The Montana Cooperative Wildlife Research Unit
The University of Montana
The Montana Cooperative Wildlife Research Unit
The University of Montana
Natural Science Building - Room 312A
Dave and his son Sam
Human caused mortality and wolves
Wolves (Canis lupus) live in family groups comprising a breeding pair, their offspring, and several related helper wolves. Mortality, however, can affect this family group structure and result in smaller packs with adopted, unrelated individuals. Little is known about how characteristics of groups (i.e. size, composition, tenure) affect population growth, individual behavior, group stability, or reproduction. States in the Rockies recently initiated public hunting and trapping seasons for gray wolves and our study is well-positioned to answer important questions about how that new source of ortality might affect gray wolf pack composition and reproduction. Additionally, population modeling of vital rates based on groups can give us insight into how differences in group size and composition affect popultion growth in this coopertivey breeding canid.
Our three focal study areas (southwest Alberta, central Idaho, and Yellowstone National Park, WY) represent a range of human-caused mortality from widely harvested and agency-controlled (SW Alberta and central Idaho) to fully protected (YNP). We intensively sampled 8-10 wolf packs in central Idaho since 2007 and recently began sampling 6-8 wolf packs in YNP and 3-8 wolf packs in SW Alberta in summer 2012. We will begin assessing the impacts of human caused mortality on wolf packs by examining pack pedigees generated via genetic samples collected from surveyed rendezvous sites in the three focal study areas. We finished field sampling in 2014 and will complete analyses in 2015.
Wolf population monitoring
Southwest Alberta wolf pooulation monitoring
Gray wolf (Canis lupus) popultions are difficult to monitor because wolves can be elusive and occur in relatively low densities. We developed a population monitoring framework in the U.S. that uses data from hunter surveys and field-based rendezvous site surveys to estimate wolf pack abundance and distribution across large areas. We began testing this framework in southwest Alberta in 2012. In 2012, our study area spanned from the International Border to Highway 1 and was bordered on the east by Highway 22, with the exception of the Porcupine Hills which we included in our surveys. In 2013, we expanded our study area north of Highway 1 along Highway 22 to the Brazeau River, and west to the eastern borders of Banff and Jasper National Parks (hunter surveys only).
We surveyed big-game hunters for wolf observations made in southwest Alberta during the 2012 and 2013 hunting season. Additionally, we conducted field surveys for wolves at predicted rendezvous sites in summers 2012 and 2013 in southwest Alberta. We mailed refrigerator magnets with our contact information to grazing leaseholders and landowners twice in 2013 to obtain wolf sightings made by the public. We also contacted several members of the South Country Trappers Association to obtain recent wolf activity information from trappers during our summer field survey season.
We combined wolf detection data from our survey methods into a patch occupancy model that estimated wolf pack abundance and distribution across our study area. Preliminary results indicate that a patch occupancy model that uses a 1,200 km2 grid cell size contains the least uncertainty in population estmates. A model that accounts for wolf misidentifications (i.e., false positives) estimated 5.9 (3.4-8.6; 95% CI) wolf packs in our study area in 2012 and 14.5 (9.3-19.7; 95% CI) in our expanded study area in 2013. We did not acquire enough public sightings of wolves or reports of wolf activity from trappers to use as a data source in our model. We were able to use the several reports we did obtain, however, to validate model estimates and found spatial overlap between model predictions and where we received public reports.
We surveyed predicted rendezvous sites for wolves in summer 2014 and will survey big-game hunters once more after the 2014 hunting season. We plan to have a full study report in 2015 that outlines a framework AESRD can use for periodic wolf population monitoring.
Idaho wolf population monitoring
Gray wolf (Canis lupus) populations can be difficult to monitor due to logistical and budgetary challenges. We devised a wolf population monitoring program rooted in patch occupancy modeling, a statistical technique that can integrate data from multiple sampling methods, allowing managers to monitor wolf populations using a suite of methods best suited for their management needs and available resources. To populate a patch occupancy model, we tested a variety of survey methods and showed strong relationships to wolf abundance and distribution. The survey methods we tested in Idaho were hunter surveys, rendezvous site surveys, howlboxes, and rub stations. Each of the survey methods we designed can provide the data needed to populate a patch occupancy model; further, some of the methods can yield highly detailed information on wolves in focal areas, providing biologists with unprecedented tools for understanding wolves in areas where management interest is high. We suggest a monitoring framework based on patch occupancy modeling, using observations available from a variety of sampling techniques, can provide reliable statewide estimates of wolf population size.
Biofence and wolves
Gray wolves (Canis lupus) can conflict with livestock production throughout Idaho, Montana, and Wyoming. Generally, wolves that prey on domestic livestock are killed by management agencies or private landowners. These actions typically stop depredations for producers in the short-term but are not a lasting solution because wolf packs generally fill the recently vacated territory within 1 year and livestock predation often continues. Most tools currently available for non-lethal control of wolves are short-lived in their effectiveness or require constant human presence. Wolves, like most canids worldwide, use scent-marking (deposits of urine, scat, and scratches at conspicuous locations) to establish territories on the landscape and avoid intraspecific conflict. We tested human-deployed scent-marks consisting of scat and urine (i.e., “biofence”) to manipulate wolf pack movements in Idaho.
We deployed 64.7 km and 64.8 km of biofence within 3 wolf pack territories in central Idaho during summers 2010 and 2011, respectively. In 2010, location data provided by satellite collared wolves in 2 of the packs showed little to no trespassing of the biofence. Sign survey at predicted rendezvous sites in areas excluded by the biofence yielded little to no recent wolf use of those areas. We also opportunistically deployed a biofence between a resident wolf pack’s rendezvous site and a nearby (1.6 km) active sheep grazing allotment totaling 2,400 animals. This pack was not implicated in any depredations in 2010. In 2011, however, location data indicated some individuals showed little aversion to trespassing the biofence. Our study provides evidence that wolf movements can be manipulated by human-distributed scent-marks but not all individuals respond strongly to the biofence. Importantly, it appears that wolves’ response to biofencing diminished between years of our study suggesting that one would need to maintain a biofence continuously to ensure effectiveness. We believe more frequent refreshing of the biofence, year-round presence once the biofence is established, an adequate buffer distance from the area to be excluded, and the use of howlboxes may fortify biofenceing, but further study is needed to test this.
Natural Sciences Room 205
Missoula, MT 59812