46-3 Sat Jan 2 Microhabitat diversity influences physiology and phenology in an Antarctic insect Teets, NM*; Spacht, DE; Potts, LJ; Gantz, JD; Lee, RE; Denlinger, DL; University of Kentucky, Lexington; Ohio State University, Columbus; University of Kentucky, Lexington; Hendrix College, Conway; Miami University, Oxford; Ohio State University, Columbus n.teets@uky.edu http://www.teetslab.com
The midge Belgica antarctica is Antarctica’s only endemic insect and occupies diverse habitats with considerable variation in vegetation, hygric conditions, and temperature. However, the extent to which microhabitat diversity influences fine-scale distribution, physiology, and phenology has not been assessed. To identify ecological drivers of population density, we measured arthropod abundance and microhabitat conditions across five islands. Across plots, midge abundance was highly variable (0-40,000 larvae m-2), and models that included both abiotic and biotic features of the microhabitat best explained this variation. There were few strong predictors of density, but midges tended to be associated with terrestrial algae. In a subsequent study, we assessed the extent to which microhabitat diversity influences phenology and metabolic physiology in five midge populations. Despite the proximity of these habitats (four were on the same island within one hectare), there were considerable differences in thermal conditions, with average temperature differing more than 2°C between the warmest and coolest location. These environmental differences corresponded with physiological differences, as seasonal changes in size, metabolic rate, and biochemical composition were site-specific. There were also significant differences in phenology across sites, indicating that fine-scale microhabitat variation could lead to reduced gene flow between temporally isolated populations. Together, these results indicate that fine-scale environmental characteristics strongly influence the distribution and physiology of midges and should be accounted for when predicting responses to environmental change.