Neighborhood interactions on seedling survival were greatly altered following an extreme winter storm

Abstract

Extreme climatic events (ECEs) are predicted to increase in frequency and magnitude under scenarios of global change. It is well known that ECEs impact community structure and dynamics, but how ECEs alter community assembly remains unclear. The strength of local neighborhood interactions should be altered following ECEs, which could provide a mechanistic basis for how ECEs impact forest community dynamics. In a subtropical forest in China, we monitored the survival of more than 7800 understory seedlings representing 116 tree and shrub species since 2006, and this forest experienced an extreme and unexpected winter storm in February 2008. Here, we quantified changes in the effects of intraspecific and interspecific competition, as well as the effects of environmental variables driving seedling survival before and after the storm. We found that seedling density and Simpson diversity greatly increased after the winter storm. Seedling mortality and recruitment peaked in the second year after the storm, and then returned to pre-storm levels in subsequent census years. Seedling survival was negatively affected by conspecific and heterospecific tree density before the winter storm, while after the storm, survival was affected by conspecific seedling density and nearest taxon functional diversity (NTFd’) of tree neighbors, as well as by environmental variables. Moreover, we found a significant difference between abundant and less-abundant species in response to local neighborhood interactions before and after the storm. In short, community dynamics and the effects of local neighborhood on seedling survival were significantly altered following the extreme winter storm. Our study suggests that integrating abiotic and biotic interactions before and after ECEs, and taking functional traits into consideration, contributes to a better understanding of the biological response of forest community dynamics to environmental fluctuations.