An assessment of factors influencing territory size and the use of hunter surveys for monitoring wolves in Montana
Reliable knowledge on the status and trend of carnivore populations is critical to their conservation. Direct and indirect methods of monitoring carnivores, however, are time consuming and expensive to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a tim...
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| Format: | Other/Unknown Material |
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University of Montana
2010
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| Online Access: | https://scholarworks.umt.edu/etd/118 https://scholarworks.umt.edu/context/etd/article/1137/viewcontent/Rich_Lindsey_Thesis.pdf |
| Summary: | Reliable knowledge on the status and trend of carnivore populations is critical to their conservation. Direct and indirect methods of monitoring carnivores, however, are time consuming and expensive to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost-efficient method for monitoring the growing population of gray wolves (Canis lupus). I evaluated whether a multi-season patch occupancy model (POM) could be used to accurately estimate the abundance and distribution of wolf packs in Montana from 2007 to 2009. I evaluated hunter sightings of wolves as an index of occupancy and assessed model accuracy by comparing POM estimates to Montana Fish, Wildlife and Parks minimum wolf pack counts (Nmin). To develop a POM robust to variation in territory size, I investigated how territory sizes of wolf packs were affected by ecological factors. In the future, when territory sizes cannot be estimated directly, these ecological factors can be used to predict and monitor changes in territory sizes. I estimated territories for 38 wolf packs in Montana using 90% adaptive kernels, created generalized linear models (GLM) representing combinations of ecological factors hypothesized to effect territory size, and evaluated the predictive power of the top GLM using a jack-knife approach. I estimated 82 (SE = 31; Nmin = 82), 124 (SE = 28; Nmin = 102), and 145 (SE = 28; Nmin = 118) wolf packs in Montana in 2007, 2008, and 2009, respectively. I found territory size was positively related to terrain ruggedness, lethal controls, and human density and negatively related to number of surrounding packs relative to the size of the territory. The top GLM had good model fit (R² = 0.68, P < 0.0005, df = 37) and successfully predicted territory sizes (β1 = 0.88, SE = 0.14, P < 0.0005). Patch occupancy models, using hunter surveys as the sampling method, combined with an understanding of territory size, offers promise as a method for accurately monitoring elusive carnivores at ... |
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