Nonlinear effects of climate and density in the dynamics of a fluctuating population of reindeer.

Nonlinear and irregular population dynamics may arise as a result of phase dependence and coexistence of multiple attractors. Here we explore effects of climate and density in the dynamics of a highly fluctuating population of wild reindeer (Rangifer tarandus platyrhynchus) on Svalbard observed over a period of 29 years. Time series analyses revealed that density dependence and the effects of local climate (measured as the degree of ablation [melting] of snow during winter) on numbers were both highly nonlinear: direct negative density dependence was found when the population was growing (Rt > 0) and during phases of the North Atlantic Oscillation (NAO) characterized by winters with generally high (1979-1995) and low (1996-2007) indices, respectively. A growth-phase-dependent model explained the dynamics of the population best and revealed the influence of density-independent processes on numbers that a linear autoregressive model missed altogether. In particular, the abundance of reindeer was enhanced by ablation during phases of growth (Rt > 0), an observation that contrasts with the view that periods of mild weather in winter are normally deleterious for reindeer owing to icing of the snowpack. Analyses of vital rates corroborated the nonlinearity described in the population time series and showed that both starvation mortality in winter and fecundity were nonlinearly related to fluctuations in density and the level of ablation. The erratic pattern of growth of the population of reindeer in Adventdalen seems, therefore, to result from a combination of the effects of nonlinear density dependence, strong density-dependent mortality, and variable density independence related to ablation in winter.

Activity pattern of arctic reindeer in a predator-free environment: no need to keep a daily rhythm.

Arctic Cervids face considerable challenges in sustaining life in a harsh and highly seasonal environment, and when to forage is a key component of the survival strategy. We predict that a cervid maximizes net intake of energy to change the duration of feeding-ruminating cycles depending on season, and pays no attention to light or other activity-entraining cues. Still, in periods of bad weather it may pay energetically to reduce exposure and heat loss. We investigated environmental impact on the seasonal and daily activity pattern of a food-limited, predator-free arctic deer, the Svalbard reindeer. We found that the reindeer indeed had season-dependent feeding-rumination intervals, with no distinct peaks in activity at sunrise and sunset, as would be expected if animals maximize energy intake rates in predator-free environments. However, they temporarily reduced activity when exposed to low temperature and increased precipitation during winter, possibly to conserve energy. We provide insight into the behavioural strategy of Svalbard reindeer which enables them to cope with such an extreme environment.

Continuous and discrete extreme climatic events affecting the dynamics of a high-arctic reindeer population.

Climate at northern latitudes are currently changing both with regard to the mean and the temporal variability at any given site, increasing the frequency of extreme events such as cold and warm spells. Here we use a conceptually new modelling approach with two different dynamic terms of the climatic effects on a Svalbard reindeer population (the Brøggerhalvøya population) which underwent an extreme icing event ("locked pastures") with 80% reduction in population size during one winter (1993/94). One term captures the continuous and linear effect depending upon the Arctic Oscillation and another the discrete (rare) "event" process. The introduction of an "event" parameter describing the discrete extreme winter resulted in a more parsimonious model. Such an approach may be useful in strongly age-structured ungulate populations, with young and very old individuals being particularly prone to mortality factors during adverse conditions (resulting in a population structure that differs before and after extreme climatic events). A simulation study demonstrates that our approach is able to properly detect the ecological effects of such extreme climate events.