Global Change Biology (2003) 9, 536±546
Response of terrestrial carbon uptake to climate
interannual variability in China
M I N G K U I C A O *, S T E P H E N D . P R I N C E *, K E R A N G L I {, B O T A O {, J E N N I F E R S M A L L * and
XUEMEI SHAO{
*Department of Geography, Rm. 2181 LeFrak Hall, University of Maryland, College Park, MD 20742-8225, USA, {Institute of
Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
Abstract
The interest in national terrestrial ecosystem carbon budgets has been increasing because
the Kyoto Protocol has included some terrestrial carbon sinks in a legally binding
framework for controlling greenhouse gases emissions. Accurate quantification of the
terrestrial carbon sink must account the interannual variations associated with climate
variability and change. This study used a process-based biogeochemical model and a
remote sensing-based production efficiency model to estimate the variations in net
primary production (NPP), soil heterotrophic respiration (HR), and net ecosystem production (NEP) caused by climate variability and atmospheric CO2 increases in China
during the period 1981±2000. The results show that China's terrestrial NPP varied between 2.86 and 3.37 Gt C yr21 with a growth rate of 0.32% year21 and HR varied between
2.89 and 3.21 Gt C yr21 with a growth rate of 0.40% year21 in the period 1981±1998.
Whereas the increases in HR were related mainly to warming, the increases in NPP
were attributed to increases in precipitation and atmospheric CO2. Net ecosystem
production (NEP) varied between 20.32 and 0.25 Gt C yr21 with a mean value of
0.07 Gt C yr21, leading to carbon accumulation of 0.79 Gt in vegetation and 0.43 Gt in
soils during the period. To the interannual variations in NEP changes in NPP contributed
more than HR in arid northern China but less in moist southern China. NEP had no a
statistically significant trend, but the mean annual NEP for the 1990s was lower than for
the 1980s as the increases in NEP in southern China were offset by the decreases in
northern China. These estimates indicate that China's terrestrial ecosystems were taking
up carbon but the capacity was undermined by the ongoing climate change. The estimated NEP related to climate variation and atmospheric CO2 increases may account for
from 40 to 80% to the total terrestrial carbon sink in China.
Keywords: China, climate change, interannual variability, terrestrial carbon sink
Received 16 September 2002; revised version received and accepted 9 December 2002
Introduction
The interest in the terrestrial carbon sink at national
levels has been increasing (Schimel et al., 2000; Tate et al.,
2000; Fang et al., 2001; Pacala et al., 2001) since the agreement of Kyoto Protocol was reached because the treaty
include some terrestrial carbon sinks in a legally binding
framework for reducing greenhouse gases emission.
High uncertainties in estimating the terrestrial carbon
Correspondence: M. Cao, Department of Geography, Rm. 2181
LeFrak Hall, University of Maryland, College Park,
MD 20742-8225, USA, tel. ‡301 405 7891, fax ‡301 314 9299,
e-mail: [email protected]
536
sink in part cause the international disagreement in the
negotiation of the Kyoto Protocol and the debate about
how to implement the treaty (IGBP, 1998). The terrestrial
carbon sink has high spatial and temporal variability, and
the temporal variability has different characteristics at
different scales (e.g. seasonal, interannual, and decadal
scales), so accurate estimates of the terrestrial carbon sink
must account the high spatial and temporal variations.
Many factors such as changes in climate, atmospheric
CO2 and land use cause the variations in the terrestrial
carbon sink. The growth enhancement by changes in
climate and atmospheric composition was believed to
account for a large part of the terrestrial carbon sink
(Friedlingstein et al., 1995; Thompson et al., 1996), but
ß 2003 Blackwell Publishing Ltd
T E R R E S T R I A L C A R B O N U P T A K E V A R I A T I O N I N C H I N A 537
recent studies indicated that the contribution is minor in
the United States (Caspersen et al., 2000; Schimel et al.,
2000), and the contribution in other regions of the world
has yet to be determined. A better understanding of the
relative contributions of the natural growth enhancement
and human-induced land use change are fundamentally
important to making environmental policies and ecosystem carbon management for enhancing the terrestrial
carbon sink.
China has the third largest land area and diverse climates and biomes. Quantifying the spatial and temporal
variations of terrestrial carbon sink in China is of great
significance to understanding the global carbon dynamics. In the last decade, many studies have been conducted
to estimate China's terrestrial net primary productivity
(NPP) and carbon storage in vegetation and soils (Fang
et al., 1996; Zhou & Zhang, 1996; Xiao et al., 1998; Liu,
2001; Sun & Zhu, 2001). Using forest biomass inventory
data, a recent study estimated substantial increases in
China's forest carbon storage in the past two decades due
to national afforestation and reforestation programs (Fang
et al., 2001). However, few studies have been conducted to
estimate interannual variations and trends in the terrestrial
carbon sink in China in responses to climate variability. In
this study, we used CEVSA (Carbon Exchange in the
Vegetation-Soil-Atmosphere system, Cao & Woodward,
1998a, b) and GLO-PEM (GLObal Production Efficiency
Model, Prince & Goward, 1995; Goetz et al., 2000; Cao
et al., in press) to estimate interannual variations in NPP,
soil heterotrophic respiration (HR), and net ecosystem
productivity (NEP) caused by climate and atmospheric
CO2 increases from 1981 to 1998 in China.
Methods
Estimating NPP, HR, and NEP with the process-based
CEVSA
Terrestrial ecosystem carbon fluxes are controlled by ecophysiological factors (e.g. vegetation pattern and structure, photosynthesis, and autotrophic and heterotrophic
respiration) and environmental factors (e.g. radiation,
temperature, water, and nutrients). To describe the controls of these factors over ecosystem carbon fluxes,
CEVSA (Cao & Woodward, 1998a, b) consists of four
modules: a biophysical module calculates the transfers
of radiation, water, and heat; a plant growth module
describes photosynthesis, autotrophic respiration, carbon
and nitrogen allocation and accumulation among plant
organs, leaf area index (LAI) and litter production; and a
soil module simulates decomposition of organic carbon
and the transformations, inputs, and outputs of nitrogen
in the soil. The key processes of the models are given in
the following sections.
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
Photosynthesis, NPP, and LAI Rates of plant photosynthesis depend on the biochemical efficiency of CO2 assimilation and the CO2 diffusion into leaf intercellular
spaces through stomata (Collatz et al., 1991; Woodward
et al., 1995). Plant CO2 assimilation and stomatal conductance interact with each other and are regulated by environmental factors such as radiation, temperature, air
humidity, soil moisture, and atmospheric CO2 concentration (Collatz et al., 1991; Woodward et al., 1995).
A part of the carbon fixed in photosynthesis is consumed
in autotrophic respiration that maintains living tissue
and synthesizes new tissue. NPP is the difference between the gross photosynthesis and autotrophic respiration. Based on the above processes, CEVSA calculates
rates of plant photosynthesis, stomatal conductance, and
autotrophic respiration for determining LAI and NPP
(Woodward et al., 1995; Cao & Woodward, 1998b). In
the calculations, the plant canopy is divided into layers
each of which has a unit of leaf area index, and the rates
of CO2 assimilation and stomatal conductance of each
layer are calculated separately. LAI is determined based
on the maximization of the net carbon assimilation of the
whole canopy and the water balance between water
supply and evapotranspiration (Woodward et al., 1995).
Carbon allocation and turnover in vegetation According to
the resource balance hypothesis (Chapin et al., 1987),
plants adjust carbon allocation among plant organs to
balance resource acquisition (e.g. light, carbon, nutrients
and water). CEVSA calculates the carbon allocation
among leaves, stems and roots based on the mesophyll
resistance to CO2 assimilation and stomatal resistance to
water vapor (Givnish, 1986). The carbon allocated to
various plant organs is given a mean residence time
with a statistical distribution that varies with plant functional type. The carbon storage in various plant organs
and litter production are estimated based on the carbon
allocation, autotrophic respiration, residence time, and
the mortality. Litter production was assumed to occur at
the end of the growing season in deciduous forests and
seasonal grasses and at the beginning of the growing
season in a seasonal evergreen vegetation and to spread
distributing evenly over the year in evergreen vegetation
(Cao & Woodward, 1998b).
HR, soil carbon storage, and NEP CEVSA divides soil
organic matter into surface litter, root litter, microbes,
and slow and passive carbon pools (Cao & Woodward,
1998b). Litter entering soils is transformed into soil
organic matter and is released into the atmosphere in
microbial decomposition. All carbon transformations
and decomposition in these pools are treated as firstorder rate reactions that are affected by temperature,
soil moisture, nitrogen availability, soil texture, and the
538 M . C A O et al.
lignin/nitrogen ratio. Nitrogen transformations between
these pools follow carbon flows and are equal to the product of the carbon flux and the nitrogen/carbon ratio of the
pool that receives the carbon. HR is determined as the total
carbon releases as gaseous products during microbial
decomposition. The difference between NPP and HR, defined as NEP, representing the net ecosystem-atmosphere
carbon flux provided there is no other disturbance such as
fire and harvest.
Data sources and model runs We ran CEVSA with observation-based data of climate, atmospheric CO2, and vegetation distribution at a spatial resolution of 0.58 and a
time-step of one month. The climate data included
monthly mean values of temperature, precipitation,
water vapor pressure, wet day frequency, diurnal temperature range, and sunshine duration (New et al., 2000).
Monthly mean atmospheric CO2 concentrations were
obtained from the measurements in the Mauna Loa,
Hawaii (Keeling & Whorf, 2002). The current actual
vegetation distribution was derived from a land cover
map based on the observation of NOAA Advanced
Very High Resolution Radiometer (AVHRR, Hansen
et al., 2000). The information on soil properties was derived from the FAO-IIASA-ISRIC global soil data set
(Batjes et al., 1997). Using the climate, vegetation and
soil data, we first ran CEVSA with an average climate
for the period 1951±1980 until an ecological equilibrium
was reached. Starting from the equilibrium status, we
then made dynamic simulations from January 1951 to
December 1998 with transient changes in climate and
atmospheric CO2. The run from 1951 to 1980 was to
establish realistic initial pool sizes of carbon, carbon and
water for the period 1981±1998.
St is the incident PAR in time t. Nt is the fraction of
incident photosynthetically active radiation (PAR)
absorbed by vegetation canopy (Fapar) calculated as a
linear function of NDVI (Prince & Goward, 1995). eg is
the light utilization efficiency of the absorbed PAR by
vegetation in terms of gross primary production. R is
autotrophic respiration calculated as a function of standing above-ground biomass, air temperature, and photosynthetic rate (Prince & Goward, 1995; Goetz et al., 2000).
Detailed descriptions of the algorithms for these variables
are given in (Prince & Goward, 1995; Goetz et al., 2000;
Cao et al., in press).
Satellite data sources and processing GLO-PEM was driven
with the Pathfinder AVHRR Land (PAL) data at resolutions of 8 km and 10 days derived from channels 1, 2,
4 and 5 of AVHRR sensors aboard the NOAA-7, 9, 11, and
14 satellites ( James & Kalluri, 1994). While the effects of
Rayleigh scattering and ozone were corrected in producing the Pathfinder data sets ( James & Kalluri, 1994),
cloud screening (Rossow et al., 1996) was carried out in
GLO-PEM. The equatorial crossing time of AVHRR
changed substantially both within and between the satellite platforms (Gutman, 1999a), the orbital drift effects on
the thermal bands were corrected here using the
approach of Gleason et al. (2002). The incident PAR was
obtained from the International Satellite Cloud Climatology Project (Frouin & Pinker, 1995). The data of precipitation were derived from Global Precipitation
Climatology Program (GPCP) data sets, inferred from
infrared and microwave satellites (Huffman & Bolviv,
2000).
Results
Estimating NPP with the remote sensing-based GLO-PEM
Terrestrial net primary productivity (NPP)
We also estimated interannual variations in NPP using
the remote sensing-based GLO-PEM (Prince & Goward,
1995; Goetz et al., 2000; Cao et al., in press). GLO-PEM
uses data almost entirely from satellite observation, including both the normalized difference vegetation index
(NDVI) and meteorological variables, therefore provides
an independent estimate to evaluate the results of
CEVSA. GLO-PEM consists of linked components that
describe processes of canopy radiation absorption, utilization, autotrophic respiration, and the regulation of
these processes by environmental factors such as temperature, water vapor pressure deficit, and soil moisture
(Prince & Goward, 1995; Goetz et al., 2000; Cao et al., in
press):
X
NPP ˆ
…St Nt †eg R
The estimated NPP with CEVSA ranged from
40 g C m yr 1 for open shrubs to 1200 g C m 2 yr 1 for
evergreen broadleaf forests. The temporal variation of
NPP was dominated by the seasonal cycle between 2.1
and 112.9 g C m 2 month 1 with a coefficient of variation
(CV) of 88% (Fig. 1). The deseasonalied anomaly of NPP
(a difference between the NPP of a given month and the
mean value for that month in the analysis period) had a
CV of only 7.5% (Fig. 1). Annual total terrestrial NPP
varied between 2.86 and 3.37 Gt C, the mean value for
the period 1981±1998 was 3.09 Gt C (Fig. 2). The interannual magnitude of NPP (a difference between the maximum and minimum annual NPP) was 0.48 Gt C, 15.6%
of the average value. At the national level, the interannual variation in NPP was correlated with precipitation
(R2 ˆ 0.55, P < 0.01) but was not with temperature. However, temperatures affected the responses of NPP to
t
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
T E R R E S T R I A L C A R B O N U P T A K E V A R I A T I O N I N C H I N A 539
Anomaly
NPP
120
100
5
80
0
60
40
−5
Monthly NPP (g C m−2)
20
1982 1984
(a)
1988
1990 1992
NPP
HR
1994
1996 1998
Litter
0
2000
NEP
0.3
3.4
0.2
0.1
3.2
0
−0.1
3
−0.2
−0.3
−0.4
2.8
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
(b)
1.5
1
Temperature (8C)
Atmospheric CO2 (Pa)
Precipitation (mm yr−1)
100
50
0.5
0
−0.5
−1
0
Precipitation
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
1986
NEP (Gt C yr−1)
precipitation; increases in temperature appeared to enhance the increases of NPP in wet years (e.g. 1998, 1994
and 1990) and the decreases in dry years (e.g. 1982, 1986
and 1997), and decreases in temperature appeared to
moderate the reduction of NPP in dry years (e.g. 1984
and 1995, Fig. 2).
The response of NPP to climate variability differed
between regions (Fig. 3, Table 1). In arid Northwest and
North China, NPP was clearly correlated with precipitation (R2 ˆ 0.97, P < 0.01); almost every increase (decrease)
in precipitation caused an increase (decrease) in NPP,
and the large interannual variability in precipitation
NPP made NPP highly variable with a CV of 14.9%. In
Northeast China that has a cool climate but warm
summer, annual NPP were also sensitive to variations
in precipitation (R2 ˆ 0.75, P < 0.01), and the correlation
with temperature was weak (R2 ˆ 0.12, P < 0.05). In warm
and moist Southeast China, NPP was correlated negatively with temperature (R2 ˆ 0.27, P < 0.05) but had no
correlation with precipitation, however, annual NPP was
usually high in the years with moderate precipitation
(e.g. in 1985, 1992, 1996) and was low in the years with
very high precipitation (e.g. 1983 and 1998, Fig. 3). In
Southwest China that has moderate temperature and
precipitation, NPP had the minimum interannual variability among various regions with a CV of 1.8% (Table 1),
and its interannual variation was correlated positively
with both temperature (R2 ˆ 0.53, P < 0.01) and precipitation (R2 ˆ 0.49, P < 0.01).
NPP decreased markedly in 1997 because of a combined warming and drought (Fig. 2). In this year, the
national mean NPP was lower than the average level by
6.5% and reduced by from 8 to 24% in Northeast, North,
and Northwest China with decreases of precipitation by
from 12 to 28% and increases of temperature by from 0.6
to 1.2 8C. The decreases were particularly large, by
more than 120 g C m 2 yr 1, in Songnen Plain, HuangHuai-Hai Plain, and Loess Plateau. NPP increased
NPP, litter, and HR (Gt C yr−1)
−10
1980
Temperature and atmospheric CO2
Fig. 1 Temporal variations in nationally
mean net primary production (NPP). The
deseasonalied anomaly was calculated as
the difference between a monthly NPP
and the mean value for that month. The
solid straight line is the trend line of the
anomaly.
Monthly NPP anomaly (g C m−2)
10
−50
−1.5
−100
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Fig. 2 Changes in annual net primary production (NPP), litter
production, soil heterotrophic respiration (HR), and net ecosystem production (NEP) (a), and interannual anomalies in national
mean temperature, precipitation, and atmospheric CO2 concentration (b).
substantially in 1998 when both temperature and precipitation reached the highest on the record in the 20th century, which increases by 0.97 8C and 13%, respectively,
from the average levels for the analysis period. In this
year, the national mean NPP was 11% higher than the
average level, and the increases occurred almost in all
regions, especially in Northeast, North, and Southwest
China where precipitation increased by over 25%.
Annual NPP had an increasing trend by 0.32% year 1
2
(R ˆ 0.21, P < 0.05) during the period 1981±1998. The
540 M . C A O et al.
HR
NEP
0.12
0.08
0.36
0.04
0.32
0
0.28
−0.04
0.24
−0.08
0.2
−0.12
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
NPP
HR
NEP
0.04
0.43
0.02
0.41
0
0.39
−0.02
−0.04
0.37
−0.06
0.35
−0.08
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
0.5
NPP
HR
NEP
North
Southeast
Southwest
0.16
0.12
0.46
0.08
0.04
0.42
0
0.38
−0.04
−0.08
0.34
NEP (Gt C yr−1)
NPP and HR (Gt C yr−1)
Northeast
Northwest
0.06
NEP ( Gt C yr−1)
0.4
0.45
NPP and HR (Gt C yr−1)
NPP
NEP ( Gt C yr−1)
NPP and HR (Gt C yr−1)
0.44
−0.12
0.3
−0.16
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
HR
NEP
0
1.32
−0.04
1.24
−0.08
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
NPP
HR
NEP
0.06
0.66
0.04
0.62
0.02
0.58
0
NEP (Gt C yr−1)
0.04
1.36
1.28
0.7
0.08
NPP and HR (Gt C yr−1)
−1
1.4
NPP
NEP (Gt C yr−1)
NPP and HR (Gt C yr )
1.44
0.54
−0.02
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Fig. 3 Interannual variations in net primary production (NPP), soil heterotrophic respiration (HR), and net ecosystem production (NEP)
in various climate regions. The mean temperature and precipitation for the regions were given in Table 1.
mean NPP for the later 1990s (1995±1998) was 4.1%
higher than that for the earlier 1980s (1981±1985). NPP
increased mainly in North, Southeast, and Southwest
China but decreased in some regions in Northeast and
Northwest China such as Loess Plateau, Da Xiao Xingan
Mountains, and Sanjiang Plain (Fig. 4). Increases in NPP
occurred in the regions that had significant increases in
precipitation, such as North and Southwest China where
annual mean precipitation increased by over 3.0% from
the 1980s to the 1990s (Table 1). North China Plain and
Liaohe Plain recovered in the later 1990s from the
drought that sustained in the 1980s and the earlier
1990s, and precipitation in southern coastal regions and
Southwest China continued to increase in a trend starting
from the 1960s (Li & Zhang, 1992; Zhou et al., 2000). In
addition, atmospheric CO2 increases helped to enhance
NPP through the fertilization effect on photosynthesis.
According to experimental data (Curtis & Wang, 1998;
Medlyn et al., 2000), the increase in atmospheric CO2
concentration by 1.5 ppmv yr 1 during the period
1981±1998 can increase NPP by about 0.20% year 1.
NPP estimated with satellite data The remote sensingbased GLO-PEM estimated that annual total NPP varied
between 2.77 and 3.33 Gt C with a mean value of
3.00 Gt C, which is very close to the result of CEVSA
(Fig. 5). The interannual anomalies and trend of NPP
also agree generally with the results of CEVSA ± both
estimates indicated that NPP decreased in the mid-1980s
with drought, increased in the mid-1990s with increased
precipitation, and declined markedly in 1997 with record
drought and warming (Fig. 5). However, the growth rate
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
T E R R E S T R I A L C A R B O N U P T A K E V A R I A T I O N I N C H I N A 541
Table 1
Changes in climate and ecosystem carbon fluxes in China's vegetated lands
Northeast
Temperature (8C)
1980s
1990s
Change* (8C)
2.32
2.72
0.40
Precipitation (mm yr 1)
1980s
574
1990s
570
Change* (%)
1.0
NPP (Gt C yr 1)
1980s
1990s
Change*
0.40
0.41
0.01
CV** (%)
6.3
North
6.24
6.70
0.46
447
462
3.4
0.38
0.40
0.02
14.8
Northwest
5.74
6.12
0.38
255
258
1.2
Southeast
Southwest
17.16
17.61
0.45
11.63
11.90
0.27
1397
1440
3.1
0.32
0.32
0.00
12.8
1008
1039
3.1
Whole China
8.71
9.07
0.36
722
739
2.4
0.64
0.65
0.01
1.31
1.35
0.04
3.05
3.13
0.08
4.2
1.8
4.8
1
HR (Gt C yr )
1980s
1990s
Change*
0.40
0.42
0.02
0.37
0.39
0.02
0.29
0.31
0.02
0.62
0.62
0
1.30
1.33
0.03
2.98
3.07
0.09
CV** (%)
4.5
5.3
6.0
4.6
2.8
3.1
NEP (Gt C yr 1)
1980s
1990s
Change*
0.00
0.01
0.01
0.01
0.01
0.00
0.03
0.01
0.02
0.02
0.03
0.01
0.01
0.02
0.01
0.07
0.06
0.01
*The change is from the 1980s and to the 1990s.
**CV is the coefficient of interannual variations in the period 1981±1998.
of 0.57% year 1 (R2 ˆ 0.25, P < 0.05) estimated with GLOPEM was higher than the estimate with CEVSA. Using
observed actual absorption of PAR by vegetation as the
major driver, GLO-PEM had the capacity to detect the
effects of various factors on NPP, including land use
changes that were reported having increased forest coverage and carbon stock in the last decades (Fang et al.,
2001; Li & Zhu, 2002), but CEVSA just accounted the
influences of climate and atmospheric CO2. This difference may explain the higher estimate of NPP growth with
GLO-PEM. The extra decreases of NPP in 1992 and 1993
estimated with GLO-PEM may be related to the interference to the satellite sensors by the aerosols from the
volcanic eruptions of Pinatubo in 1991 (Gutman, 1999b).
The GLO-PEM estimates at higher resolution (8 km)
provided more details of the spatial variations in NPP
than the estimates with CEVSA at 0.58 resolution (Fig. 4).
Both of the models estimated that NPP increased in most
regions during the last two decades. However, GLO-PEM
did not detect the large decreases of NPP in Da Xiao
Xingan Mountains and the upper reaches of the Huai
River estimated by CEVSA. The climate data used in
both GLO-PEM and CEVSA show warming and drying
occurred in these regions in the late 1990s, but the NDVI
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
that was used to drive GLO-PEM had no significant
decreases in these regions. In addition, the estimated
increase of NPP in North China with GLO-PEM was
smaller than the CEVSA result because satellite-derived
precipitation had only moderate increases in this region
in the late 1990s.
Soil heterotrophic respiration (HR)
The nationally mean HR changed between 10.0 and
70.9 g C m 2 month 1 with a CV of 59%, but the deseasonalied anomaly had a CV of only 5.3% (Fig. 6), smaller
than the variability in NPP. Annual HR varied between
2.89 and 3.21 Gt C with a mean value of 3.02 Gt C (Fig. 2).
At the national level, annual HR was positively correlated with temperature (R2 ˆ 0.56, P < 0.01) but was not
with precipitation. As expected, HR reached the highest
in the warmest years 1997 and 1998, but the spatial pattern of the increases differed between the two years. In
1997, annual HR increased by 0.18 Gt C with an increase
of temperature by 0.41 8C and a decrease of precipitation
by 2.5% from the average levels. In this year, HR increased significantly in Northeast and Southeast, but it
had no increase in arid North and Northwest China. In
542 M . C A O et al.
CEVSA
NPP anomaly (g C m−2 month−1)
10
g C m−2 yr −1
GLO-PEM
5
0
−5
−10
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
3.4
< −20
−20 to 0
0
0 − 20
20 − 40
40 − 60
> 60
CEVSA
CEVSA
GLO-PEM
GLO-PEM
NPP (Gt C yr−1)
3.2
3
2.8
2.6
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
1998, HR increased as both temperature and precipitation
reached the highest on the record in the 20th century. In
this year, HR increased mainly in the central and southwestern China with combined increases in temperature
and precipitation, but decreased in Northeast China with
increases in precipitation.
In arid Northwest and North China, HR varied with
changes in temperatures, but its correlation with precipitation was not significant although water supply is
limited in these regions. In cool Northeast China, HR
was correlated positively with temperature but negatively with precipitation. In Southeast China, HR was
not correlated with the changes in either temperature or
precipitation; nevertheless, it increased more often in dry
years than in wet years. In Southwest China, HR was
correlated positively with both temperature and precipitation, the highest HR occurred in warm and wet
years.
10
Anomaly
HR
80
5
60
0
40
−5
20
Monthly HR (g C m−2 )
Fig. 4 Changes in net primary production (NPP) from the
period 1981±1985 to 1995±1998 estimated with the processbased CEVSA and the remote sensing-based GLO-PEM.
Monthly HR anomaly (g C m−2 )
Fig. 5 A comparison between the estimated national net primary production (NPP) with the process-based CEVSA and the
remote sensing-based GLO-PEM.
−10
0
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Fig. 6 Temporal variations in nationally mean soil heterotrophic respiration (HR). The deseasonalied anomaly was calculated as the difference between a monthly HR and the mean
value for that month. The solid straight line is the trend line of
the anomaly.
During the period 1981±1998 HR increased by 0.40%
year 1 (R2 ˆ 0.45, P < 0.01) with increases in temperature
by 0.04 8C yr 1 (R2 ˆ 0.42, P < 0.01). Annual total HR increased from 2.94 Gt C in the early 1980s to 3.13 Gt C yr 1
in the late 1990s. The increases of HR occurred in almost
all regions, particularly in Northeast Plain, Inner
Mongolia, Loess Plateau and the coastal areas of Southwest China, where annual mean HR for the late 1990s is
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
T E R R E S T R I A L C A R B O N U P T A K E V A R I A T I O N I N C H I N A 543
g C m−2 yr −1
g C m−2 yr −1
< −60
−40 to −20
−20 to 0
< −20
−20 to 0
0
0 −20
20 −40
40 −60
> 60
Net ecosystem production (NEP)
The estimated spatial variations in NEP are shown in
Fig. 8. The mean monthly NEP varied between 15.9 to
39.8 g C m 2, equivalent to a magnitude from 1.02 to
2.55 Gt C month 1 in the national total NEP (Fig. 9).
Annual total NEP changed between 0.32 and 0.25 Gt C
with a CV of 196% (Fig. 2). The mean annual NEP was
0.07 Gt C, indicating that China's terrestrial ecosystems
took up carbon under the climate variation and atmospheric CO2 increases. The mean total carbon storage in
the analysis period was estimated 13.7 Gt in vegetation
and 82.9 Gt in soils (Li et al., 2003). The carbon storage in
vegetation increased consistently with increases in NPP,
the total increase in the analysis period was 0.79 Gt (Fig.
10). The carbon storage in soils increased only 0.43 Gt and
had clear negative fluctuations (Fig. 10) because HR was
higher than litter input in biome years (Fig. 2). The mean
annual NEP for the whole period was close to zero in
most of regions, but significant positive NEP occurred in
Northeast China Plain, south-eastern Tibet, Huang-HuaiHai Plain, and the southern China and significant negative NEP occurred in Da Xiao Xingan Mountains, Loess
Plateau, Yunnan-Guizhou Plateau, and the hilly regions
of Southeast China (Fig. 8). NEP reached the highest in
1996 with a combined increase in NPP and decrease in
HR (Fig. 2), and the increases were particularly great in
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
Fig. 8 Temporal variations in nationally mean net ecosystem
production (NEP). The deseasonalied anomaly was calculated as
the difference between a monthly NEP and the mean value for
that month. The solid straight line is the trend line of the
anomaly.
10
Anomaly
NEP
40
30
5
20
0
−5
10
0
−10
Monthly NEP (g C m−2)
higher by over 40 g C m 2 than for earlier 1980s (Fig. 7).
The decadal mean HR for the 1990s was higher than for
the 1980s by 3.0%, and the increases were generally
higher in the northern China than in the southern
China: the increases from the 1980s to the 1990s were
5.1% in Northeast, Northwest, and North China, but
were only 2.3% in Southeast China and had no increase
in Southeast China (Table 1).
0 − 20
20 − 40
40 − 60
Monthly NEP anomaly (g C m−2)
Fig. 7 Changes in soil heterotrophic respiration (HR) from the
period 1981±1985 to 1995±1998.
0
−10
−20
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
Fig. 9 Mean net ecosystem production (NEP) for the period
1981±1998.
North China Plain, where temperatures decreased by
0.4 8C and precipitation increased by 28% than the average levels. NEP was the lowest in 1997 when NPP
reached the lowest and HR the highest level because of
the severe drought and warming across northern China
(Fig. 2).
Changes in NPP and HR contributed 63 and 37%,
respectively, to the interannual variations in NEP.
Annual NEP generally increased (decreased) with increases (decreases) in NPP, however, in some years HR
played the dominant role in the changes in NEP. For
example, despite increases in NPP, NEP in 1988 and
1994 decreased because of high increases in HR (Fig. 2).
Decreases in HR with a cooling caused by the Mt. Pinatubo eruption in 1991 (Hansen et al., 1996) were responsible to the increases in NEP in 1992 and 1993. The
relative contribution of NPP and HR to the variation of
NEP also differed between regions. In northern China,
NPP played the dominant role, for example, the CV of
544 M . C A O et al.
NPP in Northwest and North China was about twice of
HR (Table 1), contributing over 80% to the variations in
NEP. However, in southern China HR had higher CV
than NPP and hence contributed more to the interannual
variations in NEP (Table 1). For example, the CV of HR in
Southwest China was higher than NPP by 56% (Table 1)
and accounted for 65% of the interannual variations in
NEP.
NEP had no a statistically significant interannual trend
because of the high variability (Fig. 9), but the decadal
mean NEP for the 1990s were lower than that for the
1980s by 0.01 Gt C. NEP increased in Southwest and
Southeast China with increases in precipitation, but the
increases was offset by the decreases in Northeast and
Northwest China with a strong warming and decreases
or little increases in precipitation (Table 1). At the national level, annual NEP was positively correlated with
precipitation (R2 ˆ 0.26, P < 0.05) as NPP, but the relationship with temperature was complicated. NEP in cool
years was generally high (e.g. 1983±1985, 1991±1993,
and 1996), but in warm years it increased (decreased)
with increases (decreases) in precipitation (Fig. 2).
Discussion and conclusions
This study estimated that China's terrestrial NPP varied
between 2.86 and 3.37 Gt C yr 1 and was increasing by
0.32% year 1 during the analysis period. The spatiotemporal variations in NPP simulated with the processbased model are in good agreement with the estimates
based on satellite observational data. HR varied between
2.89 and 3.21 Gt C yr 1 and was increasing by 0.40%
year 1. The national total NEP ranged from 0.32 to
0.25 Gt C yr 1 with a mean value of 0.07 Gt C yr 1, leading
to carbon accumulation of 0.79 Gt in vegetation and
0.43 Gt in soils. To the interannual variations in NEP,
the changes in NPP contributed more than HR in the
arid northern China, but changes in HR contributed
more in the moist southern China. Because of the high
interannual variation, NEP had no consistent interannual
trend, but the decadal mean NEP for the 1990s was lower
by 0.01 Gt C than for the 1980s. The decreases in NEP in
the 1990s were due to higher HR increases than NPP in
Northwest and Northeast China.
The global NEP caused by climate change and atmospheric CO2 increases ranged from 0.5 to 1.5 Gt C yr 1 in
the 1980s and 1990s (Cramer et al., 2001; Cao et al., 2002).
The estimated NEP for China in the present study accounts for 5±14% of the world's total, and it is close to the
0.08 Gt C yr 1 estimated for the United States (Schimel
et al., 2000). The carbon uptake caused by land use change
in China varied from 0.02 (Fang et al., 2001) to
0.09 Gt C yr 1 (Li & Zhu, 2002) during the past two
decades. Adding the land use-induced carbon uptakes
Fig. 10 Changes in vegetation and soil carbon storage in China.
to that caused by climate variations and atmospheric
CO2 increases as the present study estimated, the total
terrestrial carbon sink in China was from 0.09 to
0.16 Gt C yr 1 during the last two decades. To the total
carbon sink, the growth enhancement by climate change
and atmospheric CO2 increases contributed from 44 to
78%. This fraction agrees with the estimates for the global
terrestrial carbon sink (Friedlingstein et al., 1995;
Thompson et al., 1996), but is much larger than the estimates for the conterminous United States, where the bulk
of the terrestrial carbon sink was suggested to arise from
the abandonment of agricultural lands and fire suppression (Caspersen et al., 2000; Schimel et al., 2000). In China,
although afforestation and reforestation programs have
increased the areas of forests and hence carbon sequestration (Fang et al., 2001; Li & Zhu, 2002), there has been
no large-scale abandonment of agricultural lands.
The global carbon budget shows that the net terrestrial
carbon uptake increased from 0.2 Gt C yr 1 in the 1980s to
1.4 Gt C yr 1 in the 1990s (Prentice et al., 2001; Schimel
et al., 2001). Changes in climate and atmospheric CO2
enhanced global NEP substantially and accounted for
most of the increases in the terrestrial carbon sink from
the 1980s to the 1990s (Cao et al., 2002). In contrast, NEP
in China decreased from the 1980s to the 1990s because of
a stronger warming than the global average. Global terrestrial temperature increased by 0.26 8C in northern high
latitudes and by 0.22 8C in low latitudes from the 1980s
and 1990s (Folland et al., 2001), but the increases were
0.40 8C in arid northern China and 0.34 8C in moist southern China (Table 1). The strong warming made the temperatures in arid northern China were often higher than
the average for the 20th century by 1 8C (Li & Zhang,
1992; Zhou et al., 2000), causing higher increases in HR
than in NPP. The precipitation in northern China has
been declined since the 1960s, it recovered in the later
1990s but was still lower than that in the wet 1950s (Li &
Zhang, 1992; Zhou et al., 2000). Continued increases in
precipitation may reverse the NEP decreases in the last
ß 2003 Blackwell Publishing Ltd, Global Change Biology, 9, 536±546
T E R R E S T R I A L C A R B O N U P T A K E V A R I A T I O N I N C H I N A 545
two decades, however, if the current warming trend
sustains and precipitation has no substantial increase
as some climate change projections suggested (Zhou
et al., 2000), China's terrestrial NEP may continue to
decrease.
Acknowledgements
In the study, Cao MK, Prince SD, and Small J were supported by
US National Aeronautics and Space Administration (NASA)
under the contract NAG 5932. Li K, Tao B, and Shao X were
supported by the Knowledge Innovation Program of the Institute
of Geographic Sciences and Natural Resources Research, Chinese
Academy of Sciences under the contract CXIOG-E01-02-04. Helpful comments of two anonymous reviewers are gratefully acknowledged.
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