Thursday, August 15, 2013

New paper finds tree-ring proxy temperature data is 'seriously compromised'

More bad news for Michael Mann: A new paper published in Climate of the Past finds that 'modern sample bias' has "seriously compromised" tree-ring temperature reconstructions, producing an "artificial positive signal [e.g. 'hockey stick'] in the final chronology." Needless to say, Mann's hockey sticks are also seriously compromised by statistical techniques that produce hockey sticks from random numbers, use of upside-down data, the trick to hide the decline, the most important tree in the world, use of bristlecone pines which were condemned by the NAS for use as temperature proxies, and a complete lack of validation skill


Much of the work in dendrochronology, and dendroclimatology in particular, relies on accurate, unbiased reconstructions of tree growth long into the past. As a result, a great deal of effort has been put into trying to isolate important trends and identify potential 5 biases. However, one major bias called “modern sample bias”, first identified by Melvin (2004), is still largely neglected in applied studies, despite its potential impact on all regional curve standardization chronologies (Brienen et al., 2012a). 

Dendrochronologists observed that the older a tree was, the slower it tended to grow, even after controlling for age- and time-driven effects. The result is an artificial downward signal in the regional curve (as the older ages are only represented by the slower growing trees) and a similar artificial positive signal in the final chronology (as earlier years are only represented by the slow growing trees), an effect termed modern sample bias. When this biased chronology is used in climate reconstruction it then implies a relatively unsuitable historic climate. Obviously, the detection of long term 15 trends in tree growth, as might be caused by a changing climate or carbon fertilization, is also seriously compromised (Brienen et al., 2012b). More generally, modern sample bias can be viewed as a form of “differing-contemporaneous-growth-rate bias”, where changes in the magnitude of growth of the tree ring series included in the chronology over time (or age, in the case of the regional curve) skew the final curve, especially 20 near the ends of the chronology where series are rapidly added and removed (Briffa and Melvin, 2011).

Clim. Past Discuss., 9, 4499-4551, 2013

A likelihood perspective on tree-ring standardization: eliminating modern sample bias

J. Cecile, C. Pagnutti, and M. Anand
University of Guelph, School of Environmental Sciences, Guelph, Canada
Abstract. It has recently been suggested that non-random sampling and differences in mortality between trees of different growth rates is responsible for a widespread, systematic bias in dendrochronological reconstructions of tree growth known as modern sample bias. This poses a serious challenge for climate reconstruction and the detection of long-term changes in growth. Explicit use of growth models based on regional curve standardization allow us to investigate the effects on growth due to age (the regional curve), year (the standardized chronology or forcing) and a new effect, the productivity of each tree. Including a term for the productivity of each tree accounts for the underlying cause of modern sample bias, allowing for more reliable reconstruction of low-frequency variability in tree growth.

This class of models describes a new standardization technique, fixed effects standardization, that contains both classical regional curve standardization and flat detrending. Signal-free standardization accounts for unbalanced experimental design and fits the same growth model as classical least-squares or maximum likelihood regression techniques. As a result, we can use powerful and transparent tools such as R2 and Akaike's Information Criteria to assess the quality of tree ring standardization, allowing for objective decisions between competing techniques.

Analyzing 1200 randomly selected published chronologies, we find that regional curve standardization is improved by adding an effect for individual tree productivity in 99% of cases, reflecting widespread differing-contemporaneous-growth rate bias. Furthermore, modern sample bias produced a significant negative bias in estimated tree growth by time in 70.5% of chronologies and a significant positive bias in 29.5% of chronologies. This effect is largely concentrated in the last 300 yr of growth data, posing serious questions about the homogeneity of modern and ancient chronologies using traditional standardization techniques.

1 comment:


    Craig Loehle says:
    August 16, 2013 at 8:37 am

    I proposed this theory many years ago ( in 1988 and showed that data support it. The basic idea is that slower growing species (or trees within species) will live longer because the reason they grew slower was better investment in defenses such as thick bark and defensive chemicals. The oldest trees thus have a bigger percentage of the slower growing trees and the young trees are a more random sample, with more fast growing individuals. This creates the bias and the hockey stick.