An evaluation of the influence of water depth and river inflow on quantitative Cladocera-based temperature and lake level inferences in a shallow boreal lake

Abstract

Hydrological parameters can potentially have an overwhelming influence on sedimentary assemblages of Cladocera at certain sampling sites that can cause problems for palaeoenvironmental reconstructions. We applied a previously developed Cladocera-based inference model of water depth and a mean July air temperature transfer function developed in this study to a surface sediment dataset of fossil Cladocera from a lake in eastern Finland aiming to investigate the influence of stream flow and water depth on reconstruction results. The developed temperature-inference model, using the weighted averaging-partial least squares technique, had relatively favourable performance statistics suggesting that it is valid in means of performing temperature estimations. When the temperature model was applied to the intralake samples, the lotic samples had inferred values mostly within the model’s prediction error and only one lotic sample showed an underestimated temperature. Samples taken from depths over ~3 m inferred generally underestimated temperatures, although most of the values were within the model’s prediction error. The water depth reconstructions correlated significantly with the measured water depth, but the shallowest samples and most of the lotic samples yielded overestimated inferred values and the samples taken from depths >5 m showed underestimated values. In both reconstruction sets, the inferred values were underestimated in samples taken from deeper sites. Based on the present results, it may be recommendable that downcore sediment samples should be taken from intermediate depths, where also the diversity is higher, and deepest sites and inflows should be avoided. However, more research is needed to validate these results in a larger geographical context.