Population Estimation Procedures For Elk and Deer in the Black Hills, South Dakota: Development of a Sightability Model and Spotlight Survey

Wildlife managers need reliable, cost-efficient, and repeatable methods for evaluating temporal changes in estimated population parameters. However, visibility bias can cause serious underestimates of total counts when conducting aerial surveys for ungulates. The Black Hills of South Dakota are characterized by dense ponderosa pine (Pinus ponderosa), which affects sightability and accurate censusing of elk (Cervus elaphus). Few studies have evaluated aerial survey methodology for visibility bias in this region of South Dakota. We conducted elk sightability trials during January and February 2009 using a Robinson-44 helicopter with 2 observers and pilot. Radiocollared elk groups were located by ground personnel and frequencies and survey units were relayed to the helicopter crew. The helicopter crew recorded group size, sex, percent vegetation cover, snow cover, light intensity, temperature, and elk activity of radiocollared groups that were observed or missed. We used multivariate logistic regression to determine important factors of elk detection and Akaike Information Criterion (AICc) to weight competing models. From 63 sightability trials on groups containing radiocollared elk, our sightability rate was 63.5%. Data analysis revealed that model selection uncertainty existed with 3 models having AICc differences \u3c 3. However, the top 3 models consistently included group size (Σ ωi = 0.92, P = 0.015) and percent vegetation cover (Σ ωi = 0.97, P = 0.008) indicating these two variables were key factors influencing elk sightability in the Black Hills. Applying the sightability model to a survey sampling procedure should allow for stronger inferences about the elk population in the Black Hills. Additional trials should be flown in no snow conditions to determine its effect on elk sightability. We also recommend further research into earth imagery such as the canopy cover layer from the National Landcover Database (NLCD) or National Agriculture Inventory Program (NAIP) to quantify visual obstruction objectively. Spotlight surveys can be used as an alternative method to construct density estimates of ungulates when cost prohibits annual use of aerial surveys. Although spotlight surveys have been used by South Dakota Game, Fish and Parks in the past, detection functions have never been evaluated. Counts of animals are often incomplete due to visual impediments and observer error; therefore, Conventional Distance Sampling was used to generate a detection function. Spotlight surveys were conducted on road transects for elk and deer (Odocoileus spp.) between 10 and 21 August 2008 and 2009. The survey route consisted of 8 transects for a total of 43.9 km that traveled through pine forest, meadows, aspen, and spruce communities. We used radial distances and angles to calculate perpendicular distances. We also tested the hypothesis of different sighting probabilities associated with the cab versus the back of the truck. We used 4 observers with two positioned in the cab and 2 observers in the back of the truck. The front (cab) was considered the primary observer and the back (box of truck) counted any additional animals front observers did not see. In 2009, observers detected 13 groups for a total of 34 elk. Front observers detected 26 elk for a detection rate of 0.76. Back observers detected 31 elk for a detection rate of 0.91. Although detections were not significantly different (P = 0.594), front observers missed 15% more elk than back observers. Small sample sizes for elk precluded analysis using distance sampling. A total of 849 deer in 464 clusters were counted with distance data recorded for each cluster. Of these, 57.8% were antlerless, 18.3% were male, 4.2% were fawns, and 19.7% unknown. Back observers missed 56 deer for a detection rate of 0.93, while front observers missed 119 deer for a detection rate of 0.86. Although detection rates were not significantly different (P = 0.171); front observers missed 7% more deer than the back. Individual and cluster density estimates from distance sampling was 9.6 ± 2.88 and 5.6 ± 1.67deer/km2, respectively. Expected mean cluster size was 1.71 ± 0.47. Our research results indicate that deer spotlight surveys incorporating distance sampling may be a feasible alternative to aerial surveys. However, resource managers need to be aware that such efforts will require a substantial commitment in time and resources to attain the necessary data. Nonetheless, a quality survey design will obtain statistically robust results

Evaluating the Effect of Predators on White-Tailed Deer: Movement and Diet of Coyotes

Coyotes (Canis latrans) may affect adult and neonate white-tailed deer (Odocoileus virginianus) survival and have been implicated as a contributor to the decline of deer populations. Additionally, coyote diet composition is influenced by prey availability, season, and region. Because coyote movement and diet vary by region, local data are important to understand coyote population dynamics and their impact on prey species. In southeast Minnesota, we investigated the effect of coyotes on white-tailed deer populations by documenting movement rates, distances moved, and habitats searched by coyotes during fawning and nonfawning periods. Additionally, we determined survival, cause-specific mortality, and seasonal diet composition of coyotes. From 2001 to 2003, we captured and radiocollared 30 coyotes. Per-hour rate of movement averaged 0.87 km and was greater (P = 0.046) during the fawning (1.07 km) than the nonfawning period (0.80 km); areas searched were similar (P = 0.175) between seasons. Coyote habitat use differed during both seasons; habitats were not used in proportion to their availability (P \u3c 0.001). Croplands were used more (P \u3c 0.001) than their proportional availability during both seasons. Use of grasslands was greater during the fawning period (P = 0.030), whereas use of cropland was greater in the nonfawning period (P \u3c 0.001). We collected 66 fecal samples during the nonfawning period; coyote diets were primarily composed of Microtus spp. (65.2%), and consumption of deer was 9.1%. During the study, 19 coyotes died; annual survival rate range was 0.33–0.41, which was low compared with other studies. Consumption of deer was low and coyotes searched open areas (i.e., cropland) more than fawning areas with dense cover. These factors in addition to high coyote mortality suggested that coyote predation was not likely limiting white-tailed deer populations in southeast Minnesota