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 138

the slopes of each series would be virtually zero. All low-frequency variance would
have been removed from the resulting chronology (see also Fig. 1, Briffa et al. 1996 ;
Fig. 3, D'Arrigo et al. 2005 ) . With curve-fitting standardization, our ability to com-
pare the magnitude of tree growth in one decade with that in another, when they are
separated by more than half the length of the constituent sample series, is poten-
tially compromised. Hence, curve-fitting methods of tree-ring standardization are
not well suited for exploring the long-term context of recent tree growth changes in
response to factors such as recent temperature rises, increasing atmospheric CO 2 ,or
other hypothesized anthropogenic influences on terrestrial ecosystems. This is the
fundamental rationale for further exploring the potential, limitations, and possible
improvements of RCS. A number of problems have been raised in this review, and
in this final discussion we summarize several of them and point in the direction of
possible solutions.
Establishing the form of the RCS curve and applying it to produce a chronol-
ogy are both subject to potential biases. Bias in the form of the RCS curve arises
when it erroneously tracks medium-frequency variance representing common cli-
mate signal; where the fit of expected RCS curve to the underlying age-aligned
data is poor; and possibly when no allowance is made for pith offsets when align-
ing the underlying measurements (e.g., see Fig. 5.10d ) . The use of 'signal-free'
methods of standardization addresses the first of these potential problems and can
improve the accuracy of the RCS curve and reduce chronology error levels. These
errors are generally small for long (multimillennial) chronologies but can be large
for shorter chronologies. Routine implementation of signal-free methods, therefore,
forms a useful extension to RCS, particularly with regard to its application in pro-
cessing 'modern' chronologies. To address the second problem and to prevent loss
of medium-frequency climate variance, smoothing of the RCS curve must not be
too flexible, especially where sample counts are low. However, the RCS curve must
be sufficiently flexible to follow the pattern of expected growth plotted against tree
age accurately (Melvin et al. 2007 ) .
The use of pith-offset estimates in generating and applying RCS curves will pro-
duce more accurate RCS curves. This increased accuracy arises because a lack
of pith offsets introduces systematic bias in RCS curves, reducing the expected
ring width maximum in early years of tree growth and consequently lowering the
expected trend of declining growth with increasing age. Though RCS chronolo-
gies produced with and without pith offsets may be highly correlated (Esper et al.
2003 ; Luckman and Wilson 2005 ) , using pith offsets may still occasionally pro-
duce more accurate chronologies (Naurzbaev et al. 2002 ; Melvin 2004 ; Büntgen
et al. 2005 ; Esper et al. 2007 ) , as is shown by lower chronology standard errors and
a reduced frequency of local chronology bias associated with temporal concentra-
tions of young (or old) tree samples in a chronology. The routine estimation and use
of pith-offset information is, therefore, recommended.
However, other potential bias problems remain in RCS application. Any cli-
mate signal that affects the average of age-aligned sample series, e.g., the climate
trend over the length of the chronology, is unavoidably removed from each series
within the chronology. This trend-in-signal bias is minor for a long chronology and