Ecosystem respiration in coastal tidal flats can be 1 modelled from air temperature , plant biomass and 2 inundation regime 3

23 Ecosystem respiration contributes greatly to carbon emissions and losses 24 in coastal wetlands. To gain a better understanding of gaseous carbon loss from 25 a coastal wetland covered by seablite (Suaeda salsa Pall.) and to evaluate the 26 influence of environmental factors on ecosystem respiration, a multi-year in-situ 27 experiment was carried out during the growing season of 2012 through part of 28 2014. By partitioning total carbon dioxide (CO2) flux into soil respiration (Rsoil) 29 and plant respiration (Rp), we found that during mid-summer, ecosystem CO2 30 respiration rates (Reco) were within the range of 844.5 to 1150.0 mg CO2 m 31 h, while Reco was as low as 31.7 to 110.8 mg CO2 m h at the beginning 32 and the end of growing seasons. Aboveground S. salsa plant material 33 comprised 79.1% of total biomass on average, and Rp dominated Reco during 34 inundated periods. It is estimated that 1 gram of soil-emergent S. salsa biomass 35 (dry weight) could produce approximately 1.41 to 1.46 mg CO2 per hour during 36 mid-summer. When water level was below the soil surface, soil microbial and 37 belowground root respiration (Rs+r) was exponentially correlated with air 38 temperature. Based on our observation, an empirical model was developed to 39 estimate system respiration of the S. salsa marsh in the Liaohe River Delta, 40 Northeast China. This model can be applied for regional carbon budget 41 estimation purposes from S. salsa wetlands throughout Northeast China. 42 43


Introduction
Coastal wetlands are known to sequester carbon at high rates, and many are regulated by salinity to emit less methane than inland wetlands due to the greater availability of sulfate (Chmura et al., 2003;Holm et al., 2016;Lu et al., 2016).Ecosystem respiration (Reco) is believed to be the dominant gaseous carbon emissions process from coastal wetlands, weakening the carbon sink function of coastal wetlands that have the highest effluxes of CO2 (Nicholls, 2004;Smith et al., 1983).Reco includes sources of CO2 both routed through or originating from emergent plant structures (Rp) and those sources associated with soil microbial and belowground root respiration (Rs+r).Rp and Rs+r should be quantified separately because each process has its unique seasonal pattern and response to environmental factors (Li et al., 2010).Considering that CO2 generated by plant and microbial respiration is much more than CO2 generated from anthropogenic activities (Raich et al., 2010), these fluxes from natural and managed wetlands are inherently important in regulating the climate cycle in providing positive feedbacks (i.e., greater CO2 emissions; greater atmospheric warming) or negative feedbacks (i.e., reduced CO2 emissions; less atmospheric warming) (Cox et al., 2000;Davidson and Janssens, 2006;Melillo et al., 2002;Mitsch et al., 2008).Coastal wetlands have been the focus of much attention since large amounts of carbon can be stored in tidal (known as "blue carbon") and in inland non-tidal coastal wetlands, but with a notable reduction in net gaseous CO2 (and CH4) emissions when managed properly (Chen et al., 2016;Jankowski et al., 2017;Rodríguez et al., 2017;Wang et al., 2016).
Reco in coastal wetlands is influenced by many environmental factors including soil and air temperature (Arora et al., 2016;Juszczak et al., 2013), soil properties (Hassink, 1992), salinity (Neubauer et al., 2013), plant type (Xu et al., 2014), root biomass (Krauss et al., 2012), and hydrologic conditions (Guan et al., 2011).Environmental factors change greatly with time, which create bias on evaluating Reco if the full range of changing environmental conditions is not included in determinations (Marínmuñiz et al., 2015;White et al., 2014).In addition, Rp and soil microbial respiration have different responses to temperature and water level change (Dawson and Tu, 2009;Hall and Hopkins, 2015;Wu et al., 2017).
Our lack of understanding about CO2 emissions from a wide range of environments and environmental conditions results in difficulties in linking response to key factors (Wolkovich et al., 2014), yet such linkages are critical for modeling and determine area-scaled fluxes of use at regional and national levels.Statistical analyses are useful in identifying interactions and the importance of individual environmental factors in controlling Reco, but such information is often more locally relevant than globally and there has been decidedly less quantification of larger-scale influence (Iwata et al., 2015;Song et al., 2015).Modelling is an effective way to understand and evaluate CO2 exchange between ecosystems and the atmosphere (Giltrap et al., 2010;Kandel et al., 2013), given that empirical assessment often misses extreme environmental conditions.By simulating biogeochemical activities, processbased models are capable of interpreting material and energy flow from one pool to another (Giltrap et al., 2010;Metzger et al., 2015;St-Hilaire et al., 2010).
However, as more processes are considered through iterative research, the number of parameters of relevance to modelling can increase, which makes models more complicated and more difficult to apply across scales (Wang and Chen, 2012).Empirical models are easier to deploy for evaluating respiration in the same ecosystem because driving variables are connected to observations via mathematical formulas (Yuste et al., 2005).Biological processes are not typically fully integrated within models, rather statistical relationships are used to imply cause and effect, leading to imperfect model structure and larger uncertainty in model projections (Larocque et al., 2008).
Partitioning in-situ Reco into different components and determining the variables controlling each component is challenging but important (Li et al., 2010).For this approach, traditional chamber methods have advantages as flux measurements are direct and linked over small spatial scales to environmental measurements (Dyukarev, 2017;Pumpanen et al., 2004).This approach does abandon a degree of reality accomplished through eddy covariance methods (Aubinet et al., 2012;Nicolini et al., 2018).However, models can be applied effectively to develop chamber-based assessments at larger scales.
Suaeda salsa Pall is a pioneer herbaceous species of tidal marshes and is very tolerant to salinity (Baoshan et al., 2008;Guan et al., 2011).It naturally grows on highly saline soil including intertidal zones of Europe and East Asia as well as saline and alkaline soils of beaches and lakeshores in northern China.
The growing season Reco rate of S. salsa wetlands in the Liaohe River Delta and the Yellow River Delta averaged 335 to 402 mg CO2 m −2 h −1 (Ye et al., 2016) and approximately 193 mg CO2 m −2 h −1 (Chen et al., 2016), respectively.From these studies, temperature is believed the dominant controlling factor of Reco, and several exponential correlations between temperature and Reco have been developed (Xie et al., 2014).However, water level also determines soil aerobic versus anaerobic condition by enhancing or restricting oxygen availability, respectively, and plant biomass also contributes to Reco through emergent plant structures and roots embedded below the soil surface (Olsson et al., 2015).
Due to a mix of temporal and spatial characteristics of plant distributions and environmental factors in S. salsa wetlands across their geographic range, observing and measuring Reco of S. salsa marshes across this range would be cost-prohibitive (Sánchez-Cañete et al., 2017).
To gain a better understanding of gaseous carbon loss from a coastal wetland covered by S. salsa and to evaluate the contributions of plant and soil fluxes to Reco, a multi-year in-situ experiment based on the chamber method Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.was carried out during the growing seasons of 2102, 2013, and 2014.We quantify the influence of temperature, biomass, and water table on ecosystem respiration, as past studies, but we also develop a rapid assessment method (ecosystem model) to estimate system-scale Reco in S. salsa marshes of the Liaohe River delta to aid future efforts to scale beyond where experimental measurements are taken, and over potentially different environmental conditions projected for the future.This rapid evaluation model also has potential application in regional and national carbon budget estimation for S. salsa wetlands with lower costs than direct empirical assessment.

Study area
This study was conducted in the Liaohe Delta (121°25′-123°31′ E, 40°39′-41°27′ N) of Northeast China (Figure 1).Natural wetlands in the Liaohe Delta cover about 2610 km 2 , which account for about 69% of the delta area (Ji et al., 2009).In addition, rice agriculture (non-natural wetlands) comprises approximately 3287 km 2 , and is spread inside and outside of the Liaohe Delta area proper.The Liaohe Delta is located in the temperate continental monsoon zone with mean air temperature of 8.3 °C, and a mean annual precipitation of 612 mm with most rain falling in summer.The mean annual evaporation rate is 1705 mm, and the mean annual sunshine duration is around 2769 h (Luo et al., 2003).The average tidal range in the area is 2.7 m; tides are semi-diurnal.The Liaohe Delta comprise what is believed to be the largest reed (Phragmites australis Cav.Trin ex Steud) wetland in the world with a total area of approximately 800 km 2 (Brix et al., 2014).A field study site was built 16 km west of the Liaohe River mouth in a newly restored wetland on a former fallow tidal flat colonized recently by S. salsa.Saueda salsa wetlands comprise only 32 km 2 in the Liaohe River delta, but provide seasonal color to the region during flowering that draws tourists from all over China.The soil on the study sites is a silty clay loam with a sand, silt and clay content of 20%, 65% and 15%, respectively, and a soil bulk density of approximately 1.3 g cm 3 .The soil total and organic carbon content are low, averaging 9.5 g kg −1 and 6.4 g kg −1 , respectively, and total nitrogen content is 1.1 g kg −1 .Soil pH is 7.3 ± 0.4 (std.err.) and soil pore water salinity is 17 ± 2‰.

CO2 flux measurements
The CO2 fluxes were measured using a field-portable infrared gas analyzer (Li-8100A, LI-COR Biosciences, Inc., Lincoln, NE, U.S.A.) with a commercial survey chamber (8100-103).CO2 measuring range was 0 to 3000 ppm with errors less than 1.5 %.Circular survey collars (10 cm tall by 20 cm diameter) were inserted 3 to 5 cm into the soil 2 hours before measurement began to limit the influences of recent disturbance.The survey collar measured an area of 318 cm 2 .The total volume of the flux chamber was calculated as the sum of the volume of the commercial survey chamber system (~4843 cm 3 ) plus the volume inside the collar factoring insertion depth of each collar individually.CO2 concentrations were recorded at 1 Hz during 90 s measurement periods, measurements were replicated twice, and values were averaged to ensure data reproducibility (Mukhopadhyay and Maiti, 2014).Prior to each field trip, the infrared gas analyzer was factory calibrated and checked for zero drift before measurements using CO2-free nitrogen gas (Dyukarev, 2017).Six plots were established, and all had different amounts of vegetation coverage in each observation month.On each plot, three measuring procedures were included, as follows: (1) Measurement of the entire ecosystem CO2 flux by including all vegetation and soil area under that vagatation, "Reco"; (2) Measurement of plant material after cutting and removing all S. salsa at 1 to 2 cm above soil surface, Rp.We placed all S. salsa into a sealed and dark survey collar immediately after harvest (within 2 minutes) and measured CO2 flux from the still physiologically active plants.
(3) Measurement of CO2 flux within the survey chamber but without standing plants, which indicates soil microbial respiration plus respiration of roots underlying those soils, Rs+r.Rs+r was taken when soils were not inundated.3. Results and discussions
However, the relative contributions of Rs+r and Rp varied both during the season and between seasons (Figure 3).

Reco varied significantly over the growing season with peak values in
August when the weather was hot (Figure 3).The seasonal pattern was nearly identical between years, although peak Reco varied between 845 mg CO2 m −2 h −1 in 2014 and 1150 mg CO2 m −2 h −1 in 2013.During mid-summer (July and August) there was great spatial variation in Reco (as indicated by relatively large variation among measurements) due to the variations in plant biomass within the collars and also differences in water table depth at the time of specific measurements.
Rs+r generally varied in concert with Reco with highest rates in July-August, except in 2012 where rates were low (< 100 mg CO2 m −2 h −1 ) in July and August.
This corresponds to a period where the soil surface in all six measuring plots was inundated, i.e. had standing water on the soil surface.This was also the case in June-July in 2013 which also had very low Rs+r rates.The inundation probably reduces Rs+r because of the prevailing anoxic conditions in the soil which is likely to occur as a consequence of the inundation.However, emission of CO2 to the atmosphere through the water surface might also be reduced because CO2 is highly soluble in water and enters into an equilibrium with the found, and also peaked in June to August, depending on the year (Ye et al., 2016), corresponding strongly to peak seasonal aboveground biomass as well.
Our study confirms that all components of Reco follow suit, with Rs+r and Rp peaking concomitant with Reco in most instances (figure 3), tracking plant growth.

Plant biomass
Suaeda salsa is an annual herb that germinates and starts to grow in late April.The plants then follow the normal seasonal vegetation growth cycle for cold temperate regions, with flowering beginning in July and maturation of seeds occurring around late September (Mori et al., 2010).In the current study, the biomass production of S. salsa largely followed this pattern reaching a total biomass of between 530 and 930 g dry mass m −2 depending on year (Fig. 4).
Overall, the aboveground biomass constituted about 79% of the total biomass (i.e., aboveground plus belowground), but the proportion varied during the growing season.In the spring and early summer, the roots contributed a larger proportion (25% to 35%) of the total biomass whereas in the late summer and autumn the roots only constitute 15% to 20% of the total biomass.This shows that the roots of S. salsa develop prior to peak above ground biomass, and are thus slightly out of phase, suggesting an important role for early growing season root growth initiation which also influences Reco.After mid-September, aboveground biomass remains stable probably because roots at this stage are now able to support the biomass of the entire plant.Mao et al. (2011) reported that the root covers 8%~13% of total Suaeda salsa biomass in the Yellow River Delta, which was similar to our results.

Influencing environmental factors on Rs+r and Rp
Air temperature varied between 3°C and 33°C during the measuring period.
Rs+r rates were always low when the air temperature was below 18 ºC (Fig. 5), which is consistent with the findings of Ye et al. (2016).When the low fluxes measured during inundated periods were excluded, we found that Rs+r was exponentially correlated with air temperature on a seasonal scale, which has also been reported in several other studies (Bäckstrand et al., 2010;Xie et al., 2014).If we did not remove fluxes of Rs+r that were measured during inundated periods, the correlation would be significantly weakened (figure 5), suggesting a strong statistical interaction between air temperature and inundation that needs to be considered (Krauss et al., 2012).Reco also correlated weakly with air temperature probably because the combined effects of soil temperature, water table, and plant biomass on Reco were not considered (Flanagan et al., 2002;Reth et al., 2005;Zhang et al., 2016).Observations from measuring plots with large biomasses were significantly higher than the exponentially predicted values, indicating that roots in the soils probably contributed significantly to Rs+r.During inundated periods, Rs+r rates were low because water blocked both oxygen and CO2 transport (Yang et al., 2014).Water can both absorb or emit CO2 depending on the HCO 3 − /CO 3 2− balance in surface water and the dissolve balance of CO2 between surface water and the atmosphere (Wanninkhof and Knox, 2003).Suaeda salsa has very limited aerenchyma in its tissue, and no plant-mediated gas transport has been found in this species (Brix et al., 1996).
Besides, compared to the rates of Rs+r and Rp, the rates of gas exchange between surface water and the atmosphere is low.Our observations suggest that the main effect of inundation to the S. salsa marsh respiration is blocking the gas transport from the soil to the atmosphere.Hence, the Rs+r rate is very sensitive to water level variation just around the soil surface.This phenomenon was also reported in cool temperate bog located in Mer Bleue, Canada (Lafleur et al., 2005;Pugh et al., 2017).
Plants are reported to account for 35% to 90% of the total ecosystem respiration in wetlands (Johnson et al., 2000), and are therefore believed to be the dominant influencing factor for the spatial variation observed in Reco (Han et al., 2007).In the Yellow River delta, Han et al. (2014) did not find a significant relationship between Reco and biomass during the growing season in a S. salsa wetland.This may be because they did not partition Rp, as we did here.As can be seen in figure 3, Rp was close to Reco during inundated periods, which shows that the S. salsa plants contributed the most to the Reco.In all periods except August 2012, we observed a significant linear correlation between AGB and Rp the remaining points follow a unimodal distribution over time.This can be mathematically described by a Gaussian equation relating Rp/AGB over Julian day (figure 7).Some studies prefer to use the air or soil temperature as the proxy to evaluate seasonal parameters, while the accumulated temperature has been shown to be better for evaluations of plant phenology (Cannell and Smith, 1983).Since we did not measure meteorological variables on site   The rate of June and July of 2012 are significantly higher than the other values, and are thus not included in the seasonal variation estimation curve.

Modelling of components of ecosystem CO2 fluxes
As is shown in Equation 1, Reco is calculated as the sum of Rp and Rs+r.

Soil and root respiration
Rs+r was determined by water level and air temperature, which was Where kWT represents the influence factor of water table, and f(T) indicates the influence of air temperature (T in °C) on Rs+r (figure 9).Equation 3 displays the influence of water level on kWT, with the parameter, a, a constant, indicating the changing rate of water level (h in cm) relative to the soil surface on our study sites.Here, a was determined to be 4.6, indicating that water level of 1cm could block completely block the soil respiration, while -1 cm water level could provide full Rs+r compacities (figure 10).Equation 4  As is shown in figure 9, Reco in 2012 was significantly underestimated because plant activity in 2012 was higher than the other two years (figure 4).This model provides a regional rapid assessment protocol for Reco within S.
salsa marshes; Necessary environmental variables can even be obtained through remote sensing.

Conclusions
Ecosystem respiration (Reco) of a S. salsa wetland in the Liaohe Rive Delta, Reco using our proposed rapid assessment method.With regional data calculated from remote sensing, the method can be used to evaluate Reco of S.
salsa marshes on a large scale in the Liaohe River Delta, and potentially in other similar cold temperate wetland types.

Figure 1
Figure 1 The location of the study site in the Liaohe Delta, Northeast China Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.The CO2 fluxes (F, mg CO2 m −2 h −1 ) were calculated according to the following equation: dt (mol h −1 ) is the slope of the linear regression line for CO2 concentration over time; M (mg mol −1 ) is the molecular mass of CO2; P (in Pascals) is the barometric pressure; T (in Kelvin) is the absolute temperature during sampling; V (in Liters) is the total volume of the enclosure measuring space; S (in m 2 ) is the cover area of the measuring plot.V0 (22.4 L/mol), T0(273.15K) and P0 (101.3 kPa) are the gas mole volume, absolute air temperature, and atmospheric pressure under standard condition, respectively(Song et al., 2009).2.3.Experimental designFluxes of CO2 were measured approximately monthly during the growing seasons of 2012, 2013, and 2014 (figure2), for a total of 15 months of measurements over the three years.Soils of Liaohe Delta wetlands are frozen to depths of 15 cm during the months of December to March(Ye et al., 2016).
Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.Additional measurements were taken when soils were inundated, and those measurements used to partition CO2 exchange between the water surface and the atmosphere at those times.All harvested S. salsa plant material was dried to a constant mass at 65 C in a convection oven for a measure of aboveground biomass (AGB).A 15 cm deep surface soil sample was taken within each survey collar after measurements were completed during each sampling period.Living roots of S. salsa were collected, separated from the soil column and dried in an oven at 65°C to constant mass for a measure of belowground biomass (BGB).

Figure 2
Figure 2 The observing period and procedures.The observation periods from 2012 to 2014 was marked as filled grey patches on the top subplot.Vertical blue patches indicated the relative water level of a corresponding observation period.Months with continuous blue rectangles refer to inundation of all six plots; half covered refer to inundation of only some of the plots; and no blue bar equates to no inundation.The bottom subplot displays a visual depiction of procedures.Reco, Rs+r, and Rp were measured in the corresponnding sequence.

Figure 3 .
Figure 3. Seasonal variation in ecosystem respiration (Reco), soil respiration (Rs+r), and plant respiration (Rp) during the growing seasons of 2012-2014. .Errorbars are standard error of the mean values.

Figure 4
Figure 4 Seasonal variation of S. Salsa biomass during three growing seasons.Error barsindicates the standard error at each sampling period (n=6).The inserted graph

Figure 5
Figure5The relationship between the observed soil respiration (Rs+r) rates and air

(
figure 6).To demonstrate how the AGB influences Rp, the slope of the linear curves versus Julian days are shown in figure 7. The slope of the regression line varies over a growing season, and is < 0.1 mg CO2 per g dry mass per hour in October and November, probably because of plant senescence in the autumn.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.The slopes obtained for 2013 and 2014 are comparable and the difference is less than 5% in June and August.In June and July 2012, the slopes of Rp to AGB are more than twice as high as the corresponding slopes of 2013 and 2014.As the study site was established in 2012, it is possible that the biochemical conditions in the soil, including nutrient and organic carbon concentrations, were disturbed slightly.The soil might have contained more nutrients the first year, which might have led to high plant activity and corresponding high respiration rates.Disregarding the larger slopes in 2012, continuously over annual cycles, we are still able to predict respiration parameters versus S. salsa plant biomass because of the significance of seasonal time represented by Julian day as a proxy.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.

Figure 6
Figure 6The relationship between plant respiration rate (Rp) and aboveground

Figure 7
Figure 7 The seasonal variation of dry mass specific plant respiration rate (Rp/AGB).
indicates the relationship between air temperature and Rs+r during non-inundated periods, which is represented by an exponential curve (figure 5).Parameter b describes the temperature sensitivity of Rs+r and F0 (in mg CO2 m −2 h −1 ) was determined by Rs+r at 0 °C.Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.Rp in S. salsa wetlands can be determined by   =   ×   Equation 5 where mp (g dry weight m −2 ) is the biomass of S. salsa and kact was the amount of CO2 that 1 gram plant material can produce in 1 hour based on our study, and is used here to indicate the influence that seasonal plant activity has on Rp. has a seasonal signature as well, related to environmental variables such as air temperature; however, air temperatures alone were not as useful in predicting Rp as kact.A gaussian equation driving by Julian day was used to evaluate the seasonal and annual variation in kact.According to our observation and analysis, the best fit parameters of kamax, Dm, and Ds was 1.49, 214.83, and 76.63, respectively (figure 7, figure 8b).

Figure 8
Figure 8 Key parameters and the driving variables.(a): Parameter kWT changes driven by water level change near soil surface; (b): Seasonal variation of kact driven by Julian day of a year; (c): Soil respiration under different air temperatures.

Figure 9
Figure 9 The observed respiration and modelled resiration.The triangle marks represent observed Rp while the square marks represent observed Rs+r.The green and tawny bars indicate the modelled Rp and Rs+r, respectively.The modelled and observed Reco of 2012, 2013 and 2014 are colored red, green and blue, respectively.

Figure 10
Figure 10 Schemetic seasonal variation of ecosystem respiration and environmental factors in S.Salsa marsh of the Liaohe River delta.Water level in July is manully set above soil serface.More complicated environmental variables (such as water table and temperature) on plant activity, processes of gas diffusion and water HCO 3 − /CO 3 2− balance are not included in this model due to the limitation of our field observation.Besides, for only one dataset, comparing the observed data and modelled data here makes less sense.More observations or data from other S. salsa wetlands are needed to test this model on a larger scale.However, with easily obtained environmental variables (AGB, air temperature, and water regime), Reco (and by extension Rp and Rs+r) rate can be estimated on a large scale, making assessments of area-scaled CO2 emissions from this wetland type, such as conducted by Ye et al. (2016), more cost-effective in the future.
China, was observed to range from −61 to 2995 mg CO2 m −2 h −1 , with significant Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.seasonal variation.Flux partitioning confirmed that Reco was correlated with plant biomass, water regime, and air temperature.Plant biomass and plant activity controlled plant respiration, and further dominated the Reco during inundated period.Both soil and plant contributed to Reco when water level was below soil surface.Soil and root respiration is exponentially correlated with air temperature with a sensitivity of 0.113 °C−1 .Besides, S. salsa could produce as much as 1.41 to 1.46 mg CO2 g −1 dry weight h −1 during mid-summer.Air temperature, plant biomass, and hydrological regime are essential to estimate Biogeosciences Discuss., https://doi.org/10.5194/bg-2018-186Manuscript under review for journal Biogeosciences Discussion started: 27 April 2018 c Author(s) 2018.CC BY 4.0 License.estimated.On our study sites, Rs+r had an average contribution of 23.9% to total ecosystem respiration during the entire growing season.Knowing that the modelled aboveground Rp covers an average of 55.2% of Reco, plant biomass determines the spatial variation in Reco, and is therefore suggestive that our model is widely applicable to other cold temperate S. salsa wetlands through Moore and Dalva (1993)e includes living root respiration as well as soil organic matter respiration (microbial) according to our model, if we assume the living roots respire as fast as the aboveground parts.With the record of belowground biomass and the parameter   , the contribution of each component can be plant biomass, water table depth, and air temperature modeling alone.AsMoore and Dalva (1993)reported, the effects of climatic change on gas flux from peatlands are more likely to be associated with changes in the water table than with changes in thermal regime.The schematic respiration model derived from our results follow suit (figure10).