A SPATIALLY EXPLICIT MODEL OF MOOSE FORAGINGAND ENERGETICS

Abstract

Herbivores contend with spatial and temporal variation in the quality, quantity, and availability of their food resource. The energy that female moose (Alces alces) store during the summer as body fat is used to meet energy needs in winter. The foraging strategy used by an animal affects its daily and annual energy balance. Consequently, foraging strategies and the distribution of food in the landscape can affect individual fitness and population growth through their effects on the energy balance of reproductive females. Models that unify landscape structure, foraging theory, and animal energy metabolism can be used to investigate the effects of foraging strategies on survival and reproduction. We developed an energy and activity simulation environment (EASE) model that predicts the seasonal changes in energy requirements of a female moose foraging in a spatially explicit landscape with a resolution of 1 m2. We validated EASE for both moose and deer (Odocoileus spp.) with respect to body mass changes reported for feeding trials, activity times, and browse intake rates. Energy intake and body mass depended on forage abundance, its spatial distribution, and foraging strategy. In simulations with stochasticity imposed on model parameters, mean moose body mass decreased 4 kg in comparison to simulations that were deterministic. Simulated moose body mass was most sensitive to browse digestibility and least sensitive to maximum intake per day in 1-yr simulations. Moose using nonrandom foraging strategies had higher body mass and survival than moose using random foraging strategies. Differences between strategies increased as browse density decreased. Moose that selected foraging locations with higher food density or food items with higher digestibility deposited more fat and protein than less selective moose, leading to increased survival and reproduction.