T. Kumke

Combining ordination techniques and geostatistics to determine the patterns of diatom distributions at Lake Lama, Central Siberia

The patterns of spatial variation of diatom assemblages from surface sediments in Lake Lama were quantified using a combined approach of ordination and geostatistics. The aims were (i) to estimate the amount of variation between diatom assemblages within the lake, (ii) to model the spatial variability of the diatom assemblages and their diversity, and (iii) to map the diatom distributions in the lake. A correspondence analysis (CA) separated the diatom assemblages into a planktonic and a periphytic group. Rheophilic taxa were found within the periphytic group. Variogram analysis showed that only the sample scores of the first CA axis and the Shannon diversity index were spatially structured. The range of spatial correlation was estimated to be 55 km for both variables. The diversity and, to a lesser extent, the sample scores had considerable small-scale variability of about 20 and 3%, respectively. Estimates of the first component of the CA and the Shannon index were derived using block-kriging. The maps of the estimates provided a basis for partitioning Lake Lama according to the spatial structures into an eastern and a western basin, a north–south connection between the basins, and a north–south directed tip at the far eastern end. It was shown that variation in diatom assemblages is mainly spatially structured at the catchment scale and that there is a considerable amount of variation at smaller scales. According to the modeled spatial distribution, the assemblages are most likely affected by the lake size, morphology, and the water and nutrient input introduced by rivers. This has to be taken into account when paleolimnological interpretations are drawn from records of complex lake systems like Lake Lama.

Spatial variability of sedimentological properties in a large Siberian lake

Abstract.The analysis of spatial variability of lake sediment properties in Lake Lama, Central Siberia is presented. The aims were to characterize the spatial structure in lake sediment composition, to determine major spatial patterns of sediment properties by calculating estimates at locations where no samples were available, and to assess the main processes determining these patterns. Sediment properties were measured at 71 spatially distributed locations in the lake, comprising particle size distribution, biogeochemical properties such as total organic carbon, total nitrogen or stable carbon isotopes, as well as geochemical distribution of major and trace elements. Spatial analysis consisted of a principal components analysis and, subsequently, calculation and modelling of variograms to describe the spatial structure in the data as well as determination of spatial estimates using block-kriging to map spatial structure. The results showed that particle size, biogenic silica, CaO, δ13Corg, Zr and TOC/TN ratio were a major source of variability in sediment properties and, thus, dominate the sediment structure in Lake Lama. Major anomalies occurred near river inlets, depending on river size and its position as well as slope of the river bed. Other anomalies were associated with water depths, morphology of the lake basins, and wind-induced currents and re-suspension in the shallow part of the western basin. The spatial structure in sediment properties indicate that several processes act at different spatial scales. Moreover, there was a considerable amount of smallscale variability that could not be quantified due to sampling design. The results showed that heterogeneity in lake sediment composition is a main characteristic of large lake systems, and must be taken into account, especially in paleolimnological and environmental applications.

Inferred Holocene Paleotemperatures from Diatoms at Lake Lama, Central Siberia

Abstract Variations of the diatom distribution in a lake sediment core of Lake Lama, Central Siberia, were used to reconstruct paleotemperatures during the Holocene. The changes of the diatom assemblages revealed a strong association to climatic changes during this period. A transfer function based on weighted averaging partial least squares regression (WA-PLS), derived from a calibration dataset from northwestern Finnish Lapland, was used to infer July air temperatures for the area around Lake Lama. The prediction accuracy of the diatom-temperature model was 0.89°C. The analysis of the modern vs. core assemblages showed the suitability of the model for the lake sediment core. The reconstruction yielded a rapid increase in temperature at the beginning of the early Holocene. There was a period between 8000 and 6500 cal. yr BP with slightly higher temperatures, which were assigned to the Holocene thermal optimum (Hypsithermal), followed by a short and distinct temperature decrease. The period between 4000 and 2800 cal. yr BP again revealed higher temperatures. The inferred temperatures are consistent in their trends with a pollen-based paleotemperature reconstruction of the same core. The range of the diatom-based temperatures was 1.6°C, which is low compared to that of the pollen-based temperatures. This discrepancy may be explained by over- and underestimation of temperatures at the edges of the temperature range by our diatom-based model, and by the large size of this water body which could have moderated the response of diatoms to the temperature signal. The inferred temperature trends from the diatom assemblages at Lake Lama show the potential of aquatic organisms for paleoclimatic reconstructions. This is one of the very few quantitative paleoclimate reconstructions in arctic Russia. Previous research was limited mainly due to the lack of available calibration datasets. Our results also imply that, although this lack might be a drawback, an ecologically sound and reliable reconstruction is still possible and needs to be carried out in other parts of the arctic regions in order to obtain a more detailed knowledge about past regional climate and environmental changes.

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.