Nesting Success and Nest Predators in Forest Fragments: A Study Using Real and Artificial Nests

Abstract

Abstract Area sensitivity in songbirds is commonly attributed to increased nest predation in forest fragments. In 1995 and 1996, we tested whether the nest predators and nesting success of an area-sensitive forest bird, the Eastern Yellow Robin (Eopsaltria australis), varied with fragment size, and we also conducted an artificial nest experiment. The study occurred in two small (55 ha) and two large (>400 ha) forest fragments in a matrix of agricultural land in New South Wales, Australia. Predation accounted for 95% of all failures of 282 robin nests, and the survival of robin nests was negatively correlated with how frequently we observed avian nest predators near nests (i.e. nest-predator activity). Of 461 artificial nests, 84% were depredated, nearly all (99%) by birds. Thus, birds were important predators of nests. The abundance, species richness, and activity of avian nest predators were not related to fragment size. Survival of robin nests averaged 19%; nests in small fragments had a 22% chance of producing at least one fledgling compared with 15% in large fragments, but the difference was not significant. Survival of artificial nests averaged 12% in both small and large fragments. Nest-predator activity accounted for the most variation (68%) in the fate of robin nests, followed by the cumulative density of open-cup nesters (16%). The placement of robin nests had no influence on nest fate. We conclude that nest predation was not area dependent and propose food supply as an alternative hypothesis to explain area sensitivity. We suggest that, rather than being related to fragment size, nest predation increases with decreasing forest cover in a landscape. Increased nest predation in fragmented compared with contiguous landscapes may lower the population viability of songbirds in a region, and hence regional numbers. Therefore, the spatial scale at which fragmentation influences nest predation and songbird populations must be considered carefully.