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New Paper: Many Tree-Ring Analyses Highly Biased, Unreliable

Paging Michael Mann: A paper published this week finds that many tree-ring proxy studies are highly biased and calls for “great caution in the interpretation of historical growth trends from tree-ring analyses.” The authors find that “big tree selection bias” resulted in a fictitious “doubling in growth rates over recent decades.” Consequently, tree-ring analyses claiming to link growth rates to historical temperatures would show a fictitious large ‘hockey stick’ increase in temperature over recent decades.

Key Points

  • Observed increases in tree ring widths may be caused by sampling biases
  • Standard sampling methods lead to spurious trends in historical growth rates
  • Reported increases in ring width may often not be due to CO2 fertilization
Roel J. W. Brienen
School of Geography, University of Leeds, Leeds, UK
Programa de Manejo de Bosques de la Amazonía Boliviana, Riberalta, Bolivia
Emanuel Gloor
School of Geography, University of Leeds, Leeds, UK
Pieter A. Zuidema
Programa de Manejo de Bosques de la Amazonía Boliviana, Riberalta, Bolivia
Ecology and Biodiversity, Institute of Environmental Biology, Faculty of Science, Utrecht University, Utrecht, Netherlands
Forest Ecology and Forest Management, Centre for Ecosystem Studies, Wageningen, Netherlands
Tree ring analysis allows reconstructing historical growth rates over long periods. Several studies have reported an increasing trend in ring widths, often attributed to growth stimulation by increasing atmospheric CO2 concentration. However, these trends may also have been caused by sampling biases. Here we describe two biases and evaluate their magnitude. (1) The slowgrower survivorship bias is caused by differences in tree longevity of fast- and slow-growing trees within a population. If fast-growing trees live shorter, they are underrepresented in the ancient portion of the tree ring data set. As a result, reconstructed growth rates in the distant past are biased toward slower growth. (2) The bigtree selection bias is caused by sampling only the biggest trees in a population. As a result, slow-growing small trees are underrepresented in recent times as they did not reach the minimum sample diameter. We constructed stochastic models to simulate growth trajectories based on a hypothetical species with lifetime constant growth rates and on observed tree ring data from the tropical tree Cedrela odorata. Tree growth rates used as input in our models were kept constant over time. By mimicking a standard tree ring sampling approach and selecting only big living trees, we show that both biases lead to apparent increases in historical growth rates. Increases for the slow-grower survivorship bias were relatively small and depended strongly on assumptions about tree mortality. The big-tree selection bias resulted in strong historical increases, with a doubling in growth rates over recent decades. A literature review suggests that historical growth increases reported in many tree ring studies may have been partially due to the big-tree sampling bias. We call for great caution in the interpretation of historical growth trends from tree ring analyses and recommend that such studies include individuals of all sizes.