CO2 and CH4 fluxes during spring and autumn mixing periods in a ...

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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 114, G04007, doi:10.1029/2009JG000923, 2009

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CO2 and CH4 fluxes during spring and autumn mixing periods in a boreal lake (Paä¨ja¨rvi, southern Finland) Jessica Lo´pez Bellido,1 Tiina Tulonen,2 Paula Kankaala,3 and Anne Ojala1 Received 5 January 2009; revised 18 July 2009; accepted 11 August 2009; published 12 November 2009.

[1] The greatest gas loss from dimictic lakes occur during spring and autumn mixing

periods. Thus, we measured daily concentration gradients of carbon gases (CO2 and CH4) in mesohumic Lake Paä¨ja¨rvi during the mixing periods in autumn 2004 and spring 2005 and calculated and compared the fluxes using three different methods: the boundary layer diffusion model (DCO2 and DCH4), floating static chambers (FC), and changes in gas storage. CO2 fluxes were higher in autumn than in spring, whereas CH4 fluxes were lower in autumn than in spring. The method based on changes in storage underestimated the fluxes whereas the floating chambers and the boundary layer diffusion models resulted in similar estimates. However, the chambers always yielded somewhat higher fluxes. Total DCO2 flux in autumn was 883 mmol m2 and in spring, 666 mmol m2, whereas total DCH4 fluxes were 0.60 mmol m2 and 0.80 mmol m2 in autumn and spring, respectively. We calculated gas transfer velocities (k600) to explain the near surface exchange mechanism and the difference between the results based on diffusion models and chambers. Wind speed and k600 showed significant correlation. In spring the transfer velocity at similar wind speed was higher compared to the autumn. Weekly measurements of algal primary production and community respiration revealed that the lake was net heterotrophic in autumn as well as in spring. Our study showed that the excess CO2 from the lake metabolism contributed significantly to the CO2 fluxes during the mixing periods, violating the primary assumption used in the storage method. Citation: Lo´pez Bellido, J., T. Tulonen, P. Kankaala, and A. Ojala (2009), CO2 and CH4 fluxes during spring and autumn mixing periods in a boreal lake (Paä¨ja¨rvi, southern Finland), J. Geophys. Res., 114, G04007, doi:10.1029/2009JG000923.

1. Introduction [2] Recent surveys have demonstrated a worldwide supersaturation of CO2 in freshwaters [Cole et al., 1994; Algesten et al., 2004], and in contrast to terrestrial CO2 sinks, freshwater ecosystems often act as sources of CO2 to the atmosphere. This supersaturation has been related to the transport of terrestrial organic carbon to aquatic environments [Cole et al., 1994; Hope et al., 1994], and thus the microbial degradation of allochthonous dissolved organic carbon (DOC) can maintain CO2 flux to the atmosphere by causing ecosystem respiration to exceed production [del Giorgio et al., 1999]. Therefore, a clear, direct relationship exists between DOC concentration in lake water and CO2 supersaturation [Sobek et al., 2003], thus indicating that humic lakes, where abundant [cf. Kortelainen, 1993], may influence landscape carbon gas emissions. [3] In deep boreal lakes, a dimictic pattern of water column mixing profoundly affects the seasonal variation of gas transfer within the water column and exchange between the 1 Department of Ecological and Environmental Sciences, University of Helsinki, Lahti, Finland. 2 Lammi Biological Station, University of Helsinki, Lammi, Finland. 3 Ecological Research Institute, University of Joensuu, Joensuu, Finland.

Copyright 2009 by the American Geophysical Union. 0148-0227/09/2009JG000923$09.00

lake surface and the atmosphere. During summer stratification, lack of bulk mixing between the epilimnion and hypolimnion suppresses gas transfer between these layers, whereas ice cover in winter effectively stops gas exchange between the lake surface and the atmosphere [MacIntyre et al., 1995; Wetzel, 2001]. The amount of gases accumulated under the ice in winter and/or in the hypolimnion in summer greatly affects the seasonality of fluxes. Generally, the highest seasonal carbon gas effluxes have been observed to occur in spring after the ice-out, [Striegl and Michmerhuizen, 1998; Kelly et al., 2001; Striegl et al., 2001] and/or during the autumnal mixing [Riera et al., 1999; Kankaala et al., 2006]. Changes in CO2 storage after ice-out suggest that the release of accumulated CO2 is a rapid event [Striegl and Michmerhuizen, 1998; Wetzel, 2001; Rantakari and Kortelainen, 2005]. A sudden decrease in pCO2 in surface water has also been observed in boreal lakes at the time of autumn turnover [Kelly et al., 2001]. Because the onset and duration of turnover periods is largely determined by weather conditions (temperature, wind speed and direction, precipitation), interannual variations in spring and autumn gas fluxes, which together can contribute to ca. 40% of annual fluxes, can be high [Rantakari and Kortelainen, 2005]. [4] Detailed information on carbon gas emissions, related to environmental factors, are needed for accurate estimates of regional and global carbon balances and to truly under-

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Table 1. Basic Chemistry on the Surface of Lake Paä¨ja¨rvi in Autumn 2004 and Spring 2005a Period

pH

Total N

N/NO2 + NO3

Total P

PO4-P

DOC

Chlorophyll a

11 Oct to 10 Nov 2 – 12 May

7.4 (7.2 – 7.6) 7.1 (7.0 – 7.2)

1373 (1368 – 1378) 1373 (1333 – 1413)

869 (860 – 877) 1064 (1047 – 1081)

9.5 (9 – 10) 9.0 (8 – 10)

1.5 (1 – 2) 1.5 (1 – 2)

12.9 (12.3 – 13.5) 13.3 (13.2 – 13.4)

6.0 (5.3 – 6.4) 1.1 (0.6 – 1.8)

a The surface is 0 – 4 m. Mean values are in units of mg L1, except for DOC, which is in mg L1. Here n = 2 for nutrients and n = 4 for other variables in autumn and in spring, respectively. Values in parentheses indicate range.

stand the transport of carbon through the terrestrial-aquatic continuum in the landscape. This need is most obvious in the boreal zone, where lakes cover approximately 7% of the total land area and are generally characterized by a high DOC content [Kortelainen, 1993]. The boreal zone is also among the areas predicted to experience the greatest temperature increases due to global climate change [Meehl et al., 2007]. Higher temperatures will certainly affect the length of the ice-free period and water column mixing pattern of the lakes. [5] In this study, we investigated CO2 and CH4 fluxes to the atmosphere and gas transfer velocity during spring and autumn mixing periods in a large boreal lake with a high load of allochthonous organic carbon, but oxygenated hypolimnion [Tulonen et al., 2000]. We compared and estimated the gas fluxes using three methods commonly used in gas exchange studies:1) boundary layer diffusion models of CO2 and CH4 across the water-air interface, 2) floating static chambers, and 3) changes in the storage of CO2 and CH4 in the water column. The simultaneous application of the first and second method enabled calculations of gas transfer velocities. The third method was based on an assumption that, in comparison with the release of accumulated gas storages, the net amount of carbon gases produced through biological processes during mixing periods was insignificant. We hypothesized that due to the rapid warming of the surface water and the formation of the thermocline and, hence, the shorter mixing time, total CO2 and CH4 emission would be lower during spring turnover than during the autumnal mixing period. We sampled the lake intensively and visited it on 13 and 11 consecutive days in autumn and spring, respectively. The lake was also sampled weekly before and after the peak of the mixing periods. Besides carbon gases, we sampled the lake weekly for those physical and biological factors possibly contributing to the fluxes.

2. Methods 2.1. Study Area and Sampling [6] We studied carbon gas fluxes in Paä¨ja¨rvi, a boreal lake located in southern Finland (61°040N, 25°080E) with a surface area of 13.4 km2 and a maximum and mean depth of 87 m and 14 m, respectively. Mean residence time of water is 3.3 years. The catchment area (199 km2) is dominated by coniferous forests (59%), and agricultural land and peatlands cover 15% and 11% of the catchment area, respectively [Hakala et al., 2002]. The lake water is neutral (pH 7.0– 7.6), although strongly affected by allochthonous organic carbon; the concentration of dissolved organic carbon (DOC) is 10– 13 mg L1 [Arvola et al., 1996] (Table 1). Nutrient concentrations indicate that the lake is mesotrophic. The nitrogen concentration is high (total N > 1000 mg L1;

Table 1), but the phosphorus concentration is moderate (total P ca. 10 mg L1; Table 1). The chlorophyll a concentration was 6 mg L1 in autumn and 1 mg L1 in spring. [7] We sampled the lake on 11 October and 18 October 2004, and the daily sampling period began on 25 October and continued until 5 November, after which the lake was sampled on 10 November and 17 November. Subsequently, the lake began to freeze over, and by 7 December was completely ice covered. We began the spring sampling on 30 March 2005 when the lake was still ice covered. Ice-out at the end of April occurred gradually from the shallow littoral zone, and large openings in the ice cover were observed as early as two weeks before the final ice-out on 29 April. The daily sampling took place from 27 April to 6 May 2005, followed by two measurements on 9 and 12 May. Samples were always taken between 9.30 A.M. and 11.30 A.M. (solar time; GMT+2) from the middle of the lake where the maximum depth was 46 m. 2.2. Carbon Dioxide and Methane Measurements [8] Dissolved gas samples of CO2 and CH4 were taken with a Limnos sampler from 0, 1, 2, 3, 4, 10, 20, 30, and 45 m to measure the concentration gradient through the water column. Two replicates of water samples (volume 30 mL) from each depth were drawn into 60 mL polypropylene syringes, which were closed with three-way stopcocks after removing any gas bubbles. The water-filled syringes were kept in crushed ice until analysis within one hour upon arrival to the laboratory. The syringes were then placed in a water bath at a temperature of 20°C for 5 min. For the gas chromatograph (GC) headspace analysis, nitrogen gas was added in a proportion of 50% of the volume; after mixing, the gas was injected into 12 mL Labco Exetainer1 vials (Labco Limited, High Wycombe, Buckinghamshire, UK). Samples from the overpressurized vials were then delivered to the GC by a Gilson 222 XL autosampler (Gilson Inc., Middleton, Wisconsin, USA) through a 1 mL Valco 10-port valve (VICI Valco Instruments Co. Inc., Houston, Texas, USA). Analyses were carried out with an Agilent 6890 N (Agilent Technologies, Santa Clara, California, USA) GC equipped with a flame ionization detector (FID) (temperature 210°C) and a thermal conductivity detector (TCD) (temperature 120°C, oven 40°C, PlotQ capillary column, flow rate 12 mL min1, He as a carrier gas). The GC was calibrated with CO2 using concentrations of 103 and 999 ppm, and with CH4 using concentrations of 10 and 493 ppm (Oy AGA Ab, Finland). The coefficient of variation between replicate measurements was generally P), due to decomposition of allochthonous organic carbon load, is typical of boreal lakes [Salonen et al., 1983; Hessen, 1985; Jones, 1992]. In the boreal zone, warm autumns are expected to become more frequent as a consequence of climate change, which will delay freezing over, and in-

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creasing precipitation may further enhance the loading of organic carbon from the surrounding catchment area [Kortelainen, 1993; Rantakari and Kortelainen, 2005]. Thus, fluxes of CO2 from the boreal lakes to the atmosphere, due to the decomposition of allochthonous organic carbon, are presumably increasing in future climate conditions. [32] The estimated CH4 fluxes from Lake Paä¨ja¨rvi during the mixing periods were generally lower than those from boreal, alpine, and temperate lakes and ponds [cf. Huttunen et al., 2003]. In a lake featuring an oxic water column throughout the year, the bulk of the CH4 produced in the sediment is oxidized on the sediment surface or in the water column or both, thus releasing a minor proportion to the atmosphere [e.g., Utsumi et al., 1993]. All of the three methods we applied yielded higher CH4 flux estimates for spring than for autumn. Higher springtime fluxes were due to the accumulation of CH4 under the ice cover. The lower estimates of CH4 fluxes acquired with the storage change method were probably due to sampling from the middle of the lake only. Shallow littoral areas presumably contribute to the gas concentration at the surface layer [cf. Bastviken et al., 2008] and, thus, the efflux estimates acquired with the boundary layer models and FC methods are higher, but also more realistic.

5. Conclusions [33] We observed rapid changes in CO2 and CH4 concentrations and fluxes between the lake and the atmosphere in spring as well as in autumn. In autumn, the total amount of CO2 released was slightly higher than in spring. In spring there was a larger pool of CO2 and the gas transfer velocities were higher than in autumn, i.e., k600 values appeared not only site-specific but also time-specific. The fluxes of CH4 as well as gas transfer velocities were higher in spring than in autumn. [34] In general, the boundary layer diffusion models and the static chambers yielded identical results. Our measurements suggest that a change in storage method underestimated the carbon fluxes in Lake Paä¨ja¨rvi by 45% for CO2 and 65% for CH4 when compared to boundary layer diffusion models, and between 60% and 70% when compared to the static chambers method. [35] During mixing periods the excess CO2 from the lake metabolism contributed significantly to the CO2 fluxes, which violated the assumption of minor contribution of metabolism, used in the change in storage method. [36] Acknowledgments. This study was funded by the NECC (Nordic Centre of Excellence for Studies of Ecosystem Carbon Exchange and its Interactions with the Climate System) and the Academy of Finland (project name BORWET, 201623). We thank the Lammi Biological Station of the University of Helsinki for its working facilities, Jussi Huotari for comments and Stephen Stalter for the language revision. Moreover, the significant contribution of two unknown reviewers that helped to improve the manuscript.

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P. Kankaala, Ecological Research Institute, University of Joensuu, PO Box 111, FIN-80101 Joensuu, Finland. J. Lo´pez Bellido and A. Ojala, Department of Ecological and Environmental Sciences, University of Helsinki, Niemenkatu 73, FIN-15140 Lahti, Finland. ([email protected]) T. Tulonen, Lammi Biological Station, University of Helsinki, Paä¨ja¨rventie 320, FIN-16900 Lammi, Finland.

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