沙漠研究 19-1, 41 - 43 (2009 )Journal of Arid Land Studies“Desert Technology IX ”
Refereed Paper

Estimation of Climate Change Effects on Arid Land Afforestation Technologies
for CO2 Sequestration
Yasuyuki EGASHIRA1, Yoshinori HATASA1, Keisuke NISHIDA1, Korekazu UEYAMA1
Abstract: Estimation of climate change effects on arid land afforestation for CO2 sequestration
was attempted. A tree growth model was prepared by modifying the 3-PG model to reproduce
tree growth in an afforestation trial in Leonora, Western Australia. Data from CCSM3.0 wereused as input data to the tree growth model and estimated the future trends in tree growth in thearid land of Western Australia. A reduction of rainfall and rising of average temperatures byclimate change are predicted there, and these two factors are tending to reduce the tree growth.
Further investigations on the other arid area show tree growth in some area will beenhanced according to the global warming.
Keywords: Arid land afforestation, Carbon sequestration, Global climate change

1. Introduction
Carbon sequestration by arid land afforestation has been expected as an effective countermeasure for
global warming problem. A research project of afforestaion was attempted in Leonora, Western Australia(Kojima et al., 2006), using some technologies, such as water management, tree species selection, anddemonstrated its potentials. In this work, we attempted to examine the effect of climate change on thegrowth of trees planted in arid land. If the forests in arid lands are not vulnerable, the global warming
process will be reduced as expected. However, if the climate changes will wilt the forests, thesequestrated carbon will be released again and speeding up global warming. Additionally, possibilities ofafforestation in arid areas other than Western Australia, were examined, and response of the tree growth tothe climate changes in the selected areas were also examined.
2. Materials and Methods
In this work, a tree growth simulator was executed using various weather data from a GCM (globalclimate/circulation model) simulation under various scenarios in SRES (Special Report on Emission
Scenario) of IPCC (Intergovernmental Panel on Climate Change).
For GCM, the results of some simulations in "IPCC Data Distribution Centre" were compared to theobserved weather data at the experimental site in the afforestation project, Leonora, Western Australia,
during 2000 to 2006. As a result, CCSM 3.0 (Community Climate System Model) from the National
Center for Atmospheric Research (http://www.ccsm.ucar.edu) was selected, because of its superior
reproducibility for the temperatures and rainfalls in the arid area.
The tree growth simulator is similar to the 3-PG model (Landsberg and Waring, 1997). In this model,
tree growth basically depends on the monthly solar radiation, and additionally functions of discount factors
for some environmental effects, such as average rainfall and average temperature, are defined andparameters in these functions are adjusted to fit the observed data. Using parameter sets for Eucalyptus
globulus from literature (Sands and Landsberg, 2002) as a default, parameters having a significant effect on
the tree growth were selected and adjusted to reproduce the growth data of Eucalyptus camaldulensis,
which obtained from the afforestation project at Leonora, Western Australia. It should be mentioned that,
because of the limitation of empirical information, a positive effect of increased CO2 concentration on thetree growth was not taking into account in this simulation model. The results obtained from this simulator
should be considered as a pessimistic case from the view point of growing trees.
In the analysis of the other arid lands in the world, averages of annual rainfall data for past 10 years
were calculated based on the "CPC Merged Analysis of Precipitation (CMAP)" (Xie and Arkin, 1996) from1

Division of Chemical Engineering, Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka-shi, Osaka, Japan;
Fax no. +81-6-6850-6259, Tel no. +81-6-6850-6259, E-mail: egashira@cheng.es.osaka-u.ac.jp

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Climate Prediction Center (CPC http://www.cpc.noaa.gov), and arid regions within the world were selectedon the basis of rainfall 200 to 300 mm/y of rainfall. Additionally, regions in a cold area were larger than 3
˚C. Some groups of adjacent meshes of candidates were gathered and representation points for eachgroup were selected to estimate the future trends.

Annual年平均気温[℃]
Ave. Temp. [°C]

Annual年間降雨量[mm/year]
Rainfall [mm/y]Tree Weight after
6060ヵ月後の樹木重量[t/ha]month [t/ha]

3. Results and Discussion
To evaluate tree growth potential in Leonora, Western Australia, simulations of 5-year-growth ofplanted trees starting at various years until 2100 were attempted. From data sets of CCSM 3.0, themonthly average of minimum and maximum temperatures, monthly total rainfalls, and solar irradiation,
were used to perform simulation. IPCC Data Distribution Center provides 3 to 4 data sets from CCSM
3.0 for each emission scenario in SRES for
270
exploring the chaotic behavior of climatic
simulations. So, the results of tree growth180simulation performed using each data set fromCCSM 3.0 were averaged for each emission
scenario.
90
Tree growth at arid lands in WesternAustralia turned out to be reduced with global
02000
2020
2040
2060
2080
2100
warming. As shown in Figure 1, under theStart植林開始年[西暦]of Plantation [y]scenario A1B, a case of significant climatechange, growth of trees planted from 2096 toFig.1. The predicted tree growth of ations in
2100 is less than 70% of that of from 2011 toLeonora, Western Australia, at various2015.
starting year.
Figure 2 shows the change of predicted
rainfalls by CCSM 3.0, with the assumption ofincreasing green house gas emission in the340
scenario A1B. This data were selected from the320
simulation results provided by IPCC Data
300
Distribution Center. The decreasing trend of
280
260
rainfall shown in this figure is thought to be the240
cause of the decrease in simulated tree growth,220
because this growth evaluation is focused on arid
200
region. Additionally, an increasing trend of2000
2020
2040
2060
2080
2100
西暦[年]
Year
temperature shown in Figure 3, is anothercandidate for this tree growth suppression. Thisis because, in the tree growth simulation,Fig. 2. The predicted trend of annual rainfall attemperature for maximum tree growth is set to 15
Leonora.
˚C, and the temperatures depart from this optimalvalue with its increasing. By comparing the30
factors expressing stresses of dryness and high25
temperature under meteorological conditions for20
the end of this century, it turned out that the15
reducing rainfall has more contribution to the10reducing tree growth.
5The other arid areas in the world were0
selected as an afforestation candidate as200020202040
2060
2080
2100
西暦[年]
Year
mentioned before, and investigations on the effectof climate change were conducted. The factors
Fig. 3. The predicted trend of annual averagefor dryness and temperature of eachtemperature at Leonora. The horizontal
line shows the optimal temperature forrepresentation point for the gathered mesh groups
tree growth in the simulator.
were examined. Comparing those factors ofyear 2000 and 2100, these groups were classified

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Increasin
Not changing
Decreasin

Fig. 4. Results of future trend estimations that attempted for the afforestation candidate aridareas in the world.

as decreasing, increasing, and not so affected areas, in the case of serious climate change.
Figure 4 shows the results of climate change evaluation for arid lands in the world. Some areas,including Leonora, Western Australia, are classified as the group of decreasing ability on growth trees, andthese areas may not be suitable for afforestation aimed at CO2 sequestration. Afforestation in the otherareas are not restricted by the climate change, and the such area will be selected as an afforestation target.
Additionally, in some areas, including Colorado and Wyoming, will be enhanced according to the global
warming although an excessive expectation should be restricted in considering uncertainty of simulation tothe future. In addition, it should be again stressed that this is the pessimistic prediction because thepositive effect of increased CO2 concentration on photosynthetic activity is omitted.
4. Conclusions
The estimation of climate change effects on arid land afforestation for CO2 sequestration wasattempted by using a data from CCSM3.0 and a model of tree growth (similar to the 3-PG model) inLeonora, Western Australia. In Leonora, a reduction of rainfall and rising of average temperatures by
climate change are predicted and these two factors are tending to reduce the tree growth. Furtherinvestigations on the other arid area show tree growth in some area will be enhanced according to theglobal warming. Though the more detailed evaluations of future trends are required, arid area with
reducing trend for a tree growth ability should be avoided in afforestation.
Acknowledgement
This work was conducted under the supports of Mitsui & Co., Ltd. Environment Fund and the New
Energy Development Organization (NEDO).
ReferencesKojima T., Hamano H., Abe Y., Tanouchi H., Egashira Y., Saito M., Law J., Takahashi N.. Yamada K. (2006): Basic Data of Research
Project on Large Scale Afforestation of Arid Land for Carbon Fixation near Leonora in Western Australia. J. Arid Land Studies,
16(3): 167-174
Landsberg J.J., Warig R.H. (1997): A generalised model of forest productivity using simplified concepts of radiation-use efficiency,
carbon balance and partitioning. Forest Ecology and Management, 95: 209-228
Sands P.J., Landsberg J.J. (2002): Parameterisation of 3-PG for plantation grown Eucalyptus globulus. Forest Ecology andManagement, 163: 273－292
Xie P., Arkin P.A. (1996): Global Precipitation: A 17-Year Monthly Analysis Based on Gauge Observations, Satellite Estimates, andNumerical Model Outputs. Bull. Amer. Meteor. Soc., 78: 2539-2558.