In 2008, the Quality Deer Management Association (QDMA) developed a map of white-tailed deer density with information obtained from state wildlife agencies. The map contains information from 2001 to 2005, with noticeable changes since the development of the first deer density map made by QDMA in 2001. The University of Minnesota, Forest Ecosystem Health Lab and the US Department of Agriculture, Forest Service-Northern Research Station have digitized the deer density map to provide information on the status and trends of forest health across the eastern United States. The QDMA spatial map depicting deer density (deer per square mile) was digitized across the eastern United States. Estimates of deer density were: White = rare, absent, or urban area with unknown population, Green = less than 15 deer per square mile, Yellow = 15 to 30 deer per square mile, Orange = 30 to 40 deer per square mile, or Red = greater than 45 deer per square mile. These categories represent coarse deer density levels as identified in the QDMA report in 2009 and should not be used to represent current or future deer densities across the study region. Sponsorship: Quality Deer Management Association; US Department of Agriculture, Forest Service-Northern Research Station; Minnesota Agricultural Experiment Station. Resources in this dataset:Resource Title: Link to DRUM catalog record. File Name: Web Page, url: https://conservancy.umn.edu/handle/11299/178246

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 routes 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.

Updated December, 2024CONCENTRATION AREA: Corridors of riparian habitat along river or stream courses that support higher populations of white-tailed deer, serve as travel corridors and are considered critical habitat for white-tailed deer. HIGHWAY CROSSING: Specific highway areas near riparian habitat zones that have historically been sites of substantial white-tailed deer mortalities. OVERALL RANGE: The area which encompasses all known seasonal activity areas within the observed range of a population of white-tailed deer. WINTER RANGE: That part of the range of a species where 90 percent of the individuals are located during the average five winters out of ten from the first heavy snowfall to spring green-up, or during a site specific period of winter as defined for each DAU.This information was derived from Colorado Parks and Wildlife field personnel. Data was captured by digitizing through a SmartBoard Interactive Whiteboard using topographic maps and NAIP imagery at various scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35). These data are updated on a four year rotation with one of the four Colorado Parks and Wildlife Regions updated each year. These data are not updated on a statewide level annually.

This data publication includes vector digital data files containing white-tailed deer (Odocoileus virginianus) densities during 1982, 1994-1999, and 2001-2005 in the continental United States. Using object-based image analysis followed by random forests classification, we rapidly digitized choropleth maps of white-tailed deer densities, allowing access to deer density information stored in images. This method rapidly reclaimed informational value of deer density maps and similarly may be applied to digitize a variety of published maps to geographic information system layers.Digitization of white-tailed deer densities during 1982 in the United States.Data were originally published on 12/13/2019. Minor metadata updates were made on 03/11/2024.

In heterogeneous landscapes, resource selection constitutes a crucial link between landscape and population-level processes such as density. We conducted a non-invasive genetic study of white-tailed deer in southern Finland in 2016 and 2017 using fecal DNA samples to understand factors influencing white-tailed deer density and space use in late summer prior to the hunting season. We estimated deer density as a function of landcover types using a spatial capture-recapture (SCR) model with individual identities established using microsatellite markers. The study revealed second-order habitat selection with highest deer densities in fields and mixed forest, and third-order habitat selection (detection probability) for transitional woodlands (clear-cuts) and closeness to fields. Including landscape heterogeneity improved model fit and increased inferred total density compared with models assuming a homogenous landscape. Our findings underline the importance of including habitat covariates w..., ,

This dataset consists of occurrence observations for white-tailed deer in the National Park Service Heartland Inventory and Monitoring Network Parks. Because of their impacts on vegetation, disease transmission, visitor health, and vehicle-deer collisions, park managers at Arkansas Post National Memorial, Pea Ridge National Military Park, and Wilson’s Creek National Battlefield identified white-tailed deer as a vital sign for monitoring. Monitoring white-tailed deer populations better positions park management to take action to mitigate concerns involving deer. The overall goals of HTLN white-tailed deer monitoring are to 1) document annual changes in the number of white-tailed deer, as changes could signal presence of illegal deer harvest, disease, or other acute factors of concern for park management; 2) document long-term trends in the number of white-tailed deer to help park management determine if measures need to be taken to maintain herd health, minimize vegetation damage within a park, or alleviate visitor health concerns; and 3) annually map locations of white-tailed deer observed to assist park management in assessing the influences of management actions on deer usage of an area, habitat type, etc.

description: This report is on a project conducted to provide additional analysis of GPS and VHF data that was initially collected from white-tailed deer at Quivira National Wildlife Refuge (QNWR) between 2007 2009. The primary objectives of the additional analysis were to: 1) assess patterns of habitat selection by male deer in response to specific crop types and prescribed fires, and 2) to assess temporal variation in patterns of private land-use by both male and female white-tailed deer, particularly in relation to the hunting season. In addition, continued distance-sampling surveys were conducted during both 2010 and 2011 and results of these surveys were analyzed and compared to previous data collected on QNWR from 2007-2009. The current project successfully completed these objectives and the following report should provide useful information relevant to management of the white-tailed deer population at QNWR. In addition, with the documented occurrence of CWD in Stafford County from a deer harvested during the 2011 hunting season, the combined data from this report and Blecha et al. (2010) should provide important information about conditions prior to CWD arrival and can also be used to inform management decisions designed to mitigate CWD spread on and around the refuge.; abstract: This report is on a project conducted to provide additional analysis of GPS and VHF data that was initially collected from white-tailed deer at Quivira National Wildlife Refuge (QNWR) between 2007 2009. The primary objectives of the additional analysis were to: 1) assess patterns of habitat selection by male deer in response to specific crop types and prescribed fires, and 2) to assess temporal variation in patterns of private land-use by both male and female white-tailed deer, particularly in relation to the hunting season. In addition, continued distance-sampling surveys were conducted during both 2010 and 2011 and results of these surveys were analyzed and compared to previous data collected on QNWR from 2007-2009. The current project successfully completed these objectives and the following report should provide useful information relevant to management of the white-tailed deer population at QNWR. In addition, with the documented occurrence of CWD in Stafford County from a deer harvested during the 2011 hunting season, the combined data from this report and Blecha et al. (2010) should provide important information about conditions prior to CWD arrival and can also be used to inform management decisions designed to mitigate CWD spread on and around the refuge.

This data publication contains vector digital files of white-tailed deer (Odocoileus virginianus) densities during 1950, 1970, 1982, and 2001-2005 in the southeastern United States.Provide digitized maps of white-tailed deer densities over time in the southeastern United States.

The user can click on the "Info" tab within both models to see a description of how the models are run.

description: During the past decade white-tailed deer (Odocoileus virginianus) browsing has caused considerable damage to the under-story of the bottomland forest areas located on the north side of Squaw Creek National Wildlife Refuge (SCNWR) (Figure 1). In an effort to reduce deer browse damage a refuge hunt was established in 1988 and has taken place, in various forms, continually since that time. Although over 100 deer are typically harvested each year, under-story regeneration is limited to non-existent (Durbian unpublished, 2001). There are several hypotheses which may explain the slow under-story regeneration rate including: 1) Current harvest levels are not high enough to control deer; 2) Immigration from surrounding areas is compensating the loss due to harvest; and 3) Some other factor or combination of factors is preventing under-story regeneration. In order to begin evaluating the possible effects of the harvest program on deer at SCNWR, and to begin evaluating the previously mentioned hypotheses, a survey method was needed to obtain accurate deer densities.; abstract: During the past decade white-tailed deer (Odocoileus virginianus) browsing has caused considerable damage to the under-story of the bottomland forest areas located on the north side of Squaw Creek National Wildlife Refuge (SCNWR) (Figure 1). In an effort to reduce deer browse damage a refuge hunt was established in 1988 and has taken place, in various forms, continually since that time. Although over 100 deer are typically harvested each year, under-story regeneration is limited to non-existent (Durbian unpublished, 2001). There are several hypotheses which may explain the slow under-story regeneration rate including: 1) Current harvest levels are not high enough to control deer; 2) Immigration from surrounding areas is compensating the loss due to harvest; and 3) Some other factor or combination of factors is preventing under-story regeneration. In order to begin evaluating the possible effects of the harvest program on deer at SCNWR, and to begin evaluating the previously mentioned hypotheses, a survey method was needed to obtain accurate deer densities.

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 winter ranges for White-Tailed Deer (odocoileus virginianus) in the Selkirk population in Washington. They were developed from 149 winter sequences collected from a sample size of 94 animals comprising GPS locations collected every 4 hours.

A study assessing the effects of changes in deer density on physical parameters of deer in northwest Florida flatwoods. Biological data from white-tailed deer harvested from a pine flatwood study site in northwest Florida from 1980-89 were used to evaluate the relationship between herd density and physical parameters. Deer density was reduced significantly (P 0.05) between population density and these parameters. Although density was reduced by over 3-times, improvements in deer physical parameters were not observed. It appeared-red that herd reduction did little to improve nutritional plane. Apparently, the physical parameters of deer were insensitive to changes in density and their use in population management on poor quality habitats may be limited.

trap data file (tdf)Comma separated file with header in first line. Information is on Spatial-Capture-Recaptures sampling plots. Each plot is 20mx20m. Each plot was visited once per week (=occasion) during three weeks. Plots were cleaned of feces prior data collecttion. Fecal samples were taken and analysed. File contains an identifier (ID) for each trap, its spatial location (X and Y; unit in meter) and whether it was operational (1) or not (0) during each of three occasions (occ1, occ2, occ3).tdf.txtencounter data file (edf)Comma separated file with header in first line. File contains spatial capture recapture data on individuals which were identified using DNA extracted from fecal pellets sampled in plots (see tdf file) for which 12-14 microsatellite markers could be amplified. Each individual is a unique genotype based on these markers. The information contains Session (always 1), identifier for each individual (ID), during which week it was encountered (occasion), and in which samp...

Deer Body Mass Data

Juvenile survival is a highly variable life-history trait that is critical to population growth. Antipredator tactics, including an animal's use of its physical and social environment, are critical to juvenile survival. Here, we tested the hypothesis that habitat and social characteristics influence coyote (Canis latrans) predation on white-tailed deer (Odocoileus virginianus) and mule deer (O. hemionus) fawns in similar ways during the neonatal period. This would contrast to winter when the habitat and social characteristics that provide the most safety for each species differ. We monitored seven cohorts of white-tailed deer and mule deer fawns at a grassland study site in Alberta, Canada. We used logistic regression and a model selection procedure to determine how habitat characteristics, climatic conditions, and female density influenced fawn survival during the first 8 weeks of life. Fawn survival improved after springs with productive vegetation (high integrated Normalized Difference Vegetation Index values). Fawns that used steeper terrain were more likely to survive. Fawns of both species had improved survival in years with higher densities of mule deer females, but not with higher densities of white-tailed deer females, as predicted if they benefit from protection by mule deer. Our results suggest that topographical variation is a critical resource for neonates of many ungulate species, even species like white-tailed deer that use more gentle terrain when older. Further, our results raise the possibility that neonatal white-tailed fawns may benefit from associating with mule deer females, which may contribute to the expansion of white-tailed deer into areas occupied by mule deer.

White-tailed deer (WTD) can exert substantial impacts on the ecosystems in the Southeastern United States. WTD populations in Vicksburg National Military Park (VICK) have not been surveyed since 2010. This study aimed to develop a cost-effective visual count-density conversion method using WTD counts from spotlight surveys and density estimates from fecal-DNA spatially explicit capture-recapture (SECR) models. We conducted spotlight surveys of WTD in January, March, and May, 2023. Average visual counts of WTD were 96.0 in January, March, and May. Direct visual deer counts were greater than those of the 2009 VICK WTD spotlight surveys by 40%-220%. Average WTD relative abundances were 8.5 deer per mile in January, March, and May, respectively. Average density estimated by distance sampling models was 0.65 deer per ha. We used eight microsatellite markers to genotype WTD fecal samples, fecal DNA spatially explicit capture-recapture models estimated 778 WTD within VICK. The WTD densities were positively related to the proportions of forests and open fields in VICK. White-tailed deer appeared to be overabundant within VICK, causing concerns relative to WTD-human conflicts and exacerbating the risk of wildlife disease transmission. We proposed a method for estimating WTD densities with visual counts, which will allow park staff to convert WTD visual counts from spotlight surveys to WTD densities until substantial changes in VICK’s vegetation and/or habitat management occur. The timely, cost-effective monitoring of WTD populations can help park staff better manage natural resources within VICK, including the mitigation of the damages caused by overabundant WTD to natural resources.

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Adult sex ratio and fecundity (juveniles per female) are key population parameters in sustainable wildlife management, but inferring these requires abundance estimates of at least three age/sex classes of the population (male and female adults and juveniles). Prior to harvest, we used an array of 36 wildlife camera traps during 2 and 3 weeks in the early autumn of 2016 and 2017 respectively. We recorded white-tailed deer adult males, adult females and fawns from the pictures. Simultaneously, we collected fecal DNA (fDNA) from 92 20mx20m plots placed in 23 clusters of four plots between the camera traps. We identified individuals from fDNA samples with microsatellite markers and estimated the total sex ratio and population density using Spatial Capture Recapture (SCR). The fDNA-SCR analysis concluded equal sex ratio in the first year and female bias in the second year, and no difference in space use between sexes (fawns and adults combined). Camera information was analyzed in a Spatial C...

There are 9 datasets. one distance sampling dataset, 4 resource selection datasets, and 4 outputs from bootstrapped resource selection models the use the estimated correction factor. The 4 resource selection datasets have data that can be used in a binomial generalized linear mixed effect model to create the correction factor. The distance sampling data set is used to estimate density, and the 4 resource selection datasets can be subset to used points only to estimate the animal distribution relative to transects.

This population appears to be near nutritional carrying capacity based on the moderately high APC value, the levels of other parasites and pathologic conditions, and the general physical parameters of the animals. Currently, the herd does not appear to have any significant density related health problems, and we did not encounter any overtly diseased deer. The herd has moderate immunity to epizootic hemorrhagic disease viruses, but prediction of future activity by the hemorrhagic viruses is not possible. Our data indicate that the herd can be maintained near its present density without undue risk of declines in herd health provided that habitat quality remains stable. Any significant increase in density can be expected to be accompanied by problems with a syndrome of parasitism and malnutrition. The physical parameters for this population are generally lower than those for the Yazoo National Wildlife Refuge animals, and my explanation for this is the higher soil fertility and more extensive availability of agricultural crops at Yazoo National Wildlife Refuge.