LAUSR

Abstract Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130–3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman–Olff–Fresco (HOF) models. A series of pollen–climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.