Recovery of moth and butterfly (Lepidoptera) communities in a polluted region following emission decline

International audience

Английский. Environmental pollution is one of the major drivers of the present-day decline in global biodiversity. However, the links between the effects of industrial pollution on insect communities and the underlying species-specific responses remain poorly understood. We explored the spatial pattern in insect communities by analysing 581 samples of moths and butterflies (containing 25,628 individuals of 345 species) collected along a strong pollution gradient in subarctic Russia, and we recorded temporal changes in these communities during the pollution decline that occurred from 1992 to 2006. In the 1990s, the diversity of the Lepidoptera community was positively correlated with the distance from the copper-nickel smelter at Monchegorsk. The overall abundance of Lepidoptera did not change along the pollution gradient, although the abundance of many species decreased with increasing pollution. The responses of each individual species to pollution were associated with its life history traits. The abundances of monophagous species that fed inside live plant tissues and hibernated as imagoes or pupae were not affected by pollution, whereas the abundances of oligophagous and polyphagous species that fed externally on plants and hibernated as larvae generally declined near the smelter. Substantial decreases in aerial emissions from the smelter between 1992 and 2006 resulted in an increase in the diversity of moths and butterflies in severely polluted habitats, whereas their overall abundance did not change. This recovery of the Lepidoptera community occurred due to the reappearance of rare species that had been previously extirpated by pollution and was observed despite the lack of any signs of recovery of the vegetation in the heavily polluted sites. We conclude that the recovery trajectories of insect communities following emission control can be predicted from studies of their changes along spatial pollution gradients by using space-for-time substitution.