Date of Award:


Document Type:


Degree Name:

Master of Science (MS)




Daniel R. MacNulty


Moose in Utah represent the southernmost naturally occurring populations of moose in the world. Concerns over possible numeric declines and a paucity of baseline data on moose in the state prompted the Utah Division of Wildlife Resources to initiate a study of moose demography in collaboration with Utah State University. The objectives of this study were to 1) determine reproductive rates of moose in Utah and the factors which influence them, and 2) combine aerial count data from multiple management units within the state to identify factors which influence interannual variation in population growth rates.

We constructed generalized linear models to relate maternal body condition and age to reproductive success. We found that body condition (P = 0.01) and age (P = 0.02) contributed significantly to the probability of pregnancy and the best model describing this relationship was nonlinear. Body condition also related positively to subsequent calving (P = 0.08) and recruitment (P = 0.05), but model selection suggested the relationship for these metrics was best described by linear models. A meta-analysis of moose reproductive rates in North America suggested that reproductive rates declined significantly with latitude (P ≤ 0.01), i.e. as populations approached their southern range limit.

We used Bayesian state-space models to combine moose count data from different management units to estimate statewide population dynamics between 1958 and 2013. This approach incorporated uncertainty in population counts arising from observation error. Population density and warm winter temperatures negatively influenced population growth rate with a high degree of confidence; 95% Bayesian Credible Intervals for these variables did not overlap zero. Short-term projections of moose abundance in the state suggested that the population will likely remain stable despite projected increases in winter temperature.

Results from this study will aid managers in achieving management objectives as well as future decision making. The unique characteristics of the population also have application toward understanding the dynamics of populations of cold-adapted species at their southern range limit.