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Coyote Abundance and Food Habits at the Rocky Mountain Arsenal National Wildlife Refuge in 2005

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Coyote Abundance and Food Habits at the Rocky Mountain Arsenal National Wildlife Refuge in 2005 COYOTE ABUNDANCE AND FOOD HABITS AT THE ROCKY MOUNTAIN ARSENAL NATIONAL WILDLIFE REFUGE IN 2005 FINAL REPORT March 15, 2006 .. Noelle Ronan USFWS 2003 U.S. Department of the Interior U.S. Fish and Wildlife Service Rocky Mountain Arsenal National Wildlife Refuge Commerce City, Colorado Project Lead: Noelle Ronan, USFWS Rocky Mountain Arsenal NWR, CO Project Assistants: Michelle Long, Metro State College, Denver, CO Michael Cunningham, Metro State College, Denver, CO Diane Buell, USFWS Rocky Mountain Arsenal NWR, CO Abstract: We examined relative abundance, absolute density, and seasonal (late-winter through early fall) food habits of coyotes at the Rocky Mountain Arsenal National Wildlife Refuge in Colorado from March through September 2005. We used scat deposition rates to evaluate relative abundance, distance sampling to estimate density, and scat analysis to evaluate food habits in two major habitat types: woodland-prairie in the south and prairie in the north. There was wide variation in relative abundance (scats/mile/day) per season and survey period. Abundance ranged from 0.44 in early March to a low of 0.01 in August. The southern area had 3 times more scat deposition compared to the northern area which was likely associated with differences in habitat and prey availability. The estimated population size during August was 19 coyotes (95% C.I. = 12-29) with a density of0.29 / krn 2 (95 % C.I. = 0.18-0.44). Coyote density had decreased by more than half compared with an estimate obtained in 1992. Food supplies have been noted as the predominant restraint on coyote populations, and fluctuating prey populations may be responsible. A diverse diet is apparent in many coyote populations, including our study. Over the entire study period, small mammals were an important part of coyote diet (60%) while deer were 12%, mid-sized rodents 10%, rabbits 9%. Birds, reptiles, insects, and plants constituted only a small percent of the diet. This trend was evident during late-winter and spring though the diet was more diverse in summer and early fall. Deer constituted the majority of the diet during summer as coyotes exploited abundant young fawns. The percent of deer in scats was higher in the southern area where deer used tree groves for cover during fawning. While the causes of fawn mortality are varied, high predation of fawns by coyotes at our study site was well documented in 2005 and field data suggest that this may be a contributing factor to low recruitment. However, a lack of sufficient cover may predispose fawns to greater predation through increased susceptibility. 2 INTRODUCTION Research and management of coyote populations requires estimation of key demographic parameters such as density (Henke and Knowlton 1995) and resource use (Litvaitis et al. 1994). The relationship between predator and prey can not be fully assessed without adequate estimates of population densities (Pyrah 1984), and determining a predator's diet helps explain their relationship with prey, thus clarifying the community structure (Ueda et al. 2004). Population size can be expressed as density, the number of individual animals per unit area; or relative abundance, a ranking of populations based on an indicator of population size (Henke and Knowlton 1995, Lancia et al. 2004). Estimating coyote population size is difficult due to their secretive nature and often low densities. Methods commonly used to survey coyote populations include scent stations, vocalization responses, scat counts, mark-recapture, and aerial surveys. Understanding coyote food use also is important to management. Diet can be determined efficiently from analysis of scat which is available year-round, can be collected without disturbing the target species (Litvaitis et al. 1994 ), and is logistically practical (Henke and Knowlton 1995). Seasonal variation in coyote diet has been well documented (Andrews and Boggess 1978, Johnson and Hansen 1979, Henke and Knowlton 1995) and suggests opportunistic feeding behavior (Bowyer et al. 1983). The coyote population at our study site, the Rocky Mountain Arsenal National Wildlife Refuge (RMANWR), is of interest because they are the primary predator and have an important influence on other wildlife. Coyote depredation on deer has been a popular topic of interest and investigation (Truett 1979), and coyote predation on ungulate fawns has been well documented (Gese and Grothe 1995). A study at RMANWR was initiated in 2004 to investigate the possible 3 factors influencing low mule deer (Odocoileus hemionus) and white-tailed deer (Odocoileus virginianus) recruitment. Using radio telemetry, high fawn mortality(> 75 %) was documented (A. Rinker, USFWS, unpubl. data). While the causes of fawn mortality are varied, high predation of fawns by coyotes has been well documented and field data at RMANWR suggest that this may be a contributing factor to low recruitment. Deer populations have been surveyed (classification counts and/or population estimates) yearly at RMANWR since 1996, but the trends may be difficult to interpret without adequate data on predator abundance. In 1992, Hein found that coyote density at RMANWR was high (0.71 /kni) relative to similar studies (Camenzind 1978, Pyrah 1984). An estimate of population size at one point in time is of limited value when concerned with questions regarding status (Lancia et al. 2004). Furthermore, coyote density may not be comparable to the 1992 estimate due to changes in prey availability. There were no estimates of coyote density at RMANWR after 1992 and the food habits of RMANWR coyotes have not been previously studied. The purpose of this study was to elucidate coyote relationships with prey by 1) estimating coyote relative abundance using scat deposition rates; 2) estimating coyote absolute density using distance sampling methodology; 3) describing the seasonal food habits of coyotes by identifying mammal hair remains and other materials in scats; and 4) locating coyote den sites or den areas (the land area around a litter den or rendezvous site; Pyrah 1984). STUDY AREA This study was conducted at RMANWR, Commerce City, Colorado (39° 48' N, 104° 56' W), which is 16 km northeast of Denver in Adams County, elevation 1600 m. RMANWR is an 2 approximately 16,300 acre (66 krn ) high-plains urban refuge consisting of remnant short-grass 4 prairie, non-native grassland, scattered tree groves/woodlands, wetlands, and prairie dog (Cynomys ludovicianus) communities. RMANWR is bordered by residential and industrial development, some agriculture, and Denver International Airport. RMANWR is a Superfund site undergoing significant remediation to contain and remove contaminants from past chemical weapons and pesticide production (USFWS 1999, Hoffecker 2001 ). Habitat restoration activities are also ongoing. RMANWR provides habitat for a diversity of wildlife such as migratory birds, including bald eagles (Haliaeetus leucocephalus) and burrowing owls (Athene cunicularia), deer, and coyotes. METHODS Abundance and Density Relative Abundance We estimated relative abundance of coyotes by determining the scat deposition rate along LO-mile segments of unimproved and infrequently traveled roads (Henke and Knowlton 1995; Fig. 1) from March through September 2005. Paved and heavily traveled roads were excluded because either vehicle traffic would negatively influence scat persistence (Henke and Knowlton 1995) or conditions would be unsafe. The study area has two major habitat types: woodland­ prairie in the southern portion (south of i 11 Ave.; "south") and prairie in the northern portion (north of i 11 Ave. ; "north"). We randomly selected 18 road segments, with 9 in the north and 9 in the south. Twenty miles of road were surveyed each count period. Scat counts were conducted approximately every 2 weeks, in conjunction with scat collection for food habits analysis (see below). Road segments were cleared of all scat prior to the initial count period. Field guides (Rezendes 1992, Halfpenny 1998) were used to correctly identify coyote scat. The 5 sample unit was the number of coyote scat piles per transect. Road transects were traveled by truck at slow speeds (:S 20 mph). Because failure to detect scats causes bias, transects were traveled twice in the same day, once in each direction. An index of coyote relative abundance was calculated as the number of scats/mile/day (Henke and Knowlton 1995). Due to seasonal changes in scat abundance resulting from differences in the amount and type of prey consumed, comparisons of relative abundance were not made across seasons (Henke and Knowlton 1995). We also did not make comparisons among road segments because some were not spatially independent (Kendall et al. 1992). Absolute Density We used distance sampling methodology (Buckland et al. 2001) along line transects to determine an absolute density estimate and analyzed data in program Distance (Laake et al. 1998). This method models the probability of detecting an animal as a function of perpendicular distance and the detection function. The main assumptions include 1) objects directly on the line are always detected; 2) objects are detected at their original location; and 3) distances and angles are measured correctly. Assistants were trained to use equipment and estimate distances to ensure that field techniques met the critical assumptions. The section line roads were the transect routes, which fom1ed a systematic grid (Fig. 2). Because detection probability likely differs among habitats, we stratified the study area by the major habitat types represented in the north and south. Two teams (driver and 1 observer per team) traveled the study area daily during August 2005; one team surveyed the north and the other team surveyed the south. Surveys were conducted from sunrise to 1200 and/or from 1600 to approximately 1900. An observer recorded the distance and sighting angles of all coyotes using a laser rangefinder (Bushnell YardagePro) and compass, respectively. Coyotes were recorded as the number observed in a group (i.e. 1, 2 6 ... n); a group represented one sample. To obtain a sufficient sample size, the data from the repeated surveys were pooled prior to analysis.
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