Double the dates and go for Bayes - Impacts of model choice, dating density and quality on chronologies

被引:134
作者
Blaauw, Maarten [1 ]
Andres Christen, J. [2 ]
Bennett, K. D. [3 ,4 ]
Reimer, Paula J. [1 ]
机构
[1] Queens Univ Belfast, Sch Nat & Built Environm, Belfast BT7 1NN, Antrim, North Ireland
[2] Ctr Invest Matemat CIMAT, Guanajuato 36023, Guanajuato, Mexico
[3] Univ St Andrews, Sch Geog & Sustainable Dev, St Andrews KY16 9AL, Fife, Scotland
[4] Queens Univ Belfast, Queens Marine Lab, Portaferry BT22 1PF, North Ireland
关键词
Age-depth model; Radiocarbon dates; Chronological uncertainties; Bayesian statistics; AGE-DEPTH MODELS; CLIMATIC-CHANGE; LAKE-SEDIMENTS; RAISED BOGS; RADIOCARBON; RECORD; MIDHOLOCENE; AMS;
D O I
10.1016/j.quascirev.2018.03.032
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Reliable chronologies are essential for most Quaternary studies, but little is known about how age-depth model choice, as well as dating density and quality, affect the precision and accuracy of chronologies. A meta-analysis suggests that most existing late-Quaternary studies contain fewer than one date per millennium, and provide millennial-scale precision at best. We use existing and simulated sediment cores to estimate what dating density and quality are required to obtain accurate chronologies at a desired precision. For many sites, a doubling in dating density would significantly improve chronologies and thus their value for reconstructing and interpreting past environmental changes. Commonly used classical age-depth models stop becoming more precise after a minimum dating density is reached, but the precision of Bayesian age-depth models which take advantage of chronological ordering continues to improve with more dates. Our simulations show that classical age-depth models severely underestimate uncertainty and are inaccurate at low dating densities, and also perform poorly at high dating densities. On the other hand, Bayesian age-depth models provide more realistic precision estimates, including at low to average dating densities, and are much more robust against dating scatter and outliers. Indeed, Bayesian age-depth models outperform classical ones at all tested dating densities, qualities and time scales. We recommend that chronologies should be produced using Bayesian age-depth models taking into account chronological ordering and based on a minimum of 2 dates per millennium. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:58 / 66
页数:9
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