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Measured and modeled biomass growth in relation tophotosynthesis acclimation of a bioenergy crop (Reed canarygrass) under elevated temperature, CO2 enrichment anddifferent water regimes

Zhen-Ming Ge a,b,*, Xiao Zhou c, Seppo Kellomaki b, Heli Peltola b, Christina Biasi d,Narasinha Shurpali d, Pertti J. Martikainen d, Kai-Yun Wang b

a State Key Laboratory of Estuarine and Coastal Research, East China Normal University, 200062 Shanghai, Chinab School of Forest Sciences, University of Eastern Finland, Joensuu Campus, Yliopistokatu 7, P.O. Box 111, FIN-80101 Joensuu, FinlandcShanghai Research Center for Transport, Port and Shipping Development, 200025 Shanghai, ChinadDepartment of Environmental Science, University of Eastern Finland, P.O. Box 1627, FIN-70211 Kuopio, Finland

a r t i c l e i n f o

Article history:

Received 24 August 2010

Received in revised form

26 June 2012

Accepted 29 August 2012

Available online 27 September 2012

Keywords:

Photosynthesis

Biomass

Simulation

Climate change

Water table level

Phalaris arundinacea L.

* Corresponding author. School of Forest SFIN-80101 Joensuu, Finland. Tel.: þ358 13 25

E-mail address: zhenming.ge@uef.fi (Z.-M0961-9534/$ e see front matter ª 2012 Elsevhttp://dx.doi.org/10.1016/j.biombioe.2012.08.

a b s t r a c t

The seasonal biomass growth and photosynthesis performance of a bioenergy crop, Reed

canary grass (Phalaris arundinacea L.) under elevated temperature (ambient þ 3.5 �C), CO2

enrichment (700 mmol mol�1) and different water regimes, was examined. To quantify the

contributions of acclimated photosynthesis to biomass growth under the environmental

treatments, a simplified model was parameterized to simulate the seasonal biomass

accumulation of this bioenergy crop. As a result, we found that during the early growing

periods, the photosynthesis, leaf development and above-ground biomass growth of the

plants were enhanced under elevated temperature conditions, due to higher temperature

sum for crop development compared to ambient temperature conditions. However,

elevation of temperature resulted also in earlier senescence and lower total biomass of RCG

at the final harvest, which effect was the most pronounced with low soil water table. As

a comparison, CO2 enrichment increased significantly the leaf development, photosyn-

thesis and total biomass growth over the whole growing season. Under the combined

elevation of temperature and CO2, the acclimation of photosynthesis and total biomass of

the plants at the final harvest was similar to those caused by elevated temperature alone.

In general, high water table favored the photosynthesis and biomass growth of the plants.

To conclude, the simplified model built for this bioenergy crop simulated well the

dynamics of seasonal canopy photosynthesis and biomass growth, and with good accu-

racy. Meanwhile, the uncertainty of model was also discussed.

ª 2012 Elsevier Ltd. All rights reserved.

ciences, University of Eastern Finland, Joensuu Campus, Yliopistokatu 7, P.O. Box 111,1 4441; fax: þ358 13 251 4444.. Ge).ier Ltd. All rights reserved.019

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2252

1. Introduction In the above context, the aim of this work was to examine

The drained cut-over peat mining sites on organic soils are

frequently cultivated for bioenergy crops such as Reed canary

grass (hereafter RCG, Phalaris arundinacea L.) in northern

Europe [1]. An important question on these organic soils is

how to optimize the biomass production of RCG and the

carbon balance of sites simultaneously [2e4]. This is impor-

tant challenge as on the drained peat mining sites organic

soils have a high risk of significant soil carbon losses [5].

Climate change, however, is likely to have a large impact

on carbon accumulation in the biomass of RCG on peatlands.

In Finland, the mean annual temperature is expected to

increase by 2e7 �C with a concurrent elevation of CO2 by the

end of the 21st century [6,7]. The changing climate may also

affect soil water availability and the consequent carbon

uptake and plant growth, and finally plant biomass. In fact,

the drought episodes are expected to become more frequent

and limit plant growth even in the central boreal zone [8].

Many studies have been conducted to understand the

effects of temperature, CO2 and soil water availability on

photosynthesis of C3 herbaceous crops (e.g., wheat Triticum

spp. and riceOryza spp.) in natural and agricultural ecosystems

[9e13]. In some earlier studies, increased temperature has

been found to reduce crop biomass by decreasing photosyn-

thesis, which could be a result of earlier deactivation of

photosynthetic enzyme [11,13]. However, it was also reported

that temperature had no significant effects on the biomass

growth of crops [14]. In general, CO2 enrichment is expected to

substantially increase net photosynthetic CO2 uptake and

water use efficiency, and decrease transpiration through

reducing stomatal conductance [15]. On the other hand, the

stomatal response of plants exposed to CO2 enrichment has

been found to vary among species [16,17]. The combined

elevation of temperature and CO2 will also affect carbon

uptake (photosynthesis), reflecting possibly some offsetting

acclimation responses [12,18]. Drought has substantial nega-

tive influences onmanyphysiological processes of plants such

as photosynthesis, stomatal behavior, chlorophyll fluores-

cence and metabolite accumulation (e.g., [19]). It has been

shown that high soil water availability favored the high rate of

CO2 fixation by photosynthesis of RCG in the abandoned

peatland [1]. It has also been previously demonstrated that

increasing drought episodes will inhibit many growth

processes, and that CO2 enrichment will partially mitigate

some of these adverse effects [20].

Most of previous studies have focused on the interim

photosynthetic performance of plant to climate change (i.e.

temperature and CO2 elevation), though a few follow the

response along the whole growing periods (e.g., [21]). This is

despite, the plant growth and biomass accumulation are

usually the focuses of research regarding the bioenergy crop.

Up to date, there are very few studies that have either dealt

with interaction among climatic factors and soil water avail-

ability (e.g., [20,22,23]). Thus, there is limited understanding

available of the predicted biomass growth (through modeling

approach) based on the photosynthetic acclimation of the

boreal bioenergy crop (RCG) under the conditions of climate

change.

the seasonal acclimation of photosynthesis and biomass

growth of RCG under elevated temperature (ambient þ 3.5 �C),CO2 enrichment (700 mmol mol�1) and varying soil water

regimes. For this purposewe conducted a factorial experiment

with RCG microcosms taken from a cut-over peat site to

greenhouses where the environmental conditions could be

accurately controlled either separately or concurrently over

whole growing season. More specifically, the objective of this

study was (1) to understand the seasonal characteristics of

measured photosynthesis performance and biomass growth

of RCG, and (2) to model the seasonal biomass accumulation

with acclimated photosynthesis of RCG under different

temperature, CO2 enrichment and soil water regimes based on

a simple biomass growth model parameterized for RCG.

2. Material and methods

2.1. Plant material and growing conditions

The RCG sampling was conducted in the Linnansuo peatland

(latitude 62�3201200 N; longitude 30�2504500 E) in Eastern Finland.

The field has been cultivated since 2001 (i.e. the cultivation

was seven years old at the time of sampling) by a peat & bio-

energy production company (Vapo Energy Ltd.). The cultiva-

tion of RCG on peat soils generally follows a 10e15 year

rotation cycle. The RCG variety cultivated in the Linnansuo

peatland was ‘Palaton’ obtained from Seed Link Inc. (Canada)

by the Finnish seed company (S.G. Nieminen Oy). The general

RCG cultivation practice in the Fenno-Scandinavian region is

to harvest the crops in the spring of the following year. After

harvesting, the Linnansuo peatland is fertilized with nitrogen

(N) 59.5 kg ha�1, phosphorus (P) 14.0 kg ha�1 and potassium (K)

45.5 kg ha�1. Fertilizers are applied every year.

In March 2009, the RCG-peat monoliths were transplanted

into high density polyethylene containers with internal size of

80 cm L � 60 cm W � 40 cm D (large size selected to reduce

stress on the root system, see Shurpali et al. [24]). The volume

of peat bulk sample was almost equal to the size of the

container, and the gaps between peat and container were

tamped with the small peat pieces.

In April 2009, 48 containers with microcosms were moved

into a greenhouse at Mekrijarvi Research Station (latitude

62�4601500 N, longitude 30�5802100 E, belong to University of

Eastern Finland), about 30 km from the Linnansuo peatland.

The greenhouse consists of two main structural sections: (i)

control and facility center and (ii) 16 growth chambers [25].

Each chamber is an independent research unit, around 16 m2

in size. Room height is 4 m and the internal volume is 64 m3.

The 16 chamber units were divided into 4 climate treatments

following a factorial design: (i) ambient temperature and CO2

concentration (around 370 mmol mol�1) (CON), (ii) elevated

temperature and ambient CO2 concentration (ET), (iii) CO2

enrichment (around 700 mmol mol�1) and ambient tempera-

ture (EC), and (iv) elevated temperature and CO2 enrichment

(ETC). During the period of RCG cultivation (2009e2010), the

CON chambers were set to follow outside free air temperature

and CO2 concentration, while the target mean temperature

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2 253

was set at þ3.5 �C above the outside ambient temperature in

the ET and ETC chambers (see technical details and perfor-

mance of the chamber system in detail, [25]).

Three containers in each chamber were treated with three

soil water table levels, i.e. high water table level (HW, 100%

volumetric soil water content), normal water table level (NW,

w50% as field measurement), and low water table level (LW,

w30%). The wilting point of drained agriculture peatland is

about 20e30% of volumetric soil water content in Finland [26].

The irrigation targets were regulated with the manual soil

moisture sensors. In order to avoid edge effects the containers

were rotated once a week. The growth characters (height,

stem diameter, leaf length and leaf area) of RCG in four

replicates of each climate treatment were relatively homoge-

nous, as listed in Table 1.

2.2. Measurements

2.2.1. Layout of measurementsOver two growing seasons (2009e2010), the measurements of

photosynthetic responses and biomass growth (detail see

below) weremade on six occasions during the growing season

in 2010. These measurement periods are denoted by Roman

numerals; Approximately, I: 30th Maye15th June, II: 16th

Junee30th June, III: 1st Julye15th July, IV: 16th Julye1st

August, V: 2nd Auguste15th August, VI: 16th Auguste15th

Table 1 e Mean (SE) of height, stem diameter, leaf lengthand leaf area (per shoot) in 4 replicates of each ambientclimate (CON), elevated temperature (ET), CO2 enrichment(EC), elevated temperature and CO2 (ETC) chamber andfield data during fifth growth period (period V, see Section2.2.1) averaged by all water table levels. The plant shootsgrown in the sample basal area of 153.4 cm2 (14 cm-diameter) based on 4 sampling replicatesweremeasured.One-wayANOVAanalysiswas used to test the significantdifferences at P £ 0.05 level.

Treatment Stemheight(cm)

Stemdiameter(mm)

Leaflength(cm)

Leafarea(cm2)

CON-1 106.7 (10.1) 0.24 (0.01) 16.6 (1.7) 28.5 (2.7)

CON-2 107.2 (10.1) 0.23 (0.01) 16.4 (1.1) 28.3 (2.8)

CON-3 106.8 (10.1) 0.24 (0.01) 16.3 (1.1) 28.2 (2.5)

CON-4 106.6 (10.3) 0.23 (0.01) 16.6 (1.1) 28.6 (2.4)

P 0.20 0.09 0.40 0.44

ET-1 95.3 (9.2) 0.24 (0.01) 16.6 (1.3) 27.7 (1.3)

ET-2 92.4 (9.2) 0.25 (0.01) 16.2 (1.2) 28.1 (1.9)

ET-3 93.3 (9.2) 0.24 (0.01) 16.3 (1.7) 28.3 (1.9)

ET-4 98.1 (9.2) 0.24 (0.01) 16.2 (1.4) 27.8 (2.3)

P 0.55 0.15 0.29 0.12

EC-1 110.5 (10.3) 0.27 (0.01) 18.2 (1.1) 30.7 (1.9)

EC-2 109.3 (10.5) 0.26 (0.01) 18.8 (1.2) 30.4 (1.9)

EC-3 109.6 (10.5) 0.28 (0.01) 18.4 (1.3) 30.4 (1.7)

EC-4 109.3 (10.7) 0.27 (0.01) 18.7 (1.8) 30.8 (1.0)

P 0.31 0.08 0.24 0.16

ETC-1 105.6 (10.3) 0.24 (0.01) 18.3 (1.1) 28.8 (1.7)

ETC-2 105.5 (10.2) 0.26 (0.01) 18.1 (1.1) 29.3 (2.4)

ETC-3 105.0 (10.3) 0.27 (0.01) 18.3 (1.2) 32.5 (3.7)

ETC-4 105.3 (10.3) 0.26 (0.01) 18.2 (1.2) 29.2 (2.8)

P 0.41 0.07 0.62 0.16

September, roughly following the RCG development stages in

the field [27] (from “before flag emergence” to “seed ripening

and plant senescence”).

2.2.2. Measurements of gas exchangeThe gas exchange measurements on the RCG leaves were

restricted to the time period between 0800 and 1100 h on

sunny and generally cloud-free days, to minimize diurnal

effects on photosynthesis. The light-saturated net photosyn-

thetic rates (Psat, mmol m�2 s�1) of intact, second fully

expanded leaves of RCG were measured under

1500 mmol m�2 s�1 photosynthetic photon flux densities

(PPFD), using infrared gas analyzers built into a 2 � 3 cm

standard leaf chamber in a portable Li-6400 infrared gas-

exchange system (Li-6400, Li-cor Inc., Nebraska, USA). The

CO2 source for the measurements was a computer-controlled

CO2 mixing system supplied with the Li-6400, and the CO2

concentration in leaf chamber was kept at 370 � 1 mmol mol�1

and 700 � 2 mmol mol�1 under ambient and elevated CO2

conditions, respectively. The CO2 supply was controlled as

less than 0.1 mmol mol�1 variation in 5 s. During all

measurement processes, the temperature inside the leaf

chamber was kept at 20 � 1 �C. VPDwas kept 1.0 � 0.1 kPa and

relative humidity of the air in the leaf chamber was set above

60%. Leaves were equilibrated at saturating PPFD before

initiation of the light response. Sufficient timewas allowed for

the saturated PPFD to stabilize and the concentration of CO2

inside the leaf chamber to mix totally before logging the

measurements (typically requiring 20 min or less). As

stomatal movements are very dynamic due to the complex

regulation by multiple factors, only light-saturated stomatal

conductance ( gsat, mol m�2 s�1), which is usually correlated

with the average daily mean conductance, was measured.

2.2.3. Measurement of growth parameters and biomassRCG were harvested immediately after gas exchange

measurement using a ring with 14 cm diameter (around

154 cm2) down to the soil surface, to identify the harvest area.

From each treatment, total plants were taken to determine

leaf length (LL, cm) and leaf area (LA, cm2). The number of

shoots in each sample plot was recorded. The leaf area of the

fully expanded leaves was determined by using a leaf area

meter (Li-3100, Li-cor Inc., Nebraska, USA).

After harvesting the aboveground part, a soil core (14 cm

diameter) was additionally taken for determining the below-

ground root biomass. The soil core was sampled to a depth of

35 cm, thus, up to the maximum rooting depth of the plants

[24]. In the laboratory conditions, the harvested roots were

carefully washed over a 0.2 mm sieve. However, only living

roots were sampled. The roots were also separated into coarse

(diameter > 2mm) and fine roots, respectively. The increment

of root biomass was calculated based on the initial root

biomass at the beginning of the growing season.

Harvested leaves, stems and roots were dried in a forced-

air oven at 70 �C for at least 72 h to determine dry mass.

Leaf development and organ dry mass were calculated as an

average at shoot level. As the seed production of RCG is

slightly unreliable (because of seed shattering and occasion-

ally poor panicle production) we did not take seed biomass

into account [28].

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2254

2.2.4. Statistical analysis of measurementsStatistical analyses were carried out using the SPSS (Chicago,

IL) software package (Version 16.0). Physiological parameters

(i.e. Psat and gsat), growth and biomass characters (i.e. LA, LL,

and organ biomass) were tested for the various treatment

effects (CO2, temperature and soil water table level) and their

interactions using three-way ANOVA. The results for different

measurement periods (Periods IeVI)were analyzed separately.

Differences between treatments are identified at P � 0.05.

Furthermore, mean differences among the four climate

chambers (CON, ET, EC and ETC chambers) and among the

three different soil water table levels (HW,NWand LW) in each

climatic chamber were also tested using Tukey’s HSD test.

2.3. The model

2.3.1. Outlines for modelingA simplified biomass growthmodel was constructed based on

known principles of photosynthesis, autotrophic respiration,

and growth increment and biomass partitioning. Plant

photosynthesis is calculated by scaling leaf level Farquhar’s

biochemical model [29,30] up to canopy-level implemented

through a sunlit and shaded leaves separation algorithm

[31,32]. The allometric carbon partitioning is identified [33],

and the seasonal carbon loss of root respiration is taken into

account [34]. In this model, seasonal acclimation of the

photosynthetic parameters of RCG, as well as seasonal

dynamics of the carbon allocation in plant, under elevated

temperature, CO2 enrichment and varying soil water table

regimes are highlighted [30,32,33].

The rate of leaf-level net photosynthesis (Pn) is limited by

the processes shown in Eqs. (1)e(4) [29]: the Rubisco (ribulose-

1,5-bisphosphate carboxylase/oxygenase) limited rate of

photosynthesis (Pc) and the RuBP (ribulose-1,5-bisphosphate)

regeneration-limited rate of photosynthesis (Pj), considering

the regulation by gs (stomatal conductance) and Ci (intercel-

lular CO2 concentration). In addition, gs is assumed to be

controlled by the net radiation on canopy (Ra), air temperature

(Ta), vapor pressure deficit (Da), atmospheric CO2 (Ca) and soil

water content (qs). Besides the Farquhar’s equations, the two

core photosynthetic parameters of the maximum rate of

Rubisco activity (Vcmax) and the maximum rate of electron

transport (Jmax) are also related to the phase of maturity based

on the daily temperature sum (TS, degree days), using the

quadratic functions in Eq. (6).

Pn ¼ min�Pc;Pj

�(1)

Pc ¼ Vcmax

�Ci � G�

Ci þ Kcð1þ O=KoÞ�� Rd (2)

Pj ¼ fðJmaxÞ�

Ci � G�

4 Ci þ 8 G�

�� Rd (3)

Ci ¼ Ca � Pn=gs (4)

gs ¼ max�gs:maxfðRaÞfðTaÞfðDaÞfðCaÞfðqsÞ; gs:min

�(5)

Vcmax; Jmax ¼ fðDHa; DHd; DS; c; TSÞ (6)

TS ¼X

ðTd � 5Þ (7)

where Rd is the day-respiration rate, G* is the CO2 compensa-

tion point in the absence of dark respiration, Kc and Ko are the

Michaelis constants for CO2 and O2, respectively, O is the

oxygen concentration, DHa is the enthalpy of activation, DHd is

the enthalpy of deactivation, DS is the entropy, c is a param-

eter, and Td is the daily average temperature.

An integrated sunlit/shaded algorithm is used to consider

the canopy-level carbon uptake (Pnc) with the area fraction of

sunlit (LAsun) and shaded leaves (LAsh) in Eq. (8). To relate

photosynthesis to the nitrogen concentration of leaf (NL)

within canopy layers, we assumed Vcmax, Jmax and Rd in the

models to be linear functions of NL in Eq. (9) [31,35]. The

dynamics of light regime within canopy layers is estimated

based on [31].

Pnc ¼ LAsunPn:sun þ LAshPn:sh (8)

Vcmax:i; Jmax:i; Rd:i ¼ c1ðNL � c2Þ (9)

where Pn.sun and Pn.sh are photosynthesis separately accoun-

ted for the contribution of sunlit and shaded leaf fractions,

respectively, i is the layer, and c1 and c2 are regressed

parameters.

Seasonal root respiration (Rroot) in this model is identified

as a ratio of net photosynthesis under varying soil water

conditions during different growth stages [34].

Regarding seasonal day matter (B) partitioning between

above (leaf and stem) and below (root) parts of RCG, the carbon

allocation in plant is firstly calculated during the development

stages expressed as the quadratic functions of TS for above-

and below-ground fractions in Eqs. (11) and (12) [33]. Then, the

carbon-biomass conversion factors [33] for plant organs are

used to determine the seasonal accumulation of above-

ground biomass (Babove) and increment of below-ground

biomass (Bbelow).

B ¼ Babove þ Bbelow (10)

Babove ¼ ðPnc � RrootÞvc:aCini:afðTSÞ (11)

Bbelow ¼ ðPnc � RrootÞvc:bCini:bfðTSÞ (12)

where vc.a and vc.b are the carbon-biomass conversion factors

for above- and below-ground organs, respectively, and Cini.a

and Cini.b are the initial rates of carbon allocation for above-

and below-ground organs, respectively.

2.3.2. Model parameterization and testing of modelperformanceThe model was parameterized based on measured RCG (or

other herbaceous crops) data and other data reported in the

literature. More specifically: (1) We parameterized the photo-

synthesis equations from the measured data set of RCG

focusing on the seasonal acclimation of photosynthetic

parameters to environmental treatments and phase of

maturity (quantified as temperature sum) [30], as well as the

distribution of nitrogen in canopy under elevated tempera-

ture, CO2 enrichment and varying soil water regimes and [32];

(2) Data from the literature for the ratio (ranging 10e20%) of

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2 255

root respiration to photosynthesis in response to soil water

conditions during different growth stages (jointing, anthesis

and grain-filling) [34], was used to approximate the seasonal

carbon loss of root respiration; (3) The parameters used in the

calculation of carbon allocation were fitted using the reported

data for RCG in [33]; (4) The carbon content of leaves, stems

and roots of RCG usedwere 44� 0.19, 46� 0.81 and 47� 2.46%,

respectively, regardless of growing periods and environ-

mental treatments [33]. Therefore, the mean constant values

were used as carbon-biomass conversion factors for calcu-

lating the dry matter accumulation in the plant organs.

The model requires climatic and environmental variables

as inputs, which were recorded based on the sensor set

installed in the chamber system [25]. The driving variables of

solar radiation, air temperature, air humidity, atmospheric

CO2 concentration, and soil water content were averaged

hourly and daily for different sub-models for the growing

period from 1st April to 30th September 2010. In order to

determine the accuracy of the simulations, the relative biases

and the root mean square errors (RMSEs) were calculated.

bias ¼ 100�P�

yi � byi

��nPbyi=n

(13)

RMSEs ¼ 100�ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP�

yi � byi

�2=ðn� 1Þ

qPbyi=n

(14)

where n is the number of observations, and yi and yi are the

measured and modeled values.

3. Results

3.1. Measured gas exchange, leaf development andbiomass accumulation of RCG

3.1.1. Gas exchangeDifferent effects of CO2 levels were significant (P< 0.05) for the

light-saturated net photosynthesis (Psat) and light-saturated

stomatal conductance ( gsat) regardless of water levels and

growing periods (Table 2). However, differences between

temperature regimes were not significant for all the above

parameters. Growing periods affected also significantly

Table 2 e Main and interactive effects (F values) between tempparameters of gas exchange, leaf development and biomass grvalues: *P < 0.05; ns non-significant differences.

Factors Gas exchange Leaf development

Psat gsat LA SLA Leaf

Period (P) 11.4* 11.17* 94.9* 87.9* 103.3*

Temperature (T ) 0.1 ns 0.160 ns 1.6 ns 107.0* 12.3*

CO2 (C ) 33.3* 27.83* 15.4* 42.1* 36.7*

Water level (W ) 10.7* 7.20* 12.3* 38.9* 19.3 n

T � C 0.1 ns 0.18 ns 0.4 ns 0.4 ns 0.8 ns

T � W 0.2 ns 2.16 ns 0.2 ns 3.3 ns 1.3 ns

C � W 0.2 ns 8.43* 0.0 ns 0.9 ns 0.1 ns

T � C � W 0.3 ns 3.64* 0.0 ns 1.2 ns 0.3 ns

(P < 0.05) all gas exchange parameters. Over all the periods,

statistically significant (P < 0.05) interaction was found for

CO2 � T � W in regard to Psat. For gsat, significant interactions

between CO2 � W and CO2 � T � W interactions across the

various measurement periods were detected (Table 2).

The values of Psat were lower at the beginning of growing

periods, showing a peak at the end of June (under elevated

temperature) or in the middle of July (under ambient

temperature), and thereafter decreased during the latter part

of the growing period. During the first growing periods (period

IeIII), Psat tended to be higher in the ET chambers (on average

17% higher, P < 0.05) than in the CON chambers regardless of

water levels (Fig. 1, Table 3). However, during periods IVeVI,

Psat was, on average, 13% lower in the ET chambers than that

in the CON chambers. CO2 enrichment (EC and ETC) increased

Psat, on average, by 33% (P < 0.05) compared to ambient CO2

(CON and ET) through all the growing periods (Fig. 1), regard-

less of temperature treatments and water levels. Psat in the

ETC chambers was, on average, 41% higher compared to the

CON chambers during periods IeIII, but the increase was

much smaller (on average 18% higher) during the periods

IVeVI (Fig. 1, Table 3).

Over all growing periods and soil water table levels, the

values of gsat were, on average, 35% lower (P < 0.05) under CO2

enrichment compared to ambient CO2 (Fig. 1). However, it was

not significantly affected by temperature elevation during the

growing periods. Over all water table levels, gsat was under

elevated temperature (ET and ETC), on average, 17% higher

(P < 0.05) compared to ambient temperature (CON and EC)

conditions, during growing periods IeIII. During the latter

periods (IVeVI), gsat was, on average, 18% lower (Fig. 1).

Irrespective of growing periods and climatic treatments,

Psat and gsat were statistically significantly (P < 0.05) higher in

HWandNW (on average 24% and 27% higher) compared to LW

of RCG (Fig. 1, Table 3).

3.1.2. Leaf developmentFor leaf area (LA), significant differences existed between CO2

enrichment and soil water table levels. For specific leaf area

(SLA), significant (P < 0.05) differences were observed among

temperature, CO2 enrichment and soil water table level

regimes. No significant interactions for them were found for

the leaf growth, however (Table 2).

erature, CO2, water table level and growing periods on theowth. Symbols used in the three-way ANOVA. Significance

Biomass growth

Stem Above-ground Coarseroot

Fineroot

Below-ground

324.2* 243* 221* 267* 263*

4.1* 7.4* 3.8 ns 4.2 ns 4.3 ns

22.3* 30.2* 20.2* 24.5 * 24.3*

s 27.2* 26.6* 7.9* 12.6 * 11.6*

0.0 ns 0.2 ns 4.6 ns 3.3 ns 3.4 ns

1.0 ns 1.2 ns 0.1 ns 0.1 ns 0.1 ns

0.0 ns 0.0 ns 0.2 ns 0.1 ns 0.1 ns

0.0 ns 1.1 ns 0.1 ns 0.1 ns 0.1 ns

P(µ

mol

m s

) CON EC ETC

5

10

15

20

25

30 HW NW LW

0.1

0.2

0.3

g (m

ol m

s)

0

ET

10

20

30

40

50

60 HW NW LW

LL

(cm )

0

5

10

15

20

25

Periods

300

II III IV VI

0

200

100

0 V I II III IV VI V I II III IV VI V I II III IV VI V I

LA

(cm

)S

LA

(cm

g)

Fig. 1 e Mean (SE) light-saturated net photosynthetic rates (Psat), light-saturated stomatal conductance ( gsat), leaf area per

shoot (LA, bars), leaf length (LL, lines) and specific leaf area (SLA) of RCG in the ambient climate (CON), elevated temperature

(ET), CO2 enrichment (EC) and elevated temperature and CO2 (ETC) chambers combined with high (HW), normal (NW) and

low (LW) water table level during the growing periods (IeVI, see Section 2.2.1), based on 4 replicates in each chamber.

CON EC ETC HW NW LW ET

Periods

II III IV VI V I II III IV VI V I II III IV VI V I II III IV VI V I

0.2

0.4

0.6

0.4

0.8

1.2

1.6

0

0.4

0.8

1.2

1.6

Le

af B

io

ma

ss

(g)

Ste

m B

io

ma

ss

(g)

A

bo

ve

-g

ro

un

d B

io

ma

ss (g

)

Fig. 2 e Mean (SE) leaf, stem and aboveground biomass (per shoot) of RCG in the ambient climate (CON), elevated

temperature (ET), CO2 enrichment (EC) and elevated temperature and CO2 (ETC) chambers combined with high (HW), normal

(NW) and low (LW) water table level during the growing periods (IeVI, see Section 2.2.1), based on 4 replicates in each

chamber.

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2256

Table 3 e Statistical analysis (Tukey’s HSD test) of photosynthetic and leaf development parameters in four climatictreatments in the elevated temperature (ET), CO2 enrichment (EC), and elevated temperature and CO2 (ETC) chamberscompared to ambient climate (CON) chambers during the six growing periods (IeVI, see Section 2.2.1). Significant increasesand decreases at P £ 0.05 level is shown as [ and Y, respectively. The differences betweenwater table levels were tested bycomparing the normal water table level (NW) and low water table level (LW) with high water table level (HW). Significantincreases and decreases at P £ 0.05 level is shown as (D) and (L), respectively. Non-significant differences are shown as ns.Blank grid means control blank.

Parameters Treatment I II III IV V VI

HW NW LW HW NW LW HW NW LW HW NW LW HW NW LW HW NW LW

Psat CON (ns) (�) (ns) (�) (ns) (�) (�) (�) (ns) (�) (ns) (ns)

ET [ [(ns) ns(�) [ ns(�) ns(�) ns ns(�) ns(�) ns ns(�) ns(�) ns ns(�) ns(�) ns ns(ns) ns(�)

EC [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(�) [(�) [ ns ns ns(�)

ETC [ [(�) [(�) [ [(�) [(�) [ [(ns) [(�) [ ns(�) ns(�) [ ns(ns) ns(�) ns ns(ns) ns(�)

gsat CON (ns) (�) (ns) (�) (ns) (�) (ns) (�) (ns) (�) (ns) (�)

ET [ [(ns) [(�) [ [(�) [(�) ns ns(ns) ns(�) ns ns(ns) ns(�) Y Y(ns) Y(�) Y Y(ns) Y(�)

EC ns ns(ns) ns(ns) Y Y(ns) Y(ns) Y Y(ns) Y(ns) Y Y(ns) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�)

ETC ns ns(ns) ns(�) ns Y(�) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�)

LA CON (ns) (ns) (ns) (ns) (ns) (ns) (ns) (ns) (ns) (�) (ns) (�)

ET [ [(ns) [(ns) [ [(ns) [(ns) ns ns(ns) ns(�) ns ns(ns) ns(�) ns ns(ns) ns(�) ns Y(ns) Y(�)

EC [ [(ns) [(ns) [ [(ns) [(ns) [ [(ns) [(ns) ns ns(ns) ns(ns) ns ns(ns) ns(�) ns ns(ns) ns(�)

ETC [ [(ns) ns(ns) [ [(ns) [(ns) [ [(ns) [(�) ns ns(ns) ns(�) ns ns(ns) ns(�) ns ns(ns) ns(�)

SLA CON (ns) (ns) (ns) (ns) (ns) (ns) (ns) (ns) (ns) (�) (ns) (�)

ET ns ns(ns) Y(�) ns ns(ns) Y(�) Y Y(ns) Y(�) ns ns(ns) Y(�) ns ns(ns) Y(�) ns ns(ns) ns(�)

EC ns ns(ns) ns(ns) ns ns(ns) ns(ns) ns Y(ns) Y(�) ns ns(ns) Y(ns) ns Y(ns) ns(ns) ns Y(ns) ns(�)

ETC Y Y(ns) Y(ns) Y Y(ns) Y(ns) Y Y(ns) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�) Y Y(ns) Y(�)

Table 4e Statistical analysis (Tukey’s HSD test) of biomass in four climatic treatments in the elevated temperature (ET), CO2

enrichment (EC), and elevated temperature and CO2 (ETC) chambers compared to ambient climate (CON) chambers duringthe six growing periods (IeVI, see Section 2.2.1). Significant increases and decreases at P £ 0.05 level is shown as [ and Y,respectively. The differences between water table levels were tested by comparing normal water table level (NW) and lowwater table level (LW) to high water table level (HW). Significant increases and decreases at p £ 0.05 level is shown as (D)and (L), respectively. Non-significant differences are shown as ns. Blank grid means control blank.

Parameters Treatment I II III IV V VI

HW NW LW HW NW LW HW NW LW HW NW LW HW NW LW HW NW LW

Leaf biomass CON (ns) (ns) (ns) (ns) (ns) (�) (ns) (�) (ns) (�) (ns) (�)

ET [ [(ns) [(ns) [ [(ns) [(�) [ [(ns) ns(�) ns ns(ns) ns(�) ns ns(ns) Y(�) ns Y(�) Y(�)

EC ns ns(ns) ns(ns) [ ns(ns) [(ns) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�)

ETC [ [(ns) [(ns) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ ns(ns) ns(�) ns ns(ns) ns(�)

Stem biomass CON (ns) (ns) (ns) (�) (ns) (�) (ns) (�) (ns) (�) (ns) (�)

ET [ [(ns) ns(�) [ [(ns) [(�) [ [(ns) [(�) [ ns(ns) ns(�) ns ns(ns) Y(�) ns ns(ns) Y(�)

EC ns ns(ns) ns(�) [ ns(�) ns(�) [ [(ns) [(�) [ [(ns) [(�) ns ns(ns) [(�) ns ns(ns) [(�)

ETC [ [(ns) ns(�) [ [(�) ns(�) [ [(ns) [(�) [ [(ns) [(�) ns ns(ns) ns(�) ns ns(ns) ns(�)

Above-ground

biomass

CON (ns) (ns) (ns) (�) (ns) (�) (ns) (�) (ns) (�) (ns) (�)

ET [ [(ns) ns(�) [ [(ns) [(�) [ [(ns) [(�) ns ns(ns) ns(�) ns ns(ns) Y(�) ns ns(ns) Y(�)

EC ns ns(ns) ns(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�)

ETC [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ [(ns) [(�) [ ns(ns) ns(�)

Coarse root

biomass

CON (ns) (�) (ns) (ns) (þ) (�) (ns) (ns) (þ) (�) (ns) (�)

ET ns ns(ns) ns(ns) ns ns(ns) ns(ns) ns ns(ns) [(ns) ns ns(ns) ns(ns) ns Y(þ) Y(�) ns Y(ns) Y(�)

EC ns ns(ns) ns(ns) [ ns(ns) ns(ns) ns ns(ns) [(ns) [ [(ns) ns(�) [ [(þ) [(ns) [ [(ns) [(�)

ETC ns ns(ns) ns(ns) [ [(þ) ns(�) [ ns(ns) [(ns) ns [(ns) ns(�) ns ns(�) ns(�) ns ns(þ) ns(�)

Fine root

biomass

CON (ns) (ns) (þ) (�) (þ) (�) (�) (�) (þ) (�) (ns) (�)

ET [ [(ns) ns(ns) [ [(ns) [(�) [ [(�) [(�) Y [(þ) [(�) ns ns(þ) Y(�) Y Y(þ) Y(�)

EC [ [(ns) Y(�) [ Y(�) [(�) [ [(þ) [(�) [ [(ns) [(�) [ [(þ) [(�) [ [(ns) [(�)

ETC [ [(þ) ns(ns) [ [(ns) [(�) [ [(þ) [(�) [ [(þ) [(�) [ ns(ns) ns(�) [ [(þ) Y(�)

Below-ground

biomass

CON (ns) (�) (ns) (ns) (þ) (�) (ns) (ns) (þ) (�) (ns) (�)

ET [ [(ns) [(ns) [ [(ns) [(ns) [ [(ns) [(�) ns ns(ns) ns(ns) Y Y(þ) Y(�) Y Y(ns) Y(�)

EC ns ns(ns) ns(ns) [ ns(ns) [(ns) [ [(ns) [(ns) [ [(ns) [(�) [ [(þ) [(ns) [ [(ns) [(�)

ETC [ [(ns) [(ns) [ [(þ) [(�) [ [(ns) [(ns) [ [(ns) [(�) [ [(�) Y(�) [ [(þ) Y(�)

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2 257

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2258

LA and leaf length (LL) increased rapidly and reached its

peak during period IV regardless of climatic treatments and

water levels (Fig. 1). Across the whole growing period and

water table levels, CO2 enrichment significantly (P < 0.05)

increased LA and LL (15% and 31% higher) compared to that

under ambient CO2, regardless of temperature treatments

(Table 3). The maximum value of LA and LL were, on average,

3% lower, 9% higher and 3% higher in the ET, EC and ETC

chambers, respectively, compared to the CON chambers

(Fig. 1). Along with the growing period, SLA showed

a continual downward trend, regardless of climatic treat-

ments and water table levels. Under elevated temperature,

SLA dropped, however, muchmore slowly (P< 0.05) compared

to that under the ambient temperature (Fig. 1, Table 3). SLA

was not significantly modified under CO2 enrichment.

For periods VI and V, the RCG subjected to LW produced

significantly (P < 0.05) smaller leaves and SLA compared with

the well-watered plants, regardless of climatic treatments

(Fig. 1, Table 3).

3.1.3. Biomass accumulationFor biomass growth of RCG, different effects of temperatures,

CO2 and water levels were significant (P < 0.05) through the

whole growing period, except the response of below-ground

biomass to temperature (Table 2). No significant interactions

were identified in any biomass accumulation.

Regardless of climatic treatments and water table levels,

the above-ground biomass (both leaf and stem) showed a clear

increase from period I to period V. While the decrease in leaf

biomass started from the period IV in the elevated tempera-

ture chambers (Fig. 2). At the final harvest period (period VI),

irrespective of water levels, the above-ground biomass was,

on average, 12% lower in the ET chambers compared to the

CON HW NW LW E

II III IV VI V I II III IV V I

0.1

0.2

0.3

0.4

0.4

0.8

1.2

1.6

0

0.4

0.8

1.2

1.6

C

oarse R

oo

t

F

in

e R

oo

t

To

tal R

oo

t

Averag

e in

crem

en

t o

f sh

oo

t B

io

mass (g

)

Fig. 3 e Mean (SE) increment of coarse, fine root and below-grou

elevated temperature (ET), CO2 enrichment (EC) and elevated te

(HW), normal (NW) and low (LW) water table level during the gro

in each chamber.

CON chamber, with 14% and 11% lower in leaf and stem

biomass, respectively. While in the EC and ETC chambers, the

values of leaf and stem biomass were, on average, 12% (16%

and 10% higher in leaf and stem biomass, respectively) and 6%

(9% and 5% higher in leaf and stem biomass, respectively)

higher than that in the CON chambers (Fig. 2, Table 4).

Through the growing season, the increment of fine root

biomass was significantly (P < 0.05) higher than that of coarse

root biomass over different climatic treatments and soil water

table levels. At the end of measurement period, the increment

of total root biomass was, on average, 10% lower in the ET

chambers than that in the CON chambers, irrespective of

water levels (Fig. 3). In the EC chamber, the increment of root

biomass increased on average by 24% compared to the CON

chamber. However, little difference (on average 3% higher) of

the increment was found in the ETC chambers compared to in

the CON chambers (Fig. 3).

The above-ground biomass was significantly (P < 0.05)

lower in LW than that in HW and NW, through all growing

periods and climatic treatments (Fig. 2, Table 4). At the end of

measurement period, the above-ground biomass was, on

average, 19% lower (P < 0.05) in LW compared to HW and NW.

On average, the increment of below-ground biomass respon-

ded to the different water levels significantly (P < 0.05)

regardless of climatic treatments and growing periods (Table

4). In LW, the increment of total root biomass was, on

average, 24% and 28% lower (P< 0.05) than that in HWandNW

at the end ofmeasurement period, respectively (Fig. 3, Table 4).

3.2. RCG model performance

The modeled seasonal canopy net photosynthesis (Pnc),

above-ground biomass (Babove) and increment of below-

EC ETC T

Periods

VI II III IV VI V I II III IV VI V I

nd biomass (per shoot) of RCG in the ambient climate (CON),

mperature and CO2 (ETC) chambers combined with high

wing periods (IeVI, see Section 2.2.1), based on 4 replicates

Table 5e Relative bias, RMSEs and correlation coefficients(R2) between modeled and measured biomass growththrough six growing periods (n [ 6) in the ambientclimate (CON), elevated temperature (ET), CO2 enrichment(EC) and elevated temperature and CO2 (ETC) chamberscombined with high (HW), normal (NW) and low (LW)water table level.

Climatictreatment

Waterlevel

Babove Bbelow

Bias RMSEs R2 Bias RMSEs R2

CON HW 1.32 0.27 0.96 �4.20 0.58 0.90

NW 0.63 0.26 0.97 �0.85 0.21 0.94

LW 2.64 0.19 0.94 �0.33 0.36 0.95

ET HW 3.94 0.31 0.93 �3.78 0.56 0.91

NW 2.37 0.20 0.94 1.93 0.27 0.93

LW 2.30 0.32 0.94 �2.02 0.28 0.92

EC HW �3.71 0.22 0.94 �3.68 0.46 0.91

NW �3.65 0.24 0.94 �1.86 0.31 0.93

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2 259

ground biomass (Bbelow) of RCG are presented in Fig. 4. As

simulated, the values of Pnc in the elevated temperature

chambers were higher than that in the ambient temperature

chambers till mid-July, thereafter, Pnc declined rapidly

towards the end of the growing season. CO2 enrichment

increased Pnc across the growing season, compared to

ambient CO2.

The model realistically simulated the seasonal biomass

growth of RCG under each climatic treatments and water

levels (Fig. 4, Table 5). For Babove and Bbelow, correlation coef-

ficients (1:1 regression) between modeled and measured

biomass growthwere ranged from 0.93 to 0.97 and from 0.88 to

0.95, respectively, regardless of climatic treatments and water

levels. The modeled maximum Bbelow at the later growing

period was slightly higher than the measured values, and the

measured lower Bbelow in HW compared to NW was not

expressed by the model.

LW 2.96 0.22 0.94 �0.77 0.37 0.94

ETC HW �1.20 0.07 0.96 �6.53 1.07 0.88

NW �2.52 0.15 0.94 �4.24 0.52 0.90

LW 1.07 0.09 0.95 �5.73 0.67 0.89

4. Discussion

4.1. Effects of climatic factors over water table levels

We found that elevated temperature stimulated the leaf

development, light-saturated photosynthesis and above-

ground biomass growth during the early growing season. It

was probably because that the developmental stages of RCG

are triggered by thermal temperature [27]. Even quite a small

increase in temperature could also have considerable

cumulative effects on the development of leaves. However,

CON HW NW LW

ET

Da

Sh

oo

t averag

e B

(g)

0.4

0.8

1.2

1.6

0.4

0.8

1.2

1.6

0

0.3

0.6

0.9

1.2

1 Apr. st 1 May st 1 Jun. st 1 Jul. st 1 Aug. st 1 Sep. st 1 Apr. st 1 May st 1 Jun. st 1 Jul. st 1 Aug. st 1 Sep. st 1 st

Sh

oo

t averag

e B

(g)

Sh

oo

t averag

e P

(µm

old

)

Fig. 4 e Modeled (lines) canopy net photosynthesis (Pnc, per sho

ground biomass (Babove, per shoot) and increment of below-groun

(CON), elevated temperature (ET), CO2 enrichment (EC) and elev

high (HW), normal (NW) and low (LW) water table level. Themea

The arrows indicated that Pnc began to be lower in the ET and E

respectively.

the photosynthesis declined earlier under the elevated

temperature (from period IV), accompanied by a lower leaf

area during the later growing season. Therefore, less time

for carbon fixation before seed set resulted in a lower

biomass at the end of growing season. As presented previ-

ously, the temperature elevation accelerated the ontoge-

netic development and caused earlier growth senescence

resulting from the faster accumulation of thermal time for

ETC

te

Apr. 1 May st 1 Jun. st 1 Jul. st 1 Aug. st 1 Sep. st 1 Apr. st 1 May st 1 Jun. st 1 Jul. st 1 Aug. st 1 Sep. st 30 Sep. th

EC

ot) and biomass growth against measured (scatters) above-

d biomass (Bbelow, per shoot) of RCG in the ambient climate

ated temperature and CO2 (ETC) chambers combined with

sured biomass data are the same presented in Figs. 2 and 3.

TC chambers than that in the CON and EC chambers,

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2260

RCG [33]. The changes in leaf size and overall leaf area

duration can have major impacts on total canopy photo-

synthesis and biomass accumulation (even below-ground).

This thermal effect has also been found for other fast-

growing plant species [36].

In this study, CO2 enrichment stimulated the photosyn-

thesis, which was in agreement with the previous studies

[10e12]. The probable reason for this was that Rubisco in

chloroplast is not CO2-saturated at the current atmosphere

CO2 concentration status. Although O2 competes for place in

Rubisco with CO2, Rubisco after all favors CO2. Despite the

fact that CO2 may reduce gsat by up to about 33% of ambient

CO2 values, stomatal apertures are capable of supplying

sufficient CO2 to mesophyll cells (e.g., [37]). The CO2

enrichment also increases water use efficiency by

decreasing water consumption due to a decline in stomatal

conductance [38], by enhancing CO2 fixation, or by the

interaction of both [10,39]. Increased biomass growth was

also related to expanded leaf area under CO2 elevation,

which agreed with [40e42]. In our study, the CO2 enrichment

increased below-ground biomass growth. As presented by

Perez et al. [43], to alleviate the pressure of carbohydrate

accumulation in the leaves and shoots under CO2 enrich-

ment the plants may transport more carbon to the root

pools. Additionally, CO2 enrichment increases both carbon

partitioning to the rapidly cycling carbon pools (below-

ground) and root turnover due to increased demand for

below-ground resources [44].

During the early growing periods, the light-saturated

photosynthesis was highest in the ETC chambers. However,

the rate of carbon uptake in ETC was lower compared to EC

during the later periods. At the end of growing season, ETC did

not significantly enhance the biomass growth compared to

CON. This was in agreement with earlier work [14], in which it

was demonstrated that high temperatures reduce the stimu-

latory effect of CO2 enrichment on the production of crop if

both continue to increase, probably due to the accelerated

senescence and increased autotrophic respiration under

warmer environment.

4.2. Effects of soil water table levels over climatictreatments

Lower leaf area and biomass growth were found in drought-

stressed plants, which were in agreement with previous

studies [45,46]. This was related to decreased photosynthesis

compared to the well-watered plants due to limited stomatal

behavior. In our previous study [32], we found that the chlo-

rophyll fluorescence of RCG in LW was reduced significantly,

probably indicating a deactivation ormetabolic impairment in

photosynthesis center. The decrease in SLA in LWmay also be

related to the fact that drought stress also affects leaf

expansion earlier than photosynthesis [47], and the reduction

of SLA is assumed to be a way to adapt to drought conditions

[48]. The soil water table level effects have also recently been

observed in eddy covariance data in the field experiments for

RCG in Linnansuo peatland [1], i.e. high soil moisture and low

evaporation favored CO2 uptake, but low soil moisture and

high atmospheric stress severely restricted photosynthetic

activity.

4.3. Synergetic effects of climatic treatments and waterlevels

This study showed that the temperature, CO2 enrichment and

soil water table level regimes modified the physiological

responses and biomass growth of RCG. However, the statis-

tical differences on interactive effects on biomass growth

were not significant. Regarding the measured values, elevated

temperature further decreased the plant growth in LW.

Especially at late growing periods, ET produced the lowest

biomass growth in LW. On the other hand, CO2 enrichment

decreased stomatal conductance of RCG in LW, indicating that

plants were prevented from excessive water loss, as pre-

sented by Aranjuelo et al. [37]. Our results also revealed that

CO2 enrichment together with ambient temperature and high

water availability resulted in the highest total biomass

growth.

4.4. Evaluation of RCG model performance againstmeasurements

In line with the measured seasonal dynamics of the light-

saturated photosynthesis of RCG, the modeled canopy photo-

synthesis was also higher in the elevated temperature cham-

bers during the early growing period with a rapid decline

towards the end of summer, compared to ambient tempera-

ture. The model performance was based on specific parame-

terization of the key photosynthetic parameters in response to

seasonal leaf nitrogen within canopy layers [32] and tempera-

ture sum [30], which was various in the ambient and elevated

temperature chambers. Based on the quadratic algorithm, the

higher temperature sum during the early period increased the

photosynthetic parameters in the elevated temperature

chambers. However, the subsequent much higher thermal

accumulationreduced thevaluesofparametersmore than that

in the ambient chambers. In addition, the photosynthesis of

RCG under the CO2 enrichment and varying water conditions

was reasonably well simulated by our model with the accli-

mation of the photosynthetic parameters [30]. Furthermore,

the seasonal pattern of carbon allocation to different organs of

RCG was calibrated for the model [33], resulting in a relatively

high correlation between the modeled seasonal biomass

growth and measured values. But, the model slightly over-

estimated the below-ground biomass growth, and it did not

express a slightly lower increment of below-ground biomass in

HW compared to NW, as measured. One of the probable

reasons was the lack of data on the root mortality. Therefore,

less dry matter is partitioned to the root system when soil

water is excessively provided, as presented by Adiku et al. [49].

5. Conclusions

Through this study, we found that elevated temperature and

water shortage had affected strongly negatively the biomass

accumulation of RCG, due to thermal effects and resource

limitation in regard to the impacts on photosynthesis perfor-

mance. The CO2 enrichment positively enhanced the carbon

uptake and growth of bioenergy crop. This stimulation might

be attributed to higher leaf area and “CO2-fertilzation” effect.

b i om a s s a n d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2 261

However, the stimulatory effect of CO2 enrichment on the

biomass growth of RCG was offset by temperatures elevation.

To mitigate the adverse impact of higher temperature, with

enough high soil moisture on the drained peatlands, RCG

could be expected to be capable to adapt relatively well to the

expected climate change. Moreover, different cultivars would

be tested in order to identify those with characteristics that

would adapt to climate change.

Regarding the model, there must be some uncertainties

and scarcities because of the potential absence of

comprehensive experimental setup and parameterization

on the complex processes of plant physiology and growth.

Nevertheless, the current model for RCG biomass growth

could be much improved for field management and adap-

tive strategy to climate change, if more information were

available.

Acknowledgments

This work was funded through the National Program on

Key Basic Research Project of China (No. 2010CB951204), the

Finland Distinguished Professor Programme (FiDiPro) of the

Academy of Finland (No. 127299-A5060-06) and the National

Natural Science Foundation of China (No. 41201091). The

controlled environment chamber system was covered by the

European Regional Development Fund (ERDF) granted by the

State Provincial Office of Eastern Finland. Matti Lemettinen,

Alpo Hassinen and Risto Ikonen, at Mekrijarvi Research

Station, are thanked for technical assistance. Dr. David Gritten

is greatly thanked for revising the language of this paper.

r e f e r e n c e s

[1] Shurpali NJ, Hyvonen NP, Huttunen JT, Clement RJ,Reichstein M, Nykanen H, et al. Cultivation of a perennialgrass for bioenergy on a boreal organic soil e carbon sink orsource? Global Change Biol Bioenerg 2009;1(1):35e50.

[2] Turunen J, Turunen K, Tolonen S, Tolvanen M, Remes JR,Jungner H. Carbon accumulation in the mineral subsoil ofboreal mires. Global Biogeochem Cy 1999;13(1):71e9.

[3] Maljanen M, Martikainen PJ, Aaltonenal H, Silvola J. Short-term variation in fluxes of carbon dioxide, nitrous oxide andmethane in cultivated and forested organic boreal soils. SoilBiol Biochem 2002;34(5):577e84.

[4] MinkkinenK,KorhonenR,SavolainenT,Laine J.Carbonbalanceandradiative forcingofFinnishpeatlands1900e2100the impactof forestry drainage. Global Change Biol 2002;8(8):785e99.

[5] Doornbosch R, Steenblik R. Biofuels: is the cure worse thanthe disease?, vol. 3. Paris: OECD; 2007. 2007 Sep. p.57 ReportNo. SG/SD/RT.

[6] Carter TR, Jylha K, Perrels A, Fronzek S, Kankaanpaa S.FINADAPT working paper 2: FINADAPT scenarios for the 21stcentury: alternative futures for considering adaptation toclimate change in Finland. Helsinki: Finnish EnvironmentalInstitute Mimeographs; 2005 Nov. p. 42 Report No. 332.

[7] Ruosteenoja K, Jylha K, Tuomenvirta H. FINADAPT workingpaper 15: climate scenarios for FINADAPT studies of climatechange adaptation. Helsinki: Finnish EnvironmentalInstitute Mimeographs; 2005 Dec. p. 32 Report No. 345.

[8] Kellomaki S, Strandman H, Nuutinen T, Peltola H, KorhonenKT, Vaisanen H. FINADAPT working paper 4: adaptation offorest ecosystems, forests and forestry to climate change.Helsinki: Finnish Environment Institute Mimeographs; 2005Dec. p. 44 Report No. 334.

[9] Sage RF, �Santrucek J, Grise DJ. Temperature effects on thephotosynthetic response of C3 plants to long-term CO2

enrichment. Plant Ecol 1995;121(1):67e77.[10] Drake BG, Gonzalez-Meler MA, Long SP. More efficient plants:

a consequence of rising atmospheric CO2? Annu Rev PlantPhysiol Plant Mol Biol 1997;48:609e39.

[11] Ziska LH. Growth temperature can alter the temperaturedependent stimulation of photosynthesis by elevated carbondioxide in Abutilon theophrasti. Physiol Plantarum 2001;111(3):322e8.

[12] Jablonski LM, Wang XZ, Curtis PS. Plant reproduction underelevated CO2 conditions: a meta-analysis of reports on 79crops and wild species. New Phytol 2002;156(1):9e26.

[13] Crafts-Brandner SJ, Salvucci ME. Rubisco activism constrainsthe photosynthetic potential of leaves at high temperatureand CO2. Proc Natl Acad Sci U S A 2000;97(24):13430e5.

[14] Cheng WG, Sakai H, Yagi K, Hasegawa T. Interactions ofelevated [CO2] and night temperature on rice growth andyield. Agr Forest Meteorol 2009;149(1):51e8.

[15] Long SP, Ainsworth EA, Rogers A, Ort DR. Rising atmosphericcarbon dioxide: plants FACE future. Ann Rev Plant Biol 2004;55(1):591e628.

[16] Morison J. Stomatal response to increased CO2

concentration. J Exp Bot 1998;49(9):443e52.[17] Wullschleger SD, Tschaplinski TJ, Norby RJ. Plant water

relations at elevated CO2 e implications for water-limitedenvironments. Plant Cell Environ 2002;25(2):319e31.

[18] Vu JCV, Allen Jr LH, Boote KJ, Bowes G. Effects of elevated CO2

and temperature on photosynthesis and Rubisco in rice andsoybean. Plant Cell Environ 1997;20(1):68e76.

[19] Ohashi Y, Nakayama N, Saneoka H, Fujita K. Effects ofdrought stress on photosynthetic gas exchange, chlorophyllfluorescence and stem diameter of soybean plants. Plant Biol2006;50(1):138e41.

[20] Qaderi MM, Kurepin LV, Reid DM. Growth and physiologicalresponses of canola (Brassica napus) to three components ofglobal climate change: temperature, carbon dioxide anddrought. Physiol Plantarum 2006;128(4):710e21.

[21] Borjigidai A, Hikosaka K, Hirose T. Carbon balance ina monospecific stand of an annual herb Chenopodium albumat an elevated CO2 concentration. Plant Ecol 2009;203(1):33e44.

[22] Hamerlynck EP, Huxman TE, Loik ME, Smith SD. Effects ofextreme high temperature, drought and elevated CO2 onphotosynthesis of the Mojave desert evergreen shrub, Larreatridentate. Plant Ecol 2000;148(2):183e93.

[23] Martınez-Carrasco R, Perez P, Morcuende R. Interactiveeffects of elevated CO2, temperature and nitrogen onphotosynthesis of wheat grown under temperature gradienttunnels. Environ Exp Bot 2005;54(1):49e59.

[24] Shurpali NJ, Hyvonen NP, Huttunen JT, Biasi C, Nykanen H,Pekkarinen N, et al. Bare soil and reed canary grassecosystem respiration in peat extraction sites in easternFinland. Tellus B 2008;60(2):200e9.

[25] Zhou X, Ge ZM, Kellomaki S, Wang KY, Peltola H,Martikainen PJ, et al. Multi-objective environment chambersystem for studying plant responses to climate change.Photosynthtica 2012;50(1):24e34.

[26] Myllys M, Sinkkonen M. The area and distribution ofcultivated organic soils in Finland. Suo 2004;55(3e4):53e60.

[27] Sahramaa M, Jauhiainen L. Characterization of developmentand stem elongation of reed canary grass under northernconditions. Ind Crop Prod 2003;18(2):155e69.

b i om a s s an d b i o e n e r g y 4 6 ( 2 0 1 2 ) 2 5 1e2 6 2262

[28] Lewandowski I, Scurlock JMO, Lindvall E, Christou M. Thedevelopment and current status of perennial rhizomatousgrasses as energy crops in the US and Europe. BiomassBioenerg 2003;25(4):335e61.

[29] Farquhar GD, von Caemmerer S, Berry JA. A biochemicalmodel of photosynthetic CO2 assimilation in leaves of C3

species. Planta 1980;149(1):78e90.[30] Ge ZM, Zhou X, Kellomaki S, Zhang C, Peltola H,

MartikainenPJ, et al. Acclimationofphotosynthesis inaborealgrass (Phalaris arundinaceaL.) underdifferent temperature,CO2

and soil water regimes. Photosynthetica 2012;50(1):141e51.[31] Kellomaki S,WangKY. Effects of long-termCO2 and temperature

elevationoncrownnitrogendistributionanddailyphotosyntheticperformance of Scats pine. Forest Ecol Manag 1997;99(3):309e26.

[32] Ge ZM, Zhou X, Kellomaki S, Wang KY, Peltola H,Martikainen PJ. Responses of leaf photosynthesis, pigmentsand chlorophyll fluorescence within canopy position ina boreal grass (Phalaris arundinacea L.) to elevatedtemperature and CO2 under varying water regimes.Photosynthetica 2011;49(2):172e84.

[33] Ge ZM, Zhou X, Biasi C, Kellomaki S, Wang KY, Peltola H,et al. Carbon assimilation and allocation (13C labeling) ina boreal perennial grass (Phalaris arundinacea) subjected toelevated temperature and CO2 through a growing season.Environ Exp Bot 2012;75(1):150e8.

[34] Liu HS, Li FM. Photosynthesis, root respiration, and grainyield of spring wheat in response to surface soil drying. PlantGrowth Regul 2005;45(2):149e54.

[35] Field C, Mooney HA. The photosynthesis-nitrogenrelationship in wild plants. In: Givinsh TJ, editor. On theeconomy of form and function. Cambridge: CambridgeUniversity Press; 1986.

[36] Sanders GE, Turnbull ND, Clark AG, Colls JJ. The growth anddevelopment of Vicia faba in filtered and unfiltered open-topchambers. New Phytol 1990;116(1):67e78.

[37] Aranjuelo I, Perez P, Hernandez L, Martinez-Carrasco R,Sanchez-Diaz M. The response of nodulated alfalfa to watersupply, temperature and elevated CO2: photosyntheticdown-regulation. Physiol Plantarum 2005;123(1):348e58.

[38] Mott KA. Sensing of atmospheric CO2 by plants. Plant CellEnviron 1990;13(7):731e7.

[39] SaxeH, EllsworthDS,Heath J. Treeand forest functioning inanenriched CO2 atmosphere. New Phytol 1998;139(3):395e436.

[40] Vargas LA, Andersen MN, Jensen CR, Jørgensen U. Estimationof leaf area index, light interception and biomassaccumulation of Miscanthus sinensis ‘Goliath’ from radiationmeasurements. Biomass Bioenerg 2002;22(1):1e14.

[41] Dermody O, Long SP, DeLucia EH. How does elevated CO2 orozone affect the leaf-area index of soybean when appliedindependently? New Phytol 2006;169(1):145e55.

[42] Lawlor DW. Photosynthesis, productivity and environment. JExp Bot 1995;46(S):1449e61.

[43] Perez P, Morcuende R, Martın del Molino I, Martınez-Carrasco R. Diurnal changes of Rubisco in response toelevated CO2, temperature and nitrogen in wheat grownunder temperature gradient tunnels. Environ Exp Bot 2005;53(1):13e27.

[44] Niklaus PA, Glockler E, Siedwolf RC, Korner C. Carbonallocation in calcareous grassland under elevated CO2:a combined 13C pulse-labelling/soil physical fractionationstudy. Funct Ecol 2001;15(1):43e50.

[45] Flexas J, Medrano H. Drought-inhibition of photosynthesis inC3 plants: stomatal and non-stomatal limitations revisited.Ann Bot 2002;89(2):183e9.

[46] Sinclair TR, Muchow RC. System analysis of plant traits toincrease grain yield on limited water supplies. Agron J 2001;93(2):263e70.

[47] Tardieu F, Granier C, Muller B. Modelling leaf expansion ina fluctuating environment: are changes in specific leaf areaa consequence of changes in expansion rate? New Phytol1999;143(1):33e43.

[48] Xu ZZ, Zhou GS. Combined effects of water stress and hightemperature on photosynthesis, nitrogen metabolism andlipid peroxidation of a perennial grass Leymus chinensis.Planta 2006;224(5):1080e90.

[49] Adiku SGK, Braddock RD, Rose CW. Modelling the effect ofvarying soil water on root growth dynamics of annual crops.Plant Soil 1996;185(1):125e35.