Holozäne Umweltentwicklung im fernöstlichen Sibirien
Physische Geographie
Zusammenfassung der Projektergebnisse
Russian Far East is an important climate-sensitive region situated at the border of the Eurasian landmass and the North Pacific. It is situated at the eastern end-loop of the global thermohaline ocean conveyor belt and is strongly affected by atmospheric teleconnections (Pacific Decadal Oscillation, El-Niño/Southern-Oscillation, Arctic Oscillation), oceanographic, cryospheric, tectonic, and volcanic processes in the Arctic and subarctic Pacific regions and neighboring landmasses of north-eastern Eurasia. However, Far East remains among the least studied regions on Earth and quantitative climate reconstructions from here are still very rare. Therefore, the motivation of this project is to provide qualitative and quantitative palaeoenvironmental data for a better understanding of Holocene climate dynamics at the continental-maritime intersection in easternmost Eurasia, comprising the Kamchatka Peninsula and the Kurile Islands. We reconstructed the Holocene climate changes along a high- to low-latitude transect that follows the Kurile-Kamchatka Arc. Reconstructions are based on proxies, derived from lake sediments, including chironomids, biomarkers, diatoms, pollen and sedimentological data. One of the most important approach is to develop and apply new regional chironomid-based inference models for reconstructing mean July air temperature (T July). The developed in the course of our project regional inference models for Russian North and Far East is based on a vast data set of the lakes from northern Eurasia that arose from merging together previously developed by us data sets from eastern and western Russia and our new data. The studied lacustrine sediment records included 8 cores (3 from Kamchatka and 5 from Kuril Islands), that were chosen, to cover regional environmental gradients and to provide best temporal resolution. Analysis of the data has demonstrated spatial differences in timing and magnitude of the middle to late Holocene climatic episodes (Holocene Climatic Optimum, Medieval Warm Period, Little Ice Age) and strong influence of the local environmental processes including volcanic activities and neotectonics movements, that often played more important than climate role in development of vegetation and lake ecosystems. Regional to hemispheric-scale forcings associated with climatic fluctuations in the region especially notably influenced landscape development in the Kuril Islands. However, the environmental shifts in these islands are not of similar magnitude and have more complex spatial and temporal patterns. These differences are the result of changes in island sizes during the Holocene transgressions and regressions; microclimatic relief variability in the islands; preservation of island biota in localized refugia when conditions were unfavorable; and disruption of island ecosystems by volcanic activity. To better document the regional pattern of palaeoclimatic events and to unveil the background mechanisms driving the successions in ecosystems in the Kuril-Kamchatka region, more multi-proxy qualitative and quantitative palaeoecological studies are needed. The developed within the frame of the project chironomid database and inference models for reconstructing T July provide valuable instruments in different aspects of palaeoecological studies that can be applied not only regionally but at a broader geographical scale. Within the frame of the current project both, the new chironomid-based databases, and models have been already widely applied for palaeoclimatic reconstructions, pioneering biodiversity studies and for further development of palaeolimnological databases in several regions across Eurasia, including sites in Fennoscandia, West and Central Russia, Polar Ural and Siberia, Altay, Mongolia, and Northern America.
Projektbezogene Publikationen (Auswahl)
-
2015. Northern Russian chironomid-based modern summer temperature data set and inference models. Global and Planetary Change 134: 10-25
Nazarova L, Self A, Brooks SJ, van Hardenbroek M, Herzschuh U, Diekmann B.
-
2017. Changes in temperature and water depth of a small mountain lake during the past 3000 years in Central Kamchatka reflected by chironomid record. Quaternary International 447: 46-58
Nazarova L, Bleibtreu A, Hoff U, Dirksen V, Diekmann B.
-
2017. Reconstruction of Holocene environmental changes in Southern Kurils (North-Western Pacific) based on palaeolake sediment proxies from Shikotan Island. Global and Planetary Change 159: 25– 36
Nazarova L, Grebennikova ТА, Razjigaeva NG, Ganzey LА, Belyanina NI, Arslanov KА, Kaistrenko VМ, Gorbunov АО, Kharlamov АА, Rudaya N, Palagushkina O, Biskaborn BK, Diekmann B
-
2018. Holocene thermokarst and pingo development in the Kolyma Lowland 1 (NE Siberia). Permafrost and Periglacial Processes 29(3): 182-198
Wetterich S, Schirrmeister L, Nazarova L, Palagushkina O, Bobrov A, Pogosyan L, Savelieva L, Syrykh L, Matthes H, Fritz M, Gunther F, Opel T
-
2019. Reconstruction of Holocene environmental changes in North-Western Pacific in relation to paleorecord from Shikotan Island Doklady Earth Sciences 486 (2): 76–80
Nazarova LB, Razjigaeva NG, Diekmann B, Grebennikova ТА, Ganzey LА, Belyanina NI, Arslanov KА, Kaistrenko VМ, Gorbunov АО, Kharlamov АА, Golovatuk LG, Syrykh LS, Subetto DА
-
2019. Spatial distribution of environmental indicators in surface sediments of Lake Bolshoe Toko, Yakutia, Russia. Biogeosciences 16: 4023–4049
Biskaborn BK, Nazarova L, Pestryakova LA, Syrykh L, Funck K, Meyer H, Chapligin B, Vyse S, Gorodnichev R, Zakharov E, Wang R, Schwamborn G, Diekmann B
-
2020. Metrics of structural change as indicators of chironomid community stability in high latitude lakes QSR
Mayfield RJ, Langdon PG, C. Doncaster P, Dearing JA, Wang R, Nazarova LB, Medeiros AS, Brooks SJ
-
2020. Temperature change as a driver of spatial patterns and long-term trends in chironomid (Insecta: Diptera) diversity. Global Change Biology 26: 1155-1169
Engels S, Medeiros AS, Axford Y, Brooks SJ, Heiri O, Luoto TP, Nazarova L, Porinchu DF, Quinlan R, Self AE
