline. Hence, the effects of ungulate browsing on oak forests are of great interest to ecologists, conservationists and forest and wildlife managers. We sampled tree regeneration and ungulate foraging activity across a range of canopy disturbances (35-90% basal area removed) in 34 stands of the Quabbin and Ware River Watershed Forests. Browsing was very high across the plots with about 80% of red maple and oak stems browsed. Taller stems were generally browsed more frequently than shorter stems. Oak regeneration in the smaller size classes was generally lower in stands with higher percent cover of hay-scented fern. The proportion of browsed red maples and oaks generally increased with increasing density of these taxa. Despite intensive herbivory, oaks appear to be regenerating well with increased light in these partially harvested stands.

Most of the Southeast mule deer herd winters along the Owyhee River in regions containing sagebrush communities and Columbia Basin grassland mixed with non-native annual grasslands. These mule deer either migrate west to summer ranges on Road Canyon and Gravel Ridges or east to the Owyhee Mountains along the Idaho border, with one mule deer migrating as far as Bald Mountain, 38.3 mi (61.6 km) into Idaho. Summer ranges feature shrubland, Columbia Basin grasslands, western juniper, and evergreen forests. In 2014, the Buzzard Complex fires burned 398,596 acres (161,306 ha), including Road Canyon, allowing medusahead and other non-native grasses to invade areas with originally low perennial plant abundance. Five mule deer winter separately near U.S. Route 95, in areas containing higher percentages of western juniper. In the spring, they travel southeast into Nevada to summer on the Santa Rosa Range, with one mule deer migrating to the Tuscarora Mountains. Of the Southeast mule deer that were tracked for at least 100 days, 82 percent migrate seasonally, with several moving to summer ranges in different states, complicating issues of population management. The Southeast mule deer herd faces several challenges, including highways and the low abundance of preferred browse. The northeastern section of U.S. Route 95 had an AADT value of 2,007 vehicles in 2018 and intersects multiple migration corridors, with mule deer commonly crossing the highway along Succor Creek and Rock Creek Flat. In summer, Southeast mule deer spend more time in riparian zones and must compete with grazing cattle in the Owyhee Mountains for high-quality forage during drought years when natural water sources evaporate. These mapping layers show the location of the stopovers for mule deer (Odocoileus hemionus) in the Southeast population in Oregon. They were developed from 140 migration sequences collected from a sample size of 37 animals comprising GPS locations collected every 5−13 hours.

Billions of animals migrate to track seasonal pulses in resources. Optimally timing migration is a key strategy, yet the ability of animals to compensate for phenological mismatches en route is largely unknown. We studied a population of mule deer (Odocoileus hemionus) in Wyoming that lack reliable cues on their desert winter range, causing them to start migration 70 days ahead to 52 days behind the wave of spring green-up. By adjusting movement speed and stopover use, however, individual deer arrive at the summer range within an average 6-day window. Late migrants move 2.5 times faster and spend 72% less time on stopovers than early migrants, which allows them to catch the green wave. Ungulates, and potentially other migratory species, possess cognitive abilities to recognize where they are in space and time relative to key resources. Such behavioral capacity may allow migratory taxa to maintain foraging benefits amid rapidly changing phenology. Methods Animal capture and handling From 2014–2020, we captured n = 220 adult female mule deer (>1-yr-old) in the Red Desert near Rock Springs, Wyoming, USA (41° 35′N, 109° 12′W) as part of a long-term study. We recaptured deer each March and December for a total of n = 528 animal-years of data. All deer were captured via helicopter net-gunning1,2. Mule deer in this portion of the Sublette Herd migrate a variety of distances to their summer ranges in northwestern Wyoming3,4. Herein, we focused on n = 72 long-distance migrants (n = 152 animal-years) that migrated 134–293 km and spent the summer north of Pinedale, WY (42° 51′N, 109° 51′W). During captures, we used an electronic platform scale (± 0.1 kg) to measure body mass (kg) and a portable ultrasound (Ibex, E.I. Medical Imaging, Loveland, CO) to measure maximum rump fat (mm). Following previously applied methods5, we used body mass, maximum rump fat, and a body-condition score to estimate percent-scaled ingesta-free body fat (IFBFat)5,6. For captures in March, we used an ultrasound to determine pregnancy, including fetal rate (number of fetuses per deer) and fetal development via measures of the fetal eye diameter (mm). To estimate the age of each deer, we extracted the lower right incisiform canine and used cementum annuli aging technique7–9, which was conducted by the Matson’s Laboratory in Manhattan, Montana, USA. From 2014–2020, we outfitted all deer with store-on-board or iridium GPS collars that collected locations every 1–2 hrs (Advanced Telemetry Systems, Isanti, MN, USA; Lotek Wireless, Newmarket, ON, CAN; Telonics, Mesa, AZ, USA). We also included GPS collar data from a previous study on the Sublette Mule Deer Herd (2011–2013)4 to analyze movement for n = 27 additional deer (n = 66 animal-years), which were outfitted with store-on-board GPS collars that collected locations every 3 hours (Telonics, Mesa, AZ, USA). All animal capture and handling protocols were approved by the Wyoming Game and Fish Department (Chapter 33-937) and an Institutional Animal Care and Use Committee at the University of Wyoming (20131111KM00040, 20151204KM00135, 20170215KM00260, 20200302MK00411). Delineation of migratory routes and seasonal ranges We used Net Square Displacements (NSDs10) to determine the timing of spring and autumn migration, delineate migratory routes, and determine the net displacement (km) between the start of spring migration and each GPS location along the migratory route. We determined winter range use for each deer by extracting GPS locations between the end of autumn migration and the start of spring migration (or between the time of capture and start of spring migration if the end of autumn migration was unknown). We determined summer range use for each deer by extracting GPS locations between the end of spring migration and the start of autumn migration (or between the end of spring migration and time of collar failure or mortality on summer range). We used a 95% Kernel Utilization Distribution (KUD11) to delineate the winter range (41.63 ± 7.26 km2 [x̄ ± 95% CI]) and summer range (7.26 ± 1.61 km2) of each animal-year. We removed 0.10%, 0.09%, and 0.24% of all GPS locations during migration, on winter range, and on summer range, respectively, because the movement rate between consecutive locations was greater than 10.8 km/hr and indicated an inaccurate GPS fix. Green wave surfing We evaluated the ability of mule deer to track green-up of plants during spring migration by analyzing the synchronicity between movement and peak IRG. We determined IRG by extracting the first derivative of double-logistic curves that were fitted to the annual time series of NDVI12. Days from peak IRG (hereafter referred to as Days-From-Peak) were calculated as the difference in days between the date of every GPS location for a deer and the date of peak IRG at the same GPS location12,13. A theoretically perfect surfer occupies a location on the same day that peak IRG occurs (Days-From-Peak = 0)12. We calculated mean Days-From-Peak and IRG for each day and kilometer of an individual’s migration to reduce pseudoreplication and account for irregular GPS fixes12,13. We quantified an individual’s location on the green wave at the start and end of spring migration by calculating the difference in days between the mean date of peak IRG on each seasonal range and the date an individual departed their winter range or arrived at their summer range. References

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The Area 10 mule deer population is one of the largest deer herds in the state, accounting for roughly 20 percent of the statewide mule deer population. The Area 10 herd is comprised of several sub populations that occupy the majority of the Ruby Mountains, are highly migratory,and exhibit long distance migrations from summer to winter ranges. Several key stopovers occur within the migration corridor for the Area 10 deer migration. The largest stopovers are located along the Harrison Pass Road on both sides of Toyn Creek,the west side of Pearl Peak and Sherman Mountain, Little and Big Bald Mountains near the Bald Mountain Mine complex, and Bourne to Orchard Canyons west of Warm Spring Ranch. The winter range encompasses a very large area and is distributed along the lower elevations of the Ruby Mountains from Interstate 80 to US Highway 50, a span of approximately 120 miles. Some extended migrations have occurred even farther to the south near Highway 6 in extreme winter years. Several migratory pathways in Area 10 face challenges to permeability including livestock fences, impediments to the migration path from mineral extraction, competition from wild horses, and increasing highway traffic in some portions of the range. These data provide the location of migration stopovers for mule deer (Odocoileus hemionus) in the Ruby Mountains, Elko County, Nevada. They were developed from Brownian bridge movement models (Sawyer et al. 2009) using 290 migration sequences collected from a sample size of 155 animals comprising GPS locations collected every 1-25 hours.