Developing a modern pollen-climate calibration data set for Norway

Modern pollen-climate data sets consisting of modern pollen assemblages and modern climate data (mean July temperature and mean annual precipitation) have been developed for Norway based on 191 lakes and 321 lakes. The original 191-lake data set was designed to optimize the distribution of the lakes sampled along the mean July temperature gradient, thereby fulfilling one of the most critical assumptions of weighted-averaging regression and calibration and its relative, weighted-averaging partial least-squares regression. A further 130 surface samples of comparable taphonomy, taxonomic detail and analyst became available as a result of other projects. These 130 samples, all from new lakes, were added to the 191-lake data set to create the 321-lake data set. The collection and construction of these data sets are outlined. Numerical analyses involving generalized linear modelling, constrained ordination techniques, weighted-averaging partial least-squares regression, and two different cross-validation procedures are used to asses the effects of increasing the size of the calibration data set from 191 to 321 lakes. The two data sets are used to reconstruct mean July temperature and mean annual precipitation for a Holocene site in northwest Norway and a Lateglacial site in west-central Norway. Overall, little is to be gained by increasing the modern data set beyond about 200 lakes in terms of modern model performance statistics, but the down-core reconstructions show less between-sample variability and are thus potentially more plausible and realistic when based on the 321-lake data set.