Date of Award:

5-2010

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Wildland Resources

Advisor/Chair:

Mary M. Conner

Abstract

Monitoring population trend and estimating vital demographic parameters are essential for effective management of a mule deer (Odocoileus hemionus) population. Because of financial constraints, many wildlife agencies use computer models to obtain indirect indices of population size and trend as an alternative to annual field-based estimates of population size. These models are based primarily on herd composition counts and harvest rates from hunter-harvest surveys, and are rarely field validated. I developed an alternative method for monitoring population dynamics of wintering populations of mule deer. I designed a hybrid monitoring program that combined annual vital rate monitoring to track changes in population growth rate with a field-based approach for estimating population abundance. The program allocated resources optimally towards the most critical components of mule deer population dynamics, and consisted of 4 field surveys: annual monitoring of age ratios, overwinter fawn survival, and annual doe survival, with field-based estimates of population size only once every 4 years. Surveys were conducted from 2006 to 2008 in Wildlife Management Unit (WMU) 2, Utah, and cost $29,298 per year, prorated over 4 years. Unfortunately, financial constraints prohibit the implementation of this monitoring program in every WMU in Utah. Instead, the program can be implemented in select WMUs throughout the state, with survival data collected in these core units, providing estimates for nearby satellite units. To establish core-satellite unit pairs, I developed a proxy method for determining correlation in survival rates between core and satellite units using model-simulated estimates. I demonstrated this core-satellite method using WMU 2 as a core and WMU 3, an adjacent unit, as a satellite. Finally, I compared a multiple data sources (MDS) model with a herd composition-based population model, POP-II. The MDS model better approximated observed data, and provided statistical rigor. Overall, the hybrid program was less costly and provided more precise estimates of population trend than could be achieved with a monitoring program focused on abundance alone, and was more defensible than herd composition monitoring. After establishing correlations in doe and fawn survival between core and satellite units, data collected in core units via the hybrid program could then be used to model the mule deer population dynamics of other units using MDS modeling procedures. This combined approach could be an effective statewide program for monitoring mule deer populations.

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