Abstract

AbstractNumerical techniques were used to study chironomid distribution and abundance in lakes from a 1000 km transect in Finland, with special interest on the effect of local summer air temperatures on chironomid assemblages. The final aim of the study was to develop a chironomid‐based palaeotemperature inference model. The dataset consisted of 82 lakes (of which 77 were used in the model after deletion of outliers), with catchments spanning from boreal coniferous forests to mountain birch woodland and tundra vegetation. Numerical analysis showed that the mean July air temperature was the most significant variable explaining the distribution and abundance of chironomids in Finnish lakes. Weighted‐averaging partial least squares techniques were used to develop a palaeotemperature inference model for mean July air temperature reconstructions. The model performance statistics were favourable, with cross‐validated coefficient of determination (r2) of 0.78, root mean squared error of prediction of 0.721°C and maximum bias of 0.794°C. Based on these values, the transfer function is a valid means of performing quantitative palaeotemperature estimates in downcore studies. Copyright © 2008 John Wiley & Sons, Ltd.

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