J. Jpn. Soc. Soil Phys.
土壌の物理性No. 130, p.3 ∼ 10 (2015)

Comparison of drought tolerances in a root water uptake modelfor two co-occurring grass species in Mongolia
Aki YANAGAWA1 , Haruyuki FUJIMAKI2 , Toshiya OKURO3 , Undarmaa JAMSRAN4
and Kazuhiko TAKEUCHI5

Abstract: Drought stress due to sparse rainfall is one of
the main factors determining plant species composition
in semi-arid ecosystems. The tolerance of two dominant
perennial grasses of northeastern Asia, Leymus chinensis
and Stipa krylovii, to continuously changing drought stress
was compared. Their responses to the stress were evaluated in terms of the parameter values in Feddes model.
The results indicated that transpiration in S. krylovii began
to decrease at a higher matric potential (−102 cm) than in
L. chinensis. L. chinensis has higher performance in transpiration rate at a higher matric potential. In contrast, it
seemed that greater tolerance of L. chinensis for drought
stress is inconsistent at lower matric potentials (−104 cm).
Thus, the tolerance for drought stress was ambiguous but
depended on the degree of stress. Furthermore, S. krylovii
maintained a low transpiration rate under a lower matric potential, implying that this species is well-adapted todrought stress because it can continue transpiration, evenunder severe drought stress conditions. Notably, the estimated values for root water uptake according to Feddes
revealed strategic responses in both plants for survival insemi-arid regions.
Key Words : Stipa krylovii; Leymus chinensis, root water
uptake, drought stress, Feddes model

1. Introduction
Drought stress is a critical inhibitor of plant growth insemi-arid ecosystems and results from sparse and irregular
rainfall. As typical semi-arid grassland, Hustai National
Park in Mongolia is characterized by sparse and irregular rainfall. Leymus chinensis and Stipa krylovii are the1 Department of Civil and Environmental Engineering, Tokyo Instituteof Technology, 2-12-1-M1-6 Ookayama, Meguro-ku, Tokyo 152-8552,
Japan. Corresponding author : 柳川 亜季，東京工業大学大学院理工学研

究科
2 Arid Land Research Center, Tottori University, 1390 Hamasaka, Tottori,

680-0001, Japan.
3 Graduate School of Agricultural and Life Sciences, The University ofTokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
4 Center for Ecosystem Study, Mongolian State University of Agriculture,210153 Ulaanbaatar, Mongolia.
5 Integrated Research System for Sustainability Science, The Universityof Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-8654, Japan.
2013 年 11 月 13 日受稿 2015 年 6 月 5 日受理

dominant perennial grasses in this area (Yuan et al., 2005;
van Staalduinen and Anten, 2005). L. chinensis predominates in habitats with relatively abundant water (Chen etal., 2005). S. krylovii is a more abundant and important
species in drier areas (Chen et al., 2005) such as the typical moderately grazed grasslands in Mongolia (van Staalduinen and Anten, 2005; Hoshino et al., 2009). With overgrazing, S. krylovii tends to be replaced by L. chinensis(Hilbig, 1995; Hoshino et al., 2009; van Staalduinen etal., 2007). Therefore, previous studies have suggested thatthese plants may be useful key indicators of grazing intensity; however, there is insufficient quantitative knowledge of their stress-response characteristics. Some studies have indicated that the two species have distinct differences in morphology, compensatory growth, and tolerance
to drought stress (van Staalduinen and Anten, 2005; Shinoda et al., 2010), but little is known about their differencesin real-time responses to drought stress and how these differences contribute to the distribution of the species.
Evaluation of the tolerances of these key plants todrought stress should help elucidate and predict the dynamics of species composition and net primary production
in response to climate change and human activity in semiarid ecosystems. Previous evaluations of drought stress onplants have been based on the assessment of dry matterproduction and dry matter content in various tissues at different inputs, such as under continuous wet or dry conditions (Wang, 2004; Chen et al., 2005; van Staalduinen andAnten, 2005; Yuan et al., 2005). Without understanding
how a plant dynamically responds to stresses, predictinghydrological processes, vegetation growth, and shifts insuch ecosystems is difficult. Macroscopic root water uptake (RWU) models, such as Feddes model (Feddes et al.,1978), deal with the nonuniform distribution of the matricpotential by discretizing the soil and root profiles. Therefore, reliable evaluation of stress tolerance should be possible if such a model is used. Feddes model, which is basedon stress-response functions and the active root distribution, is widely employed in user-friendly hydraulic sim-

土壌の物理性

4

ulation models of soil-plant-atmosphere systems, such as
HYDRUS (Šimůnek et al., 2006) and SWAP (van Dam etal., 1997). Notably, the plant-specific parameter values in
Feddes model can be universal indices of the tolerance ofplants to stress because they are assumed to be independentof the experimental conditions.
The objective of this study is to compare the tolerancesof S. krylovii and L. chinensis to sequential changes indrought stress. Because net primary production is strongly
related to transpiration and the prediction of transpiration
rates under drought conditions is hydrologically important,
the transpiration rate was the focus of the evaluation of tolerance to drought stress in this study.

第 130 号(2015)

Tcal = ∫Tp
ρr (z) dz∫

αρr (z) dz(5)

In this study, numerical integration was performed with the
Riemann sums at a spatial increment of 0.5 cm.
This model does not consider compensated water uptake, which describes the compensation for root water uptake reduction in dry layers by enhanced uptake in wet layers. However, since the magnitude of the compensated water uptake was assumed to be not so significant in our previous studies, we assume the simple root water uptake modelis accurate enough if appropriate parameter values are used(Fujimaki et al., 2008; Fujimaki and Kikuchi, 2010; Yana-

2. Theory

gawa and Fujimaki, 2013).
In Feddes model, the rate of water uptake, S (day−1 ) asa function of depth z (cm), which is a sink term in the continuity equation, is obtained by multiplying the RWU reduction coefficient α by the potential water uptake rate Sp(day−1 ) (Feddes and Raats, 2004; Feddes et al., 1978):

3. Materials and methods
3.1 Experimental plants
Tillers of five S. krylovii and five L. chinensis plants

S (z) = α Sp (z)(1)

were taken from Mongolia (lat. 47◦ 46’48” N, long. 105◦
54’56” E, mean elevation 1378 m a.s.l.), where the cli-

To express the reduction in the water uptake rate in response to drought stress, the following equation was employed:
1
( )p
α=
(2)
1 + hh50

mate is semi-arid and continental (mean annual temperature +1◦ C) with a short growing season in summer (fromJune to August), during which time more than half ofthe precipitation is recorded (mean annual precipitation
232 mm, CV 31 %). These climatic data were obtained

Sp (z) = β (z) Tp(3)from the Hustai National Park climatic station for the years
1999–2005.

hh

where h is the matric potential, and h50 and p are fitting parameters (van Genuchten, 1987). Note that h50 is the matric potential when the water uptake is 50 % of its potential
rate; these parameters, therefore, represent simple indicesof the stress tolerance of the plants. The potential water
uptake (Sp ) rate is proportional to both the normalized root
density and root activity β (cm−1 ) and the potential transpiration rate Tp (cm day−1 ):The normalized root density β is defined as the density ofactive roots as a function of depth z that is normalized suchthat integrating over the root zone yields unity:

β (z) = ∫ρr (z)
ρr (z) dz(4)

where ρr is the density of the active roots, often represented
by the root length density (cm−2 ). Because the transpiration rate Tcal is the integral of S over the root zone, Tcal iscalculated as follows:

Fig. 1 Drying and wetting soil water retention curves for Kantoloam.

論文：Comparison of drought tolerances in a root water uptake model for two to-occurring grass species

5Fig. 3 Photos of Stipa krylovii (left) and Leymus chinensis(right).

Fig. 2 Schematic of the experimental setup.

Table 1 Experimental treatment and type of sensor for each column.
Plant
ColumnTreatment
SensorStipa krylovii
S1

S2

S3

Drought stress
Soil moisture and temperature

Leymus chinensis
SR1

SR2

No stress
No sensors

3.2 Experimental setup

L1

L2

Drought stress
Soil moisture and temperature

LR1

LR2

No stress
No sensors

the column at the bottom (Fig. 2).

The experiment was conducted in a greenhouse locatedTo monitor the hourly volumetric water content, θ , andin the Biotron Laboratory at the University of Tokyo.

temperature in the soil, three dielectric moisture probes

The internal temperature was maintained at approximately(10HS, Decagon Devices, Inc. Pullman, WA) were in-25 ◦ C during the day (06:00–18:00) and 20 ◦ C at night

serted horizontally into three columns for each species: S1,(18:00–06:00), and the average humidity was 59 %. The

S2, and S3 for S. krylovii and L1 and L2, for L. chinensis

day length was set at 15 h (05:00–20:00) by supplementing(Table 1, Fig. 3). Insertion was performed such that thenatural light with mercury-vapor lamps.

centers of the rods (there were three rods for each sensor)

Ten columns (25 cm i.d. and 30 cm high) were placed inwere located at depths of 5, 15, and 25 cm, respectively

the greenhouse. Table 1 shows the experimental treatment(Fig. 2). In addition, each type of moisture probe was cal-and type of sensor for each column. Air-dried Kanto loam

ibrated at three points: the water content of the soil was(sand 50 %, silt 44 %) was packed into the columns to ameasured for the air-dried soil, the saturated soil, and thebulk density of 0.82 g cm−3 . The water-retention curve forsoil at the end of the experiment.

the Kanto loam obtained using the evaporation method for

Four reference columns, two (SR1 and SR2) for S.

the drying curve and the hanging water method for the wet-krylovii and two (LR1 and LR2) for L. chinensis, wereting curve, which was used to estimate the matric potential

used to measure the potential transpiration under contin-

from the soil moisture content, is shown in Fig. 1. To min-ued irrigation with tap water for growth and 2000-fold di-imize nonuniformity during packing, the mass of every 5

luted liquid fertilizer (N-P-K = 6-10-5, Hyponex Japan,

cm of packed soil was measured before the next soil incre-

Osaka, Japan) but were not equipped with soil moisture

ment was added. The soil surface was covered with white 1

and EC probes. The water containing the liquid fertilizer

cm-thick styrene foam to prevent evaporation, thus allow-

was added to the reference columns using a sprinkling can

ing only transpiration (Fig. 2). Cotton-filled glass pipes (1within a few minutes, but without causing ponding, in or-

cm o.d. and 15 cm long) were placed at the bottom of eachder to replace the amount of water, that was taken up dur-column to allow gravity drainage through a hole in side ofing the previous day (determined based on the decrease inweight).

土壌の物理性

6

第 130 号(2015)

to Tri during the non-stress period (m − n + 1). During thestress period, Tp was estimated by multiplying η byTri , assuming that the growth correction factor is invariant overthe stress period.
One S. krylovii or L. chinensis tiller was transplanted
into each column on October 7, 2008. The stress period
was initiated after healthy plants were grown using irrigation with tap water (EC < 0.01 dS m−1 ) and 2000-folddiluted liquid fertilizer (1 dS m−1 ). Because there were
cotton-filled glass pipes for gravity drainage at the bottoms of the columns, the lack of oxygen supply shouldhave been minimized. The water supply was completely
stopped in order to initiate the drought stress period. The
Fig. 4 Profiles of root length density at the end of experiment.

drought stress period was terminated when the relativetranspiration (i.e., the actual transpiration rate divided by

3.3 Experimental scheme

the potential transpiration rate) dropped to less than 75 %.

The method presented by Yanagawa and Fujimaki

At the end of the experiment, soil samples were taken(2013) was followed. Although the drought stress period

from each 5 cm layer. The roots were cut at the bound-

was the end of December, the experiment finished at thearies of each of the 5 cm layers using a pair of scissors

end of March. Consequently, it was possible that the root

and a sharp knife. The roots were then separated fromdensity at the end of the experiment was different from thatthe soil by sieving the air-dried soil samples through a 0.8of the drought stress period. Since the end of drought stressmm screen. The segments of the roots were scanned atperiod is almost half of the whole experimental period, the600 dpi to obtain digital images, and the total length ofdata for the drought stress period was also inversely an-

the root segments in each layer was automatically calcu-

alyzed assuming half of the root depth at the end of thelated using the SimpleDigitizer program (www.alrc.tottori-

experiment while keeping the shape of the root density at

u.ac.jp/fujimaki/download/SimpleDigitizer) using the in-the end of the experiment.

tersection method (Newman, 1966). The total root length

The daily transpiration rate was measured by manuallyweighing each column every night at 8 p.m. The poten-

density distribution for each column was then plotted (Fig.
4).

tial transpiration was calculated by multiplying the mean

Consequently, the normalized root density, daily po-

value of the potential transpiration rate for the reference

tential transpiration rate, and actual daily transpiration

columns (SR1, SR2, LR1, and LR2) by correction factors

rate as well as hourly soil moisture and hourly ma-

for the individual differences in growth. Because Tp in-tric potential values calculated based on the soil mois-

evitably differs from plant to plant due to nonuniformity inture content of the Kanto loam (Fig. 1) were used tomicrometeorological conditions and genetic differences, acalculate the parameter values for the RWU reduction

growth correction factor, η , was introduced for each plant:

coefficient for each column. The program PERF, which

)
m (
1
Ti
η=
∑ Tri
m − n + 1 i=n

is available at http://www.alrc.tottori-u.ac.jp/fujimaki(6)/download/windows.html, was used to estimate the parameter values in the stress response function based on thewhere Tri is the average transpiration for the two reference
columns , and m and n are the final and first day of analysis
period, respectively. Thus, the value for η is the averagevalue for the ratio of the transpiration on the ith day, Ti ,Levenberg-Marquardt maximum neighborhood method(Marquardt, 1963) to minimize the sum of the root meansquare error (RMSE) between the measured and calculated
daily transpiration.

論文：Comparison of drought tolerances in a root water uptake model for two to-occurring grass species

7

Table 2 Optimized parameter values and observed and calculated total amount of transpiration.
Stipa krylovii
S1

S2

Leymus chinensis

ColumnRoot Depth

Full

h50
p
RMSE

−2021 −2389 −1580 −1561 −1424 −1410 −1675 −1787
1.49
1.89
1.98
1.43
1.43
1.56
1.63
1.36
0.07
0.08
0.09
0.08
0.05
0.04

Half

Period12/4 –/27
Total transpiration
Observed
17.48
Calculated 17.04 17.01

Full

S3
Half

Full

Half

12/4 –/26

12/4 –/25

21.94
21.67 21.75

13.39
12.96 13.39

Stipa krylovii

Average
Full
Half

L1
Full

L2
Half

Half

Average
Full
Half−1200 −1337 −765 −683 −983 −1010
4.18
3.28
3.90 3.78 4.04
3.53
0.13
0.12
0.10 0.13
12/4 –/23

17.60
17.22 17.38

Full

39.74
38.92 38.76

12/4 –/24
22.85
31.30
20.97 21.70 29.95 30.23

Leymus chinensis

Fig. 5 Time series of volumetric water content (VWC) and ratio of actual to potential transpiration:(a) Stipa krylovii (S1) and (b) Leymus chinensis (L1).

sidered to be reliable. The total transpiration for L.chiensis

4. Results

was higher than that of S. krylovii during the analysis period (Table 2).

The time series for the volumetric water content andFig. 6 compares the measured and calculated ratios ofratio of the actual to potential transpiration are shown in

the actual to potential daily transpiration for full and half

Fig. 5. The ratio of actual to potential transpiration started

root depths. The actual and potential transpiration were

to decrease less than unity clearly when volumetric water

daily measured according to the weight of the column

content at the depth of 15 cm became less than 0.4. Ta-

under stress and no-stress (reference) conditions, respec-ble 2 lists the optimized parameter values and measured

tively. The calculated transpiration ratios were derived ac-and calculated transpiration results for S. krylovii and L.

cording to Eq. (5) based on the optimum sets of parameterchinensis after being subjected to drought stress assuming

values for h50 and p (Table 2). Large discrepancies be-

full and half root depths (Full and Half in Table 2) based on

tween the measured and calculated values occurred when

the root distribution at the end of the experiment (Fig. 4).

the potential transpiration was either very low or high. Ex-

The parameter values for drought stress and the total cal-

cept for such data, however, most of the calculated values

culated transpiration results did not vary so much during

were similar to the corresponding experimental results.

the growing period regardless of the root depth. Therefore,

Since the parameter values for drought stress did not

the parameter values for drought stress (h50 , p) were con-vary so much even if using the half root depth, the RWU

土壌の物理性

8

第 130 号(2015)

Fig. 6 Comparison of measured and calculated ratios of actual to potential daily transpiration:(a) full root length and (b) half root length.

reduction coefficient α according to equation 2 using ob-

The values for p were substantially greater for L.

tained parameter values are shown only for the full rootchinensis than S. krylovii (Table 2). The difference in thelength condition in Fig. 7. Bold lines show the matric po-p values represents the difference in the sharpness of thetential range of experiment. Each two or three columns

reduction in the RWU beyond the threshold value for thewere a set of replicates. As can be observed in this fig-

two species. A low p value indicates a low sensitivity ofure, the tolerance for drought stress varied with the degree

the RWU to drought stress. In addition, the transpirationof drought stress with the both condition of full and half

rate for S. krylovii decreased more gradually than that ofroot length. In addition, it was found that transpiration for

L. chinensis (Fig. 7).

S. krylovii began to decrease earlier than for L. chinensis

5. Discussion

under drying process.

Although the tolerance to drought stress of S. krylovii
and L. chinensis has been reported (e.g., S. krylovii is considered more drought tolerant than L. chinensis; Chen etal., 2005), the results of the present study indicated thattranspiration for S. krylovii began to decrease at a higher
matric potential (−102 cm) than for L. chinensiss. If thepresent results fully supported those of previous studies(Chen et al., 2005; van Staalduinen and Anten, 2005),
then the S-shaped curve for drought stress in S. krylovii
would have always appeared to the right of the curve for
L. chinensis. However, the results of the present study
indicate that the relationship between the drought stresshresponses of the two species changes with the degree ofdrought stress. A previous study implied a higher sen-Fig. 7 Drought stress response functions for Leymus chinensis(L1 and L2) and Stipa krylovii (S1, S2, and S3).

sitivity of L. chinensis to drought stress (Wang, 2004).
This sensitivity would correspond to the higher value of

論文：Comparison of drought tolerances in a root water uptake model for two to-occurring grass species

9

Aknowledgements

p in L. chinensis. Unfortunately, the response at approximately −104 cm could not be observed directly, and thus
remains to be investigated (bold lines in Fig. 7 show theWe thank S. Okubo (National Institute for Agro-matric potential range in the experiment). However, it

Environmental Sciences) and T. Okayasu for their helpful

can be concluded that because transpiration was greatercomments. We also thank T. Watanabe (Biotron Labora-

for L. chinensis, S. krylovii is more suited to surviving

tory, Graduate School of Agricultural and Life Sciences,drought conditions from the viewpoint of saving soil wa-

The University of Tokyo) for his technical assistance withter. It means S. krylovii has a competitive advantage under

the greenhouse experiment. The helpful comments on thecontinuously water limited condition such as in grassland.

manuscript by N. Toride, K. Kosugi and two anonymous

Since L. chinensis can use water more quickly, it seems

referees are also appreciated. This study was performedthat L. chinensis has a competitive advantage in plant com-under the Global Environmental Research Fund of Japan’s

munities with low density such as degraded bare grassland

Ministry of the Environment (“Desertification control andor river bank.

restoration of ecosystem services in the grassland regions

In addition, the results of the present study suggest thatof North-East Asia”; no. G-071), with additional support

evaluation of stress responses using the parameters forfrom Japan Society for the Promotion of Science Research

Feddes model may provide more detail than previous stud-

Fellowships for Young Scientists, awarded to A. Hoshino

ies when investigating continuous changes in the matric(no. 20-7002) and A. Yanagawa (no. 24-7604).

stress conditions for these two main species in Mongolia.

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旨乾燥ストレスは，半乾燥地域の植物生態系において重要な要素である．北東アジア地域の主要な草本である Leymus chinensis と Stipa krylovii について，乾燥条件を連続的に変化させ，乾燥耐性を調べた．
ストレス応答パラメーターの推定には Feddes の吸水モデルを用いた．乾燥ストレスが低いときは，L.

chinensis の耐乾性が高く，S. krylovii は乾燥ストレスが高いときにより高い耐性を示した．S. krylovii
は，高い乾燥条件下でも蒸散速度を維持できるため，乾燥に適応した種であると考えられた．吸水モデ
ルに基づくパラメーター推定によって，半乾燥地域において生き延びるための戦略的応答を評価することができた．
キーワード：Stipa krylovii，Leymus chinensis，根による吸水，乾燥ストレス，Feddes の吸水モデル