Abstract
We used multivariate statistical techniques to analyse the distributions of surface sediment chironomid assemblages with respect to surface-water temperature, and an additional set of 27 environmental variables, in 30 freshwater lakes of northern Fennoscandia. Our study transect spans boreal coniferous forest to subarctic tundra and includes a steep temperature gradient. Canonical correspondence analysis (CCA) with forward selection and associated Monte Carlo permutation tests revealed that there were statistically significant (P<0.05) relationships between chironomid distributions and two environmental variables, namely lakewater temperature and maximum lake depth. A constrained CCA with temperature as the only predictor variable suggested that the relationship between lakewater temperature and chironomid composition was sufficiently robust for developing a weighted-averaging (WA) based quantitative inference model that will allow palaeotemperature reconstructions using subfossil chironomid remains preserved in lake sediments.
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