Supplementary Materials
SM 1. Topographic variables retrieved from the ASTER DEM
The ASTER instrument was on board Terra satellite that was launched on Dec. 18, 1999.
The validation study in Japan concluded that its vertical accuracy was -0.20 m overall, with
-0.7 m over bare ground and +7.4 m over forested areas, with a 0.23 pixel horizontal
accuracy (Tachikawa et al., 2011). A comparison with the Shuttle Radar Topography Mission
(SRTM) and GEODATA DEM-95 datasets in Australia concluded that the ASTER DEM accuracy
is approx. 15 m (Hirt et al., 2010), while another study in northern India indicated the ASTER
DEM accuracy to be 13-18 m (Mukherjee et al., 2013). Better accuracies (5 m – 10 m) were
found in a study in northern Algeria and southern Tunisia (Athmania and Achour, 2014). The
ASTER global DEM (GDEM) Version 2 data have a horizontal resolution of 1 arc second. The
DEM was downloaded from U.S. Geological Survey (http://gdex.cr.usgs.gov/gdex/) and
converted to 30 m resolution in Albers equal-area projection using ArcGIS. Considering the
uncertainties in locating the true coordinates of individual trees, buffers of 5-meter radii
were constructed for the trees sampled and then used to summarize the elevation values
from the ASTER DEM using the zonal summary function in ArcGIS with a processing cell-size
of 0.01 m. We compared the GPS elevations and the extracted DEM elevations (SM Fig. 1)
and found a very good relationship between the two elevation variables (R2 = 0.9795). The
relationship is generally linear except for the lower elevations below 3900 m (SM Fig. 1),
where for some reasons the GPS elevations were consistently lower than the DEM
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elevations. In the following, we will report only the DEM elevations unless it is otherwise
noted.
Insert SM Figure 1 here
Also using the 5-m buffers, slope gradient and growing-season direct solar radiation
values for individual trees are obtained from the ASTER DEM. Direct solar radiation is
essentially a function of slope gradient and aspect, considering the position of the sun in sky
and integrated for a specific season, such as the growing season as April-August with the
unit of Watt-Hours/m2. It is calculated using the Area Solar Radiation function of ArcGIS
(http://webhelp.esri.com/arcgisdesktop/9.2/index.cfm?TopicName=Area_Solar_Radiation),
for a subset of the ASTER DEM of 8.3 x 8.8 km area centered at the sampling site with the
following settings: default latitude of 36.1842°N, “skysize” of 512 corresponding to the
default day interval of 14 days, and increment of 0.5 hours. All terrain analyses were
performed using ArcGIS (version 10, ESRI, Redlands, CA).
SM 2. Chronology statistics of different elevation zones
SM Figure 2 presents common statistics of the chronologies at different elevations for
comparison purposes. Various mean correlations (rbar) measure the strength of covariation
among the tree-ring series used in chronology construction. Mean sensitivity represents the
relative change of ring width from one year to the next (Fritts, 1976). Such year-to-year
variability of tree growth is most likely caused by the sensitivity of tree growth to
environmental variability, typically ranging from 0.15 for most complacent trees to 0.65 for
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very drought-sensitive conifers in this region (Shao et al., 2009; Shao et al., 2010).
Percentages of missing rings in the study region represent how extreme environmental
conditions (most likely severe droughts) impacted tree growth at a given site (Shao et al.,
2005). ). Signal-to-noise ratio (SNR) is a measure of the common signal strength among the trees
used in the chronology (Cook and Kairiukstis, 1990; Wigley et al., 1984). Expressed population
signal (EPS) measures how well a chronology with a finite number of trees replicates a
hypothetical “true” chronology. A threshold of 0.85 is commonly considered as the
acceptable level of EPS for dendroclimatological studies (Cook and Kairiukstis, 1990; Wigley
et al., 1984).
The chronology statistics do not show unidirectional increasing or decreasing trends
with elevation (SM Fig. 2). Of the 10 elevation zones, mean sensitivity and percentage of
missing rings were generally lower at higher elevations, but at ERG8, these values were
lower than those in the adjacent elevation zones. Both the all-series and between-tree rbar
values and the variance explained by PC1 show a similar pattern, with two troughs at ERG9
(3884 m) and ERG2 (4190 m) (SM Fig. 2a). The percent of missing rings representing
harshness of the growth environment shows high values in the mid-section and then again
at the high elevation zones (SM Fig. 2b).
Insert SM Figure 2 near here
SM 3. Possible problems in climatic data prior to 1970
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In initial exploration of growth-climate relationships, we selected two climatic variables,
previous September to current March temperature (Tp9c3) and previous July to current June
precipitation (Pp7c6), to represent the overall effects of temperature and precipitation,
respectively. Selection of these variables are based on previous studies in this region (e.g.,
Shao et al., 2010; Shao et al., 2005; Zhu et al., 2008). Then we calculated the correlation
coefficients between these climatic variables and individual chronologies for moving 30-year
periods during 1955-2010 with 5-year increments. The correlation coefficients averaged for
all 10 elevation zones show that precipitation had relatively robust correlations with the tree
ring data during the entire study period while temperature’s correlations started with very
low values but significantly improved after 1970 (SM Fig. 3). It is outside the scope of this
study to fully investigate the causes of such inconsistencies, but we speculate that such
variations were due to changes in the instrumental data quality. Poorer matches between
the tree-ring reconstructed and observed temperature variables prior to the 1980s have
been reported in previous studies across the TP (Deng et al., 2014; Fan et al., 2009; Gou et
al., 2008; Gou et al., 2007; Liang et al., 2008; Liu et al., 2009; Lv and Zhang, 2013; Yang et al.,
2010; Zhang et al., 2014). It is possible that the lack of reinforcement of the standard
observation procedures in practice during the earlier years had a greater impact on the
quality of the temperature data, as compared to the impact on the precipitation data.
Actually, for precipitation (pp7c6), the mean correlation with the tree-ring series for the
entire study period (1955-2010) was 0.686, higher than any of the 30-year sub-periods,
while the mean correlation between temperature and tree-ring series during this period was
0.418, lower than the mean correlations during the sub-periods of 1975-2004 and
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1980-2009. To avoid problematic data of the earlier year and retain as large sample sizes as
possible, we used the data for the period 1970-2010 in growth-climate relationship analysis.
(Insert SM Figure 3 near here)
Additional References for Supplementary Materials
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available ASTER-GDEM ver1, SRTM ver4.1 and GEODATA DEM-9S ver3 digital elevation
models over Australia. Australian Journal of Earth Sciences 57: 337-347
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Figures of Supplementary Materials
SM Figure 1 DEM elevation values vs. GPS elevation values of the 358 sampled trees. For
trees located less than 5 m apart, the same GPS locations were used. The horizontal lines
indicate the boundaries of the 10 elevation zones, named as ERG1 to ERG10. Also labeled
are the mean elevations of the 10 elevations zones.
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SM Figure 2. Variations of chronology statistics by the elevation zones: a) rbars, first-order
autocorrelation (AC), and percent of variance explained by PC1; b) percent of missing rings,
standard deviation (STD), mean sensitivity (MS), and signal-to-noise ratio (SNR). All statistics
are for the 1801-2010 common period, except for the percent of missing rings, which is
based on the full lengths of individual chronologies ranging from 868 to 2736 years.
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SM Figure 3. Correlation coefficients of tree-ring chronologies to annual precipitation
(previous July-current June, Pp7c6) and winter temperature (previous September-current
March, Tp9c3) for consecutive 30-year periods during 1955-2009 (with 5-year increments),
averaged for all elevations. The last two bars represent the correlations for the entire
instrumental period 1955-2010. Significance levels, represented by the dotted and dashed
lines, are for a sample size of N = 30.
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