ANTHROPOGENIC FACTORS CAUSE DETECTABLE COMPOSITIONAL VARIATIONS IN LAND SNAIL DEATH ASSEMBLAGES

Biological communities are shaped by numerous environmental factors operating jointly over a range of temporal and spatial scales. In the Anthropocene, human activities have become increasingly important environmental components that appear to play a major role in almost every system. However, discriminating between natural and anthropogenic factors can be challenging. Here, we assess the potential impact of anthropogenic factors on species composition among land-snail shell assemblages across the Canary Archipelago.

In the summer of 2015, 34,000 land snail sub-fossil shells were recovered from the soil surface at 60 sites, distributed among each of the seven islands in the archipelago. All sites were located in the coastal scrub plant biome and were comparable in terms of many natural environmental parameters. All sites were characterized by sclerophyllous vegetation, low altitude (<500 m a.s.l.), and proximity to the coast (<2 km). The degree of human modification (e.g., landscape alteration, distance to municipal boundaries, human population density, traffic density, etc.), however, was significantly variable from site to site.

Multivariate analyses revealed that snail assemblages collected near both agricultural areas and population centers were most consistently dissimilar from all other categories of alteration, while agriculture or urban alteration alone and “pristine” sites were sometimes compositionally quite similar. Although some taxonomic variability may be in part influenced by natural factors, various human activities seem to dominate statistical sample ordinations. The results of this study support the idea that land snails are a useful proxy for detecting anthropogenic impact and point to the value of data like these for conservation efforts. Snails appear to be a highly anthropogenically-sensitive group, their shells are easily collected, and the time-averaged nature of assemblages of dead shells helps to mitigate stochastic, short-term variability.