Reconstructing climate change quantitatively over millennial timescales is crucial for understanding the processes that affect the climate system. One of the best methods for producing high resolution, low error, quantitative summer air temperature reconstructions is through chironomid analyses. We analysed over 50 lakes from NW and W Iceland covering a range of environmental gradients in order to test whether the distribution of the Icelandic chironomid fauna was driven by summer temperature, or whether other environmental factors were more dominant. A range of analyses showed the main environmental controls on chironomid communities to be substrate (identified through loss-on-ignition and carbon content) and mean July air temperature, although other factors such as lake depth and lake area were also important. The nature of the Icelandic landscape, with numerous volcanic centres (many of which are covered by ice caps) that produce large quantities of ash, means that relative lake carbon content and summer air temperature do not co-vary, as they often do in other chironomid datasets within the Arctic as well as more temperate environments. As the chironomid–environment relationships are thus different in Iceland compared to other chironomid training sets, we suggest that using an Icelandic model is most appropriate for reconstructing past environmental change from fossil Icelandic datasets. Analogue matching of Icelandic fossil chironomid datasets with the Icelandic training set and another European chironomid training set support this assertion. Analyses of a range of chironomid-inferred temperature transfer functions suggest the best to be a two component WA-PLS model with r ² _jack = 0.66 and RMSEP = 1.095°C. Using this model, chironomid-inferred temperature reconstructions of early Holocene Icelandic sequences show the magnitude of temperature change compared to contemporary temperatures to be similar to other NW European chironomid sequences, suggesting that the predictive power of the model is good.