4.3 Article

Potential bias in 'updating' tree-ring chronologies using regional curve standardisation: Re-processing 1500 years of Tornetrask density and ring-width data

期刊

HOLOCENE
卷 23, 期 3, 页码 364-373

出版社

SAGE PUBLICATIONS LTD
DOI: 10.1177/0959683612460791

关键词

climate; dendroclimatology; maximum latewood density; reconstruction; Tornetrask; tree rings

资金

  1. NERC [NE/G018863/1]
  2. Swedish Research Council VR [VR70454201]
  3. Swedish Research Council FORMAS [VR70454201]
  4. European Union [017008]
  5. Royal Swedish Academy of Sciences [FOA09V-063]
  6. NERC [NE/G018863/1] Funding Source: UKRI
  7. Natural Environment Research Council [NE/G018863/1] Funding Source: researchfish

向作者/读者索取更多资源

We describe the analysis of existing and new maximum-latewood-density (MXD) and tree-ring width (TRW) data from the Tornetrask region of northern Sweden and the construction of 1500 year chronologies. Some previous work found that MXD and TRW chronologies from Tornetrask were inconsistent over the most recent 200 years, even though they both reflect predominantly summer temperature influences on tree growth. We show that this was partly a result of systematic bias in MXD data measurements and partly a result of inhomogeneous sample selection from living trees (modern sample bias). We use refinements of the simple Regional Curve Standardisation (RCS) method of chronology construction to identify and mitigate these biases. The new MXD and TRW chronologies now present a largely consistent picture of long-timescale changes in past summer temperature in this region over their full length, indicating similar levels of summer warmth in the medieval period (MWP, c. CE 900-1100) and the latter half of the 20th century. Future work involving the updating of MXD chronologies using differently sourced measurements may require similar analysis and appropriate adjustment to that described here to make the data suitable for the production of un-biased RCS chronologies. The use of 'growth-rate' based multiple RCS curves is recommended to identify and mitigate the problem of 'modern sample bias'.

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