Quantitative reconstructions of Holocene and Late Pleistocene palaeotemperatures in Yakutia, North-Eastern Russia using regional Chironnomid inference model
Zusammenfassung der Projektergebnisse
The Republic of Yakutia, is located in the northeastern part of Russia. This part of Eurasia represents one of the Earth’s most extreme semi-arid continental settings, whose role in the Arctic climate system so far is poorly understood. Main focus of our project was to develop a regional chironomid inferred temperature model for Yakutia, and to make a high-resolution Holocene and Late Pleistocene temperature reconstructions in Yakutia using this model. In total 201 lakes were investigated. Based on the availability of chironomids remains in sediments 150 of them were included into the statistical analysis. A total of 147 taxa were identified in all investigated lakes. Complete list of chironomid taxa found in Central Yakutian lakes is published at Russian Chironomid homepage (http://www.biosoil.ru/tendipes/catalog.htm). T July and water depth were identified as the strongest predictor variables explaining the chironomid communitiy composition and distribution of the taxa in our data set. The first in Northern Russia chironomid inference models for quantitative reconstructions of Mean July and Water Depth fluctuations models were developed using two unimodal regression calibration techniques: simple weighted averaging (WA) and weighted averaging partial least squares (WA-PLS). The twocomponent TJuly WA-PLS model had the best performance. It produced a strong coefficient of determination (r 2 boot = 0.87), root mean square error of prediction (RMSEP = 1.93), and max bias (max bias boot = 2.17). For WD, the one-component WA-PLS model had the best performance (r2 boot = 0.62, RMSEP = 0.35, max bias boot = 0.47). Merging Yakutian and other data sets (64 lakes from Polar Ural and west Siberia and 157 Norwegian lakes) has shown that chironomid assemblages were most strongly correlated with mean July air temperature in both the Russian and Norwegian datasets. Two chironomid inferred statistical models have been developed: West Siberian chironomidinferred temperature model; first in the world chironomid-continentality inference model. Analysis of a range of chironomid-inferred temperature model suggest the best to be a two component weighted averaging and partial least squares (WA-PLS model) with r2jack = 0.92 and RMSEP = 0.89°C. The differing responses between the Norwegian and Russian faunas led to the development of a 149 lake, 120 taxa chironomid-continentality inference model. The 2-component WA-PLS model was the minimal adequate model with r2jack = 0.73 and RMSEP = 9.9. A continentality model has the potential to detect these seasonal changes in climate. Reconstruction of the Holocene and late Pleistocene palaeoclimate variability in Yakutia, using the model and advanced analysis of the fossil chironomid fauna from 3 long sediment cores using the Noth Russian chironomid incerence model revealed Mid- Holocene maximum took place between 7,0 to 4,5 kyr BP. The quality of the predictive strength of the model was tested during the multy - proxy investigation of the paleontological records of western Beringia during the last interglacial, 100 kyr BP. For quantitative MTWA reconstructions of the last interglacial, three different methods were used for the various bioindicators in the Oyogos Yar record. The pollen-based BMA reconstruction resulted in a MTWA range between 11°C and 17.6°C with a most probable value of 13°C. The mutual climatic range of plant species found in the macrofossil record falls between 12.7 and 13.6°C for MTWA. An MTWA of 12.9 ± 0.9°C and a water depth of 1.00 ± 0.34 m were reconstructed using transfer functions based on the chironomid assemblages. Very important result of this investigation was high level of conformity of the reconstruction of air temperature made with chironomid inference model with the results obtained from other palaeoecological proxies. Results of the investigations are of a special interest for a worldwide Corporate Strategy project “Industry Impacts of Climate Change”.
Projektbezogene Publikationen (Auswahl)
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2007. Chironomid larvae (Diptera: Chironomidae) as palaeoclimatic proxy. Advances in Current Biology. 127 (6) 601-613. (in Russian)
Nazarova L.B., Brooks S.J.
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2007. Limnological characteristics of lakes in the lowlands of Central Yakutia, Russia. Journal of Limnology 66: 40–53
Kumke T., Ksenofontova M., Pestryakova L., Nazarova L., Hubberten H.-W.
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2008. Chironomids (Diptera: Chironomidae) of Central Yakutian lakes and their indicative potential for palaeoclimatic investigations. Contemporary problems of ecology. 1(3): 335-345
Nazarova L., Pestryakova L.A., Ushnickaja L.A., Hubberten H.-W.
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2008. Diatom responses to 20th century climate warming in lakes from the northern Urals, Russia. Palaeogeography, Palaeoclimatology, Palaeoecology 259: 96 –106
Solovieva N, Jones VJ., Birks HJ.B, Appleby PG., Nazarova L.
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2008. Zooplankton of Vilyuy Lowland lakes. Scientific transactions of KSU. Series: natural sciences. 150 (1): 114-120. (in Russian)
Kondrateva Т.А., Sokolova V.А., Pestrjakova L.А., Nazarova L.B., Diekmann B.
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2009. Altay Mountains as a key region for climate driven ecological research. Environmental Radioecology and Applied Ecology. 15(2); 3-7
Nazarova L., D. Nourgaliev, L. Frolova, O. Palagushkina, N. Rudaya, D. Nazarov, O. Tumanov, Kosareva L., P. Krylov, L. Gafiatullina, D. Gilmanova, R. Sabirov
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2009. Zooplanktonic communities of arctic lakes and main abiotic factors forming them. Scientific transactions of KSU. Series: natural sciences. 151 (2). (in russian)
Frolova L.A., Nazarova L.B., Pestryakova L., Herzschuh U.
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2010. Chironomid-based inference models for estimating mean July air temperature and water depth from lakes in Yakutia, northeastern Russia. Journal of Palaeolimnology
Nazarova L., Herzschuh U., Wetterich S., Kumke Th., Pestjakova L.
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The role of benthic bioindicators in palaeoclimatic investigations. Science and Innovations in Modernization of Russia and World Development: International Humboldt Conference, 22 – 24 April 2010, Moscow. Moscow Humboldt Club; Eds. Т.S. Illarionova- М.: Institute for Energy of knowledge, 2010. - 223 pp. (in Russian)
Nazarova L.