Understanding indirect interspecific effects (IIEs) on population dynamics is key for predicting community dynamics. Yet, empirically teasing apart IIEs from other interactions and population drivers is data-demanding. We used stochastic population models parameterized with long-term vital rate time series to simulate population trajectories and examine IIEs in a high-arctic vertebrate trophic chain: Svalbard reindeer, its scavenger (Arctic fox), and a migratory fox prey (barnacle goose). Reindeer carcass supply shaped fox abundance fluctuations, subsequently affecting goose fluctuations. Yet reindeer and goose population growth rates were only weakly correlated, probably due to stochasticity, density dependence and life history traits. However, by isolating the effects of individual processes within our simulation model, we demonstrate the presence of strong IIEs on goose population fluctuations and extinction probability. Thus, we highlight the long-term impact of species interactions, including IIEs, on species coexistence and communities, beyond immediate effects and short-term fluctuations.

Demographic correlations are pervasive in wildlife populations and can represent important secondary drivers of population growth. Empirical evidence suggests that correlations are in general positive for long-lived species, however little is known about the degree of variation among populations in relation to local conditions. For three widely geographically separated Atlantic puffin populations (Fratercula arctica), we compared the relative importance of survival-reproduction correlations for two cross-season correlations, reflecting either effects of non-breeding season or breeding season conditions. Demographic rates and their correlations were estimated with an integrated population model, and their respective contributions to variation in population growth were calculated using a transient-LTRE. Demographic correlations were positive for all three populations, but their strength differed. By comparing three populations with geographically distinct foraging areas throughout the year, this study shows that demographic correlations are, in part, driven by environmental conditions, which impacts their population viability and vulnerability to environmental change.