A Closer Look at Regional Curve Standardization of Tree-Ring Records: Justification of the Need, aWarning of Some Pitfalls, and Suggested Improvements in Its Application - Dendroclimatology - page 140

The technique of aligning and averaging tree index series by ring age allows
the investigation of bias. Comparison of tree indices sorted according to different
criteria (e.g., by contemporaneous growth rate (Fig. 5.4b ) , tree age, tree diameter,
latitude, altitude, aspect, or packing density) will allow the identification of potential
systematic biases in RCS chronologies. The technique of 'end-aligning' (Fig. 5.7 ) ,
in which both the age-related trend and the climate signal are removed, is an addi-
tional method of identifying potential bias (Section 5.4.3.2 ) . The signal-free method
is also a tool that can be used to test for residual bias in chronologies; measurement
series are divided by the final chronology and the residual signal will represent bias,
or the limits of the standardization method (Melvin and Briffa 2008 ) .
The count of trees needed to produce a 'robust' chronology is often gauged by
using the mean interseries correlation to calculate the expressed population signal
(EPS; Wigley et al. 1984 ; Briffa and Jones 1990 ) . However, estimates of EPS are
strongly influenced by (biased towards) the correspondence between index series
on short (primarily interannual) timescales. Experiments using ring width data from
Torneträsk (Grudd et al. 2002 ) and Finnish Lapland (Eronen et al. 2002 ) have eval-
uated the robustness of chronology confidence in RCS. This work (Melvin 2004 ,
Section 6.3.3) explored the influence on the standard deviations of chronologies
(the average standard deviation of all yearly values) produced by varying sample
counts in differently filtered tree index series. The results suggest that if a replica-
tion of 10 trees is required for a 30-year high-pass-filtered chronology to exhibit a
specific mean standard deviation, a 100-year high-pass-filtered chronology would
require a replication of 18 samples, while an RCS chronology would need 62 con-
stituent samples to achieve the same standard deviation. Increasing tree counts can
improve chronology confidence, but will not remove systematic bias. Mitigating
bias in RCS may improve confidence but will not remove the requirement for large
sample replication.
The age band decomposition (ABD) method (Briffa et al. 2001 ) amounts to
an alternative method of applying the RCS technique. If the mean value of each
'age band' is aligned by ring age, it will form a stepped version of the RCS curve.
The ABD method therefore suffers from many of the problems of RCS, especially
'modern-sample bias,' and equal care must be taken in the use of this method and
in the interpretation of the results.
Subfossil chronologies, like modern chronologies, are still susceptible to the
contemporaneous-growth-rate bias. One possibility of mitigating this bias is to iden-
tify and remove the influence of fast- versus slow-grown trees, but only when they
are identified in samples growing under the same climate conditions.
Some modifications of the application of RCS go some way towards obtaining
these objectives, ranging from the alternative use of two sub-RCS curves (Esper
et al. 2002 ) to the use of multiple RCS curves (Melvin 2004 , Section 5.7 ) . In
the former, two different classes of RCS curve shape are identified from among
those in the full dataset, and each is applied separately to the relevant group of
sample series. This process removes substantial potential bias that would result
from detrending series that exhibit linearly decreasing ring widths with age with
an expectation of exponential decay and vice versa. However, this is an extreme