Can snow depth be used to predict the distribution of the high Arctic aphid Acyrthosiphon svalbardicum (Hemiptera: Aphididae) on Spitsbergen?
Peer reviewed, Journal article
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Background: The Svalbard endemic aphid Acyrthosiphon svalbardicum (Heikinheimo, 1968) is host specific to Dryas octopetala L. ssp octopetala (Rosaceae). It has been hypothesized that the aphid is present on those areas with a thin winter snow cover and which therefore clear of snow earlier in the season. This early snow clearance results in a longer growing period and allows the aphid to experience at least the minimum number of degree days required to complete its life cycle. However, this hypothesis lacked a detailed field validation. We aimed to test the relationship between the aphid distribution and time of snow clearance at landscape scale, mapping snow depth at peak of snow accumulation for the two succeeding years 2009 and 2010 and examining site occupancy and plant phenology the following summers. Additionally, the distribution range mapped by Strathdee & Bale (1995) was revisited to address possible changes in range along the coast of the fjord. Results: A linear relation between snow depth and timing of snow melt was found but with strong inter-annual and landscape variation. Both snow depth and plant phenology were found to affect patch occupancy. In August, the aphid, at the three life stages scored (viviparae, oviparae/males and eggs), was present most frequently in those D. octopetala patches with the most advanced plant phenology and which showed shallower snow depths in spring. However, many patches predicted to contain aphids were empty. The aphid distribution range has expanded 4.7 km towards the fjord mouth from 1995. Conclusions: Snow depth alone, and hence date of snow clearance, cannot precisely define species distribution at landscape scale, as this cannot explain why are they unoccupied patches under shallow snow depths with advanced plant phenology. We nonetheless present a model Arctic system that could form the basis for long term monitoring for climate- driven species shifts.