Abstract
This study aimed to reconstruct the climatic moisture conditions of the Mid- Russian Upland through the Holocene. Surface moisture conditions in the study region were inferred from published pollen records from the Klukva peatland, in the north-west of the Mid-Russian Upland. Three climatic indices were derived from previously- published reconstructions of mean annual temperature and precipitation: the Climate Moisture Index, the Aridity Index and the Budyko Dryness Index. A simple modeling approach to reconstruct annual potential evapotranspiration and net radiation was developed and used to estimate the indices for different periods of the Holocene. The moisture indices were compared with independent proxies of climate moisture such as peatland surface wetness, reconstructed from testate amoebae and regional fire activity, reconstructed from charcoal. Results show that the surface moisture conditions in the study region were characterized by large variability. Periods of mild temperature and moderately wet conditions were followed by dry periods, which resulted in significant changes in palaeoenvironments. The method developed for calculation of potential evapotranspiration and indices of surface moisture conditions could be a useful tool for climate reconstructions. Our results demonstrate the detailed and nuanced palaeoclimate data which can be derived from pollen data.
Highlights
Information about spatial and temporal variability of climate and vegetation in past epochs is important for better understanding of climate-vegetation interactions and prediction of possible vegetation changes under future climate change scenarios
The method developed for calculation of potential evapotranspiration and indices of surface moisture conditions could be a useful tool for climate reconstructions
The results of climatic reconstructions based on pollen data from the Klukva peatbog show clear temporal variability in surface moisture conditions, derived by the modelling approaches applied here
Summary
Information about spatial and temporal variability of climate and vegetation in past epochs is important for better understanding of climate-vegetation interactions and prediction of possible vegetation changes under future climate change scenarios. Many methods are based on analysis of pollen data in order to reconstruct long-term temperature variability. While pollen-based temperature reconstructions often perform well, reconstructions of climatic moisture conditions are largely limited to assessing major changes between wetter and drier phases (Velichko et al 2002; Stančikaite et al 2008; Inisheva et al 2013; Kalnina et al 2015). Other studies have compared pollen-based moisture reconstructions to independent reconstructions of local surface moisture based on methods such as plant macrofossil and testate amoeba analysis from peatlands (Lamentowicz et al 2008; Bunbury et al 2012; Gałka et al 2017; Tsyganov et al 2017)
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