Global Ecology and Biogeography, (Global Ecol. Biogeogr.) (2014) 23, 144–155
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R E S E A RC H
PAPER
Climate-driven global changes in carbon
use efficiency
Yangjian Zhang1*, Guirui Yu1, Jian Yang2, Michael C. Wimberly3,
XianZhou Zhang1, Jian Tao1, Yanbin Jiang1 and Juntao Zhu1
1
Key Laboratory of Ecosystem Network
Observation and Modeling, Institute of
Geographic Sciences and Natural Resources
Research, Chinese Academy of Sciences, 11A
Datun Road, Beijing 100101, China, 2State
Key Laboratory of Forest and Soil Ecology,
Institute of Applied Ecology, Chinese Academy
of Sciences, Shenyang 110016, China,
3
Geographic Information Science Center of
Excellence, South Dakota State University,
Wecota Hall, 1021 Medary Avenue South,
Brookings, SD 57007-3510, USA
ABSTRACT
Aim Carbon use efficiency [net primary production (NPP)/gross primary production (GPP) ratio] is a parameter related to the allocation of photosynthesized
products by plants and is commonly used in many biogeochemical cycling models.
But how this parameter changes with climates is still unknown. Faced by an aggravated global warming, there is a heightened necessity in unravelling the dependence
of the NPP/GPP ratio on climates. The objective of this study was to examine how
ongoing climate change is regulating global patterns of change in the NPP/GPP
ratio. The study finding would elucidate whether the global vegetation ecosystem is
becoming more or less efficient in terms of carbon storage under climatic
fluctuation.
Location The global planetary ecosystem.
Methods The annual NPP/GPP ratio of the global terrestrial ecosystem was
calculated over a 10-year period based on Moderate Resolution Imaging Spectroradiometer data and an ecosystem productivity model. The temporal dynamics of
the global NPP/GPP ratio and their dependence on climate were investigated.
Results The global NPP/GPP ratio exhibited a decreasing trend from 2000 to
2009 due to decreasing NPP and stable GPP over this period. The temporal dynamics of the NPP/GPP ratio were strongly controlled by temperature and precipitation. Increased temperature lowered the NPP/GPP ratio, and increased
precipitation led to a higher NPP/GPP ratio.
*Correspondence: Yangjian Zhang, Institute of
Geographic Sciences and Natural Resources
Research, Chinese Academy of Sciences, 11A
Datun road, Beijing, Beijing 100101, China.
E-mail: [email protected]
Conclusions The NPP/GPP ratio exhibits a clear temporal pattern associated
with climatic fluctuations at a global scale. The associations of the NPP/GPP ratio
with climatic variability challenge the conventional assumption that the NPP/GPP
ratio should be consistent independent of environmental conditions. More importantly, the findings of this study have fundamental significance for our understanding of ongoing global climatic change. In regions and time periods experiencing
drought or increased temperatures, plant ecosystems would suffer a higher ecosystem respiration cost and their net productivity would shrink.
Keywords
Climate, GPP, global scale, NPP/GPP ratio, NPP, temporal dynamics.
I N T RO D U C T I O N
Increasing atmospheric CO2 concentrations and global climate
change have heightened our need to better understand ecosystem carbon cycle responses to the changing environment. Gross
primary production (GPP), net primary production (NPP) and
autotrophic respiration (Ra) are three basic and highly related
components of carbon cycling. GPP represents the amount of
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photosynthesis by all plants measured at the ecosystem scale
(Luo & Reynolds, 1999; Chapin et al., 2002). NPP is the balance
between the carbon gained by GPP and the carbon released by
plant respiration, i.e. NPP = GPP – Ra (Chapin et al., 2002;
Zhang et al., 2009). Ra plus heterotrophic respiration (Rh)
constitutes ecosystem respiration (Re), i.e. Re = Ra + Rh.
Theoretically, when the ecosystem reaches an equilibrium status,
NPP (GPP – Ra) will be equal to Rh and NPP – Rh will be zero.
DOI: 10.1111/geb.12086
© 2013 John Wiley & Sons Ltd http://wileyonlinelibrary.com/journal/geb
Global carbon use efficiency dynamics
In reality, however, due to their drastically different response
time, NPP – Rh value of a system reaching an equilibrium status
would barely be zero. Vice versa, a system with zero value of
(NPP – Rh) cannot be an indicator of an equilibrium status.
The carbon fixed via photosynthesis is allocated to a variety of
usages, including 50–70%, that is returned immediately to the
environment through Ra (DeLucia et al., 2007; Luyssaert et al.,
2007). These allocation processes are highly relevant to understanding ecosystem carbon cycles and carbon storage, as they
strongly influence the residence time and location of carbon in
the ecosystem. For example, the residence times of the carbon
used for maintenance respiration and the carbon used for the
structural biomass of organs are drastically different (Campioli
et al., 2011). To date, although many studies have been conducted on carbon exchange between plants and the atmosphere,
there are still fundamental unanswered questions about the fate
of the carbon taken up by the ecosystem and its relationship
with the environment and ecosystem types.
The NPP/GPP ratio, or carbon use efficiency, is a commonly
used parameter that reflects the carbon allocated to NPP and to
Ra, the two basic components of GPP. This parameter indicates
the fraction of total assimilated carbon being incorporated into
new tissues and represents the efficiency with which ecosystems
sequester carbon from the atmosphere in terrestrial biomass
(Valentini et al., 2000; DeLucia et al., 2007). The NPP/GPP ratio
is a critical ecosystem property for carbon cycle research because
it is often used to calculated GPP from NPP, or likewise to
estimate Ra as the difference between GPP and NPP (Waring
et al., 1998; Zhang et al., 2009; Macinnis-Ng et al., 2011). For
many carbon cycle or productivity models such as CarnegieAmes-Stanford approach and marine biological laboratory/soilplant-atmosphere canopy model, the NPP/GPP ratio acts as a
fundamental ecosystem model parameter (Potter et al., 1993;
Williams et al., 1997). A minor modification of the parameter’s
value can result in a drastic change in model predictions. For
example, when scaling up landscape model results to a terrestrial
biosphere scale, a 25% increase of this parameter value is
equivalent to enhancing the ecosystem NPP by > 37%, which
could have considerable impacts on estimates of global C
sequestration (DeLucia et al., 2007).
To date, many empirical and field monitoring studies have
been conducted to determine the environmental and biological
controls on the NPP/GPP ratio, including temperature, precipitation, CO2 level and plant age (Ryan, 1991; Cheng et al., 2000;
Van Iersel, 2003; Reich et al., 2006; Metcalfe et al., 2010). Most
studies have concluded that the NPP/GPP ratio is a fixed value
independent of ecosystem type (Gifford, 1994, 1995, 2003; Ryan
et al., 1994; Landsberg & Gower, 1997; Dewar et al., 1998;
Waring et al., 1998) and is constant across various CO2 and
temperature levels for herbaceous and woody plants (Gifford,
1994, 1995; Dewar et al., 1999; Tjoelker et al., 1999; Cheng et al.,
2000). Treating Ra/GPP as constant is a simple and practical way
to incorporate respiration CO2 release into long-term vegetation
productivity models despite the considerable complexity of Ra
and its environmental influences (Gifford, 2003). Many models,
such as CASA (Potter et al., 1993) and FOREST-biogeochemical
cycles (Running & Coughlan, 1988), use a fixed value for the
NPP/GPP ratio across different ecosystems for quantifying Ra.
In other research, the assumption of a constant NPP/GPP
ratio value has been challenged by field observations and modelling studies (Medlyn & Dewar, 1999; Chapin et al., 2002; Xiao
et al., 2003; DeLucia et al., 2007; Zhang et al., 2009). A number
of studies have found that the NPP/GPP ratio varies with ecosystem type, climate, soil nutrients and geographic locations
(Lambers, 1982; Xiao et al., 2003; DeLucia et al., 2007; Maseyk
et al., 2008). A recent study found that forests in high-nutrientavailability areas allocate more photosynthesis to plant biomass
production than forests in low-nutrient-availability areas (Vicca
et al., 2012). Previous findings that the NPP/GPP ratio is independent of biotic and environmental factors have been criticized
for lacking data consistency and continuity over time and space.
These findings have primarily been either based on discrete
measurements of individual plants or small plots of vegetation
in a green house or conducted at a landscape scale over short
time periods (Ryan et al., 1997; Piao et al., 2010). Studies conducted at a single site have limited relevance for other ecosystems, and considerable errors can arise when such patchy data
are scaled up to regional or global levels over long time scales
(Mooney, 1991; Luo & Reynolds, 1999).
New studies utilizing data over broad areas and relatively long
time periods are needed to disentangle the issues related to the
relationship between respiration cost and biotic and environmental factors and to determine how photosynthesis and respiration acclimate to a changing climate. Identifying the ecological
factors controlling the NPP/GPP ratio can significantly improve
our understanding of the carbon cycle, including its interannual variability and long-term trends under climate change.
The newly developed Moderate Resolution Imaging Spectroradiometer (MODIS) NPP and GPP products provide a rare
opportunity to study the dependence of the NPP/GPP ratio on
the environment and climate. These products have the strengths
of global coverage, high geolocation accuracy and high radiometric resolution (Wan et al., 2004), and have been validated as
being consistent with ground flux tower-based GPP and fieldobserved NPP (Zhao et al., 2005; Heinsch et al., 2006). The
MODIS products can capture the spatial and temporal patterns
in GPP and NPP across various biomes and climate regimes and
have been successfully utilized to explore temporal trends in
global NPP (Zhao & Running, 2010, 2011) and the spatial
pattern of the global NPP/GPP ratio (Zhang et al., 2009).
The sole previous global study of the NPP/GPP ratio focused
only on its spatial patterns, and the validity of the conclusions
might be sensitive to the simplified parameters used in the
MODIS NPP and GPP product algorithms (Zhang et al., 2009).
In particular, several basic biome-specific physiological parameters such as the maximum radiation conversion efficiency, the
respiration rate per unit of leaf and livewood biomass were set at
constant values within each biome, limiting the spatial heterogeneity within each biome (Heinsch et al., 2003). Aside from
being constrained by simplified parameters, the previous findings regarding the pattern of the NPP/GPP ratio at a regional
scale relied on only 4 years of data. A longer temporal analysis,
Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
145
Y. Zhang et al.
which is achievable using recently generated data, would more
comprehensively consider the inter-annual variability of the
NPP/GPP ratio and its relationship with climate.
The objective of this study was to examine how ongoing
climate change is regulating global NPP/GPP ratio dynamics.
Specifically, we investigated how the changing climate is driving
the NPP/GPP ratio of global plant ecosystems by exploring its
temporal dynamics using 10 years of remotely sensed model
data. The findings will shed light on the changes in global plant
ecosystem carbon use efficiency and respiration costs in
response to a changing environment and have the potential to
improve global carbon sequestration accounting and advance
global change research.
MATERIALS AND METHODS
MODIS GPP data
Annual 1-km-resolution GPP and NPP data from 2000 to 2009
in TIF format and the WGS84 geographic coordinate system
were downloaded from the Numerical Terradynamic Simulation
Group (NTSG) at the University of Montana (http://www.
ntsg.umt.edu/) and converted into a grid format in ArcGIS
software
(http://www.esri.com/software/arcgis/index.html).
Non-vegetated areas, including water bodies, barren land and
built-up areas for which there are no calculated GPP data, were
eliminated from the analysis.
The latest Collection 5 (MOD17) MODIS GPP values are
calculated as follows:
GPP = ε max × 0.45 × SWrad × FPAR × fVPD × fTmin,
where emax is the max radiation use conversion efficiency of the
vegetation; SWrad is short-wave downward solar radiation, of
which 45% is photosynthetically active radiation (PAR); FPAR is
the fraction of incident PAR that is absorbed by the plant
canopy; and fVPD and fTmin are the reduction scalars from water
stresses (high daily vapour pressure deficit) and low temperature
(low daily minimum temperature Tmin), respectively. Each
parameter value is obtained from the Biome Parameter
Look-Up Table (BPLUT), which contains parameters for specific
leaf area (SLA) and respiration coefficients for representative
vegetation in each biome type (Running et al., 2000; White et al.,
2000). Among the parameters used in calculating GPP, FPAR is
estimated via satellite remote sensing; PAR, SWrad, fVPD and
fTmin are derived from meteorological field data; and emax is
determined based on the theory of Monteith (1972) for each
biome. The GPP product has been validated by comparison with
data from 250 global eddy flux towers, and the results showed
strong correlations between the modelled GPP and the sitederived GPP data (Heinsch et al., 2006).
MODIS NPP data
NPP is calculated as the difference between GPP and respiration,
which includes both maintenance and growth components. To
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model respiration, leaf mass is first estimated from the leaf area
index (LAI) and SLA as Leaf_Mass = LAI/SLA, where LAI is
obtained from the MOD15 product and SLA is obtained from
the BPLUT. Then, root biomass is calculated as Root_Mass =
Leaf_Mass ¥ root_leaf_ratio, where root_leaf_ratio is the ratio
of root to leaf biomass obtained from the BPLUT.
Maintenance respiration is calculated on a daily basis based
on the parameters for maintenance respiration per unit of leaf
and root biomass obtained from the BPLUT. Live woody tissue
is obtained from the difference between the annual maximum
leaf mass and the mass of livewood, and the associated livewood
maintenance respiration is then calculated based on the respiration rate per unit of live wood carbon per day obtained from
the BPLUT.
Growth respiration (GR) is calculated on an annual basis. The
annual leaf GR is calculated as Leaf_GR = (annual maximum
leaf mass) ¥ (annual turnover proportion of leaves) ¥ (leaf base
GR). The annual respiration values for root, livewood and deadwood growth are calculated as ratios of leaf GR. These parameters are obtained from the BPLUT.
Finally, NPP is calculated as follows:
NPP = GPP − (Rml + Rmr + Rmw ) − (Rgl + Rgr + Rgw + Rgd ),
where Rml, Rmr and Rmw are maintenance respiration by leaves,
fine roots and livewood, respectively, and Rgl, Rgr, Rgw and Rgd are
GR for leaves, roots, livewood and deadwood, respectively. More
detailed information on the techniques used for modelling GPP
and NPP can be found in related publications (Heinsch et al.,
2006; Zhao et al., 2006).
The NPP product was validated using the Ecosystem ModelData Intercomparison (EMDI) NPP data set (Olson et al.,
2001). The EMDI NPP data set is composed of 2523 sites that
represent the majority of global biomes. The validation process
demonstrated that the modelled NPP results agree well with
field NPP data.
Land cover, temperature and precipitation data
To be consistent with the GPP and NPP results, we used land
cover data from the MOD12Q1 product and climate data (temperature and precipitation) from the NCEP/DOE II reanalysis
climatic data sets in this study. The University of Maryland land
cover classification system, which comprises 11 vegetation types
and other non-vegetated land use types (Table 1), was used with
the 1-km resolution MOD12Q1 product (land cover type 2 in
the MOD12Q1 data sets). All tiles of landcover data were
merged together and converted into TIFF format using the
MODIS reprojection tool (https://lpdaac.usgs.gov/tools/modis_
reprojection_tool), then converted into grid format and the Sinusoidal projection in ArcInfo to match the NPP and GPP data.
NCEP/DOE II reanalysis data sets of temperature and precipitation from 2000 to 2009 were obtained from the National Oceanic
and Atmospheric Administration (ftp.cdc.noaa.gov) innetCDF
format and converted into grid format using fme software
(http://www.safe.com/fme/fme-technology).
Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
Global carbon use efficiency dynamics
Table 1 The 10-year trend, 10-year mean and maximum inter-annual difference (MID) of the net primary production (NPP)/gross
primary production (GPP) ratio for each ecosystem at the global and hemisphere scales from 2000 to 2009.
Global
Northern Hemisphere
Ecosystems
Trend
(per year)
Mean
1
2
3
4
5
6
7
8
9
10
11
All
0.00050
-0.00150
0.00170
-0.00070
0.00050
-0.00020
-0.00060
0.00100
0.00040
0.00004
0.00030
-0.00007
0.58
0.43
0.51
0.46
0.55
0.48
0.55
0.51
0.47
0.55
0.54
0.53
MID
MID/
Mean
(%)
Trend
(per year)
Mean
0.021
0.031
0.076
0.033
0.022
0.023
0.019
0.019
0.042
0.011
0.014
0.014
3.6
7.3
14.9
7.2
4.0
4.8
3.5
3.7
9.0
2.0
2.6
2.7
0.0005
-0.0008
0.0016
0.0011
0.0005
0.0008
0.0008
0.0016*
0.0039*
0.0004
0.0005
0.0007
0.5853
0.4125
0.5137
0.4688
0.5488
0.4755
0.5792
0.5184
0.4000
0.5523
0.5399
0.5410
Southern Hemisphere
MID
MID/
Mean
Trend
(per year)
Mean
MID
MID/
Mean
(%)
0.022
0.015
0.075
0.054
0.022
0.033
0.013
0.021
0.059
0.013
0.017
0.014
3.7
3.6
14.6
11.5
4.0
7.0
2.3
4.1
14.7
2.4
3.2
2.6
-0.0011*
-0.0021
-0.0028*
-0.0057
-0.0016*
-0.0024
-0.0050
-0.0001
-0.0012
-0.0021
-0.0017*
-0.0025
0.593
0.438
0.524
0.441
0.609
0.501
0.463
0.500
0.500
0.522
0.554
0.479
0.012
0.045
0.024
0.098
0.015
0.034
0.093
0.044
0.061
0.036
0.025
0.059
2.0
10.3
4.6
22.2
2.5
6.8
20.1
8.8
12.2
6.9
4.5
12.3
*Indicates that the trend is significant at a 95% confidence level.
Ecosystem type codes: 1, Evergreen needle-leaf forest; 2, Evergreen broadleaf forest; 3, Deciduous Needle-leaf forest; 4, Deciduous broadleaf forest; 5,
Mixed forest; 6, Closed shrub; 7, Open shrub; 8, Woody savanna; 9, Savanna; 10, Grass; 11, Crops.
Trend: the changing slope of the NPP/GPP ratio from 2000 to 2009; MID, maximum inter-annual difference, the largest difference between any 2 years
from 2000 to 2009; Mean: 10-year mean NPP/GPP ratio between 2000 and 2009.
Analysis
The spatial pattern of the NPP/GPP ratio was mapped using the
10-year mean NPP/GPP ratio value. The uncertainty level of the
10-year mean NPP/GPP ratio for each pixel was calculated via
bootstrapping using the ‘boot’ package implemented in the r
statistical software environment (Mudelsee & Alkio, 2007; R
Development Core Team, 2008). This method resampled the
10-year observations of NPP/GPP ratio 1000 times with replacement and calculated the mean of each sample. The 95% confidence limits were computed based on the resulting sample. The
uncertainty of the global 10-year mean NPP/GPP ratio was
presented as the width of the confidence interval (i.e. difference
between the upper and lower bounds) at a 95% confidence level.
The temporal dynamics of NPP, GPP and the NPP/GPP ratio
were explored for the global distribution of ecosystem types. In
addition, the temporal dynamics of the NPP/GPP ratio were
examined for each individual ecosystem type. To investigate the
temporal trend in the NPP/GPP ratio from 2000 to 2009, its
annual average value was plotted against time and the slope was
computed to estimate the annual change rate. The statistical
significance of the relationships among NPP, GPP and the
NPP/GPP ratio flux and climatic variation was tested by linear
regression using spss statistical software (SPSS Inc., 2010). A
Maximum Inter-annual Difference (MID) index was calculated
as the biggest difference between any random 2 years from 2000
to 2009 to indicate the largest annual NPP/GPP ratio variation
in our studied period.
To explore the geographic variability in these trends, this
study refined the analysis by classifying the global terrestrial
ecosystem into multiple NPP/GPP change interval zones based
on the slope sign and magnitude. The average precipitation and
temperature trends for each zone from 2000 to 2009 were calculated. The increase or decrease in the NPP/GPP ratio was
linked to temperature and precipitation by plotting the average
change magnitude within each zone against the average changes
in temperature and precipitation.
RESULTS
Global distribution and uncertainty of the
NPP/GPP ratio
The global NPP/GPP ratio exhibited a spatial pattern closely
associated with climate. In general, the NPP/GPP ratio is high in
cold and dry regions and low in warm regions with abundant
precipitation (Fig. 1a). In areas with low NPP/GPP ratios such
as Western Australia, the Sahel and savannah regions of northern Africa, northern India and the central Amazon plains, the
uncertainty is high. In contrast, the uncertainty is low in areas
with high NPP/GPP ratios, such as the high latitude regions of
the Northern Hemisphere (N.H.) and the Andes Mountains in
South America (Fig. 1b).
Global temporal NPP/GPP ratio dynamics
Over the past 10 years, global NPP has decreased, whereas GPP
has remained almost unchanged, leading to a decreasing NPP/
GPP ratio under increased precipitation and temperature at a
global scale (Fig. 2). Statistically, the correlations between NPP
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147
Y. Zhang et al.
(a) Global NPP/GPP ratio spatial pattern
(b) The uncertainty level of the NPP/GPP ratio
Figure 1 The spatial pattern of the 10-year (2000–2009) mean net primary production (NPP)/gross primary production (GPP) ratio (a)
and the width of the confidence interval (difference between upper and lower bounds) of the mean NPP/GPP ratio at a 95% confidence
level (b). A wider confidence interval represents a higher uncertainty.
Figure 2 Net primary production
(NPP), gross primary production (GPP),
NPP/GPP ratio, temperature and
precipitation trends from 2000 to 2009.
The sign and the P-value for NPP, GPP,
NPP/GPP ratio, temperature, and
precipitation are –, –, –, +, +, and 0.6,
0.946, 0.893, 0.105 and 0.082,
respectively.
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Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
Global carbon use efficiency dynamics
Figure 3 The spatial pattern of the net
primary production (NPP)/gross primary
production (GPP) ratio trend from 2000
to 2009 (eight equal-interval zones were
differentiated: zone 1: < -0.009; zone 2:
-0.009 to -0.006; zone 3: -0.006 to
-0.003; zone 4: -0.003–0; zone 5:
0–0.003; zone 6: 0.003 to -0.006; zone 7:
0.006–0.009; zone 8: > 0.009).
and temperature and precipitation are stronger than those
between GPP and temperature and precipitation. The regression
equation between GPP and temperature and precipitation is
GPP = 119.58 - 1.927 ¥ [temperature] + 0.011 ¥ [precipitation]. The P-values for the overall regression equation and for
each independent variable are all non-significant at an alpha
level of 0.05. The regression equation between NPP and temperature and precipitation is NPP = 75.04 – 3.127 ¥ [temperature] + 0.1 ¥ [precipitation]. The P-values for the overall
equation and for temperature and precipitation are 0.001, 0.004
and 0.054, respectively.
At a finer scale, the temporal trend varies with location
(Table 1, Fig. 3). In the N.H., the ratio increased by 0.0007 per
year. In the Southern Hemisphere (S.H.), the ratio decreased by
0.0025 per year over the time period studied, indicating a higher
rate of change than in the N.H. The ratio has increased over 56%
of the vegetated land areas in the N.H. (Fig. 3), mostly concentrated in North America, central Africa, India, and the middle
and high latitude zones of East Asia. The areas with decreasing
NPP/GPP ratios were primarily located in Eastern Europe,
central Asia and high latitude zones in west Asia. The NPP/GPP
ratio decreased over 68% of the vegetated land areas in the S.H.,
including large parts of South America, Africa, and Australia.
Each ecosystem exhibited a distinct temporal trend (Table 1).
The global terrestrial plant ecosystem exhibited a decreasing
NPP/GPP ratio over time, driven primarily by decreases in four
ecosystems: evergreen and deciduous broadleaf forests, and
open and closed shrubs. The S.H and N.H. ecosystems exhibited
distinctive NPP/GPP ratio trends, as evidenced by an increasing
NPP/GPP ratio for all N.H. ecosystems except evergreen
broadleaf forest and decreasing NPP/GPP ratios for all S.H.
ecosystems.
Climatic controls on the global temporal pattern in
the NPP/GPP ratio
Temperature increases and decreases have not been consistent
across the world over the past 10 years. The greatest increases
(0.16°C yr-1) have occurred in Western Australia and Tibet
(Fig. 4a). The greatest decreases (-0.16°C yr-1) have occurred in
central North America and Alaska. Most parts of the Eurasian
continent except India have become drier over the past 10 years.
The greatest precipitation increases have occurred in the south
Asian islands, central Africa and the western Brazilian Highlands. The greatest precipitation decreases have occurred in
southern China, the northern part of South America and the
southwestern edge of the Brazilian Highlands (Fig. 4b).
The NPP/GPP ratio exhibited a globally positive correlation
with precipitation and a negative correlation with temperature
in most vegetated areas from 2000 to 2009 (Fig. 4c & d). More
specifically, in the S.H., the NPP/GPP ratio demonstrated a positive correlation with precipitation and a negative correlation
with temperature in 74 and 90% of the vegetated areas, respectively. In the N.H., 67% of the vegetated areas had a positive
correlation with precipitation, and 77% of the vegetated areas
had a negative correlation with temperature. Globally, the areas
with highly significantly negative (at 99% confidence level), significantly negative (at 95% confidence level, excluding areas
with 99% confidence level), non-significantly, significantly positive and highly significantly positive relationships with precipitation account for 2, 2.7, 73, 9.2 and 12.2% of the vegetated
areas, respectively. The areas with highly significantly negative
(at 99% confidence level), significantly negative (at 95% confidence level, excluding areas with 99% confidence level), nonsignificant, significantly positive and highly significantly positive
relationships with temperature account for 18.4, 11.2, 68.6, 1.2
and 0.6% of the vegetated areas, respectively.
The correlations between temporal NPP/GPP ratio trends and
temperature and precipitation trends from 2000 to 2009 differed
among ecosystem types (Table 1). The NPP/GPP ratio trend was
negatively correlated with temperature for all ecosystems,
whereas it had a positive relationship with precipitation for all
ecosystems except global, N.H and S.H. evergreen needle-leaf
forests and mixed forest ecosystems and global crop ecosystems.
Based on the direction and magnitude of the trend in the
NPP/GPP ratio, eight equal-interval NPP/GPP ratio trend zones
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149
Figure 4 The spatial pattern of the temperature (a) and precipitation (b) trends from 2000 to 2009 and the correlations between the net primary production (NPP)/gross primary production
(GPP) ratio and (c) temperature and (d) precipitation. Highly significant (+), significant (+), non-significant, significant (–) and highly significant (–) represent relationships that are positive
and statistically significant at a 99% confidence level, positive and significant at a 95% level, non-significant, negative and significant at a 95% level, and negative and significant at a 99% level,
respectively.
Y. Zhang et al.
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Global carbon use efficiency dynamics
Figure 5 The dependency of the net primary production
(NPP)/gross primary production (GPP) ratio trend on
temperature and precipitation. The NPP/GPP ratio trend zones
represent the slope of the NPP/GPP ratio change trend; Trend_T
represents the slope of the temperature change trend, and
Trend_P represents the slope of the precipitation change trend.
(< -0.009 yr-1, -0.009 to -0.006 yr-1, -0.006 to -0.003 yr-1,
-0.003 to 0 yr-1, 0 to 0.003 yr-1, 0.003 to 0.006 yr-1, 0.006 to
0.009 yr-1, > 0.009 yr-1) were identified (Fig. 3). There were four
decreasing NPP/GPP ratio zones and four increasing NPP/GPP
ratio zones. Spatially, the highest NPP/GPP increase zones were
concentrated in central North America, the southern edge of the
Amazon basin and central Africa. The highest NPP/GPP
decrease zones were located primarily in Western Australia,
southern Africa and the western Pampas region of South
America. This NPP/GPP ratio trend gradient demonstrated a
clear relationship with temperature and precipitation. The
strongest negative NPP/GPP ratio trends occurred where positive temperature trends were the highest and precipitation
trends were close to zero. Conversely, the highest positive NPP/
GPP ratio trends occurred where positive precipitation trends
were highest and temperature trends were negative (Fig. 5).
DISCUSSION
Understanding the patterns of spatial and temporal variability
in the NPP/GPP ratio, the resulting impacts on carbon use efficiency, and the ways in which these are related to climatic factors
at both global and biome scales is essential for advancing our
knowledge of global terrestrial carbon cycling and its response
to ongoing climate change (Medlyn & Dewar, 1999; Cheng et al.,
2000; DeLucia et al., 2007; Zhang et al., 2009). A more accurate
understanding of these relationships through time can ultimately result in more reliable estimates of global carbon storage
and fluxes. Remote sensing-based NPP and GPP data that are
high resolution and continuous in both the spatial and temporal
dimensions, e.g. MODIS NPP and GPP, enable examination of
the patterns of temporal variation in the NPP/GPP ratio at a
global scale.
The NPP/GPP ratio trend is different between the N.H and
S.H., which might be related to their dissimilar climate change
patterns over the past 10 years. In the S.H., large parts of Australia, South Africa and South America have simultaneously
experienced decreasing precipitation and increased temperatures, which in combination are likely to lower the NPP/GPP
ratio. In the N.H., a large part of Eurasia has experienced simultaneous increased temperatures and decreased precipitation, but
the proportion of the area with decreasing precipitation is relatively lower than in the S.H. Zhao & Running (2010) similarly
found that there are different ecosystem productivity dynamics
between the S.H and N.H. due to these distinct climatic change
trends.
The NPP/GPP ratio pattern along climate fluxes as revealed
by this study using model NPP and GPP products is comparable
with findings based on field measurement data. For example,
based on results collected from approximately 100 field sites
around the world, Piao et al. (2010) found a higher NPP/GPP
ratio for temperate forests than for tropical forests. In another
field measurement based study, temperate forests were indicated
to have a higher NPP/GPP ratio than tropical forests (Delucia
et al., 2007). An increasing NPP/GPP ratio with enhanced precipitation has also been found in other related model studies
(Lieth, 1975) and field precipitation control experiments conducted at an Amazon forest (Metcalfe et al., 2010). On the other
hand, there are some discrepancies between the present remote
sensing model study and field measurement based studies. For
example, Delucia et al. (2007) and Piao et al. (2010) found that
boreal forests have a lower NPP/GPP ratio than temperate
forests, which is opposite to the present study. The discrepancies
possibly stem from two reasons. First, the present study and the
field measurement based studies are targeting different areas.
The present study is set to summarize global continuous surface
results for each ecosystem, while the field measurement-based
studies only address the limited field site area. Then, the spatial
distribution and the number of field sites, and site conditions
would affect their representativeness. The field sites Delucia
et al. (2007) and Piao et al. (2010) used are overlapped in many
areas. In the two studies, there were only four boreal and five
clustered boreal sites, respectively, and the study sites were fundamentally biased to temperate forests. The global NPP/GPP
ratio map showed that there is a high spatial heterogeneity
within each ecosystem. For example, among the boreal forest
sites used in Piao et al. (2010), the Russian and Sweden sites
happen to have a low NPP/GPP ratio. Another important point
to note is that forest stand age and data retrieving method can
significantly affect the NPP/GPP ratio on each site. The tropical
forest sites included in Delucia’ studies are composed of two
young forest sites and two old forest sites, and the boreal forest
is composed of all old forests (stand age > 100 or at least > 50),
while the temperate forests are mostly young forests. Previous
studies have proved that young forests have a higher NPP/GPP
ratio than mature forests (Delucia et al., 2007; Piao et al., 2010),
which would boost NPP/GPP ratio value for temperate forests
and change the NPP/GPP ratio trend from tropical to boreal
forests.
Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
151
Y. Zhang et al.
Plants prioritize saving temporary carbohydrates and nutrient
reserves over growing new tissues, and thus they are inherently
slow growing (Grime & Hunt, 1975). For example, when faced
with environmental stresses such as decreased water potential or
nutrient supply, the immediate actions of plants are to slow down
water or nutrient supply to seedlings and decrease leaf growth
rate, while the rate of photosynthesis changes occurs afterwards
(Hsiao, 1973; MacDonalds et al., 1986). Under decreased precipitation, a higher proportion of energy needs to be allocated to
respiratory costs, and consequently, a lower proportion is available to construct new tissues (Metcalfe et al., 2010). Under warm
and dry conditions, the hot, dry atmosphere and declined soil
water cause stomatal closures and decrease carbon assimilations,
but Re could still be high (Arneth et al., 1998).
During periods of low temperature, less Ra results in larger
carbon reserve accumulation (Ryan, 1991; Metcalfe et al., 2010).
During warmer periods, more biological activities, a longer
growing season and associated nutrient deficiencies can all lead
to a lower NPP/GPP ratio (Chambers et al., 2004; Delucia et al.,
2007). Enhanced precipitation would reduce fine root production and fine root respiration, which can result in a less than
proportionate increase in respiration and, consequently, an
increased NPP/GPP ratio (Ryan et al., 1996).
Normally, it has been observed that the rate of respiration
increases exponentially with temperature (Ryan et al., 1995),
whereas the rate of photosynthesis tends to stabilize over a wide
range of temperatures, i.e. 20–35°C (Teskey et al., 1995;
Lindroth et al., 1998). As a result, plants have to incur relatively
higher respiration costs with increased temperature. The present
study found that NPP responded more strongly to changes in
precipitation and temperature than GPP, which is in line with
this general understanding of plant biology and plant growth.
The spatially explicit NPP/GPP ratio values obtained from
MODIS model products are constrained by hard-coded biophysical parameters in the model (Zhang et al., 2009). Due to
the various types of bias and errors associated with modelled
ecosystem productivity products, their applications for addressing mechanistic issues of ecosystem response to climates are also
highly constrained. Besides the biophysical input parameter
errors, there are two additional main potential sources of error
in the MOD17 GPP products: meteorology and radiometry.
Meteorological errors stem from using coarse-scale interpolated
climate data. Radiometric errors arise from underlying errors in
the MODIS LAI/fPAR algorithm. The meteorology data determine the climatic inputs and vapour pressure deficit, which are
among the most critical factors in controlling photosynthesis.
The MOD17 products utilized spatially interpolated meteorology data at a relatively coarse scale (1.00° ¥ 1.25°) of point data,
which cannot capture much of the finer-scale variability in these
variables. The high uncertainty of the NPP/GPP ratio in areas
with low values revealed that carbon use efficiency is not as
stable in these areas as in high-value areas. Thus, climatic variability might lead to relatively larger carbon fluxes in these areas.
These features of the MOD17 NPP and GPP products significantly affect the accuracy of their use for exploring the dependency of the NPP/GPP ratio on spatial variability in climate. In
152
contrast, the temporal dynamics of NPP and GPP are more
likely to be driven by climatic variability than the spatial patterns. Thus, conclusions about the dependence of the NPP/GPP
ratio on climatic variability over time are likely to be less biased
compared with the conclusions about spatial relationships
derived from MOD products. The radiometric model logic
might introduce certain degree of bias, too. The model logic
stipulates each environmental constraint acts on the maximum
values of productivity in a linear way. But in reality, the assumed
linearity is too simple. Many ecosystems respond to elevated
temperature or enhanced precipitation in a non-linear manner
(Norby & Luo, 2004; Zhou et al., 2008). In addition, soil moisture was not directly included in the model, which would likely
lower the model accuracy. The future model needs to incorporate soil moisture effects more comprehensively.
This study only analysed the relationship between the NPP/
GPP ratio and climate over a 10-year time horizon due to the
limitation imposed by data availability. Information about plant
growth under longer-term dry and wet periods also needs to be
examined for a more complete picture of how the NPP/GPP
ratio responds to climatic flux. Phenomena taking place over
longer time duration, such multi-decadal climate change trends,
are beyond the detectability of this study. However, the findings
of this study still have fundamental significance for our understanding of longer-term climate trends. As revealed in this study,
higher precipitation can increase the NPP/GPP ratio, whereas
increases in temperature can lower the NPP/GPP ratio. Along
both spatial and temporal dimensions, at times and in places
experiencing abnormal drought, the NPP/GPP ratio would
accordingly decrease, which represents a lower net productivity
for farmland and a lower net growth for forests and grasslands.
Likewise, the increased evapotranspiration that resulted from
higher temperatures would weaken the NPP/GPP ratio, which in
turn results in similar consequences to drought. Under a projected warming climate and accompanying higher evapotranspiration, significant areas of the global terrestrial plant ecosystem
would be exposed to a hotter and drier environment, under
which circumstances the NPP/GPP ratio would be expected to
decrease because the Re cost would increase and global terrestrial ecosystem carbon use efficiency would decrease as a result.
Besides improving biogeochemical model performance, the
finding about a climate regulated NPP/GPP ratio can be a useful
guide for agricultural and forest management activities. For
example, Land Use, Land-Use Change and Forestry, and Reducing Emissions from Deforestation and forest Degradation and
other activities have been implemented to mitigate the effects of
climate change. But their efficiencies would depend on the NPP/
GPP ratio of the forest sites where these activities are implemented. Activities implemented in a site with higher NPP/GPP
ratio will bring greater and more immediate efficiencies.
ACKNOWLEDGEMENTS
This study is funded by the 973 Program (2013CB956302) of the
Ministry of Science and Technology of China, the ‘thirteenth
five-year plan’ strategic technology project (2012ZD005) of the
Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
Global carbon use efficiency dynamics
Institute of Geographic Sciences and Natural Resources,
Chinese Academy of Sciences, and the ‘one hundred talents plan’
programme of Chinese Academy of Sciences.
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Global Ecology and Biogeography, 23, 144–155, © 2013 John Wiley & Sons Ltd
Global carbon use efficiency dynamics
BIOSKETCH
Yangjian Zhang is a professor working at the Institute
of Geographic Sciences and Natural Resources
Research, Chinese Academy of Sciences. His research
involves applications of ecosystem productivity models
and field studies in the field of landscape and global
ecology. He addresses critical questions about the
impacts of global change on ecosystems through an
effective combination of modelling, geospatial analysis
techniques, and field sampling and experimentation.
Editor: Martin Sykes
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