How deer count day works in metro Detroit, Click on Detroit, Jan 15 2015
On the Trail: Results of the northeast Michigan deer browse study, ABC12.com, May 28, 2018Anna Mitterling of Michigan United Conservation Clubs goes over the results of a deer browse study she conducted in northeast Michigan to survey how much potential food is available and how many deer are in the area.
Drones Fly Over Sound Shore To Hunt Down Accurate Deer Population Count, Yonkers Daily Voice, Feb 9, 2017“I am using a thermal and visible light camera on the drone. We use a video, then count any deer that show up. Some flights show nothing. Residents were advised and are aware of this activity, that’s also an FAA requirement. We avoid houses, except large yards. Flights have to be done safely and you can’t fly over people,” Williams said.
Population size, density, & dispersal, Khan Academy, no dateTwo important measures of a population are population size, the number of individuals, and population density, the number of individuals per unit area or volume. Ecologists often estimate the size and density of populations using *quadrats * and the mark-recapture method.
Monitoring Muleys, MTOutdoors, Sept-Oct 2016Deer population extremes are a problem. When overabundant, mule deer overbrowse shrubs such as mountain mahogany and bitterbrush, which can take years to recover. “Because continual overbrowsing reduces the amount of browse through time, it slowly reduces the number of deer the habitat can sustain,” says Waltee, now the FWP biologist in Sheridan. “That’s what we’re seeing in southwestern Montana.”
Belvedere deer droppings could reveal whether population needs managing, MarinIJ.com, Aug 5, 2016Belvedere officials could spend big bucks for a stool study that would determine how many deer populate the stately island. The program to be considered at a City Council meeting Monday would require wildlife researchers to analyze deer droppings, which contain DNA, allowing them to estimate the number and sex ratio of the herd.
Ball State study: Deer ready to overrun some urban areas, Fox News, Feb 4, 2016A new analysis by a Ball State University researcher has found many Midwestern communities could soon be overrun with white-tailed deer because more than twice as many fawns survive in urban areas compared to rural.
Tim Carter, a biology professor, says young deer are more than twice as likely to survive in an urbanized area as compared to rural. Ball State researchers spent 2013-14 tracking deer around the area of the Bloomington, Indiana.
Hunters, scientists dispute deer count, The Redding Pilot, March 17, 2015When talking about the two surveys, Mr. Hyatt said that “it doesn’t mean that either of these are perfect. By nature, you’re estimating a wild animal population and getting not an absolute count but an index of abundance.”
“I just want to count them! Considerations when choosing a deer population monitoring method”, Wildlife Biology 2014r. We compared population estimates or indices from: distance sampling, aerial surveys, spotlight counts, and faecal pellet counts. For each we estimated the labour input, cost, and precision. The coefficient of variation varied with method and time of year from 8.7 to 36.6%. Total labour input per sampling event varied from 11 to 136 h. Total costs of vehicles and equipment per sampling event varied from AU $ 913 to $ 2966. Overall, the spotlight method performed the best at our study site when comparing labour input, total cost and precision. However, choice of the most precise, cost effective method will be site specific and rely on information collected from a pilot study.
Revealed: The Truth About Spotlight Deer Surveys, Deer and Deer Hunting, Sept 29, 2014Researchers identified 4,508 deer during 79 Bronson Forest surveys. Thermal imagers detected 85 percent (3,861 deer) of the total deer seen, and spotlights detected only 48 percent (2,174 deer) of the total. Likewise, of the deer observed, 33 percent were observed by the thermal imagers and spotlights, but 51 percent were only detected by thermal imagers, and 14 percent were only detected by spotlights.
This study demonstrated that the likelihood of detecting an individual whitetail during spotlight surveys is very low, averaging about 41 percent of the time.
5 Survey Methods for Deer Management, BuckManager, Aug 17, 20145. Aerial Surveys – This survey method is not practical for most hunters and land managers, but it makes sense for those managing large blocks of land upwards of 7,500 acres. It does not work well in heavily-forested areas because of limited visibility. Aerial surveys for deer are best performed over more open areas such as grassland-dominated habitats or those comprised of low-shrublands. Helicopters are typically used but small, fixed-winged planes are the right choice for really large properties since they are less expensive. I imagine unmanned drones will be another, less-expensive alternative for deer surveys shortly.
Mt. Lebanon deer survey results inconsistent, The Almanac, May 29, 2014In 2013, an aerial survey counted 342 deer. A year later, a similar survey counted only 196 deer.
Merlin Benner, president of Wildlife Specialists, addressed the discrepancy: the most likely explanation for the different survey numbers is that the deer simply moved temporarily – especially given the severe winter in 2014.
He described aerial surveys as “state of the art,” adding that the only way to get more consistent results would be a “mark and capture” type of study. In those studies, deer are caught, tagged, released and tracked to get a more accurate picture of their travels. Benner emphasized that these studies are significantly more expensive and time consuming than aerial surveys.
Results and Description of the Redding Aerial Deer Survey, Connecticut Agricultural Experiment Station, Jan 24, 2014
AERIAL SURVEYS FOR WHITE-TAILED DEER IN TEXAS, Texas Parks and Wildlife, Clifton The helicopter survey is considered by some to be the most accurate census for determining populations on a given unit of land. The total number of deer recorded on helicopter surveys should not be considered a complete count of all deer. Studies by Texas A&M University, Kingsville indicate that accuracy of helicopter surveys in South Texas is fairly consistent, but they can underestimate deer density by 60-70%. The information gathered from this type of survey should be used as population trend information and for the preparation of annual harvest recommendations with the understanding that the deer density figures are probably conservative.
Estimating White-tailed Deer Abundance at the Blue Hills Reservation using Distance Sampling, The Commonwealth of Massachusetts, Division of Fisheries and Wildlife, Nov 2013Distance Sampling Data Analysis Models including observer or vehicle type as covariates performed worse (based on AIC) than models including only habitat type as a covariate. The estimate of density, using MCDS with habitat type as a covariate and the half-normal key function, was 67 deer per square mile or 85 deer per square mile of deer habitat, calculated by dividing the density estimate (Table 1 and Appendix b) by the proportion of the study area considered deer habitat (80% forested and other cover).
East Hampton Town Deer Survey Results May Not Reflect True Population, June 11 2013Results of a highly-anticipated aerial survey count of East Hampton Town’s deer population are in, and the count came in at 877 deer, a dramatic decline from the 3,293 deer that were tallied in 2006 by a different method, known as a roadside distance sampling. While Ms. Wolffsohn explained that the number is not an accurate head count of the town’s entire deer population—rather it is an index figure that is more representative of a trend, she said. It’s virtually impossible to get a head count of the actual number of deer in the town, she said. Various factors cloud the data, including vegetation that deer are shielded by, which prevents infrared technology from detecting their heat. Also, comparing the two different methods used to tally deer is like comparing “apples and oranges” she said.
Reliability and precision of pellet-group counts for estimating landscape-level deer density, Human Wildlife Interactions, Spring 2013. The pellet-group technique produces reliable and precise estimates of deer density, is inexpensive, requires little training to implement, and is best suited to northern hardwood forests where snow and cold result in minimal deterioration of pellet groups. Unless corrected for hunter harvest and overwinter mortality, pellet-group counts represent average overwinter density and overestimate spring density
SURVEYS USED TO MONITOR THE DEER HERD, Wisconsin Dept of Natural Resources, 2013-05-20
Guidelines for Monitoring Elk and Mule Deer numbers in New Mexico, New Mexico State University, Extension Service, 2012The most common trend indices used by landowners include minimum counts, spotlight or ground counts, and pellet group surveys. Unfortunately, most of these commonly used trend indices have many assumptions that usually result in trend information of uncertain value, and very few have been calibrated to actual population size.
Reliability and precision of pellet-group counts for estimating landscape-level deer density, David S.DeCalesta, Human–Wildlife Interactions 7(1):60–68, Spring 2013The pellet-group technique produces reliable and precise estimates of deer density, is inexpensive, requires little training to implement, and is best suited to northern hardwood forests where snow and cold result in minimal deterioration of pellet groups. Unless corrected for hunter harvest and overwinter mortality, pellet-group counts represent average overwinter density and overestimate spring density.
Detection and stratification approaches for aerial surveys of deer in prairie–parklands, CSIRO Publishing, Sept 2012For management decisions that require accurate and precise estimates of large mammal population numbers, aerial surveys are considered reliable despite their cost. However, aerial surveys may still suffer from underestimation because of undetected animals and low precision as a result of inefficient sampling designs.
Guidelines for Monitoring Elk and Mule Deer Numbers in New Mexico, New Mexico State University, 2012The best supported sightability model for New Mexico corrected for both group size and level of activity: U = −1.773 + (0.3249 × G) + (0.7689 × A)
where G is the group size and A is a class variable for mule deer activity at the time of observation (when the deer group was first seen from the helicopter) and is coded 1 for moving deer and −1 for standing or bedded deer. Positive coefficients for both group size and increasing activity indicate that detectability of mule deer increases as both group size and degree of movement increase. Sighting probabilities of mule deer groups plateau at > 0.99 when group size reaches 22, regardless of group activity. For group sizes of 1 to 25, sighting probabilities vary with both group size and activity, with group size having a proportionately greater effect. During surveys, sighting probabilities for a lone mule deer are approximately 0.10 if bedded/standing and 0.34 if moving. If the group size of mule deer was 10, sighting probabilities increase to approximately 0.67 and 0.90 for bedded/standing and moving, respectively. Because mule deer groups are largest in winter, surveys can maximize detectability of mule deer, and thus numbers counted and precision of population estimates (by minimizing sighting error), by conducting mule deer surveys in winter when group sizes are largest. This model fit the observed data well and correctly predicted 82% of sighting outcomes.
Estimating Deer Populations on Your Property: Population Dynamics, University of Missouri Extension, 2012Dispersal is the permanent movement of an animal from its birth area to a new home range. White-tailed deer dispersal normally involves yearling bucks leaving the area where they were born to establish a home range in a new area. Research has shown that in agricultural areas bucks may disperse over 20 miles from their birth area. This buck dispersal reduces the probability of inbreeding and explains why managers are unable to control the genetic composition of a population. Does do not normally disperse but tend to stay close to their birth area.
Comparison of aerial surveys and pellet-based distance sampling methods for estimating deer density [abstract], et al., Rachael E. Urbanek, Wildlife Society Bulletin, March 2012Wildlife biologists require density estimates for white-tailed deer (Odocoileus virginianus) to facilitate management. Aerial surveys are often used to obtain density estimates, but are subject to problems necessitating the consideration of novel techniques. During winters 2008 and 2009, we estimated deer density on 6 forest preserves near Chicago, Illinois, USA, using aerial surveys and pellet-based distance sampling (PBDS) methods to provide a comparison of these 2 density-estimation techniques. Density estimates from aerial surveys were obtained by dividing both the raw count of deer observed on each preserve (unadjusted aerial density) and the raw count divided by 0.75 (i.e., assuming a 75% detection rate; adjusted aerial density) by the area of the preserve.
Comparison of visual-based helicopter and fixed-wing forward-looking infrared surveys for counting white-tailed deer Odocoileus virginianus, Wildlife Biology 17: 431-440 (2011)We surveyed five plots: four 41.4 km2 plots with free-ranging white-tailed deer Odocoileus virginianus populations in Wisconsin and a 5.3 km2 plot with a white-tailed deer population contained by a high fence in Michigan. We surveyed plots using both fixed-wing FLIR and helicopters, both with snow cover and without snow. None of the methods counted more deer than the other when snow was present. Helicopter counts were lower in the absence of snow, but lack of snow cover did not apparently affect FLIR.
A Review of Deer Management in Michigan, Michigan Department of Natural Resources, 2009
Pages of information on deer survey mechanisms
Estimating deer abundance in suburban areas with infrared-triggered cameras, Paul Curtis et al, Digital Commons, 4/1/2009Traditional population survey techniques are not always practical in urban or suburban wildlife studies. IRCs have advantages over aerial surveys and ground drives in populous areas as the camera surveys are quiet, unobtrusive, and obtain data at all hours (Wilson et al. 1996). The IRC method may be the most suitable technique for studies of urban wildlife where it is difficult to otherwise measure animal abundance.
Deer Population Surveys – How Good Are They?, Ag News and Views, November 2007There are numerous types of surveys, including track counts, infrared-triggered camera surveys, aerial surveys with helicopters and, spotlight surveys. These techniques result in collecting data relative to deer numbers (density), sex ratios, reproductive rates, etc. These techniques can provide valuable insight about deer populations, but these techniques are surveys – the numbers generated using the data are estimates of population parameters, not exact numbers.
How is the deer population counted?, 12 December 2008. Layton, Julia., HowStuffWorks.com. In moderately dense forests, FLIR is up to 90 percent accurate, and in very dense forests it can count deer with up to 50 percent accuracy
On bias, precision and accuracy in wildlife aerial surveys, Wildlife Research, 2008 The empirical results from the two aerial survey studies show that few density estimates are unbiased and precise (Figs 2, 3), and suggest that the estimates of variances and biases have large sources of variation. Such variation could include observers misidentifying animals, double counting, errors in estimating distances that were used in analyses, use of single versus multiple observers, different estimators and differing numbers of parameters used in various estimators.
Conducting Aerial Surveys for White-tailed Deer, Buck Manager, May 2008The helicopter survey is considered by some to be the most accurate census for determining populations on a given unit of land. However, the total number of deer recorded on helicopter surveys should not be considered a complete count of all deer. Studies indicate that accuracy of helicopter surveys can underestimate deer density by 60-70%!
Using Distance Sampling to Estimate Densities of White-Tailed Deer in South-Central Minnesota, MICHELLE A. LARUE et al.,The Prairie Naturalist, June 2007Describe a distance sampling technique used to estimate prehunt and post-hunt population densities of deer in Watonwan County, Minnesota. Estimates of white-tailed deer density were compared between distance sampling versus population modeling, and costs for distance sampling versus aerial surveys were determined. We drove 2,704 km during 24 spotlight surveys conducted from 21 October to 28 December 2004. We observed 537 white-tailed deer during the pre-hunt period and 620 deer during the post-hunt period. Estimates of white-tailed deer density obtained via distance sampling were more than three times larger than estimates derived by population modeling. Costs for aerial surveys would have been four times greater.
Testing 2 aerial survey techniques on deer in fenced enclosures—visual double-counts and thermal infrared sensing, Wildlide Society Bull., April 2005We evaluated the accuracy of 2 aerial survey techniques over 4 large enclosures (6.0–29.4 km2) where the deer (Odocoileus virginianus) population was reconstructed using hunting harvest and winter mortality data. We conducted surveys (n = 8) along equally spaced parallel lines. Six surveys using the double-count technique involved 2 independent observers located on the same side of a helicopter who simultaneously counted animals over narrow plots (60-m width). Four of these surveys yielded deer densities 64–83% of assumed densities (based on the reconstructed population). The 2 other surveys had accuracies of 37 and 46%, respectively, and were judged unreliable because the sighting probability of the front observer was < 0.40. We conducted 2 surveys with a thermal infrared sensor. One survey had the highest accuracy (89%) among all surveys while the other gave poor results (54% accuracy).
Happiness is a Large Pellet Pile, QUALITY WHITETAILS, FEBRUARY 2007How Accurate are Pellet Counts? The short answer: Surprisingly accurate – when used within their limits. At the BMSA, we’ve found that our pellet count results closely mirror harvest results for the preceding hunting season. This suggests that, at least on our ground, both figures provide a reliable index of deer densities.
Deer Population Survey Methods, Ken Cearley, Texas AgriLife Extention Service, Amarillo, TX, 2005? slide show
Whitetailed deer (Odocoileus virginianus) population censusing through pellet counts and spotlighting surveys, 2005?We used pellet counts and spotlight surveys to estimate the population, along with a vegetation analysis to differentiate deer density between forest types. There was a statistical different between deer abundance in the different forest types, with the conifer forests having the most deer per km^2, less in sugar maple forests and the smallest density in the aspen forests.
Using infrared-triggered cameras to survey white-tailed deer in Mississippi, Mississippi Forest & Wildlife Research Center, 2000
Deer Census Techniques, Texas Parks and Wildlife, 1999Remember, all census information is tr end data. Annual records should be retained to compare population trends and to assist in determining the impact of management practices.
Detection Rates of White-Tailed Deer with a Helicopter over Snow, J Wildlife Society Bull, 1998
Pembilier Lake and Dam: Environmental Impact StatementWinter aerial survey counts are made to determine the deer population in the area. The actual number of deer is perhaps about five times the winter aerial …
Aerial Surveys for Deer – CASIOPAAccuracy depends on topography, cover, contrast– Detectability Estimated between 75 and 90%
Deer Density Estimation (Pellet Group Count)This technique, used to estimate deer density, requires 4 pieces of data: 1. Number of pellet groups deposited per day per deer (constant) 2. Period of time pellet groups are deposited, 3. Number of pellet groups counted in plots, 4. Area sampled by plots for pellet groups