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No. 56 Improvement of Terrestrial Ecosystem Model in terms of High CO2 ResponseAkihiko Ito *, Atsuhiro Iio, Minaco Adachi, Masako Senda, Tomohiro Hajima, Koki Hikosaka, Ichiro Terashima
* Correspondence: National Institute for Environmental Studies, Japan; Japan Agency for Marine-Earth Science and Technology; e-mail: itoh@nies.go.jp
45
50
55
60
65
70
75
0.8
0.82
0.84
0.86
0.88
0.9
0.92
0.94
0.96
1900 1920 1940 1960 1980 2000
NPP
AET
WUE
Year
NP
P (P
g C
/ yr
) or A
ET
(10
3 km
3 /
yr)
WU
E (g
C /
kg w
ater
)
0 100 200 300 400 500 600
-80
-60
-40
-20
0
20
40
60
80
Fekete et al. 2002 (WBM)Fekete et al. 2002 (CMP)
VISIT (this study)
0 100 200 300 400 500 600
-80
-60
-40
-20
0
20
40
60
80
Cramer et al. 1999VISIT (this study)
(a) Runoff
(km3 / yr) (Tg C / yr)
(b) NPP
La
titu
de
(d
eg
ree
)
canopy
actual evapotranspiration (AET)[65.0]
precipitation[107.2]
photosynthesis[124.6]
net primary production (NPP)[59.5]
water-use efficiency (WUE)[ 0.915 g-carbon / kg-water ]
ecosystemrespiration
auto
rtoph
ic
trans
pi-
ratio
n
evap
orat
ion
inte
rcep
tion
hete
rotro
phic
leaf-stomata
leaf area
runoff [42.2]
water erosion [1.2]
plantbiomass[519.7]
stocks (flows)[Pg C (/ yr)]
stocks (flows)[103 km3 (/ yr)]
soilorganicmatter
[1289.6]
soilmoisture
(root uptake)
(sap flow)
(litterfall)
fire, BVOC, CH4, etc.
(a)
(b)
0°
60°
90°
30°
-30°
-60°
0°
60°
90°
30°
-30°
-60°0° 60°-60° 120°-120° 180°-180°
0° 60°-60° 120°-120° 180°-180°
AET(kg m–2 yr–1)
NPP(kg C m–2 yr–1)
0
1000
800
600
400
200
0
1.0
0.8
0.6
0.4
0.2
(a)
(b)
0°
60°
90°
30°
-30°
-60°
0°
60°
90°
30°
-30°
-60°0° 60°-60° 120°-120° 180°-180°
0° 60°-60° 120°-120° 180°-180°
WUES(g C kg–1)
0.0
2.0
1.5
1.0
0.5
WUEL(g C kg–1)
0
45
40
35
30
25
20
15
10
5
PhotosynthesisPEPPs model
RespirationPEPPs model
AllocationPEPPs model
N absorptionPEPPs model
CO2
Leaf areaReproduction
C/N balance
Plant hormone
Signal transfer
Consortium target
CO2NET study(CO2 response information transfer network )
Acclimation
Soil N
Stomata PEPPsmodel
Model plantsFACE/OTC
・ High CO2 exp.・ N-level manipulat.• Omics analysis• PEPPs obs.・ Leaf gas exchange・ Growth analysis• Isotope tracer・ etc.
-300
-200
-100
0
100
200
Disturbance
Elevated CO2
Temperature
Precipitation
Radiation
Non-linearity
GPPRENEP
Car
bon
budg
et, 1
994–
2009
(g C
m –
2 yr
–1 )
Sca
ling
coef
fici
ents
(–)
-2
-1
0
1
2
3
Disturbance
Elevated CO2
Temperature
Precipitation
Radiation
GPPRENEP
-50
0
50
100
150
200
250
300
350
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
-50
0
50
100
150
200
250
300
350
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
-50
0
50
100
150
200
250
300
350
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Year
Obs.VISIT (control)
(a) GPP
(b) RE
(c) NEP
CO
2 flu
x (g
C m
–2
mon
th –
1 )
Leaf Stem Root
Leaf Stem Root
Dead leaf Dead stem Dead root
Active Intermediate Passive
talltrees
litter
humus
floorplants
Atmospheric CO2
allocation
photosynthesis respiration
decomposition min
eral
izat
ion
litter fallallocation
FGPP
GPP – AR – HR = –NEENEP
Auto. Resp.
Eco. Resp.
Hetero. Resp.
Soil Resp.
=
Comprehensive studies of plant responses to high CO2 world by an innovative consortium of ecologists and molecular biologists
Model development : VISIT
Study 1:Detection and attribution of global change and disturbance impacts on a tower-observed ecosystem carbon budget: a critical appraisal
Study 2 : Water-use efficiency of the terrestrial biosphere: a model analysis focusing on interactions between the global carbon and water cycles
Observations worldwide are providing an increasing amount of atmosphere–ecosystem flux
data. Thus, establishing a data-mining methodology to detect significant trends and attribute
changes to specific factors is important. This study examined the possibility of detecting
significant trends in observed data at a test site with one of the longest records of flux
measurements (Takayama, Japan). Statistical tests using non-parametric methods showed
a ‘likely’ trend (i.e., detected at 66–90% confidence levels) of increasing carbon
sequestration. To investigate the change in carbon sequestration in relation to biological
and environmental factors (ambient CO2, temperature, radiation, precipitation, and
disturbance), mechanistic and numerical methods were applied. A process-based model
was used for the mechanistic attribution of change, and an optimal fingerprinting method in
combination with model-based sensitivity simulations for numerical attribution. At the study
site, local disturbances appeared to exert an impact on the observed carbon sequestration,
whereas climatic factors made moderate contributions. These results indicate the feasibility
of detection and attribution using current flux measurement data, although more evidence is
needed to confirm global coherence.
Carbon and water cycles are intimately coupled in terrestrial ecosystems, and
water-use efficiency (WUE, carbon gain at the expense of unit water loss) is
one of the key parameters of ecohydrology and ecosystem management. In this
study, the carbon cycle and water budget of terrestrial ecosystems were
simulated using a process-based ecosystem model, called Vegetation
Integrative SImulator for Trace gases (VISIT), and WUE was evaluated: WUEC
defined as gross primary production (GPP) divided by transpiration, and WUES
defined as net primary production (NPP) divided by actual evapotranspiration.
Total annual WUEC and WUES of the terrestrial biosphere were estimated as
8.0 and 0.92 g C kg–1 H2O, respectively, for the period 1995–2004. Spatially,
WUEC and WUES were only weakly correlated. WUES ranged from <0.2 g C
kg–1 H2O in arid ecosystems to >1.5 g C kg–1 H2O in boreal and alpine
ecosystems. The historical simulation implied that biospheric WUE increased
from 1901 to 2005 (WUEC, +7% and WUES, +12%) mainly as a result of the
augmentation of productivity in parallel with the atmospheric carbon dioxide
increase. Country-based analyses indicated that total NPP is largely determined
by water availability, and human appropriation of NPP is also related to water
resources to a considerable extent. These results have implications for (1)
responses of the carbon cycle to the anticipated global hydrological changes;
(2) responses of the water budget to changes in the terrestrial carbon cycle; and
(3) ecosystem management based on optimized resource use.
ReferencesIto A (2012) Detection and attribution of global change impact on a
tower-observed ecosystem carbon budget: a critical appraisal. Environmental Research Letters, 7, 1–6.
Ito A, Inatomi M (2012) Water-use efficiency of the terrestrial biosphere: a model analysis on interactions between the global carbon and water cycles. Journal of Hydrometeorology, 13, 681–694.
Scales
Targets
Mutant / transgenic p
lant
Omics
Inter-specifi
c compariso
n
Model parameterization
Simulation / validation
Molecule / cell
Individual / o
rgan
Ecosystem
Earth
Molecular biology
Ecophysiology
Simulation study
This project explores “inclusive elucidation of plant
response to elevated atmospheric CO2
concentration” , i.e., an urgent issue to establish a
basis to make prediction of the plant CO2 fixation in
response to global environmental change, through the
formation of a consortium of ecologists and molecular
physiologists. First, we raise plants under high CO2
conditions and analyze the dynamics of information
network concerning environmental response by
means of targeted omics, allowing us to grasp the
whole features of plant CO2 response. Then, we
specify analytical factors and apply them to
representative species of natural ecosystems
including tree species, in order to clarify the plant high
CO2 response with respect to environmental
dependence and inter-species differences in a
quantitative and inclusive manner. Based on these
findings, we develop a molecular physiological model
of individual plant high CO2 response, which will be
provided to ecosystem model researchers. Finally, we
break a new direction of molecular physiology to
make effective contribution to plant individual-level
studies and to make substantial progress in botanical
science.
To achieve these purposes, we analyze
phenotypic ecophysiological parameters (PEPPs)
such as stomatal conductance, photosynthetic rate,
respiration rate, C/N balance, allocation (aboveground
/ belowground, leaf / stem and branching), and
growth, which are usually used in ecophysiological
studies, by means of indoor remote sensing,
high-definition gas exchange measurement, stable
isotopic tracer experiment, and other methods,
utilizing previously-identified mutant plants that have
functional loss and gain in CO2 response factors. In
parallel with the PEPPs responses, we elucidate the
whole features of plant CO2 response by
understanding the dynamics of CO2 response
information-transfer network (CO2NET) through
targeted omics for plant metabolites and hormones.
We establish and maintain a platform to measure the
group of marker factors such as genes, enzymes,
metabolites, and hormones, which play key roles in
the CO2NET.
This study used the process-based terrestrial model: Vegetation Integrated
SImulator for Trace gases (VISIT: Inatomi et al 2010; Ito 2010). The model
consists of sub-modules simulating radiation budget, hydrology, phenology, and
carbon and nitrogen cycles. The ecosystem structure is simplified into four
sectors of carbon stock: canopy trees, floor plants, dead biomass (litter), and
mineral soil (humus). Each carbon stock sector is then divided into several
carbon pools; for example, the tree sector is composed of leaf, stem, and root
pools (see Ito et al [2005] for a schematic diagram). Photosynthetic CO2
assimilation, which is gross primary production (GPP) at the ecosystem scale, is
estimated as a function of leaf area index (LAI; estimated from the leaf carbon
pool and specific leaf area), canopy light absorption coefficient, and leaf-level
photosynthetic parameters (Ito and Oikawa 2002). Plant and soil respiration rates
are estimated from the pool-specific respiration rate, pool size, and response to
temperature. Total respiration is called ecosystem respiration (RE). Net
ecosystem production (NEP; equivalent to net CO2 exchange with the
atmosphere) is calculated as the difference between GPP and RE.
Photograph. Members of the project: Comprehensive studies of plant responses to high CO2 world by an innovative consortium of ecologists and molecular biologists.
Figure 1. Phenotypic ecophysiological parameters [PEPPs] in relation to plant CO2 response investigated by the project.
Figure 2. Scales and research targets of the project, in which consortium of molecular biology, ecophysiology, and simulation study will be formed.
Figure 3. Schematic diagram of carbon cycle in the VISIT model.
Figure 5. Scaling coefficients estimated by the optimal fingerprinting method for the carbon budget change at the Takayama site.
Figure 6 Contributions of different factors to net carbon sequestration observed at the Takayama site. Results of the mechanistic attribution on the basis of process-based model (VISIT) simulations.
Figure 4. Comparison between the observed and model-estimates CO2 fluxes.
Figure 10. Latitudinal distribution of (a) runoff discharge and (b) net primary production (NPP) of terrestrial ecosystems around 2000, as simulated by the Vegetation Integrated SImulator for Trace gases (VISIT) model. The model estimations are compared with those of Fekete et al. (2002) for runoff, who used a water-balance model (WBM) and reported a composite result based on observational data (CMP), and Cramer et al. (1999) for NPP, who used 17 terrestrial ecosystem models.
Figure 6. Summary schematic diagram of the carbon cycle and water budget of terrestrial ecosystems estimated by the VISIT model for 1995–2004.
Figure 9. Global distribution of (a) annual actual evapotranspiration (AET) and (b) annual net primary production (NPP), simulated by the VISIT model for 1995–2004.
Figure 8. Global distribution of (a) canopy-level water-use efficiency (WUEC, defined as NPP/AET) and (b) stand-level water-use efficiency (WUES, defined as GPP/TR), simulated by the VISIT model for 1995–2004.
Figure 7. Interannual variability in the global net primary production (NPP), actual evapotarnspiration (AET), and water-use efficiency (WUE) simulated by the VISIT model for 1901–2005.
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