Population Ecology Estimating Occupancy and Predicting Numbers of Gray Wolf Packs in Montana Using Hunter Surveys LINDSEY N. RICH, 1 Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, MT 59812, USA ROBIN E. RUSSELL, Montana Fish, Wildlife and Parks, 1420 East Sixth Avenue, P.O. Box 200701, Helena, MT 59620, USA ELIZABETH M. GLENN, Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, MT 59812, USA MICHAEL S. MITCHELL, Montana Fish, Wildlife and Parks, 1420 East Sixth Avenue, P.O. Box 200701, Helena, MT 59620, USA JUSTIN A. GUDE, Montana Fish, Wildlife and Parks, 1420 East Sixth Avenue, P.O. Box 200701, Helena, MT 59620, USA KEVIN M. PODRUZNY, Montana Fish, Wildlife and Parks, 1420 East Sixth Avenue, P.O. Box 200701, Helena, MT 59620, USA CAROLYN A. SIME, U.S. Geological Survey, Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, MT 59812, USA KENT LAUDON, Montana Fish, Wildlife and Parks, 490 North Meridian Road, Kalispell, MT 59901, USA DAVID E. AUSBAND, Montana Cooperative Wildlife Research Unit, University of Montana, Missoula, MT 59812, USA JAMES D. NICHOLS, U.S. Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708, USA ABSTRACT Reliable knowledge of the status and trend of carnivore populations is critical to their conservation and management. Methods for monitoring carnivores, however, are challenging to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost- efficient method for monitoring gray wolf (Canis lupus) populations. Montana Fish, Wildlife and Parks (MFWP) conducts annual telephone surveys of >50,000 deer and elk hunters. We explored how survey data on hunters’ sightings of wolves could be used to estimate the occupancy and distribution of wolf packs and predict their abundance in Montana for 2007–2009. We assessed model utility by comparing our predictions to MFWP minimum known number of wolf packs. We minimized false positive detections by identifying a patch as occupied if 2–25 wolves were detected by 3 hunters. Overall, estimates of the occupancy and distribution of wolf packs were generally consistent with known distributions. Our predictions of the total area occupied increased from 2007 to 2009 and predicted numbers of wolf packs were approximately 1.34– 1.46 times the MFWP minimum counts for each year of the survey. Our results indicate that multi-season occupancy models based on public sightings can be used to monitor populations and changes in the spatial distribution of territorial carnivores across large areas where alternative methods may be limited by personnel, time, accessibility, and budget constraints. Ó 2013 The Wildlife Society. KEY WORDS Canis lupus, carnivores, gray wolf, monitoring, northern Rocky Mountains, occupancy, public sightings. Carnivores are difficult to monitor on large spatial scales because they live at low densities and are often nocturnal, secretive, and difficult to observe (Crete and Messier 1987, Schonewald-Cox et al. 1991, Mills 1996). A variety of effective field survey methods (e.g., aerial counts, scat and track surveys, radiotelemetry, camera trapping, genetic sampling) have been developed for monitoring carnivores (Crete and Messier 1987, Gros et al. 1996, Becker et al. 1998, Gompper et al. 2006), yet most of these techniques are impractical to apply across large spatial scales given constraints on personnel, time, accessibility, and budgets (Potvin et al. 2005). In contrast, public sightings can be used to monitor carnivore populations across large areas (Berg et al. 1983, Crete and Messier 1987, Fanshawe et al. 1991, Gros et al. 1996); public sightings, however, often suffer from misidentifications and unreliable reporting (Gros et al. 1996). Direct (e.g., live capture) and indirect (e.g., camera traps or track surveys) monitoring techniques provide detection– non-detection data, which can be used in an occupancy model (MacKenzie et al. 2006) to estimate the probability that landscape patches are occupied by a species of interest (i.e., occupancy). Occupancy modeling uses the patterns of detections and non-detections over multiple visits to individual patches on the landscape to estimate occupancy rates while accounting for imperfect detection of the species of interest (MacKenzie et al. 2002, 2006; Bailey et al. 2004). Occupancy models can be developed for a single season, or patch-specific colonization and extinction probabilities can Received: 31 July 2012; Accepted: 18 September 2012 Published: 26 June 2013 1 E-mail: lindseyrich83@gmail.com The Journal of Wildlife Management 77(6):1280–1289; 2013; DOI: 10.1002/jwmg.562 1280 The Journal of Wildlife Management  77(6)