Climate, trophic interactions, density dependence and carry-over effects on the population productivity of a migratory Arctic herbivorous bird

Abstract

Several driving forces can affect recruitment rates in bird populations. However, our understanding of climate-induced effects or bottom–up vs top–down biological processes on breeding productivity typically comes from small-scale studies, and their relative importance is rarely investigated at the population level. Using a 31-year time series, we examined the effects of selected environmental parameters on the annual productivity of a key Arctic herbivore, the greater snow goose Anser caerulescens atlanticus. We determined the extent to which breeding productivity, defined as the percentage of juveniles in the fall population, was affected by 1) climatic conditions, 2) fluctuations in predation pressure caused by small rodent oscillations, and 3) population size. Moreover, we took advantage of an unplanned large-scale manipulation (i.e. management action) to examine the potential non-lethal carry-over effects caused by disturbance on spring staging sites. The most parsimonious model explained 66% of the annual variation in goose productivity. The spring North Atlantic Oscillation and Arctic snow depth were the primary climatic parameters inversely affecting the production of juveniles, likely through bottom–up processes. Indirect trophic interactions generated by fluctuations in lemming abundance explained 18% of the variation in goose productivity (positive relationship). Mean temperature during brood-rearing and disturbance on staging sites (carry-over effects) were the other important factors affecting population recruitment. We observed a strong population increase, and found no evidence of density-dependent effects. Spatially restricted studies can identify factors linking environmental parameters to local bird reproduction but if these factors do not act synchronously over the species range, they may fail to identify the relative importance of mechanisms driving large-scale population dynamics.