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Removing the no-analogue bias in modern accelerated tree growth leads to stronger medieval drought

Authors: Karl Uwe Heußner; Ernst van der Maaten; Ernst van der Maaten; Tobias Scharnweber; Thomas Struwe; Marko Smiljanic; Marieke van der Maaten-Theunissen; +6 Authors

Removing the no-analogue bias in modern accelerated tree growth leads to stronger medieval drought

Abstract

AbstractIn many parts of the world, especially in the temperate regions of Europe and North-America, accelerated tree growth rates have been observed over the last decades. This widespread phenomenon is presumably caused by a combination of factors like atmospheric fertilization or changes in forest structure and/or management. If not properly acknowledged in the calibration of tree-ring based climate reconstructions, considerable bias concerning amplitudes and trends of reconstructed climatic parameters might emerge or low frequency information is lost. Here we present a simple but effective, data-driven approach to remove the recent non-climatic growth increase in tree-ring data. Accounting for the no-analogue calibration problem, a new hydroclimatic reconstruction for northern-central Europe revealed considerably drier conditions during the medieval climate anomaly (MCA) compared with standard reconstruction methods and other existing reconstructions. This demonstrates the necessity to account for fertilization effects in modern tree-ring data from affected regions before calibrating reconstruction models, to avoid biased results.

Keywords

550, Climate Change, Temperature, Water, Forests, Article, Droughts, Trees, Europe, North America, Life Science, Humans, ddc: ddc:

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    22
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Top 10%
Average
Top 10%
Green
gold