Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques

Zander, Paul D.; Żarczyński, Maurycy; Tylmann, Wojciech; Rainford, Shauna-Kay; Grosjean, Martin (2021). Seasonal climate signals preserved in biochemical varves: insights from novel high-resolution sediment scanning techniques. Climate of the past, 17(5), pp. 2055-2071. Copernicus Publications 10.5194/cp-17-2055-2021

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Varved lake sediments are exceptional archives of paleoclimatic information due to their precise chronological control and annual resolution. However, quantitative paleoclimate reconstructions based on the biogeochemical composition of biochemical varves are extremely rare, mainly because the climate–proxy relationships are complex and obtaining biogeochemical proxy data at very high (annual) resolution is difficult. Recent developments in high-resolution hyperspectral imaging (HSI) of sedimentary pigment biomarkers combined with micro X-ray fluorescence (µXRF) elemental mapping make it possible to measure the structure and composition of varves at unprecedented resolution. This provides opportunities to explore seasonal climate signals preserved in biochemical varves and, thus, assess the potential for annual-resolution climate reconstruction from biochemical varves. Here, we present a geochemical dataset including HSI-inferred sedimentary pigments and µXRF-inferred elements at very high spatial resolution (60 µm, i.e. > 100 data points per varve year) in varved sediments of Lake Żabińskie, Poland, over the period 1966–2019 CE. We compare these data with local meteorological observations to explore and quantify how changing seasonal meteorological conditions influenced sediment composition and varve formation processes. Based on the dissimilarity of within-varve multivariate geochemical time series, we classified varves into four types. Multivariate analysis of variance shows that these four varve types were formed in years with significantly different seasonal meteorological conditions. Generalized additive models (GAMs) were used to infer seasonal climate conditions based on sedimentary variables. Spring and summer (MAMJJA) temperatures were predicted using Ti and total C (R2adj=0.55; cross-validated root mean square error (CV-RMSE) = 0.7 ∘C, 14.4 %). Windy days from March to December (mean daily wind speed > 7 m s−1) were predicted using mass accumulation rate (MAR) and Si (R2adj=0.48; CV-RMSE = 19.0 %). This study demonstrates that high-resolution scanning techniques are promising tools to improve our understanding of varve formation processes and climate–proxy relationships in biochemical varves. This knowledge is the basis for quantitative high-resolution paleoclimate reconstructions, and here we provide examples of calibration and validation of annual-resolution seasonal weather inference from varve biogeochemical data.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Geography > Physical Geography > Unit Paleolimnology
10 Strategic Research Centers > Oeschger Centre for Climate Change Research (OCCR)
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS) > Palaeoecology
08 Faculty of Science > Department of Biology > Institute of Plant Sciences (IPS)

Graduate School:

Graduate School of Climate Sciences

UniBE Contributor:

Zander, Paul David; Rainford, Shauna-Kay Doraine and Grosjean, Martin

Subjects:

500 Science > 540 Chemistry
500 Science > 550 Earth sciences & geology
500 Science > 580 Plants (Botany)
900 History > 910 Geography & travel

ISSN:

1814-9324

Publisher:

Copernicus Publications

Funders:

[4] Swiss National Science Foundation ; [UNSPECIFIED] Polish National Science Centre

Language:

English

Submitter:

Paul David Zander

Date Deposited:

20 May 2021 15:44

Last Modified:

15 Nov 2021 07:51

Publisher DOI:

10.5194/cp-17-2055-2021

BORIS DOI:

10.48350/156383

URI:

https://boris.unibe.ch/id/eprint/156383

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