Spatial distribution of environmental indicators in surface sediments of Lake Bolshoe Toko, Yakutia, Russia |
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Author: | Biskaborn, Boris K.1; Nazarova, Larisa1,2,3; Pestryakova, Lyudmila A.4; |
Organizations: |
1Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany 2Institute of Geosciences, University of Potsdam, Potsdam, Germany 3Institute of Geology and Petroleum Technologies, Kazan Federal University, Kazan, Russia
4Northeastern Federal University of Yakutsk, Yakutsk, Russia
5Department of Physical Geography and Environment, Herzen State Pedagogical University of Russia, St. Petersburg, Russia 6Department for Geography, Humboldt University Berlin, Berlin, Germany 7Institute for Biological Problems of Cryolithozone Siberian Branch of RAS, Yakutsk, Russia 8Key Laboratory of Submarine Geosciences, State Oceanic Administration, Hangzhou, China 9Department of Earth Sciences, Free University of Berlin, Berlin, Germany 10Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 12.1 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe202003067468 |
Language: | English |
Published: |
Copernicus Publications,
2019
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Publish Date: | 2020-03-06 |
Description: |
AbstractRapidly changing climate in the Northern Hemisphere and associated socio-economic impacts require reliable understanding of lake systems as important freshwater resources and sensitive sentinels of environmental change. To better understand time-series data in lake sediment cores, it is necessary to gain information on within-lake spatial variabilities of environmental indicator data. Therefore, we retrieved a set of 38 samples from the sediment surface along spatial habitat gradients in the boreal, deep, and yet pristine Lake Bolshoe Toko in southern Yakutia, Russia. Our methods comprise laboratory analyses of the sediments for multiple proxy parameters, including diatom and chironomid taxonomy, oxygen isotopes from diatom silica, grain-size distributions, elemental compositions (XRF), organic carbon content, and mineralogy (XRD). We analysed the lake water for cations, anions, and isotopes. Our results show that the diatom assemblages are strongly influenced by water depth and dominated by planktonic species, i.e. Pliocaenicus bolshetokoensis. Species richness and diversity are higher in the northern part of the lake basin, associated with the availability of benthic, i.e. periphytic, niches in shallower waters. δ18Odiatom values are higher in the deeper south-western part of the lake, probably related to water temperature differences. The highest amount of the chironomid taxa underrepresented in the training set used for palaeoclimate inference was found close to the Utuk River and at southern littoral and profundal sites. Abiotic sediment components are not symmetrically distributed in the lake basin, but vary along restricted areas of differential environmental forcing. Grain size and organic matter are mainly controlled by both river input and water depth. Mineral (XRD) data distributions are influenced by the methamorphic lithology of the Stanovoy mountain range, while elements (XRF) are intermingled due to catchment and diagenetic differences. We conclude that the lake represents a valuable archive for multiproxy environmental reconstruction based on diatoms (including oxygen isotopes), chironomids, and sediment–geochemical parameters. Our analyses suggest multiple coring locations preferably at intermediate depth in the northern basin and the deep part in the central basin, to account for representative bioindicator distributions and higher temporal resolution, respectively. see all
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Series: |
Biogeosciences |
ISSN: | 1726-4170 |
ISSN-E: | 1726-4189 |
ISSN-L: | 1726-4170 |
Volume: | 16 |
Pages: | 4023 - 4049 |
DOI: | 10.5194/bg-16-4023-2019 |
OADOI: | https://oadoi.org/10.5194/bg-16-4023-2019 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
1181 Ecology, evolutionary biology 1172 Environmental sciences |
Subjects: | |
Funding: |
This research has been supported by BMBF PALMOD (grant no. 01LP1510D), BMBF (grant no. 5.2711.2017/4.6), Russian Foundation for Basic Research (grant no. 18-45-140053 r_a), North-Eastern Federal University (grant no. SMK-P-1/2-242-17), Russian Science Foundation (grant no. 16-17-10118), Deutsche Forschungsgemeinschaft (grant nos. NA 760/5-1 and DI 655/9-1), and UArctic Chairship. The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association. |
Copyright information: |
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. |
https://creativecommons.org/licenses/by/4.0/ |