Toward an Absolute Chronology at ELK Lake, Minnesota

Aardsma, Gerald E.

doi:10.1017/s0033822200030137

Cited by 4 publications

(6 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Results show that substantial varve chronological errors exist within stratigraphic intervals of obscure laminations characterized by low carbonate contents. In conjunction with other varve records (e.g., Sprowl, 1993;Hajdas et al, 1995a,b;Aardsma, 1996;Brauer et al, 2000), these results underscore the importance of verifying varve counts with an independent chronology.…”

Section: Introductionsupporting

confidence: 63%

“…For example, cumulative errors of varve counting are often greater than 10% (e.g., Sprowl, 1993;Aardsma, 1996), potentially jeopardizing the reliability of palaeostudies that require determination of precise timing. *Authors for correspondence (e-mails: jiantian@uiuc.edu, fshu@life.…”

Section: Introductionmentioning

confidence: 99%

“…However, the accuracy of a varve-based chronology is susceptible to various sources of error, including discontinuous varve deposition through time, obscure laminations and human counting error. For example, cumulative errors of varve counting are often greater than 10% (e.g., Sprowl, 1993;Aardsma, 1996), potentially jeopardizing the reliability of palaeostudies that require determination of precise timing. *Authors for correspondence (e-mails: jiantian@uiuc.edu, fshu@life.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of varve and 14C chronologies from Steel Lake, Minnesota, USA

Tian

Brown

2005

The Holocene

View full text Add to dashboard Cite

Annually laminated sediments (varves) offer an effective means of acquiring high-quality palaeoenvironmental records. However, the strength of a varve chronology can be compromised by a number of factors, such as missing varves, ambiguous laminations and human counting error. We assess the quality of a varve chronology for the last three millennia from Steel Lake, Minnesota, through comparisons with nine AMS 14C dates on terrestrial plant macrofossils from the same core. These comparisons revealed an overall 8.4% discrepancy, primarily because of missing/uncountable varves within two stratigraphic intervals characterized by low carbonate concentrations and obscure laminations. Application of appropriate correction factors to these two intervals results in excellent agreement between the varve and 14C chronologies. These results, together with other varve studies, demonstrate that an independent age-determination method, such as 14C dating, is usually necessary to verify, and potentially correct, varve chronologies.

show abstract

Section: Introductionsupporting

confidence: 63%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of varve and 14C chronologies from Steel Lake, Minnesota, USA

Tian

Brown

2005

The Holocene

View full text Add to dashboard Cite

show abstract

“…The modern technique of radiocarbon dating of terrestrial macrofossils by accelerator mass spectrometry (AMS) reduces that problem, but few pollen sites in the area have enough such dates to detect anomalies and to establish the convincing temporal vegetational and climatic gradients. Varved sediments can provide an alternative approach to dating, but the uncertainties caused by variations in varve quality may result in a substantial cumulative error when attempts are made to count a series from the very top of the sediment to the base (Sprowl, 1993;Aardsma, 1996). These problems have made it questionable to use lake-sediment records from this region to test hypotheses about abrupt large-scale climatic dynamics (Dean et al, 2002), such as the 8.2 ka cal BP event recorded in the Greenland ice cores and European lake sediments.…”

Section: Introductionmentioning

confidence: 99%

A chronological framework for the Holocene vegetational history of central Minnesota: the Steel Lake pollen record

Wright

Stefanova

Tian

et al. 2004

Quaternary Science Reviews

View full text Add to dashboard Cite

Paleorecords from Minnesota and adjacent areas have often been used to evaluate large-scale climatic processes in the mid-continent of North America. However, most of these records are compromised by chronological flaws, making problematic any comparisons with climatic interpretations based on other records (e.g., GISP2 in Greenland). We report here a high-resolution pollen record with a secure chronology constrained by 26 14 C dates on terrestrial macrofossils from Steel Lake, central Minnesota. About 11,200 years ago (calibrated yr BP) the late-glacial Picea forest near Steel Lake was succeeded abruptly by Pinus banksiana and/or resinosa. The Pinus forest began to open 9.4 ka cal BP with the expansion of prairie taxa, and a pine parkland or savanna prevailed until about 8 ka cal BP, when Quercus replaced Pinus to become the dominant tree in the prairie areas for 4500 years. The close chronological control permits the correlation of key vegetational changes with those at other reliably dated sites in the eastern Dakotas and in Minnesota, suggesting that the abrupt decline of the spruce forest was time-transgressive from southwest to northeast during 2000 years, and that the development of prairie was time-transgressive in the same direction over 2600 years. Correlation of key pollen horizons at Steel Lake with those in the high-resolution pollen profiles of Elk Lake, ca. 50 km northwest of Steel Lake, suggests that the well-known Elk Lake varve chronology for the early Holocene is about 1000 years too young.

show abstract

“…However, the manual counting of varves is time consuming, costly and error-prone with an uncertainty typically in the order of 2-5% (Ojala et al, 2012), although, many examples of parallel varve counts and radiocarbon dating have shown erros in the order of 10-15% (Sprowl, 1993;Aardsma, 1996;Tian et al, 2005). In general, automatic and semiautomatic counting algorithms decide the use of fixed values of the decision quantity and therefore, flexible decisions are ultimately impossible (Zolitschka, 1996;Francus, et al 2002;Ojala et al, 2012).…”

Section: Accepted Manuscriptmentioning

confidence: 99%