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KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE X - 1
This manuscript has been accepted for publication in Geophysical Research Letters.
For the current manuscript status or proper reference
please check the publisher’s web page at:
http://www.agu.org/journals/gl/
Jena, July 12, 2007
Axel Kleidon
For more information or comments, please contact:1
BIOSP
HER
IC
THEORY AND
MO
DELLING
Dr. Axel [email protected] Theory and Modelling GroupMax-Planck-Institut für BiogeochemieHans-Knöll-Str. 10 • Postfach 10 01 6407745 Jena • Germany
Ph: +49-3641-576-217 • Fax: +49-3641-577-217
http://www.bgc-jena.mpg.de/bgc-theory
GEOPHYSICAL RESEARCH LETTERS, VOL. ???, XXXX, DOI:10.1029/,
Optimized Stomatal Conductance and the Climate Sensitivity to2
Carbon Dioxide3
A. KleidonMax-Planck-Institut fur Biogeochemie, Jena, Germany4
Stomatal conductance shapes the exchange of water5
and carbon of vegetated land surfaces. Previous stud-6
ies have demonstrated that optimized stomatal function-7
ing that maximizes productivity provides a realistic de-8
scription of how stomata operate. Here I investigate9
the role of optimum stomatal functioning for the sen-10
sitivity of terrestrial productivity and land surface cli-11
mate to concentrations of atmospheric carbon dioxide12
(pCO2). I conduct sensitivity simulations with a coupled13
vegetation-climate system model with different values of14
maximum stomatal conductance at different prescribed15
levels of pCO2. The optimum in stomatal conductance16
shifts to lower values with increasing pCO2, which is con-17
sistent with observed sensitivities of stomatal density of18
leaves. If this change in optimum conditions is not taken19
into account, the climate sensitivity shows (a) a general20
underestimation of terrestrial productivity under altered21
pCO2 and (b) different sensitivities of key climatic vari-22
ables to pCO2. The climate sensitivity of land temper-23
ature for a doubling of pCO2 ranges from ∆T = 2.7 K24
to ∆T = 3.2 K, depending on whether stomata adapt25
optimally or not at all. These results demonstrate that26
the assumed ability of vegetation to adapt to its environ-27
ment can have important consequences for the simulated28
climate system sensitivity to pCO2.29
1. Introduction
Stomata, small openings in leaves, link the exchange30
of water and carbon of vegetated surfaces. In order to31
fix carbon, plants take up atmospheric carbon dioxide32
through these openings while transpiring water at the33
same time. A change in the atmospheric concentration34
of carbon dioxide (pCO2) results in an altered gradient in35
pCO2 between ambient air and the leaf’s interior, thereby36
affecting the water-and carbon exchange of the vegetated37
cover (see e.g. recent study by Long et al. [2006]). Recon-38
structions of the past stomatal densities of leaves, which39
set the maximum conductance of leaves to water and40
carbon exchange, respond to pCO2 on a time scale of41
decades (Woodward [1987]). This effect has been used42
to reconstruct past pCO2 concentrations from leaf fossils43
(Retallack [2001], Beerling and Royer [2002a], Beerling44
and Royer [2002b]).45
Several studies have shown that stomatal conductance46
and change in stomatal functioning is an important factor47
in land surface exchange fluxes and thereby affect climate48
model simulations of global change (Sellers et al. [1996],49
Copyright 2007 by the American Geophysical Union.0094-8276/07/$5.00
2
KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE X - 3
Betts et al. [1997], Douville et al. [2000]). Here I test50
whether the reconstructed change in stomatal density to51
different pCO2 reflects the optimized response of vegeta-52
tion functioning to maximize productivity under altered53
pCO2 conditions (Cowan and Farquhar [1977], Kleidon54
[2004]) and estimate the consequences for the simulated55
climate sensitivity in an Earth system model of interme-56
diate complexity.57
2. Methods2.1. The Planet Simulator
I use the Planet Simulator (PlaSim), an Earth system58
model of intermediate complexity (Lunkeit et al. [2004],59
Fraedrich et al. [2005a], Fraedrich et al. [2005b]). PlaSim60
consists of a low resolution dynamic core of T21 spectral61
resolution (corresponding to a spatial resolution of 5.6◦62
* 5.6◦ longitude/latitude), a radiative transfer scheme63
which considers absorption by water vapor and clouds,64
ozone, and carbon dioxide, a prognostic cloud scheme,65
a mixed layer ocean model, a thermodynamic sea-ice66
model, a land surface model and the SimBA dynamic67
global vegetation model. The model is able to realisti-68
cally capture the large-scale patterns of the present-day69
climatology.70
The photosynthetic rate of the vegetative cover is sim-71
ulated as the minimum of a light-limited and a flux-72
limited rate. The light-limited rate is proportional to73
photosynthetically active radiation, fractional leaf cover,74
and depends on atmospheric pCO2 in a logarithmic fash-75
ion. The water limited rate is assumed to be proportional76
to the rate of transpiration divided by the gradient in77
pCO2 across the leaf boundary. Vegetation productivity78
then shapes the vegetation biomass dynamics and affects79
land surface properties such as surface albedo, surface80
roughness and the rooting zone of the soil. A parameter-81
ization of maximum stomatal conductance is added to the82
standard configuration of the model by adding a unitless83
factor gs,max to the bulk formula for the computation of84
the evapotranspiration rate. Through its effects on evap-85
otranspiration it influences the water-limited rate of pho-86
tosynthesis. The standard version of the model does not87
consider the effect of maximum stomatal conductance on88
land evapotranspiration rates, i.e. gs,max = 1. Kleidon89
[2004] has shown that the optimized value of gs,max < 190
that maximizes productivity for the present-day yields in91
reasonable climatic conditions, but results in a substan-92
tial increase in productivity. More details on the model93
are provided in Kleidon [2004] and Kleidon [2006].94
2.2. Simulation Setup
A set of sensitivity simulations was conducted at val-95
ues of pCO2 = 200, 280, 360, 540, 720, and 1000 ppm. At96
each concentration of pCO2, additional simulations were97
performed for gs,max = 0.01, 0.02, 0.04, 0.10, 0.15, 0.20,98
0.30, 0.40, 0.70, and 1.00. The parameter gs,max was99
varied globally uniform, that is, regional variations in100
gs,max were not considered here. The ”Control” simula-101
tion of the present day refers to the setup of pCO2 = 360102
ppm and gs,max = 1.00. All simulations were run with a103
mixed-layer ocean and interactive, thermodynamic sea-104
ice model, but with the same glacier mask. Oceanic105
heat transport was prescribed in these simulations with106
the heat fluxes derived from a ”Control” simulation with107
prescribed climatological sea surface temperatures. The108
simulations were run with an accelerated time stepping109
scheme for terrestrial vegetation to reach the steady state110
X - 4 KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE
within 40 model years (Kleidon et al. [2007]).111
3. Results and Discussion
The sensitivity of land averaged annual mean produc-112
tivity to gs,max and its sensitivity to pCO2 is shown in113
Fig. 1. A clear maximum is seen for all pCO2 val-114
ues, with the maximum occurring at a gs,max = 1.00115
for pCO2 = 200 ppm and subsequently lower values for116
higher values of pCO2.117
The shift to lower values of the optimum gs,max for118
higher pCO2 is consistent to the reconstructed sensitivity119
of stomatal density to pCO2 (Fig. 2). For the purpose120
of comparison of the relative sensitivity to pCO2, the121
reconstructed sensitivities are set to the optimum value122
gs,max for pCO2 = 360 ppm. This is done because the re-123
constructed sensitivity of stomatal density can be highly124
species specific, yet the simulation model represents an125
integrated value of all plants that form the whole canopy126
at a much larger scale. Fig. 2 shows that the simu-127
lated sensitivity of optimum stomatal conductance falls128
very well within the range of reconstructed sensitivities129
of stomatal density.130
The impacts of different adaptive behaviors of stom-131
atal conductance on the climate sensitivity of key vari-132
ables over land is shown in Fig. 3 for three cases: (i) the133
”Control” case is taken as the simulations where stomatal134
conductance was not adapted optimally to either present-135
day or altered pCO2 conditions (i.e. gs,max = 1.0), (ii)136
the ”Present-day” case represents the case where stom-137
atal conductance is optimized for present-day, but not138
for altered pCO2 conditions, and (iii) the ”Adapted”139
case represents the case where stomatal conductance is140
adapted for both, present-day and altered pCO2 condi-141
tions.142
The climate sensitivities of land temperature range143
from 2.7K for the ”Control” to 3.2K for the ”Adapted”144
case for a doubling of pCO2 (see Fig. 3a). This dif-145
ference in the temperature sensitivity is attributable to146
differences in the hydrologic cycle over land. While the147
sensitivity of precipitation is relatively similar among the148
simulations, the sensitivity of evapotranspiration is in-149
sensitive to pCO2 in the ”Adapted” case, but increases150
with pCO2 in the other two cases. This means that the151
net convergence of atmospheric moisture transport over152
land increases in the ”Adapted” case. Also, the lack of153
enhanced evapotranspiration rates in this case is likely154
to cause the increase in temperature sensitivity shown155
in Fig. 3a. The sensitivity in evapotranspiration is mir-156
rored in the sensitivity of cloud cover over land, with157
cloud cover increasing with pCO2 in the ”Control” and158
the ”Present-Day” cases, but declining in the ”Adapted”159
case. This decline in cloud cover in the ”Adapted” case160
results in an increase in net radiative forcing (not shown)161
that adds further to the increased temperature sensitiv-162
ity. However, due to the uncertainty in cloud cover and163
precipitation sensitivities among climate models, these164
sensitivities may depend on the specific climate model165
used.166
These sensitivities can be interpreted by the co-167
limitation of GPP by light and carbon uptake. The168
optimum in gs,max shifts to lower values with increas-169
ing pCO2 since the greater gradient across the leaf-air170
boundary interface allows for the same uptake of CO2171
with less water. The resulting reduction in ET leads to172
a temperature increase, and less cloud cover. This sen-173
sitivity is consistent with previous studies (e.g. Sellers174
KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE X - 5
et al. [1996]), but the change in stomatal conductance is175
not prescribed, but rather obtained from optimization.176
There are clearly some limitations of this study. In the177
present implementation of the optimization, gs,max is as-178
sumed to be a globally uniform parameter. This could be179
improved by performing a multidimensional optimization180
at every grid cell of the model. Another aspect not con-181
sidered here is the time scale at which maximum stom-182
atal conductance could adjust under a transient change183
in pCO2. The observations by Woodward [1987] suggest184
that it may happen at a relatively short time scale so that185
the optimization may in fact be a reasonable approxima-186
tion for the transient case as well.187
Other vegetation parameters could adapt as well, such188
as the root-shoot ratio or canopy roughness, but these are189
held constant here. Both aspects are likely to lead to an190
underestimation of productivity under the altered forc-191
ing, and it would be necessary to consider these other as-192
pects as well in the representation of a fully adaptive ter-193
restrial biosphere in climate model simulations of global194
change.195
4. Summary and Conclusion
Sensitivity simulations with a coupled vegetation-196
climate model demonstrated that the optimum stomatal197
conductance of the vegetative cover shifts to lower val-198
ues for higher levels of pCO2. This optimum response199
and the associated climatic impacts are largely consistent200
with reconstructed sensitivities of stomatal density and201
previous modelling studies. This confirms that an opti-202
mization approach seems to be reasonable in representing203
the adaptive behavior of terrestrial vegetation in the cli-204
mate system. Furthermore, it provides further indication205
that stomatal conductance indeed adapts optimally to its206
environment, and that this has important consequences207
for the climate sensitivity to pCO2 over land.208
This result has implications for the interpretation of209
changes in stomatal density in paleoclimatological recon-210
structions. A change (or no change) in stomatal density211
in the past may also reflect adaptation to other driv-212
ing factors, e.g. global warming by an increase in atmo-213
spheric methane. This would alter the energy- and water214
balances at the surface and may thereby affect the re-215
sulting optimum value of stomatal conductance. If this216
were the case, differences in stomatal density could not217
necessarily be converted into pCO2 concentrations. This218
would, however, require further testing with additional219
model simulations.220
Acknowledgments. This research was in part sup-221
ported by the National Science Foundation through grant222
ATM0513506. The author thanks Dana Royer and Richard223
Betts for their constructive reviews.224
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KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE X - 7
0
2
4
6
8
ytivitcu
dor
Pm/
Cg( 2
)d/
0.01 0.10 1.00Stomatal Conductance
200 ppm
280 ppm
360 ppm
540 ppm
720 ppm
1000 ppm
Figure 1. Sensitivity of terrestrial gross primary pro-ductivity (GPP) to maximum stomatal conductance fordifferent levels of atmospheric pCO2 concentrations, asindicated.
0.0
0.2
0.4
0.6
0.8
1.0ecnatc
ud
no
C latam
otS
200 400 600 800 1000
pCO2
optimalW87-herbariumW87-experimentBR02-eqn2aBR02-eqn3aBR02-eqn4bW03-eqn8
Figure 2. Comparison of the sensitivity of optimalstomatal conductance to observed sensitivities of Wood-ward [1987] (W87) and different relationships reportedin Beerling and Royer [2002a] (BR02) and Wynn [2003](W03). The reconstructed relationships are plotted suchthat they yield the same value as the optimum value ofthe model simulation for the present-day pCO2 concen-tration of 360ppm.
X - 8 KLEIDON: OPTIMUM STOMATAL CONDUCTANCE AND CHANGE
2.0
2.5
3.0
3.5
4.0
noitati
picerP
200 400 600 800 1000
pCO2
1.0
1.5
2.0
2.5
3.0
noitari
psnart
opav
E
200 400 600 800 1000
pCO2
30
35
40
45
50
revo
C d
uol
C
ppmppm
ControlPresent-DayAdapted
mm/d mm/d
%a. b.
c. d.12
14
16
18
20
22
erutare
pme
T
°C
Figure 3. Sensitivity of annual means of (a) near surfaceair temperature, (b) cloud cover, (c) precipitation and(d) evapotranspiration averaged over land to atmosphericpCO2 for the ”Control” model simulations (dashed lines),the simulations in which stomatal conductance is opti-mized for the present-day pCO2 only (”Present-Day”,dotted line), and the simulations for which stomatal con-ductance is optimized to the prescribed pCO2 concentra-tion (”Adapted”, solid line).