Christian Schölzel

Transfer Functions for Paleoclimate Reconstructions — Theory and Methods

In this chapter, all within the KIHZ-community used methods for deriving transfer functions in order to reconstruct paleoclimatic variables are introduced. The aim is to provide the conceptual and statistical background of the methods which are used throughout this book. A short review is given on the use of probability density functions in paleoecology. We then focus on linear and non-linear regression methods, among them are weighted averaging, weighted averaging partial least squares regression, both frequently used in paleolimnology, as well as neural network regression, which is recently used in pollen-based paleoclimate reconstructions. In addition, we review some of the validation methods for transfer functions.

Transfer Functions for Paleoclimate Reconstructions — Applications

The aim of this study was to describe the applicability and the use of transfer functions in paleoclimate and paleoenvironmental research. In this chapter, different proxies (i.e. pollen, diatoms, carbon isotopes) were used in order to reconstruct the regional climate and environmental history throughout the Holocene. Case studies based on WA and WA-PLS transfer functions using diatoms showed the capability of siliceous algae to record environmental and climatic changes. However, the paleotemperature reconstruction from diatoms and their comparison with a pollen-based temperature reconstruction at Lake Lama, Siberia only revealed similar trends indicating different processes affecting the diatoms and pollen. The WA-based TP reconstructions from diatoms at Lake Woserin and Lake Holzmaar, Germany showed the response of the organisms to increased anthropogenic activities additionally to climate. Temperature reconstructions using carbon isotopes from tree-rings at high elevation sites of the Tibetan Plateau indicated that tree growth is temperature limited, although anthropogenic effects of changing atmospheric δ13CO2 and pCO2 may influence the calibration with measured meteorological data. Beside these reconstructions, we presented the methodology of a probability-based approach for a paleoclimate reconstruction using pollen distributions from sediments of the Dead Sea which is currently carried out.