全 文 ：Effects of Climatic Factors on Tree-ring Maximum
Latewood Density of Picea schrenkiana in
Xinjiang, China
Yu SUN1*, Lili WANG2, Hong YIN3
1. China Meteorological Administration Training Center, Beijing 100081, China;
2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
3. National Climate Center, China Meteorological Administration, Beijing 100081, China
Supported by Natural Science Foundation of China (41275120, 41271120, 41301041);
Strategic Science and Technology Planning Project of Institute of Geographic Sciences
and Natural Resources Research of Chinese Academy of Sciences(2012ZD001).
*Corresponding author. E-mail: suny.12b@igsnrr.ac.cn
Received: January 25, 2016 Accepted: April 19, 2016A
Agricultural Science & Technology, 2016, 17(6): 1479-1487
Copyright訫 2016, Information Institute of HAAS. All rights reserved Resources and Environment
T he Xinjiang Uygur AutonomousRegion is located in the centralregion of Eurasia, on the north-
east border of China. It is the up-
stream of the main weather system of
the mainland of China, and has a un-
ique natural feature and diverse eco-
logical environments[1]. The unique nat-
ural feature plays an important role in
the formation of the unique climate of
Xinjiang. On one hand, Xinjiang be-
longs to the typical temperate conti-
nental arid climate region which has
abundant climatic resources including
photo-thermal and wind energies. On
the other hand, it suffers from frequent
meteorological disasters and little pre-
cipitation, the natural environment
which mankind depends on for living is
harsh, and the ecological environment
is fragile[2]. Therefore, the study on the
climate variation in Xinjiang not only
plays an important role in the econom-
ic and social development in Xinjiang,
but also is of great importance to the
understanding of Chinese or even
global climate variation.
In the forests in Xingjiang, Populus
diversifolia,PiceaschrenkianaandLar-
ix sibirica are the 3 main tree species,
whose growth ranges are distributed
from south to north sequentially[3]. They
are also the tree species firstly used
by the dendroclimatology research in
Xinjiang [4]. TheTianshan mountainous
area in middle Xinjiang is the main
distribution area of Picea schrenkiana.
It was recorded that an article about
the tree ring in Xinjiang was reported
by Wang et al.[2] firstly in August, 1963,
Abstract Based on two tree-ring maximum latewood density (MXD) chronologies of
Picea schrenkiana from the Manas River Basin, Xinjiang, the response characteris-
tics of MXD to climate variation was discussed. Correlation analysis between MXD
chronologies and instrumental records from Shihezi meteorological station showed
that each chronology was significantly and positively correlated with the maximum
monthly average temperature in July-August, and especially, the regional chronology
(RC) was the most highly correlated variable (r =0.54, P <0.001). Afterwards, the
maximum average temperature in July-August was reconstructed using RC. Com-
parison among reconstructed temperature, observed values, and the drought index
(Is) confirmed that precipitation would affect MXD when the absolute value of Is is
greater than 1.5σ (|Is| > 2.5 during 1953-2008) or near to 1.5σ over a 2-3 year
period. The response characteristics are related to the semiarid climate of the study
area. In dry years, lack of precipitation would limit the thickening of latewood cell
walls and, as a result, impact MXD. Therefore, compared with relatively humid re-
gions, the response of tree-ring MXD to air temperature similarly would be influ-
enced by extreme moisture conditions in semiarid areas, and MXD, as a tempera-
ture proxy, should be used prudently on a limited scale.
Key words Picea schrenkiana; Tree ring; Maximum latewood density; Air tempera-
ture; Precipitation
气候因子对新疆雪岭云杉树轮
最大晚材密度的影响
孙宇 1*，王丽丽 2，尹红 3 （1.中国气象局气象
干部培训学院 ，北京 100081;2.中国科学院地
理科学与资源研究所 ，北京 100101;3.中国气
象局国家气候中心，北京 100081）
摘 要 基于新疆玛纳斯河流域 2 个雪岭云
杉树轮最大晚材密度 (MXD)年表，探讨了半干
旱区 MXD 对气候变化的响应特征。 研究结果
显示 ，2 个样点 MXD 年表及其区域平均年表
(RC)均与 7~8 月平均最高气温之间呈极显著正
相关关系。 其中，RC 与 7~8 月平均最高气温相
关最高(r=0.54，P<0.001)，并利用 RC 重建了 7~
8 月份平均最高气温。重建值、观测值以及干旱
指数(Is)之间的对比分析揭示，当干旱指数绝对
值大于 1.5σ（|Is|>2.5，1953~2008 年）或连续 2~
3 年干旱指数绝对值接近 1.5σ 时，水分条件将
会对 MXD 产生影响。 这一气候响应特征与研
究区半干旱气候有关 ，在干旱年份，水分匮缺
会限制晚材细胞壁的加厚，从而影响 MXD。 因
此， 与相对湿润地区相比， 半干旱地区树轮
MXD 对气温响应的同时也会受到极端降水状
况的影响，作为气温代用指标需谨慎而有限度
的使用。
关键词 雪岭云杉；树木年轮；最大晚材密度；
气温；降水量
基 金 项 目 国 家 自 然 科 学 基 金
(41275120，41271120，41301041）； 中国科学院
地理科学与资源研究所一三五战略科技计划
项目(2012ZD001)资助。
作者简介 孙宇 （1987-），男 ，黑龙江哈尔滨
人，工程师，从事气象教育培训及树轮生态与
气候研究，E-mail: suny.12b@igsnrr.ac.cn。 *通
讯作者，E-mail: suny.12b@igsnrr.ac.cn。
收稿日期 2016-01-25
修回日期 2016-04-19
DOI:10.16175/j.cnki.1009-4229.2016.06.044
Agricultural Science & Technology 2016
Fig. 1 Schematic diagram of sampling sites in research area
Fig. 2 Standard chronologies of three sampling sites and regional chronology
and the research samples were col-
lected from the Mountain Tianshan. In
1988, Xu and Li analyzed a chronolo-
gy of Picea schrenkiana [4]. Afterwards,
the scholars from China conducted
a study on the response of ring
width and density of Picea
schrenkiana to climate, and found
that in different areas, different alti-
tudes and different months there
was certain correlation between ring
width and density with air tempera-
ture and precipitation [5-9]. On the basis
of the response studies, scholars from
China further performed the recon-
struction of large quantities of air tem-
perature and precipitation series in the
areas including Ili, providing some ba-
sis and reference for the understand-
ing of the climatic changes in the past
in various areas[10-12]. These studies all
proved that Picea schrenkiana is a
tree species very sensitive to climatic
changes, and its ring width and density
could better reflect the changes in the
climatic factors in various areas.
So far, many scholars investigat-
ed the tree-ring maximum latewood
density (MXD for short) at some rela-
tively-wet areas with high latitudes and
high altitudes, and they all found that
MXD was closely related to the air tem-
perature in the late period of the grow-
ing season. For instance, Briffa et al.[13]
reconstructed the summer air temper-
ature of European according to the
MXD indexes of conifers; Schweingru-
ber et al. [14] reconstructed the summer
air temperatures of western Europe
and western North America; Luckman
et al.[15] conducted the study on the re-
construction of summer temperature
using MXD in Alberta of Canada. In
China, Wang et al. [16] analyzed the
tree-ring MXD characteristics of Larix
gmelinii and Pinus sylvestris var. mon-
golica and their response to climate in
Helongjiang; then, Fan et al. [17] recon-
structed the summer air temperature
in the middle part of Hengduan moun-
tain region; and Duan et al. [18] per-
formed the reconstruction of the aver-
age air temperature in the period of Au-
gust-September at the Gongga Moun-
tain in the eastern Tibetan Plateau.
However, in semiarid areas, precipita-
tion change is a crucial climatic factor
limiting the growth of trees, and the
drought condition is probably to affect
the accumulation of photosynthetic
products, thereby affecting the thick-
ening of cell wall. In order to investi-
gate the effects of air temperature and
precipitation on MXD under a semiarid
climatic condition, this study discussed
the significance of water and heat to
the formation of MXD from the point of
physiology in detail by collecting tree-
ring samples of Picea schrenkiana at
the Manas River Basin in the middle
part of the Mountain Tianshan, con-
structing MXD chronologies and per-
forming correlation analysis between
them with meteorological data.
Materials and Methods
General situation of research area
The middle forest area of the
Mountain Tianshan is located at the
south margin of the Junggar Basin
with an altitude over 4 000-5 000 m,
and the Picea forest has an altitude in
the range of 1 650 -2 850 m. This
mountainous area is near to Gurban-
tunggut Desert and far away from the
sea, so the mountainous forest has
obvious continental climate character-
istics, especially for the sunny slopes.
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Agricultural Science & Technology2016
The forest soil is grayish brown forest
soil, and the middle mountain has
abundant rainfall. The Manas River is
the largest snowmelt type mountain
river in the southern Junggar Basin.
The river extends from south to north
with a total length of 324 km, and an
average volume of runoff of 11.9×108
m3 in many years. The Shihezi recla-
mation area has the characteristics of
an average altitude of 300 -500 m,
short and hot summer, an annual air
temperature at 7.5 -8.2 ℃ , sunshine
duration of 2 318-2 732 h, a frost-free
season of 147 -191 d and an annual
precipitation of 180-270 mm [13]. The
tree-ring samples were collected from
Picea schrenkiana in August, 2009,
and the specific information of the
sampling sites was shown in Table 1,
and the location and general terrain
situation of the sampling sites were
shown in Fig. 1.
Experiment methods for tree ring
samples
In field, tree-ring cores were
drilled with a growth cone with a diam-
eter of 10 mm at the breast height of
each tree in the direction perpendicular
to the exposure, and generally, 2 cores
were obtained from each tree. Sam-
ples were taken to the laboratory by
paper suckers, and subjected to natu-
ral air drying, fixation, polishing and
dating by visual inspection according
to the basic procedures of the labora-
tory treatment of tree-ring samples [19],
the width data was then acquired with
a LINTAB ring-width measuring in-
strument accurate within 0.0.1 mm,
and accurate cross dating and in-
spection were performed with a TSAP
broken line graph and the COFECHA
program[20].
After the width experiment, a
density experiment was carried out in
the climate research open laboratory
of China Meteorological Administra-
tion. According to the standard of tree-
ring density experiment [21-22], the cores
were subjected to segmentation, fixa-
tion and measurement of fiber angles,
and a Dendro2003 density measuring
system was used for cutting the cores
into thin slices with a thickness of 1
mm, photographing for an X-ray film
and converting the optical intensities
into corresponding tree-ring densities,
obtaining the actual values of 7 param-
eters, i.e. the earlywood width, the
latewood width, the tree-ring width, the
average earlywood density, the late-
wood average density, the minimum
earlywood density and the MXD. The
dating of density data was performed
with a TSAP broken line graph and the
COFECHA program according to fin-
ished width dating result with refer-
ence to the information of missed
years recorded during slicing, so as to
ensure an accurate result.
The MXD chronologies were es-
tablished with the ARSTAN program[23].
The spline function with a step length
of 2/3 of the samples was selected fi-
nally for the fitting of the growth trend
of MXD by the comparison and analy-
sis on original series and repeated try
of different fitting methods. Because
the standard chronology (STD) has
better statistical characteristics and
has higher correlation with climatic fac-
tors, this study selected the STD
chronology. The Meiyaogou (MYG)
chronology was not in good accor-
dance to the changes of the chronolo-
gies of other two sampling sites, with
the characteristics of very low correla-
tion and the shortest time, while the
STD chronologies of the other two
sampling sites had very similar change
laws (Fig. 2) with very significant corre-
lation (r=0.616, n=188 a, P<0.001), so
the MXD series of the cores from
Dashuwan (DSW) and Lucaogou
(LCG) were merged followed by re-
checking of accordance with the
COFECHA program, and after the
deletion of some series with lower cor-
relation, a regional standard chronolo-
gy (RC) was established. The statisti-
cal characteristics and common inter-
val analysis of the various chronolo-
gies were shown in Table 1.
Acquisition of meteorological data
The monthly average tempera-
ture, the maximum monthly average
temperature, the minimum monthly av-
Table 1 Description of sampling sites and statistical characters of standard chronologies (the time period for common intervals analysis,
1850-2000)a)
Code MYG DSW LCG RC
Altitude//m 1 987 2 059 2 494 -
Latitude (N) 43.82° 43.84° 43.82° -
Longitude (E) 86.07 86.03 85.89 -
Exposure North North North -
Duplicates (plants/cores) 24/48 25/49 24/46 42/82
Average sensitivity 0.050 0.045 0.055 0.061
Standard deviation 0.050 0.055 0.053 0.057
First-order autocorrelation coefficient 0.167 0.398 0.115 0.078
Starting year of SSS>85%/core number 1 848/8 1 819/12 1 689/9 1 727/10
Correlation coefficient among all cores 0.391 0.256 0.343 0.372
Intertree correlation coefficient 0.386 0.251 0.337 0.369
Intratree correlation coefficient 0.604 0.491 0.595 0.611
Signal to noise ratio 29.5 16.9 24.0 36.2
Samples Representativeness 0.967 0.944 0.960 0.973
Explained variance of the first principal component 42.6% 32.3% 37.4% 39.0%
a) SSS represents subsample-representativeness.
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Fig. 3 Monthly average temperatures and precipitations over multiple years (1953-2008) in
Shihezi meteorological station
Fig. 4 Pearson correlation analysis between MXD series and meteorological factors in
Shihezi meteorological station(1953-2008)
erage temperature, and the monthly
total precipitation of Shihezi Meteoro-
logical Station nearest to the sampling
sites were selected, and the data was
obtained from China meteorological
data sharing service system (http://
cdc.cma.gov.cn/) with a time span of
56 years (1953-2008). Shihezi mete-
orological station is located at 86°03′
E, 44°19′N, and the observation field
has an altitude of 442.9 m. Shihezi
meteorological station is a basic mete-
orological station of China without any
relocation record, the data was stan-
dardized, and no abnormal value was
found in re-checking. The monthly av-
erage temperatures and precipitations
recorded by the meteorological station
over the 56 years were shown in Fig.
3, which showed that this area was
semiarid, with the most precipitation in
the early period (April -May) of the
growing season and decreased precip-
itation in the late period of the growing
season (June -August), but the air
temperature was the highest in the pe-
riod from June to August, indicating
non-synchronous rain and heat.
Because there was a greater dif-
ference in altitude between Shihezi
meteorological station and the sam-
pling sites, the grid point data from
CRU TS3.1 (www.cru.uea.ac.uk) 0.5°
×0.5° was also selected. In compari-
son, the grid point data and the data
from the meteorological station were
very similar in changing type, the tem-
perature was lower than that from the
meteorological station by about 9 ℃ ,
which might be due to that the factors
including altitude were taken into con-
sideration during the interpolation to
the grid point data, and the higher the
altitude, the lower the air temperature;
and the precipitation was higher than
the value recorded by the meteorolog-
ical station, because the precipitation
of this area would increase with alti-
tude increasing. Due to the fact that
the difference between absolute val-
ues would not affect relevant analysis
results, the changing type of instru-
ment-measured data could represent
the change trends of climatic factors in
this area, and are more accurate
records. Therefore, this study still used
the meteorological data from Shihezi
meteorological station. The climatic in-
formation and MXD chronologies were
subjected to Pearson correlation anal-
ysis, so as to obtain the correlation
between MXD and climatic factors.
Calculation of drought index
In order to analyze the effect of
precipitation variation on MXD, this
study introduced drought index as a
reference standard, its calculation for-
mula was:
Is= R-RσR
- T-TσT
, the drought in-
dex is a homogenization index of pre-
cipitation and temperature [24], i.e., the
difference between the standardized
variable of precipitation and the stan-
dardized variable of temperature, and
in this paper: R is the monthly total pre-
cipitation, R is the mean value of the
monthly total precipitations over many
years, and σR is the mean square de-
viation of the monthly total precipita-
tions; and T is the maximum monthly
average temperature, T is the mean
value of the maximum monthly aver-
age temperatures over many years,
and σT is the mean square deviation of
the maximum monthly average tem-
perature.
There are three types of drought
indexes: (i) only considering single
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Table 2 Statistical results of the transfer equation between RC and TJuly -August and cross
validationa
Time period 1953-2008 Except 1958-1961, 1967, 1974-1976, 1985-1987, 1996-1998
Explainedvariance 29.2% 46.7%
Adjusted value of explained variance 27.9% 45.3%
F value 22.3 35.0
Sign test for first order difference 37* 30**
Sign test 40** 32**
Product mean 2.908 8 2.931 0
Reduction of error 0.245 0 0.404 1
a) * represents that the confidence level at 95% is reached; ** represents that the
confidence level at 99% is reached.
0.50
<0.001
0.64
<0.001
Correlation coefficient
P
factor, precipitation, such as the pre-
cipitation Z index; (ii) considering
double factors, precipitation and tem-
perature, such as the index selected
in this paper; and (iii) comprehen-
sively considering multiple factors,
precipitation, temperature and vol-
ume of runoff, such as PDSI [23]. Most
former studies indicated that tree-ring
density could reflect the changes in air
temperature[13,18], a small part of studies
proved the relation between tree-ring
density and precipitation[25, 27], but there
were few studies on the relation be-
tween density and PDSI, and these
studies did not show the close relation
between Picea schrenkiana MXD and
PDSI[28-29]. Therefore, this study did not
selected the first type of index due to
the singleness of the considered index
which could not encompass the factors
influencing MXD comprehensively, as
well as the third type of index to avoid
noise caused by the introduction of too
many factors with lower correlation.
The homogenization index of precipi-
tation and temperature was selected
as it could indicate two extreme states,
i.e. high temperature with little rain and
low temperature with much rain, could
response to precipitation and tempera-
ture rapidly[24], and thus was more con-
form to the research purpose.
Results and Discussion
Correlation between MXD sequence
and climatic factors
The correlation analysis used the
Dashuwan (DSW) chronology, the Lu-
caogou (LCG) chronology and the re-
gional chronology (RC) combining the
two sampling sites, the meteorological
information included the monthly aver-
age temperature, the maximum mon-
thly average temperature, the mini-
mum monthly average temperature
and the monthly total precipitation, and
the selected months were those from
October of last year to October of next
year. The results were shown in Fig. 4.
It could be seen that the correla-
tion between the various chronologies
and the precipitation of each month all
did not reached the significant level of
0.01, but the change trends of the cor-
relation coefficients accorded relative-
ly, indicating that the possible effects
of precipitation on MXD were substan-
tially the same, thought the correlation
between precipitation and MXD was
not very significant. [Furthermore, the
various chronologies also showed vary
similar changes in the correlation co-
efficients with the monthly average
temperature, the minimum monthly av-
erage temperature and the maximum
monthly average temperature, and all
had the highest correlation with the
maximum average temperature of Au-
gust of the very year. The monthly av-
erage temperature of May of the very
year showed the second highest cor-
relation with the various chronologies,
and its correlation with DSW did not
reach the significant level of 0.01, but
still reached the significant level of
0.05. In the growing season of trees,
the air temperature is positively corre-
lated with MXD, i.e., the higher the
temperature, the larger the MXD.]
The growth of trees is a continu-
ous process, so the temperatures from
May to August and from July to August
with higher correlation were averaged,
respectively, to investigate the corre-
lation between MXD and the two
month combinations. The results
showed that the MXD series had the
highest correlation with the maximum
average temperature in July -August,
and the correlation was higher than the
correlation with single month. The cor-
relation between the temperature in
May-August and the MXD series was
also very significant, but lower than
that between the temperature in July-
August and the MXD series, indicating
that MXD was very significantly affect-
ed by the temperature in May-August,
but the most important limiting factor
was the maximum average tempera-
ture in July-August, which is the pe-
riod most important for the formation
of MXD. The temperature in July-Au-
gust is the most crucial period for the
thickening of latewood cell wall, which
has already reflected by previous
studies[10,16].
Physiological analysis and com-
parison on the effect of temperature
on MXD
In May, Shihezi area has the
highest precipitation throughout the
year (as shown in Fig. 3), if the lowest
temperature rises at this time, rapid
warming in spring occurs, the growing
season begins early, and a longer
growing season is beneficial to suffi-
cient matter accumulation and cell
wall thickening, thereby resulting in
the formation of a higher MXD [16].
Picea schrenkiana mainly grows in the
period from May to August [3], and in
July and August, the fission and elon-
gation of plant cells have already fin-
ished, new leaves are also mature and
enter the photosynthetic accumulation
stage, so the growth of trees is mainly
reflected by the thickening of latewood
cell wall [30]. In the growing season, the
highest temperature plays a crucial
role in the formation of MXD, and es-
pecially in July-August, it becomes the
most important influencing factor for
MXD [10]. Though Picea schrenkiana is
a shade tree species[31], some scholars
deem that it is a tree species which
likes light or is light tolerant for the his-
torical reasons of species impoverish-
ment and the lack of pioneers, and
furthermore, after 25 years of growth,
it enters the fast-growing stage, which
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Agricultural Science & Technology 2016
Fig. 5 Comparison among the reconstructed value and observed value of the maximum
monthly average temperature and drought index from July to August
requires a full illumination condition [3].
More sunshine is often accompanied
with a high temperature, and thus, the
promoting effect of the maximum
monthly average temperature also
might be a concrete presentation of
such ecological characteristic of Picea
schrenkiana.
Chen et al.[8] also studied the tree-
ring density at the east of Yuejinqiao
(43°8′N, 87°5′E), the location of which
is at about 120 km in the southeast di-
rection of this study, with an altitude of
2 600 m and a northeast exposure.
His/her results were compared with
this study: (i) MXD had the highest
correlation with the air temperature of
August, which accorded with this
study; (ii) the average density of ear-
lywood was significantly correlated
with the air temperature of April, and
this study concluded that MXD was
significantly correlated with the tem-
perature of May, all indicating that the
climatic condition of the early period of
the growing season could decide the
starting time of the physiological pro-
cess and the length of the growing
season, and the development of early-
wood density started earlier; and (iii)
the correlation coefficient between the
average density of earlywood and the
air temperature of July in correspond-
ing year was the highest as 0.651,
which was higher than the correlation
degree between MXD and the air tem-
perature of July in this study, and the
average density of earlywood showed
the highest correlation coefficient with
the air temperature of the month com-
bination, June-July, while in this study,
MXD showed the highest correlation
with the air temperature of August, and
the air temperature in July-August had
the highest effect on MXD. These dif-
ference are mainly due to that the
physiological process of earlywood is
complete before that of latewood,
while the growth of trees is a continu-
ous progress, and various physiologi-
cal processes proceed simultaneously,
and are different in their emphasis.
Effect of changes in extreme water
condition on MXD
In order to more intuitively exhibit
the response of MXD to changes in
air temperature and to acquire the in-
formation about the effect of water
condition on MXD, the equation of lin-
ear regression between RC and the
maximum average air temperature in
July -August was established accord-
ing to the linear relation between MXD
and air temperature as: TJuly -August =
10.648RC +21.220, wherein TJuly -August
represents the maximum average tem-
perature in July-August, and RC rep-
resents the regional MXD standard
chronology with the calibration time
periods of 1953 -2008. The statistic
values of the transfer equation and the
leave-one-out cross validation were
shown in Table 2. It could be seen
from Table 2 that the explained vari-
ance and other statistic values were
not very high though the correlation
coefficient reached the very significant
level.
According to the drought index
calculation formula provided above,
the drought index in July -August of
each year was obtained. A positive
value represents a relatively wet con-
dition, while a negative value repre-
sents a relatively drought condition.
The drought index values were com-
pared with the reconstructed values
and the observed values, and the re-
sults were shown in Fig. 5. In Fig. 5,
the shaded parts represented the time
periods when the phase differences
between the reconstructed values and
the observed values were greater,
mainly including 1958 -1961, 1967,
1974 -1976, 1985 -1987 and 1996 -
1998. Fig. 5 showed that in each of
these time periods, the absolute value
of the drought index was greater than
1.5σ (|Is|>2.5，1953~2008), or the ab-
solute value of the drought index was
near to 1.5σ for 2-3 years continuous-
ly.
It was recorded that the runoff vol-
umes of theManasRiver near the sam-
pling sites were relatively larger in 1958
and 1967, when the climatic condition
might be wetter, while the time periods
1974-1976and 1985-1987 had smaller
runoff volumes as drought weather oc-
curred in the two timeperiods [32]. In ad-
dition, according to the records of me-
teorological disasters, the cities and
counties around the sampling sites
suffered from flood disaster in July -
August of 1958 and 1959; and in 1974,
1976, 1985 -1987 and 1997, drought
happened in the research area [33 -34].
The runoff records, the disaster
records and the calculation results of
drought index were in better corre-
spondence, which further verified that
the water condition changed greatly in
these time periods. Cross validation
was re-performed after deleting these
years from the original calibration time
period, and as shown in Table 2, the
explained variances increased remark-
ably; the reduction of error was 0.404
1, higher than the original 0.245 0; the
product mean was 2.931 0, which was
also better than the 2.908 8 of the
overall calibration time period; the sign
test and the sign test for first order dif-
ference both reached the confidence
level at 99%, indicating that the recon-
structed series of the maximum
monthly average temperature in July-
August was in better correspondence
with the observed value in the changes
of high and low frequency, while the
original model only reached the confi-
dence level at 95% in the sign test for
first order difference with a poor effect.
The improvement in the statistic re-
sults proved that the water condition
had greater effects on MXD in 1958-
1961, 1967, 1974 -1976, 1985 -1987
and 1996 -1998, so that MXD could
not well capture the changes in tem-
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Agricultural Science & Technology2016
perature, the fitting quality of the model
was not ideal enough, while without
these time periods, MXD could better
reflect temperature information.
The correlation coefficient be-
tween the drought index Is and MXD
was -0.445 (n=56 a，P<0.001), but it
could not give expression to the effect
of water on MXD truly. MXD was neg-
atively correlated with the precipitation
from July to August (not significant),
and positively correlated with air tem-
perature (α =0.01), while it could be
seen from the calculation formula of Is
that it was the difference between the
standardized series of precipitation
and air temperature, so Is was nega-
tively correlated with MXD. In the cali-
bration time period, the air tempera-
ture significantly affected MXD, thus it
was necessary to consider how the
changes in water condition endow the
MXD with a deviation reflecting tem-
perature information, i.e. the relation
between Is and the difference between
the reconstructed value and the ob-
served value in Fig. 5. Correlation
analysis showed that in the total cali-
bration time period, Is had a correla-
tion coefficient of 0.699 with D-value
(n =56 a, P <0.001), while in 1958 -
1961, 1967, 1974 -1976, 1985 -1987
and 1996-1998, the correlation coef-
ficient was up to 0.932 (n=14 a, P<
0.001). The correlation results in com-
bination with the qualitative analysis in
Fig. 5 could fully illustrate that the high-
er the positive value of the drought in-
dex, the wetter the climate, and a
higher positive value of the D-value
was accompanied with a relatively
larger MXD; and the lower the nega-
tive value of the drought index, the dri-
er the climate, and a lower negative
value of the D-value was accompanied
with a relatively smaller MXD.
Physiological explanation of the ef-
fect of water on MXD
There were very few reports
about the effect of water on MXD and
its physiological significance, and this
study performed speculative explana-
tion and discussion on them on the
basis of limited information:
Firstly, form the point of ecological
characteristics of tree species, Picea
schrenkiana likes wet habitats, one of
the main characteristics of its distribu-
tion areas is enough air humidity in
summer, and if the relative humidity in
summer is lower than 50% , it hardly
could survival. Under a high-tempera-
ture low-humidity condition, even if
heavy irrigation ensures abundant soil
moisture, the water loss caused by
strong tree transpiration due to dry hot
air could not be compensated [3]. Con-
sequently, the tree species quite de-
pends on water condition. Water plays
an important physiological role in
plants, and it is a main component of
cytoplasm, a reactant of metabolic
processes, as well as a solvent for the
absorption and transportation of sub-
stance by plants [35]. Just due to the
strong dependence of Picea
schrenkiana to water and the impor-
tance of water, the changes in extreme
water condition could affect the physi-
ological activities of the tree species
more easily, and MXD also would
change.
Secondly, according to previous
microscopy studies, drought stress
would inhibit the expansion of tracheid
in the primary stage of the growing
season [30]. The size of tracheid would
affect tree-ring density, because if the
cell volume is small, the specific gravi-
ty of cell wall would increase, the tree-
ring density would increase corre-
spondingly, and the density of early-
wood is affected mainly at this time[8, 36].
However, for MXD, the main influenc-
ing factor is the climatic condition in
the late period of the growing season
when the elongation of cells has
stopped already, and MXD is mainly
decided by the thickness of cell wall,
but not associated with cell size[37]. Af-
ter summer solstice, if there is more wa-
ter, the development time of latewood
would be prolonged, which ismainly re-
flected by wider latewood, larger pro-
portion of latewood in corresponding
tree ring and thicker cell wall [38]. On the
contrary, under a drought condition,
the activities of cambium would come
to an end ahead of time, the develop-
ment time of timber is shortened [39-40],
higher water demand and less water
supply result in stomatal closure,
which further results in decreases in
gas exchange and carbon fixation [41],
more carbon also would be supplied to
the growth of roots and stored [42 -43],
and therefore, the material and time
required by the thickening of cell
wall both decrease, finally resulting
in the decrease in the thickness of
cell wall [44, 46].
In addition, water is one of the raw
materials for photosynthesis, and the
oxygen released from photosynthesis
is all from water. The water required by
photosynthesis is a small part (less
than 1% ) of the water absorbed by
plants, and therefore, water deficiency
mainly lowers the photosynthetic rate
indirectly. In specific, water deficiency
results in stomatal closure of leaves,
the decrease in stomatal conductance
would negatively affect the supply
function of photosynthesis with the
drought getting more aggravate.
Meanwhile, water deficiency enhances
the amylolysis of leaves, carbohy-
drates are accumulated, and slow
transportation of photosynthetic prod-
uct reduces the demand for photosyn-
thesis [47]. The two factors both would
result in the decrease in material sup-
ply required by the thickening of cell
wall, and the MXD is relatively smaller.
At last, plant hormones could af-
fect cell growth by regulating the elon-
gation of cell wall, thereby realizing the
growth and development of plants, cur-
rently, the regulation effect of plant
hormones on cell wall growth is mainly
shown from the reconstruction of the
polysaccharide network structure of
cell wall and the promotion of expan-
sion growth of cell wall by activating
the expression of cell wall relaxing fac-
tor[48]. For instance, auxin could rapid-
ly increase the expansibility of cell
wall, and regulate the expression of
expansion and cell wall relaxing pro-
tein, thereby realizing cell growth [49];
and some cell wall-related genes are
controlled by ethylene[50]. Though there
have not been any direct reports about
the action mechanism of plant hor-
mones to the thickening of cell wall,
plant hormones have significant ef-
fects on material synthesis and de-
composition, microtubule arrangement
and cellulose deposition of cell wall [48].
Under an extreme drought or wet
condition, various hormones in plants
would change in quantity and exhibit
a series of responses including trans-
fer[47], and might affect the accumula-
tion of cell wall components by various
synergistic effects and antagonistic ef-
fects among them, resulting in the
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Agricultural Science & Technology 2016
change in MXD. Currently, the con-
version from earlywood development
to latewood development of tree ring
is verified to be controlled by hor-
mones[51]. However, whether plant hor-
mones could affect the change of MXD
is still unclear, but there might be very
close relation between them.
This study investigated the effects
of water and heat on MXD under the
semiarid condition of the northern foot
of the Tianshan Mountain, but due to
the limitation from the research
method and basic information, deeper
explanation to the effect of water on
the physiological process of MXD
could not be given. In the future, the
physiological relation between them is
hopeful to be revealed by widely sam-
pling in semiarid areas or even arid ar-
eas through microscopy means in
combination with the research meth-
ods of phytophysiology.
With the continuous development
of research method, if the effect de-
gree of water and temperature on
MXD could be judged quantitatively
and the quantitative physiological
model of water and heat on MXD could
be fitted in the future, it is anticipated
to still enable the climate reconstruc-
tion using the tree -ring index under
the condition of MXD affected by both
the temperature and water.
Conclusions
(1) The MXD of Picea schrenkian
at the Manus River Basin in Shihezi,
Xinjiang is mainly limited by the maxi-
mum monthly average temperature
from July to August. Both the early-
wood and latewood densities are af-
fected by the temperature in the early
period of the growing season.
(2) When the absolute value of
the drought index is higher than 1.5σ
(|Is |>2.5, 1953 -2008) or is near to
1.5σ continuously for 2-3 year, water
condition would limit MXD, which is re-
lated to the semiarid climate of the re-
search area.
(3) In drought years, water defi-
ciency would limit the thickening of
latewood cell wall, thereby affecting
MXD. Therefore, the response of tree-
ring MXD to air temperature would be
affected by extreme precipitation con-
ditions in semiarid areas, and tree-ring
MXD as an air temperature represen-
tative index should be used prudently
on a limited scale.
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