chrysophyte stomatocyst-based reconstruction of cold-season air temperature from Alpine Lake Silvaplana (AD 1500–2003); methods and concepts for quantitative inferences

• Published in: Journal of paleolimnology 2013-12, Vol.50 (4), p.519-533
• Main Authors: de Jong, Rixt, Kamenik, Christian, Westover, Karlyn, Grosjean, Martin
• Format: Article
• Language: English
• Subjects: Air temperature; Algae; Alpine regions; Calibration in time; Chrysophyceae; climate; Climate Change; Climate variability; cold season; Earth and Environmental Science; Earth Sciences; Freshwater & Marine Ecology; Geology; Golden algae; Lakes; Original Paper; Paleoclimate science; Paleolimnology; Paleontology; Physical Geography; regression analysis; Seasons; Sedimentology; sediments; Spring; Statistical models; Surface temperature; Synurophyceae; Transfer functions; Varves; Winter-spring temperature variability
• ISSN: 0921-2728; 1573-0417; 1573-0417
• DOI: 10.1007/s10933-013-9743-5

Relatively little is known about past cold-season temperature variability in high-Alpine regions because of a lack of natural cold-season temperature proxies as well as under-representation of high-altitude sites in meteorological, early-instrumental and documentary data sources. Recent studies have shown that chrysophyte stomatocysts, or simply cysts (sub-fossil algal remains of Chrysophyceae and Synurophyceae), are among the very few natural proxies that can be used to reconstruct cold-season temperatures. This study presents a quantitative, high-resolution (5-year), cold-season (Oct–May) temperature reconstruction based on sub-fossil chrysophyte stomatocysts in the annually laminated (varved) sediments of high-Alpine Lake Silvaplana, SE Switzerland (1,789 m a.s.l.), since AD 1500. We first explore the method used to translate an ecologically meaningful variable based on a biological proxy into a simple climate variable. A transfer function was applied to reconstruct the ‘date of spring mixing’ from cyst assemblages. Next, statistical regression models were tested to convert the reconstructed ‘dates of spring mixing’ into cold-season surface air temperatures with associated errors. The strengths and weaknesses of this approach are thoroughly tested. One much-debated, basic assumption for reconstructions (‘stationarity’), which states that only the environmental variable of interest has influenced cyst assemblages and the influence of confounding variables is negligible over time, is addressed in detail. Our inferences show that past cold-season air-temperature fluctuations were substantial and larger than those of other temperature reconstructions for Europe and the Alpine region. Interestingly, in this study, recent cold-season temperatures only just exceed those of previous, multi-decadal warm phases since AD 1500. These findings highlight the importance of local studies to assess natural climate variability at high altitudes.