Annual cycle of CO2 exchange over a reed (Phragmites australis) wetland in Northeast China

Aquatic Botany 91 (2009) 91–98

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Annual cycle of CO2 exchange over a reed (Phragmites australis) wetland in Northeast China Li Zhou a,c, Guangsheng Zhou a,b,*, Qingyu Jia d a

State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, 20 Nanxincun, Xiangshan, Haidian District, Beijing 100093, China Chinese Academy of Meteorological Sciences, China Meteorological Administration, 46 Zhongguancun South Street, Haidian District, Beijing 100081, China c Graduate School of the Chinese Academy of Sciences, 19A Yuquan Road, Shijingshan District, Beijing 100049, China d Institute of Atmospheric Environment, China Meteorological Administration, 66 Wenhua Road, Shenhe District, Shenyang 110016, China b

A R T I C L E I N F O

A B S T R A C T

Article history: Received 20 February 2008 Received in revised form 16 February 2009 Accepted 10 March 2009 Available online 16 March 2009

Net ecosystem exchange of CO2 (NEE) was measured during 2005 using the eddy covariance (EC) technique over a reed (Phragmites australis (Cav.) Trin. ex Steud.) wetland in Northeast China (1218540 E, 418080 N). Diurnal NEE patterns varied markedly among months. Outside the growing season, NEE lacked a diurnal pattern and it fluctuated above zero with an average value of 0.07 mg CO2 m2 s1 resulting from soil microbial activity. During the growing season, NEE showed a distinct V-like diel course, and the mean daily NEE was 7.48  2.74 g CO2 m2 day1, ranging from 13.58 g CO2 m2 day1 (July) to 0.10 g CO2 m2 day1 (October). An annual cycle was also apparent, with CO2 uptake increasing rapidly in May, peaking in July, and decreasing from August. Monthly cumulative NEE ranged from 115  24 g C m2 month1 (the reed wetland was a CO2 sink) in July to 75  16 g C m2 month1 (CO2 source) in November. The annual CO2 balance suggests a net uptake of 65  14 g C m2 year1, mainly due to the gains in June and July. Cumulative CO2 emission during the non-growing season was 327 g C m2, much greater than the absolute value of the annual CO2 balance, which proves the importance of the wintertime CO2 efflux at the study site. The ratio of ecosystem respiration (Reco) to gross primary productivity (GPP) for this reed ecosystem was 0.95, indicating that 95% of plant assimilation was consumed by the reed plant or supported the activities of heterotrophs in the soil. Daytime NEE values during the growing season were closely related to photosynthetically active radiation (PAR) (r2 > 0.63, p < 0.01). Both maximum ecosystem photosynthesis rate (Amax) and apparent quantum yield (a) were season-dependent, and reached their peak values in July (1.28  0.11 mg CO2 m2 s1, 0.098  0.027 mmol CO2 mmol1 photon, respectively), corresponding to the observed maximum NEE in July. Ecosystem respiration (Reco) relied on temperature and soil water content, and the mean value of Q10 was about 2.4 with monthly variation ranging from 1.8 to 4.1 during 2005. Annual methane emission from this reed ecosystem was estimated to be about 3 g C m2 year1, and about 5% of the net carbon fixed by the reed wetland was released to the atmosphere as CH4. ß 2009 Elsevier B.V. All rights reserved.

Keywords: Net ecosystem CO2 exchange Eddy covariance Reed Wetland Carbon balance

1. Introduction Concern over global climate change has stimulated much interest in investigating the processes and controlling mechanisms of CO2 transfer between atmosphere and vegetation in forest, grassland and agriculture ecosystems, identifying present and potential carbon sinks or sources, and evaluating the trends of carbon budgets in the future (Mooney et al., 1991; Ryan, 1991; Schimel, 1995; Malhi et al., 1999; Brix et al., 2001; Dunn et al., 2007). Although relatively small in area compared to forest or

* Corresponding author. Tel.: +86 10 82595962; fax: +86 10 82595962. E-mail address: [email protected] (G. Zhou). 0304-3770/$ – see front matter ß 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.aquabot.2009.03.002

grassland ecosystems, the organic carbon storage in wetland ecosystems is estimated to cover about 15% of the terrestrial organic carbon storage in the earth (Sabine et al., 2004), and its annual CO2 budget varied significantly from 180 g C m2 (carbon sink) to 97 g C m2 (carbon source) depending on different environments and vegetation types (Nieveen et al., 1998; Trumbore et al., 1999; Waddington and Roulet, 2000; Roehm and Roulet, 2003; Sottocornola and Kiely, 2005; Glenn et al., 2006; Hirota et al., 2006; Lloyd, 2006). Thus, it is important to investigate the carbon budget and its controlling mechanisms over different wetland ecosystems for accurately evaluating global carbon budgets and scientifically managing wetland ecosystems. In recent years, though there were some studies on carbon budget for wetland ecosystems, most of them were conducted over

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northern peatlands. Reed wetlands are the most widespread and productive wetlands in the world (Clevering and Lissner, 1999; Brix et al., 2001), and play important roles in wetland carbon budgets. There have been lots of studies that have proved reed wetlands as a source of atmospheric CH4 (Kim et al., 1999; Brix et al., 2001; Huang et al., 2003), however, there have been relatively few direct measurement of the CO2 exchange between the atmosphere and reed wetland ecosystem, and little evidence is available for understanding CO2 exchange and its relation to environmental control for reed wetland ecosystem, especially for its winter CO2 efflux. Here, we will report on a continuous eddy covariance measurement covering a whole year of CO2 flux over a midlatitude reed (Phragmites australis (Cav.) Trin. ex Steud.) wetland. The eddy covariance technique can provide direct measurement of net ecosystem exchange of CO2 (NEE) over wetland ecosystems (Falge et al., 2002; Baldocchi, 2003; Friend et al., 2007) for a better understanding of wetland ecosystem carbon cycle and how CO2 flux responds to the driving forces (Nieveen et al., 1998; Baldocchi, 2003; Friend et al., 2007). The objectives of this study are (1) to characterize diurnal and seasonal variations of NEE, and (2) to analyze the effects of environmental factors on NEE. 2. Data and methods 2.1. Site description The study was carried out at the Panjin Wetland Ecosystem Research Station (1218540 E, 418080 N, 7 m. a.s.l.), which belongs to the Institute of Atmospheric Environment, China Meteorological Administration (CMA), Shenyang. This station is located about 15 km west of Panjin city in Liaoning Province. This region belongs to freshwater tidal wetland, and the tidal movement is irregular and semidiurnal, with maximum and average tide heights of 4.0–5.5 m and 1.9–2.7 m, respectively, in terms of the observation data from Shuangtaihekou National Nature Reserve Administration. It experiences a continental, semihumid monsoon climate of the warm temperate zone, and has strongly seasonal variation with mean annual temperature of 8.6 8C, mean annual precipitation of 631 mm, and a frost-free period of 171 days. Mean growing season (May–October) temperature is approximately 19.9 8C with 560 mm of precipitation (Zhou et al., 2006). The terrain is quite flat, with relatively homogeneous vegetation dominated by P. australis (Cav.) Trin. ex Steud., with an area of 900 km2, which is the largest reed field in the world (Zhou et al., 2006). The soil type is silty clay, and its organic carbon content ranges from 2.2% to 2.5% (Lv et al., 2006). According to the phenological records from the Panjin Wetland Ecosystem Research Station, reed growth started around 20 April and stopped around 30 October in 2005. The temperature from March to April is the trigger for plant green up, and precipitation during the growing season controls its decline (Li et al., 2006). In July (the peak growing stage), 2005, shoot density of reed stand was about 45 no. m2. Its above-ground and below-ground biomasses were 1459 g DM m2 and 1486 g DM m2, respectively. The average height of reed canopy was about 1 m in mid-May, and reached a maximum of 3 m in late July 2005 (Jia et al., 2006). Leaf area index (total LAI, measured by canopy destructively sampled method) was 0.4 in mid-May, reached a maximum of about 4 in late July, and then declined (Jia et al., 2008). 2.2. NEE and meteorological factors NEE and meteorological factors over the reed (P. australis (Cav.) Trin. ex Steud.) wetland have been measured by a set of open-path eddy covariance (EC) instrument and a set of meteorological

instruments (the design of the instrumentation was following Baldocchi et al., 1996), respectively, since May 26, 2004. These instruments are located in the center of the reed marsh. The fetch of eddy covariance measurement is about 300 m in the predominant upwind direction (southwest). The sensors of EC flux were mounted at 4.5 m, including a fast response infrared gas analyzer (Li-7500, LI-COR Inc., Lincoln, NE, USA) for measuring instantaneous fluctuations of CO2 and H2O molar densities, and a three-dimensional ultrasonic anemometer (CSAT3, Campbell Scientific Inc., USA) for simultaneously measuring the fluctuations of vertical and horizontal wind speeds, wind direction, as well as virtual temperature. Both the anemometer and the gas analyzer were orientated away from the tower towards the direction of prevailing wind (southwest). These signals were sampled at 10 Hz, and the data were stored in a data logger (CR5000, Campbell Scientific Inc., USA). Mean scalar fluxes including sensible heat flux, latent heat flux and carbon dioxide flux were computed online every 30 min and recorded by the data logger also. Photosynthetically active radiation (PAR) was measured with a quantum sensor (LI-190Sb, LI-COR Inc., Lincoln, NE, USA) at a height of 6.5 m. Net radiation (Rn) was measured with a fourcomponent net radiometer (CNR1, Kipp and Zonen. Corp., Delft, Holland) at a height of 5 m. Air temperature and relative humidity were measured with probes (HMP45C, Vaisala, Helsinki, Finland) at 4 m and 6.5 m heights, respectively. At these two levels, wind speed was monitored with cup anemometers (014A, Campbell Scientific Inc., UT, USA). Soil temperature profile was measured with thermistors (107L, Campbell Scientific Inc., UT, USA) at 5 cm, 10 cm, 15 cm, 20 cm, 40 cm, and 80 cm depths. Soil water content (SWC) was measured at a depth of 5 cm by time domain reflectometry probes (CS616, Campbell Scientific Inc., USA). Precipitation was measured with a tipping bucket rain gauge (52203, RM Young Inc., Traverse City, MI, USA). Signals from all sensors as mentioned above were recorded by a data logger (CR23X, Campbell Scientific Inc., UT, USA) with a sampling frequency of 30 min. 2.3. Flux data processing Usually, due to system failures or data rejection, the average EC data coverage from Fluxnet (a worldwide network of stations measuring ecosystem fluxes using the eddy covariance method) sites during one year ranged from 50% to 83% (Falge et al., 2001). Online computed half-hourly CO2 flux data recorded by EC data logger and meteorological factors from meteorological tower over the reed wetland were used in this study. The half-hourly CO2 flux data were calculated as the mean covariance of vertical wind velocity and CO2 concentration scalar fluctuations (Baldocchi, 2003). The corrections (Webb et al., 1980) for the density effect due to heat and water vapour transfers and the traditional coordinate rotations (Wilczak et al., 2001) for forcing mean vertical velocity to zero were performed on half-hourly CO2 fluxes. Moreover, the following filtering algorithms were applied to half-hourly flux data for reducing the uncertainty of the data. Firstly, the flux data during precipitation were excluded. Secondly, the significant outliers (jNEEj > 3.0 mg CO2 m2 s1) were rejected (Zhang et al., 2006). Thirdly, the flux data under weak turbulence (friction velocity, U* < 0.15 m s1, determined by average value test method (Zhu et al., 2006)) were also excluded. Finally, the available flux data were more than 60% of EC flux observation data. In order to fill gaps resulting from the sensor failures or unsuitable weather conditions, the data were divided into two groups based on the length of the gap: small gaps (less than 2 h) and large gaps (more than 2 h). Small gaps were filled by linear interpolation. Large gaps were again pooled into two subgroups: (1) gaps in daytime flux data during the growing season (daytime

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defined as incident PAR > 0 mmol m2 s1), and (2) gaps in daytime flux data outside the growing season and nighttime flux data for the whole year. The mean diurnal variation approach was used for filling the former (window size, 15 days), and nonlinear regression methods for the latter (Falge et al., 2001). 2.4. Partitioning NEE into respiration and photosynthesis NEE could be partitioned into gross photosynthetic production (GPP) and ecosystem respiration (Reco) by the following equation: NEE ¼ GPP þ Reco

(1)

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photosynthetic capacity and to determine the shape of the light response curve (Ruimy et al., 1995; Frolking et al., 1998; Zhang et al., 2006). These two parameters could be derived from the relationship between NEE and PAR. For this purpose, mean diurnal patterns (bin-averages by time of day, for 15 days) of NEE and PAR were calculated. Based on these mean diurnal data, values of ecosystem Amax and a for each month during the growing season were estimated using the Michaelis–Menten model (Ruimy et al., 1995): F c ¼ Reco 

a  PAR  Amax a  PAR þ Amax

(3)

where negative and positive values of CO2 fluxes respectively represent ecosystem CO2 uptake and CO2 emission. Usually, Reco could be obtained by the relationship between Reco and soil temperature at 5 cm (Ts), in terms of the data measured directly by EC tower during nighttime under strong turbulence conditions (U* > 0.15 m s1). The relationship between Reco and soil temperature at 5 cm (Ts) could be estimated based on the Van’t Hoff equation (Waddington and Roulet, 2000):

where Fc is the net ecosystem exchange of CO2 (mg CO2 m2 s1), a is the apparent quantum yield (mmol CO2 mmol1 photon), Amax is the maximum ecosystem photosynthesis rate (mg CO2 m2 s1) at the saturated light level, Reco is the ecosystem respiration (mg CO2 m2 s1) during daytime.

Reco ¼ RT ref eBðT S T ref Þ

3.1. Meteorological conditions in 2005

(2)

where RT ref is the ecosystem respiration rate at reference temperature (Tref, 10 8C in this paper), B is a fitted site-specific parameter (B = ln(Q10)/10), Q10, an indicator of temperature sensitivity, is defined as the increased coefficient for Reco when temperature increases by 10 8C (Xu and Qi, 2001). Based on the measured NEE, GPP would be calculated by Eq. (1). Daily and monthly values of GPP and Reco were summed from the half-hourly data. 2.5. Estimation of ecosystem photosynthetic parameters The maximum ecosystem photosynthesis rate (Amax) and apparent quantum yield (a) are used as tokens of plant

3. Results

The site experienced strong seasonal variation in air temperature, with the warmest monthly mean temperature of 24.5 8C in July and the coldest value of 9.1 8C in January (Fig. 1a). Compared to long term average values (from 1971 to 2000), 2005 was slightly cooler than the average by 0.3 8C. Substantial temperature deviations from the average occurred in February, November, and December (2 8C, 3 8C and 3 8C, respectively). During the growing season (May–October) in 2005, it was warmer by 0.2 8C than the average (Fig. 1a). Monthly precipitation also showed large seasonal variation, with most rainfall in July and August (Fig. 1b). In April, May and August 2005, the precipitation was much higher than the average, while it was lower in July and September.

Fig. 1. Comparison of (a) air temperature (T) and (b) precipitation (PPT) in 2005 with long-term (1971–2000) average; (c) monthly photosynthetically active radiation (PAR) and (d) monthly average volumetric soil water content (SWC) in 2005.

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Fig. 2. Diurnal courses of CO2 flux and environmental factors for spring (May 6, the early growing season), summer (July 18, the peak growing season), and winter (December 5, the non-growing season) in 2005. (a) Net ecosystem exchange of CO2 (NEE); (b) soil water content (SWC); values of SWC on December 5 is not shown because soil was frozen for this period); (c) photosynthetically active radiation (PAR); (d) air temperature and soil temperature (T), open symbols for air temperature and filled symbols for soil temperature.

The lowest monthly PAR was observed in January and December with a value of 420 mol m2 month1, while the maximum PAR reached about 1170 mol m2 month1 in May (Fig. 1c). Soil water content increased from March (7%) to April (12%), reached the maximum (46%) in August (Fig. 1d), and decreased gradually to 8% in December. 3.2. Diurnal and seasonal variations in NEE Diurnal courses of NEE over the reed ecosystem for typical days during spring (May 6), summer (July 18) and winter (December 5) were distinctly seasonal (Fig. 2). Daily NEE was very close to night NEE on December 5, and the reed wetland acted as a small carbon source with 2.6 g CO2 m2 day1. The maximum NEE of 0.06 mg CO2 m2 s1 appeared around 14:00 h, while air temperature also reached its daily peak value (Fig. 2a and d). Diurnal NEE courses on May 6 and July 18 indicated their characteristics during

the early and the peak growing seasons, respectively. Diurnal NEE pattern of the reed ecosystem on both May 6 and July 18 showed similar trends with ‘V’ curve. The reed wetland released CO2 to atmosphere during night at a rate of 0.1 and 0.18 mg CO2 m2 s1 for the early and the peak growing seasons, respectively. At about 6:00 h, NEE became a net CO2 uptake (negative value), then increased (more negative) as PAR increased (Fig. 2a and c) corresponding to CO2 assimilation by the plants, and reached the peak values around 12:00 h with 0.51 mg CO2 m2 s1 and 1.24 mg CO2 m2 s1 on May 6 and July 18, respectively. The NEE decreased from about 12:00 h, and turned to CO2 source (positive value) around 17:30–18:00 h. The daily NEE courses on May 6, and July 18 were obviously affected by contemporaries PAR variations (Fig. 2a and c). Daily net gains of CO2 were 8.5 g CO2 m2 day1 and 26.7 g CO2 m2 day1 on May 6 and July 18, respectively. There were large seasonal variations in NEE. During the nongrowing season (from January to March, November and December)

Fig. 3. Monthly averaged diurnal variations of NEE in 2005: (a) non-growing season, (b) growing season. Monthly averaged diurnal patterns resulted from bin-averages by time of day.

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Fig. 4. Seasonal variation of monthly cumulative CO2 fluxes.

in 2005, diurnal NEE pattern in the reed ecosystem was almost absent, it was mostly due to the colder soil temperature and its little fluctuation (Fig. 2a and d), and NEE fluctuated above zero with an average value of 0.07 mg CO2 m2 s1 (Fig. 3a) probably resulting from soil microbial activity. The reed wetland was a source for atmosphere CO2 during the whole non-growing season (Fig. 4). A small CO2 assimilation started in late April. Net uptake of CO2 was observed from 10:30 h to 15:00 h due to the gemmation of reed (Fig. 3a). Then, both photosynthetic and respiratory activities increased into July, with a rapid change in photosynthesis observed from April to May (Fig. 4). Diurnal NEE showed a distinct V-like diel course for the growing season (from May to October) (Fig. 3b). The mean daily cumulative NEE was 7.48  2.74 g CO2 m2 day1 with large fluctuation from 13.58 g CO2 m2 day1 (July) to 0.10 g CO2 m2 day1 (October). From May to October, average daytime uptake of CO2 by the reed vegetation (6.8 g C m2 day1) was larger than the average respiratory losses of CO2 (4.7 g C m2 day1), the reed wetland behaved as a sink of CO2 (Fig. 4). The monthly cumulative NEE in 2005 ranged from 115  24 g C m2 month1 in July to 75  16 g C m2 month1 in November. Summing the half-hourly NEE data provided a rough estimation of the annual carbon budget over the reed ecosystem as 65  14 g C m2 year1 in 2005, which resulted from a CO2 uptake of 392 g C m2 during the growing season and a CO2 emission of 327 g C m2 outside the growing season. Thus, the reed wetland ecosystem behaved as a CO2 sink in 2005 and the CO2 emission outside the growing season was about 83% of the CO2 uptake

Fig. 5. Relationship between daytime NEE and PAR during the growing season in 2005. The daytime NEE data were averaged with PAR bin of a width of 100 mmol m2 s1. Bars denote standard errors, n > 27.

during the growing season, which showed the importance of the wintertime CO2 efflux for the annual CO2 budget of this reed ecosystem. The ratio of Reco to GPP could be used to evaluate the relative contribution of carbon exchange processes (respiration and photosynthesis) to total annual exchange (Falge et al., 2002). In 2005, it was 0.95 for the reed ecosystem on yearly scale, which was within the range (0.55–1.2) presented by Law et al. (2002), but higher than the average value of 0.83, indicating that 95% of plant assimilation was consumed by the reed plant or supported the activities of heterotrophs in the soil. The ratio of Reco to GPP in the reed ecosystem was close to an extreme-rich fen in northern Alberta (0.9) (Glenn et al., 2006). 3.3. Responses of daytime NEE to PAR The daytime pattern of NEE was closely related to the radiation regime. The magnitude of daytime NEE increased (more negative) with increasing PAR (Fig. 5), and the response of daytime NEE to PAR could be described by the Michaelis–Menten model well (r2 > 0.63, p < 0.01, details in Table 1). The seasonal variations of parameters estimated from the model, Amax and a, could be represented as single peak (in July) curves, with the highest value of 1.28 mg CO2 m2 s1 and 0.098 mmol CO2 mmol1 photon for

Fig. 6. Effects of air temperature (Tair) on maximum ecosystem photosynthesis rate (Amax) and apparent quantum yield (a). Dots show monthly mean air temperature, contemporary Amax and a, respectively.

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Fig. 7. Relationship between ecosystem respiration (Reco) and soil temperature at 5 cm during the growing season in 2005.

Table 1 Nonlinear parameter estimates for NEE–PAR rectangular hyperbolic response curves. Month

Amax (mg CO2 m2 s1)

a (mmol CO2 mmol1 photon)

n

r2

May June July August September October

0.66  0.07 0.91  0.08 1.28  0.11 0.86  0.09 0.79  0.08 0.75  0.07

0.036  0.012 0.075  0.017 0.098  0.027 0.080  0.021 0.055  0.015 0.046  0.016

58 60 60 56 50 46

0.63 0.73 0.70 0.67 0.75 0.71

Values of Amax and a represent the estimate  S. E. Ranges of r2 at p < 0.01 are applicable for all parameters.

Amax and a, respectively (Table 1). Both seasonal variations of Amax and a were influenced by air temperature (Fig. 6). The relationships between Amax, a and air temperature could be represented by exponential functions (r2 > 0.6, p < 0.1; details in Fig. 6).

Fig. 8. Relationship between ecosystem respiration (Reco) and soil temperature at the depth of 5 cm outside the growing season in 2005, and the black line is the best fit exponential relationship.

3.4. Responses of nighttime NEE to soil temperature and soil water content A specific response curve for each month during the growing season in 2005 was given in Fig. 7, in order to avoid the effects of plant phenology on the NEE-temperature function (Xu and Qi, 2001; Zhao et al., 2006). Except for July and August, the relationships between nighttime NEE (Reco) and soil temperature at 5 cm could be described by exponential function (Eq. (2)) very well (r2 ranged from 0.42 to 0.69). Q10 (resulted from the equation of B = ln(Q10)/10) of the reed ecosystem varied considerably from 1.82 to 4.06 during the growing season. Q10 values were higher in the early growing season (May), then, it dropped to 2.01, 1.82 and 1.82 in June, September and October, respectively. Outside the growing season, there was also a significant exponential relationship between Reco and soil temperature at 5 cm, and soil temperature accounted for approximately 54% of variations in Reco (Fig. 8). Q10 was estimated to be 2.23, and it was higher than those during the growing season except for May. On annual scale, the mean value of Q10 was 2.38 in 2005.

Fig. 9. Relationship between ecosystem respiration (Reco) and soil water content (SWC) during the non-frozen period in 2005. Black line is the linear fit. Data show daily mean values.

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To assess the effect of soil water content on ecosystem respiration, the nighttime averaged NEE was plotted against the nighttime averaged soil water content for the non-frozen period in 2005 (Fig. 9). The CO2 release rate seemed to increase as soil water content increased. The linear relationship could be described by: Reco ¼ 0:005  SWC þ 0:061

(4)

where SWC is soil water content (%). The results showed that soil water content could explain 50% of the variation of nighttime ecosystem respiration (p < 0.001). 4. Discussion 4.1. Magnitude of CO2 flux compared with other wetland ecosystems During the investigated year, the reed wetland in this study was a net CO2 sink of 65 g C m2 year1. Wetland ecosystems investigated by other researchers also showed a net uptake of CO2, ranging from 41 g C m2 year1 for a Scottish peatland ecosystem (Beverland et al., 1996), 76 g C m2 year1 for a northern bog (Roehm and Roulet, 2003), to 144 g C m2 year1 for a moderately rich fen in northern Alberta (Syed et al., 2006). On the other hand, a Netherlands peat bog acted as a source of CO2 probably resulting from drainage, and the annual CO2 exchange of this bog was estimated to be 97 g C m2 year1 (Nieveen et al., 1998). Annual CO2 budget at the study site was within the range of previous studies. The seasonal maximum daily amplitude in the NEE values in this study varied from 0.87 mg CO2 m2 s1 at midday to a minimum of 0.24 mg CO2 m2 s1 at night in July. These values are substantially larger than those reported for a raised bog in North Netherlands where fluxes ranged from 0.5 mg CO2 m2 s1 for daytime CO2 uptake to 0.05 mg CO2 m2 s1 for nocturnal CO2 release (Nieveen et al., 1998), and for a peatlands in western Canada where NEE values ranged from 0.22 mg CO2 m2 s1 in the day to 0.09 mg CO2 m2 s1 at night (Glenn et al., 2006) in July. The difference among those wetland ecosystems might result from different LAI (1.7 for the bog in Netherlands, 1.52 for the peatlands in Canada, and 4 for the reed wetland in this study). During the growing season, the mean daily NEE was 7.48 g CO2 m2 day1, which is similar to that from a Sphagnum-dominated bogs (6 g CO2 m2 day1) in Eurosiberian boreal forest from June to early October (Schulze et al., 1999). Outside the growing season, the mean value of NEE of the study site was 0.07 mg CO2 m2 s1. It was much higher than those reported for a northern bog (0.01 mg CO2 m2 s1, Roehm and Roulet, 2003) and a disturbed peat bog in North Netherlands (0.02 mg CO2 m2 s1, Nieveen et al., 1998). The CO2 emission outside the growing season comprised about 83% of the CO2 uptake during the growing season, and it can have a significant effect on annual net CO2 balances. If the winter effluxes from the ecosystem were ignored, the annual CO2 budget would be overestimated by 5 times. Other studies also have noted the importance of wintertime CO2 effluxes for annual CO2 budgets in peatland ecosystem (Lafleur et al., 2001; Aurela et al., 2002; Roehm and Roulet, 2003). 4.2. Ecosystem carbon uptake potential While most wetlands act as net CO2 sinks, the anaerobic decomposition allows them to act as net methane sources (Brix et al., 2001). Although the flux of methane was not measured in this study, we tried to estimate (roughly) methane flux based on the results from previous studies. According to Huang et al. (2003), the average emission rate of CH4 was 0.52 mg CH4 m2 h1 during the growing season. Kim et al. (1999) estimated that about

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20% of total methane emission occurred during the non-growing season. Thus, annual methane emission from this reed ecosystem was estimated to be about 3276 mg CH4 m2 h1, i.e., about 3 g C m2 year1. The carbon balance of the study site between net CO2 assimilation and CH4 emission was a sink of 62 g C m2 in 2005. On an annual basis, about 5% of the net carbon fixed by the wetlands was released to the atmosphere as CH4. 4.3. Controls on NEE Daytime variation in NEE was strongly affected by the diurnal course of PAR. Parameters (Amax and a) estimated from the Michaelis–Menten model between NEE and PAR showed marked trends over the growing season. Variation of parameters among different growth periods could be caused by changes in plant growth, and environmental conditions. At the study site, temperature could explain 60–80% of the seasonal variation of Amax and a (Fig. 6). Temperature restricted ecosystem photosynthesis via its influence on the activity of photosynthetic system (Lafleur et al., 2001; Zhang et al., 2006). Ecosystem photosynthetic capacity is affected not only by environmental factors, but also by plant characteristics, such as physiological activity, leaf thickness, leaf area index (LAI) and canopy development stage (Frolking et al., 1998; Moreno-Sotomayor et al., 2002). For this reed ecosystem, its LAI reached the maximum value about 4 in July. Correspondingly, the ecosystem photosynthetic capacity (Amax and a) reached their peak values. It suggests that it should be necessary for ecosystem carbon model to consider the seasonal dynamics of photosynthesis capacity parameters in order to get the accurate evaluation of carbon budget. As anticipated, our data showed an obvious temperature dependence of ecosystem respiration, and Q10 values derived for this reed wetland fell within the considerable range in Q10 for wetland ecosystems reported in the literature, 1.6–4.8 (Nieveen et al., 1998; Bubier et al., 2003; Lafleur et al., 2005). In 2005, the mean value of Q10 (2.38) was very close to the global median of 2.4 reported by Raich and Schlesinger (1992). Generally, values of Q10 for the reed wetland during the growing season were smaller than values outside the growing season (Figs. 7 and 8), which was due to higher temperature during the growing season. This agreed with the result of the previous study that Q10 and soil temperature were negatively correlated (Xu and Qi, 2001). But, in the early growing season (May), Q10 was higher even than value in the non-growing season, the possible reason might be the rapid recovery of root and rhizosphere respirations of reed wetland during this stage. Previous study for a wetland on the Qinghai-Tibetan plateau also showed a similar seasonal trend of Q10 (Hirota et al., 2006) with this site. In July and August, data in the NEE-temperature plot were considerable scatter, and NEE lacked temperature response, main reason for these could be the saturated soil water conditions (Fig. 1d) and the nighttime NEE mainly from plant respiration. Acknowledgements This work is supported by National Natural Science Fund for Distinguished Young Scholars (Grant No. 40625015) and National Key Basic Research Specific Foundation (2004CB418507-1). We also thank Dr. Yunlong Wang and Dr. Yijun Li from the Institute of Botany, Chinese Academy of Science for their helpful work during this study. References Aurela, M., Laurila, T., Tuovinen, J.P., 2002. Annual CO2 balance of a subarctic fen in northern Europe: importance of the wintertime efflux. J. Geophys. Res. Atmos. 107, 4607–4618.

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