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East European chironomid-based calibration model for past summer temperature reconstructions

Authors :
Mateusz Płóciennik
Tomi P. Luoto
Bartosz Kotrys
Ecosystems and Environment Research Programme
Faculty of Biological and Environmental Sciences
Source :
Climate Research. 77:63-76
Publication Year :
2019
Publisher :
Inter-Research Science Center, 2019.

Abstract

Understanding local patterns and large-scale processes in past climate necessitates a detailed network of temperature reconstructions. In this study, a merged temperature inference model using fossil chironomid (Diptera: Chironomidae) datasets from Finland and Poland was constructed to fill the lack of an applicable training set for East European sites. The developed weighted averaging partial least squares (WA-PLS) inference model showed favorable performance statistics, suggesting that the model can be useful for downcore reconstructions. The combined calibration model includes 212 sites, 142 taxa, and a temperature gradient of 11.3-20.1 degrees C. The 2-component WA-PLS model has a cross-validated coefficient of determination of 0.88 and a root mean squared prediction error of 0.88 degrees C. We tested the new East European temperature transfer function in chironomid stratigraphies from a Finnish high-resolution short-core sediment record and a Polish paleolake (Zabieniec) covering the past similar to 20 000 yr. In the Finnish site, the chironomid-inferred temperatures correlated closely with the observed instrumental temperatures, showing improved accuracy compared to estimates by the original Finnish calibration model. In addition, the long-core reconstruction from the Polish site showed logical results in its general trends compared to existing knowledge on the past regional climate trends; however, it had distinct differences when compared with hemispheric climate oscillations. Hence, based on these findings, the new temperature model will enable more detailed examination of long-term temperature variability in Eastern Europe, and consequently, reliable identification of local and regional climate variability of the past.

Details

ISSN :
16161572 and 0936577X
Volume :
77
Database :
OpenAIRE
Journal :
Climate Research
Accession number :
edsair.doi.dedup.....b8cd41ca27425e7ecb92bd6d4ab533ce