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Chinese Science Bulletin
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Spatiotemporal vegetation cover variations in the
Qinghai-Tibet Plateau under global climate change
XU XingKui1, CHEN Hong1 & Jason K LEVY 2
1
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;
2
Western Washington University, Huxley College of the Environment, Department of Environmental Studies, 516 High Street, Bel-
lingham, WA 98225, USA
Empirical Orthogonal Function (EOF) analysis and the related Principal Components (PC) analysis are
used to extract valuable vegetation cover derived information from the National Oceanic and Atmos-
pheric Administration (NOAA-AVHRR) s Leaf Area Index (LAI) satellite images. Results suggest that
from 1982 to 2000 global climate change has contributed to an increase in vegetation cover in the
Qinghai-Tibet Plateau. The correlation between rainfall and LAI EOF PC1 and PC2 indicates that rainfall
is the major climatic factor influencing interannual variations of average vegetation cover throughout
the entire Plateau. However, annual mean vegetation cover trends in the Qinghai-Tibet Plateau are
mainly out of phase with air temperature increasing, which is primarily responsible for nonsynchro-
nous changes of vegetation cover. In the southern ridge of the Qinghai-Tibet Plateau, recent warming
trends contribute to humid weather and favorable conditions for vegetation growth. By contrast, higher
ATMOSPHERIC SCIENCES
temperatures have led to arid conditions and insufficient rainfall in the northern part of the Plateau,
leading to drought and other climatic conditions which are not conducive to increased vegetation
cover.
Qinghai-Tibet Plateau, LAI, Empirical Orthogonal Function (EOF), climatic factor
Lying to the north of the Himalayas in Central Asia, vironmental change. These adjustments may signifi-
large swaths of the Qinghai-Tibet Plateau are uninhab- cantly affect not only the East Asian Monsoon but also
ited, leading to fewer human influences than in other summer rainfall in Yangtze River Valley, leading to haz-
ardous weather conditions[7 12].
regions of China. Significant air and land surface tem-
perature increases have been observed on the Qinghai- As vegetation adapts to regional and global climate
Tibet Plateau, in particular during the spring and win- change, long-term interactions between vegetation and
ter[1 3]. Since the 1970s, the global climate change has
the environment lead to spatial changes in the distribu-
contributed to a decrease in the coverage and depth of tion of plant species, as well as temporal phenological
frozen earth in the Qinghai-Tibet Plateau[4] and climatic changes. Dynamic ecosystem models can capture the
zone adjustments[5]. Land surface thermodynamics and complex interaction between plant physiological proc-
esses and climate variability[13 19]. Gradually increasing
fluxes have significantly influenced regional climate in
China since the 1980s[6]. For example, enhanced surface
albedo fluctuations caused by land surface changes can Received August 23, 2007; accepted December 13, 2007
profoundly influence land surface properties, leading to doi: 10.1007/s11434-008-0115-x
Corresponding author (email: ****@****.***.**.**)
pronounced changes to surface radiation and thermal Supported by the National Basic Research Program of China (Grant No.
distribution balances. As a result, temperature, pressure, 2006CB403607), the National Natural Science Foundation of China (Grant Nos.
40675047 and 40605023), the Key Project of the Chinese Academy of Sciences
wind, rainfall and other climatic variables in the Qing- (Grant No. KZCX2-YW-219), and a Western Washington University summer re-
hai-Tibet Plateau and other regions have adapted to en- search grant
www.scichina.com csb.scichina.com www.springerlink.com Chinese Science Bulletin March 2008 vol. 53 no. 6 915-922
temperatures due to global warming are having a pro- lyze the interannual variations of the vegetation cover in
nounced effect throughout the Qinghai-Tibet Plateau. In the Qinghai-Tibet Plateau: (1) the asymmetric spatio-
some regions, the perennially frozen earth is decreasing temporal distribution of land cover and physical features
rapidly and the desert area is enlarging while vegetation and (2) the temporal variations of vegetation phenology.
cover shows a decreasing trend[20 24]. In other regions,
In particular, large variations in land cover types (often
[25,26] with markedly different properties) occur each month
vegetation cover is increasing . As a result, land
due to frequent snowfall and snow melt. Accordingly,
surface properties in the Qinghai-Tibet Plateau have be-
NDVI data is not suitable for identifying interannual
come less uniform, leading to more frequent rainfall in
vegetation cover variations. Few studies have directly
eastern China and profound changes in atmospheric cir-
culation and temperature[27,28]. used NDVI data to investigate vegetation cover changes
in light of these challenges. Previous work dealing with
While species diversity arises through adaptation to
vegetation cover change on the Qinghai-Tibet Plateau
regional climate, a lack of geographic observational data
have been not been conclusive and accordingly, it is
on the Qinghai-Tibet Plateau has made it difficult to
valuable to further examine results for this region using
study the spatial distribution and annual variations of
new techniques[33,34]. Specifically, the LAI (leaf area
vegetation cover. While increasing air temperature
index) is used to analyze spatiotemporal vegetation
trends have been observed for more than 20 years, it is
cover changes in the Qinghai-Tibet Plateau. The LAI
unclear how global climate change impacts spatial-
technique can reduce ambiguities resulting from the im-
temporal vegetation cover changes in the Qinghai-Tibet
pact of non-vegetation information such as snow cover
Plateau. Accordingly, NOAA-AVHRR derived LAI data
on the surface reflectance spectrum. The acquisition of
are used to investigate spatial-temporal vegetation cover
LAI data is based on statistical findings from the global
variations on the Qinghai-Tibet Plateau. Specifically,
vegetation reflectance spectrum[35]. Moreover, our pro-
climatic factors are examined in order to reveal the
posed retrieval method is valuable for applied climate
causes which are most responsible for variations to
research such as analyzing interannual variations in
vegetation cover.
vegetation cover.
Using 1982 2000 NOAA-AVHRR remotely-sensed
1 Data sources and the spatial distribu-
data, we analyze a maximum LAI ten day interval time
tion of land surface properties for the
series at an 8 km 8 km resolution. However, it is diffi-
Qinghai-Tibet Plateau
cult to contrast seasonal LAI changes at a specific site
with others due to out of phase vegetation phenology
The Qinghai-Tibet Plateau is located in a climatic region
and extreme weather events which influence vegetation
which is subdivided into four sub-climate divisions in
cover. We use each year s maximum monthly LAI value
order to describe temperature and rainfall characteristics
as the yearly vegetation cover index. The maximum
as accurately as possible[29]: the Humid South Plateau
monthly LAI approach has a number of advantages, in-
(H1), the Sub-humid South Plateau (H2), the Sub-dry
cluding the ability to capture optimal vegetation cover
South Plateau (H3) and the Dry South Plateau (H4). Air
conditions, the capacity to remove out of phase vegeta-
temperature and rainfall patterns lead to an asymmetric
tion phenology, and vegetation cover fluctuations caused
distribution of frozen earth on the Qinghai-Tibet Plateau
by extreme weather events during the vegetation growth.
(Figure 1(a)). The spatial distribution of land cover is
shown (Figure 1(b)). A correlation analysis based on
2 Spatiotemporal vegetation cover
NOAA-NDVI satellite data (with an 8 km 8 km resolu-
changes for the Qinghai-Tibet Plateau
tion) clearly identifies four vegetation phenology re-
gions (Figure 1(c)). Longer periods of snowfall and Empirical orthogonal function (EOF) analysis is used to
snow cover occur in the Qinghai-Tibet Plateau than in investigate spatiotemporal vegetation cover changes in
other regions at a similar latitude, thereby impacting the the Qinghai-Tibet Plateau. EOF is a statistical method
spatiotemporal heterogeneity of land surface properties for the spatiotemporal decomposition of a signal or data
(Figure 1(d))[32]. set. It is to decompose two dimensional matrixes F(t, n)
with a time scale T and a spatial scale n into the multi-
There are two factors which make it difficult to ana-
916 XU XingKui et al. Chinese Science Bulletin March 2008 vol. 53 no. 6 915-922
ARTICLES
Figure 1 (a) Distribution of frozen earth in the TB[30]; (b) distribution of land cover type in the TB[31]; (c) distribution of vegetation phenology variations
in the TB; (d) monthly snow fluctuations based on weather station observational data from 1970 to 2000.
plication of a weighted temporal matrix T and an ei- the annual vegetation cover trend is dominated by the
genvector matrix X: trends and status of vegetation cover in the southern re-
gion of plateau. Since other regions have less vegetation
n
Fij = Tik X kj . (1) cover than the Humid South Plateau, it is difficult to
ATMOSPHERIC SCIENCES
k =1
analyze how vegetation cover change impacts the entire
That is, a data set F(t, n) can be approximatively ex-
plateau.
pressed in terms of primary eigenvectors and corre-
Total LAI change is composed of the first eigenvector
sponding temporal weighting coefficients. By analyzing
(representing overall average vegetation cover change)
these eigenvector and temporal weighting coefficients,
and other eigenvectors (which reflect regional differ-
the temporal and spatial changes of F(t, n) can be ex-
ences in vegetation cover change). The second eigen-
pressed. For a data set F(t, n) undergoing stable tempo-
vector accounts for 11.9% of the total variance (which
ral changes, the temporal trends are reflected in the first
accounts for most of the regional difference observed in
eigenvector while the remaining eigenvectors reflect
the vegetation cover change). The spatial distribution of
local changes.
the second eigenvector shows that an increase in vegeta-
The first and second EOF modes identify the major
tion cover in one part (i.e. southern region) of the Qing-
signals from LAI data set (Table 1). The first eigenvector,
hai-Tibet Plateau will lead to a decrease in the vegeta-
representing the overally trend of vegetation cover
tion cover in another part (i.e. the northern part) (Figure
change throughout the plateau shows almost all positive
2(b)). This phenomenon is prominent in middle-eastern
values and accounts for 50.4% of the total variance (a
regions of the plateau.
higher percentage than the variance individually ex-
The first and second PCs reflect the interannual vari-
plained by any of the other eigenvectors). The center of
ability of their respective eigenvectors. Both the first and
maximum value for the first eigenvector is located in the
second PCs show a large interannual variability and
Humid South Plateau (H1)(Figure 2(a)), implying that
Table 1 The percentage of variance explained by the eigenvectors using EOF expansion of maximum annual LAI
Serial number 1 2 3 4 5 6 7 8 9 10
Eigenvectors 7.54 1.78 1.29 0.93 0.72 0.52 0.43 0.36 0.28 0.23
Variance 50.4 11.9 8.6 6.2 4.8 3.5 2.9 2.4 1.9 1.5
XU XingKui et al. Chinese Science Bulletin March 2008 vol. 53 no. 6-915-***-***
Figure 2 Distribution of the first eigenvector (a) and the second eigenvector (b) decomposed LAI data set by EOF on the Qinghai-Tibet Plateau.
linearly increasing trends (Figure 3), suggesting that the cover ratio and precipitation. In arid regions, vegetation
averaged vegetation cover ratio is increasing, especially is quite sensitive to precipitation, and hence a negative
in the south region of plateau. However, this enlarges the correlation exists between the vegetation cover ratio and
vegetation cover ratio between the southern and northern temperature. In contrast, for regions with sufficient pre-
plateau regions. cipitation, temperature is the primary factor limiting
vegetation growth, and the influence of precipitation on
3 Impacts of climate-driven variables on vegetation growth is less important[36].
vegetation cover From the 1970 2000 observation data, the statistical
results show relatively stable precipitation levels with a
Remote sensing data includes vegetation cover informa-
slight decreasing annual mean precipitation trend during
tion which is influenced by both climate variables and
the mid-1990s in the Sub-dry South Plateau (H3). An-
human activities. The Qinghai-Tibet Plateau is relatively
nual mean temperature, however, increases significantly
undisturbed due to low population densities and hence
in all four climate divisions. Beginning in the 1990s, the
vegetation cover and ecosystem changes are primarily
warming temperature trend becomes more significant
controlled by the climate system. Precipitation and tem-
(Figure 4). Therefore, the distributions of eigenvectors
perature are two major climatic factors which affect
and PC changes from the decomposed LAI by EOF have
vegetation cover and ecosystem changes. Precipitation
a close relationship with temperature increases.
provides water for vegetation growth and with sufficient
A correlation between the annual mean LAI and pre-
precipitation (in the absence of temperature anomalies),
cipitation anomaly is calculated (Figure 5(a)). The cor-
a positive correlation exists between the vegetation
Figure 3 First and second PCs of EOF for LAI corresponding to eigenvectors.
918 XU XingKui et al. Chinese Science Bulletin March 2008 vol. 53 no. 6 915-922
ARTICLES
Figure 4 Annual mean precipitation (P) and temperature (T) in the Humid South Plateau (H1), the Sub-humid South Plateau (H2), the Sub-dry South
Plateau (H3) and the Dry South Plateau (H4) from 1970 to 2000.
ATMOSPHERIC SCIENCES
Figure 5 Precipitation anomalies (PA) and annual mean LAI (a), and the first PC of EOF for LAI (b) from 1970 to 2000.
relation coefficient (r) is 0.512 at the 95% significance fluctuations for the entire plateau region is mainly con-
level (more than 0.468). Since the LAI PC1 (for EOF) trolled by precipitation, and the regional vegetation
represents the changing trend of average LAI across the cover difference is not related to precipitation. Accord-
entire plateau region, the correlation between PC1 and ingly, other meteorological factors are likely responsible
precipitation anomaly is 0.518, at the 95% significance for the regional difference of vegetation cover.
level (Figure 5(b)). However, a significant correlation Two pieces of evidence support this hypothesis. First,
was not observed between precipitation anomalies and a significant correlation was not found between annual
other PCs. The significant correlations between precipi- mean temperature and the first or second PC. Second,
tation anomaly and LAI as well as between LAI PC1 the spatial distribution of the correlation between annual
mean temperature from 1 1 resolution observation
(for EOF) suggests that annual mean vegetation cover
XU XingKui et al. Chinese Science Bulletin March 2008 vol. 53 no. 6-915-***-***
data and annual mean LAI confirms that the effects of Plateau.
temperature on vegetation are a primary reason for the
4 Conclusions and discussion
lack of a significant correlation between overall annual
mean temperature and annual mean LAI on the Qing-
The impact of climate and other natural factors is an
hai-Tibet Plateau (Figure 6). The climate of the northern
important component of vegetation growth and ecosys-
part of the plateau is arid and semi-arid, with an annual
tem dynamics. The Qinghai-Tibet Plateau represents an
mean precipitation of approximately 240.8 mm. Ac-
ideal area to study interaction between climate and
cordingly, temperature increases cause additional
vegetation cover due to the complicated climate regime
evaportanspiration from the land surface. Vegetation
as well as a low population density (and limited human
growth is limited by severe aridity, causing a negative
activities). By analyzing precipitation and temperature
correlation coefficient. In contrast, in the humid and sub-
conditions that affect vegetation growth, it is shown that
humid southern plateau, precipitation is sufficient, and
climate divisions on the Qinghai-Tibet Plateau results in
annual mean precipitation reaches 535.4 mm. The cor-
spatio-temporal regional land cover characteristics.
relation coefficient shows the positive value as a result
Vegetation cover changes from 1980 2000 are associ-
of increasing temperature which is favorable for vegeta-
tion growth. ated with increasing temperature. In the southern regions
of the plateau, vegetation cover in Humid South Pla-
teau(H1)plays a critical role, influencing the annual
mean vegetation cover trend for the entire plateau. On
the one hand, the higher temperatures observed in the
southern Qinghai-Tibet Plateau lead to longer plant
growing periods, and an expansion of vegetation. How-
ever, it is known that vegetation water requirements also
increase with rising temperatures and expanding vegeta-
tion cover. Accordingly, a decrease in precipitation in
the Humid South Plateau (H1) would contribute to de-
Figure 6 The distribution of the correlation coefficient between LAI and
temperature.
graded vegetation cover as temperatures rise.
Vegetation cover and ecosystems possess the ability
The distribution of the second eigenvector (Figure
to adapt to the combined impact of changes in various
2(b)) is now compared with the spatial distribution of
climate elements, although vegetation growth flourishes
the correlation coefficient between LAI and temperature
most when a balance among climate elements is
(Figure 6). The distribution of the second eigenvector s
achieved. Important conclusions of this paper are pro-
negative value is found to be generally consistent with
vided below:
the negative correlation. Similarly, the distribution of the
(1) From the early 1980s to 2000, vegetation cover on
positive value in the second eigenvector is also consis-
the Qinghai-Tibet Plateau follows an increasing trend. A
tent with the positive correlation. The spatial consistency
significant percentage of the vegetation is located in the
of the climate scale suggests that temperature is respon-
humid southern region of the plateau, where vegetation
sible for the seasaw pattern of vegetation cover in the
cover change plays a decisive role in the ecology of the
southern and northern regions of plateau. In the northern
entire plateau area. Specifically, increasing vegetation
sections of the plateau, scant precipitation along with
cover in the humid south region of the plateau is driving
increasing temperatures exacerbates drought conditions,
the observed increases in vegetation cover throughout
leading to restrained vegetation growth. While southern
the entire plateau.
regions of the plateau have sufficient precipitation, in-
(2) Climate warming is responsible for the annual
creasing temperatures lead to more vegetation cover.
vegetation cover changes which exhibit the observed
Due to stable annual mean precipitation values in four
seasaw pattern between the southern and northern re-
climate divisions, it follows that increasing temperature
gions of the Qinghai-Tibet Plateau. Higher cumulative
(rather than precipitation) is the primary cause of the
temperatures are advantageous for vegetation growth
observed vegetation cover changes in the Qinghai-Tibet
920 XU XingKui et al. Chinese Science Bulletin March 2008 vol. 53 no. 6 915-922
ARTICLES
and ecosystem development in the humid southern re- ferences on the Qinghai-Tibet Plateau. Specifically, the
gion of this plateau. On the other hand, in the arid or precipitation dominates annual vegetation cover changes
semi-arid northern regions of plateau, a degradation in and drought becomes more severe with increasing tem-
vegetation cover is observed. This is particularly true peratures in the northern regions of the plateau. As a
around the Sub-dry South Plateau (H3) where vegetation result, increased vegetation growth requires more pre-
cover is relatively dense. In the northern regions of the cipitation. Meanwhile, it also causes a longer vegetation
plateau, increasing temperatures significantly impact growth period and a higher vegetation cover ratio in the
vegetation growth. Finally, vegetation degradation asso- humid southern regions of the plateau, and the vegeta-
ciated with a slight decrease in precipitation was ob- tion requires more water (similar to the water needs of
served during the mid-1990s in the northern plateau re- the arid northern plateau). Therefore, a positive correla-
gion. tion exists between precipitation and total vegetation
(3) Both temperature and precipitation are climate- cover on the Qinghai-Tibet Plateau due to rising tem-
driven factors that cause regional vegetation cover dif- peratures.
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Science in China Series D: Earth Sciences
EDITOR
SUN Shu
Institute of Geology and Geophysics
Chinese Academy of Sciences
Beijing 100029, China
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