• Understanding the population dynamics of a high-density ungulate is challenging. • We built an age/sex-structured population model for a moose population. • Our model successfully reproduced changes in abundance and demographic drivers. • We offered a way to build and calibrate complex population models with scarce data. • We identified mechanisms at play in a protected area without hunting and wolves. High-density populations can threaten the ecological integrity of ecosystems through cascading effects. In such cases, management practices must be guided by sufficient knowledge of the biological mechanisms at play. Simulation models are powerful tools for acquiring such knowledge. The moose ( Alces alces americana ) is a species that recently became overabundant in some areas of eastern North America, sometimes requiring specific management measures. While numerous models exist for moose population dynamics, few are adapted to high density populations like the one in Forillon National Park (Quebec, Canada), a protected area in which the moose's apical predator (grey wolf Canis lupus ) is absent. We developed a sex- and age-structured population model respecting these conditions that we parameterized using pattern-oriented modelling to help explain the changes in moose density observed over nearly 4 decades. The most plausible sequence of vital rates identified exhibited negative density dependence in survival, reproduction and dispersal. Predation by alternative predators, black bears ( Ursus americanus ) and coyotes ( Canis latrans ), caused substantial mortality of calves each year. Unlike elsewhere in northeastern North America, winter tick only had a slight effect on calf survival. Variations in the population’s sex ratio were mainly explained by sex-biased dispersal. Our study provides new insights concerning the dynamics of high-density ungulate populations in the absence of their apical predator, and our modelling approach helped reveal new methodological challenges and opportunities. We also present a comprehensive process to build and parameterize a complex population model using scarce data.
Tassi et al. (Wed,) studied this question.