Chironomids as indicators of climate change: a 100‐lake training set from a subarctic region of northern Sweden (Lapland)
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Multivariate numerical analyses (DCA, CCA) were used to study the distribution of chironomids from surface sediments of 100 lakes spanning broad eco‐climatic conditions in northern Swedish Lapland. The study sites range from boreal forest to alpine tundra and are located in a region of relatively low human impact. Of the 19 environmental variables measured, ordination by CCA identified mean July air temperature as one of the most significant variables explaining the distribution and the abundance of chironomids. Loss‐on‐ignition (LOI), maximum lake depth and mean January air temperature also accounted for significant variation in chironomid assemblages. A quantitative transfer function was created to estimate mean July air temperature from sedimentary chironomid assemblages using weighted‐averaging partial least squares regression (WA‐PLS). The coefficient of determination was relatively high (r2 = 0.65) with root mean squared error of prediction (RMSEP, based on jack-knifing) of 1.13 °C and maximum bias of 2.1 °C, indicating that chironomids can provide useful quantitative estimates of past changes in mean July air temperature. The paper focuses mainly on the relationship between chironomid composition and July air temperature, but the relationship to LOI and depth are also discussed.
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