Cooperative Research Units
Education, Research And Technical Assistance For Managing Our Natural Resources
Home | Intranet | Digital Measures | Help

Using demographic analyses to develop monitoring and management tools for wolves in the Northern Rocky Mountains

Duration

August 2008 - September 2011

Narrative

The University is at a unique point as detailed analysis of the tri-state database can be used to inform our patch occupancy modeling, improving its scope of inference and accuracy, and patch occupancy modeling can make dynamics derived from analyses of the tri-state database spatially explicit. Accomplishing this will require in-depth demographic modeling of the tri-state index, learning what it can tell us about population growth, vital rates, dispersion, and pack sized of a re-colonizing wolf population. The approach would have strong management application in two foreseeable ways: (1) insights into wolf population dynamics would greatly strengthen the inferences that could be derived from the patch occupancy modeling. Specifically, incoroporating trends in distribution, reproduction, and the distribution of pack sizes will allow us to generate estimates of population size (current ojectives are for estimating number of packs only), with confidence intervals, for the State of Idaho; and (2) understanding population dynamics using the unprecedented detail found in the tri-state database would provide the basis for estimating sustainable harvests of wolves following delisting. The combination of population modeling with the spatially explicit results of our monitoring protocol would allow geographically targeted planning and refinement of management practices (e.g., control actions, harvest quotas, etc) to meet local, state-wide, and regional objectives. Further, the patch methodology we are developing is not restricted to wolves. Once developed, our approach will have the potential to be adapted for use on other wide-ranging, low density species (e.g., mountain lions, black bears, fishers, etc.) for which developing robust inferences on distribution and population trend are difficult.

 

Current Staff

Federal Staff: 102

Masters Students: 247

Phd Students: 163

Post Docs: 55

University Staff: 266

5 Year Summary

Students graduated: 722

Scientific Publications: 1960

Presentations: 4355

 

Personnel

Funding Agencies

  • USFWS Region 6

Cooperative Research Units Program Headquarters Cooperators