Environment and physiology shape Arctic ungulate population dynamics

Abstract

Species conservation in a rapidly changing world requires an improved understanding of how individuals and populations respond to changes in their environment across temporal scales. Increased warming in the Arctic puts this region at particular risk for rapid environmental change, with potentially devastating impacts on resident populations. Here, we make use of a parameterized full life cycle, individual‐based energy budget model for wild muskoxen, coupling year‐round environmental data with detailed ontogenic metabolic physiology. We show how winter food accessibility, summer food availability, and density dependence drive seasonal dynamics of energy storage and thus life history and population dynamics. Winter forage accessibility defined by snow depth, more than summer forage availability, was the primary determinant of muskox population dynamics through impacts on calf recruitment and longer term carryover effects of maternal investment. Simulations of various seasonal snow depth and plant biomass and quality profiles revealed that timing of and improved/limited winter forage accessibility had marked influence on calf recruitment (±10–80%). Impacts on recruitment were the cumulative result of condition‐driven reproductive performance at multiple time points across the reproductive period (ovulation to calf weaning) as a trade‐off between survival and reproduction. Seasonal and generational condition effects of snow‐rich winters interacted with age structure and density to cause pronounced long‐term consequences on population growth and structure, with predicted population recovery times from even moderate disturbances of 10 years or more. Our results show how alteration in winter forage accessibility, mediated by snow depth, impacts the dynamics of northern herbivore populations. Further, we present here a mechanistic and state‐based model framework to assess future scenarios of environmental change, such as increased or decreased snowfall or plant biomass and quality to impact winter and summer forage availability across the Arctic.

Mechanisms matter: Predicting the ecological impacts of global change

“…To demonstrate, while previous statistical analysis found a relationship between muskox calf recruitment and winter severity, the approach taken by Desforges et al (2021) was able to identify the mechanism underlying this relationship: deeper snow depth limits winter food accessibility, increasing the likelihood that pregnant females will abort and first‐year calves struggle to compete for sufficient food. Furthermore, by tracking the changing state of individuals’ energy stores, the IBM provided novel insight into muskoxen responses to plausible environmental scenarios.…”

“…One starting point is physiology, and in this issue, Desforges et al (2021) provide an example of how this might be applied using an individual‐based physiological model to understand the response of muskoxen ( Ovibos moschatus ) to environmental change in the high Arctic. Physiological mechanisms are assumed to have been shaped by natural selection to maximize individual fitness and are thus not expected to change under novel environmental conditions (Sibly et al, 2013).…”

“…Furthermore, by tracking the changing state of individuals’ energy stores, the IBM provided novel insight into muskoxen responses to plausible environmental scenarios. Desforges et al (2021) simulate the impacts of snow depth, timing of snowfall, and their effects over consecutive years, producing a series of predictions about how potential future environmental scenarios will impact muskox demography and population size.…”

“…We suggest three major obstacles: (1) data requirements, (2) the inherent difficulties in prediction, and (3) the culture of modelling in ecology. Desforges et al (2021) provide an example upon which to discuss each in turn.…”

“…As a result of heavy data requirements, mechanistic physiological models to date have largely focused on well‐studied populations, limiting the application of these models to only a small number of longitudinal demographic studies (e.g. North Atlantic fish stocks, Boyd et al, 2018; the Amboseli elephants, Boult et al, 2018; the Zackenberg muskoxen, Desforges et al, 2021).…”