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 132

line) was not a good fit to the measured data, systematically underestimating the
juvenile values and overestimating the measured data for tree ages between 250
and 500. This situation arose because the linear fit was influenced by high-density
values measured in relatively old-age trees, many of which experienced the relative
warmth of the twentieth century in parallel in their later years. In other words, the
climate signal (as represented in the final years of the chronology) was not averaged
out in the later (oldest) section of the RCS curve. A more appropriate, unbiased
RCS curve is derived (the thick line of Fig. 5.10d ) by using a 'signal-free' approach
where the chronology variance (i.e., the best estimate of the growth-forcing signal)
is iteratively removed from the measurement series so that the resulting age-aligned
averaged measurements contain substantially little or no variance associated with
the common forcing (see Appendix, and Melvin and Briffa 2008 ) .
The density chronology produced by using the new 'unbiased' RCS curve dis-
plays potentially higher values after about 1800, and much of the comparative recent
decline in the density compared to ring width chronology is removed (Fig. 5.11d ) .
The same correction could have been achieved in this case by excluding the longest-
lived tree density samples or by fitting the RCS curve only on the data extracted from
tree rings up to 500 years old and extrapolating the RCS curve to give RCS values
for older trees. The relevant conclusion, however, is that it is important to use a
nonbiased representation of the RCS curve. Where replication is low or when there
are few samples representing the expected RCS values for old trees, and especially
when the oldest rings are all from trees sampled in the same period (e.g., three of
the four oldest trees in the Torneträsk MXD chronology were sampled in 1982), it
is particularly necessary to guard against signal bias influencing the overall shape
of the RCS curve.
5.6.2 Application of RCS Across Wide Species and Climate Ranges
In their study of ring-width changes viewed over a large area of the Northern
Hemisphere, Esper et al. ( 2002 ) (see also Cook et al. 2004 ; Frank et al. 2007 )
took data from 14 different locations, from various tree species, and standardized
them using one of two RCS curves constructed from a subdivision of all of the
measurement series. One group of measurement data displayed the familiar nega-
tive exponential pattern of declining ring width with increasing age, while the other
showed a 'weakly linear' declining trend. Two RCS curves were used because it
was clear that linearly declining ring growth was not well suited to scaling by the
curvilinear function and vice versa. However, by incorporating data from very dif-
ferent species and locations in each of the linear and nonlinear RCS curves, each is
unavoidably associated with wide confidence intervals. The measurements for trees
at a particular site location may be systematically over- or underestimated by the
use of a multisite RCS curve.
This is an extreme case of the differing-contemporaneous-growth-rate bias dis-
cussed in Section 5.4.2 . The expression of this bias in the Esper et al. ( 2002 ) context
is illustrated in Fig. 5.12 . This figure shows the local site chronologies for 5 of the 14