A 274-lake calibration data-set and inference model for chironomid-based summer air temperature reconstruction in Europe

A 274-lake calibration data-set for chironomid-based temperature reconstruction is presented which is based on the taxonomic amalgamation of a 117-lake data-set from Switzerland and a 157-lake data-set from Norway and Svalbard. Taxonomic consistency of the two data-sets was ensured by joint microscope sessions by the two involved analysts, re-identifying chironomid assemblages in the Swiss data-set to reach an identical taxonomic resolution as in the Norwegian data, and by double-checking selected samples of the Norwegian calibration data-set. The combined Swiss-Norwegian calibration data-set contains information on the distribution of 154 chironomid taxa over a July air temperature range of 3.5-18.4 degrees C, a pH range of 4.7-8.8, and an altitudinal range of 5-2815 m asl from lakes in temperate, subarctic, arctic, and alpine environments. Inference models developed based on this data-set using weighted averaging-partial least squares (WA-PLS) regression outperformed inference models based on maximum likelihood regression. After outlier deletion WA-PLS regression predicted July air temperature with a bootstrapped (cross-validated) root mean squared error of prediction (RMSEP) of 1.40 degrees C. Inference models developed from the separate regional data-sets have an RMSEP of 1.16 and 1.43 degrees C for the Norwegian and the Swiss calibration data-set, respectively. The WA-PLS inference model based on the Norwegian data-set adequately predicted July air temperature based on chironomid assemblages in the Swiss data-set (RMSEP 2.05 degrees C; r(2) 0.74). In contrast, the WA-PLS model based on the Swiss chironomid assemblages performed poorly in inferring July air temperatures based on the Norwegian chironomid assemblages (RMSEP 2.70 degrees C; r(2) 039). We attribute this discrepancy to the large proportion of chironomid taxa in Norwegian samples not represented in the Swiss data-set, the larger range of both pH and lake types included in the Norwegian calibration data-set, and the lack of some chironomid taxa with an arctic and boreal distribution in the Swiss data-set. The WA-PLS inference model based on the combined Swiss-Norwegian calibration data-set is the largest taxonomically consistent chironomid-based inference model available to date and outperforms other existing models if the r(2) and RMSEP relative to the overall temperature gradient are examined. We demonstrate that the combined model can reconstruct a larger range of temperatures when applied to fossil assemblages than models based on the Norwegian or Swiss calibration data-sets only. The combined data-set includes the majority of chironomid taxa expected in late Pleistocene and Holocene sediments of lakes from Northern, Eastern, and Central Europe as well as from southern European mountain lakes. The newly developed WA-PLS inference model is therefore well suited for developing continental-scale reconstructions of late Quaternary temperature change based on chironomid records from different parts of Europe.