1. A dynamic ecosystem budget for assessing the metabolism of a large shallow lake Fabien Cremona 1, Toomas Kõiv 1, Veljo Kisand 1,2, Alo Laas 1, Priit Zingel 1, Helen Agasild 1, Tõnu Feldmann 1, Ain Järvalt 1, Peeter Nõges 1, Tiina Nõges 1 1: Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences 2: Faculty of Science and Technology, University of Tartu

2. Background Objective Assessing lake-wide and functional group-specific metabolism (gross primary production (GPP) minus respiration (R)) in shallow and eutrophic Lake Võrtsjärv in central Estonia during three years Ecosystem approach is useful for measuring component rates but requires a huge amount of data about organisms in a lake (Andersson and Sobek 2006) The large hemiboreal Lake Võrtsjärv (Estonia) constitutes an ideal subject of this type of ecosystem approach for two reasons: -extensive metabolism studies have been carried out since 2009 with monthly sampling of food web components -despite its large surface area (270 km 2 ), L. Võrtsjärv is a very homogeneous system with a continuously mixed water column and little to no differences in temperature, concentrations of nutrients, and oxygen between lake zones (Järvet 2004; Nõges and Tuvikene 2012) It is still unclear whether lakes are autotrophic (NEP > 0) or heterotrophic (NEP < 0). Measuring above-water C fluxes is the most widespread method but: -functional group specific metabolism remains unkown (Staehr et al. 2012) -in alkaline lakes (pH > 8) CO 2 in the water column is partly converted to HCO 3 and CO 3 2- (Hanson et al 2003)

3. Area 270 km 2 Mean depth 2.8 m (max 6 m) WL fluctuation ampl. 3 m Water retention time 1 y Ice cover 135 days Eutrophic (TP 50 μg l -1 ; Chl a 24 μg l -1 ) pH = 8 Compensation depth max 2 m Background 10 km N

4. Methods NEP lake = GPP lake – R lake GPP lake = GPP phytoplankton + GPP macrophytes + GPP epiphytes R lake = R phytoplankton + R macrophytes + R bacterioplankton + R protozooplankton + R metazooplankton + R pfish + R bfish + R benthos

5. Methods Sampling for planktonic groups biomass Samples were collected in 2009-2011 at monthly interval from a pelagic monitoring station near the eastern shore with a Ruttner sampler. Primary production Phytoplankton Integral version of semi empirical model from Arst et al. (2008) GPP is a function of photosynthetically absorbed radiation (PAR) and quantum yield of carbon fixation. Macrophytes and epiphytes In situ GPP of Myriophyllum spicatum L. measured hourly and converted to daily GPP with the following equation from Nõges & Nõges (1998) : PP day = PP hour / (0.23 – (8.9 × 10 -3 DL)) with DL = numbers of hours of daylight.

6. Methods Respiration Phytoplankton Cell-specific respiration rates times the cell number of each species. For filamentous species, the number of cells was obtained by dividing filament length by mean cell length. For colonial species like Microcystis sp., we used Joung et al. (2006) method: Y = 0.00195X + 1731 where Y is the number of cells in a colony and X is the volume of the colony (10 5 µm 3 ). To find cell-specific respiration rates, first we searched for literature values for taxa whose respiration rates are documented (Table 1). If respiration rates were unavailable for a taxon, an allometric regression described in Tang and Peters (1995) was employed instead: R = 0.0068 V 0.88 Where the respiration (R, pL O 2 cell -1 h -1 ) is a function of cell volume (V, µm 3 ). Cell volume was calculated for each taxon according to the Nordic algae database (Hällfors 2004). The O 2 respired value was then converted into carbon units using a respiratory molar quotient of 1 (del Giorgio and Peters 1993) and assuming one mole of gas occupies a volume of 22.4 L at 1 atm pressure. Macrophytes R of submerged macrophytes and their associated epiphytes was calculated using a temperature-dependent empirical regression for macrophyte beds modified after Cornell and Klarer (2008): HRR = 0.57 (0.0121T + 0.0246) Where HRR is hourly respiration rate (g O 2 m -2 h -1 ) and T is temperature (°C). The 0.57 slope represents macrophyte contribution to macrophyte beds community respiration (Middelburg et al. 2005). Hourly O 2 respiration in macrophyte stands was then converted to C daily respiration by using a respiratory quotient of 1 (Williams and del Giorgio 2005). The result was finally multiplied by the lake area covered by submerged macrophytes (15%, Feldmann and Mäemets 2004).

7. Methods Respiration Protozooplankton Respiration was assessed using Fenchel and Finlay (1983) equation: R=0.063 V 0.69 where V stands for individual cell volume (1 µm 3 = 1 pg WW = 10 -6 µg WW). Oxygen volume respired was converted into carbon units (mg C ind -1 h -1 ) using a RQ = 1 which is appropriate for ammonotelic organisms like zooplankton (Ikeda et al. 2000). Molar to volume conversion was 12/22.4 and respiration per day was 24 times the hourly rate. Metazooplankton Calculated on the basis of wet weight, according to Galkowskaya (1980) for rotifers and Suschenya (1972) for other groups. Temperature-dependent corrections were made according to Winberg (1983). Bacterioplankton Calculated with the cell-carbon-content dependent equation from Tang and Peters (1995) and multiplied by bacterial abundance: R = 0.03 C 0.93 Where R is the respiration rate (pL O 2 cell -1 h -1 ) and C is the carbon content of a cell (pg C cell -1 ). RQ = 1 as productive, high-pH aquatic systems where the main substrate for bacterioplankton is produced by phytoplankton, tend to have an RQ around 1 (Berggren et al. 2012). Benthic invertebrates and bacteria Assessed by the following temperature-dependent equation modified after Gudasz et al. (2010): R = 100.0341T + 1.848 Where T is lake temperature (°C). We chose OC mineralization regression calculated in highly eutrophic and shallow (mean depth 2.7 m) Lake Vallentunasjön (Sweden) which trophic and morphometric parameters show strong similarity with those of Lake Võrtsjärv. Fish Fish biomass obtained from the 2009-2011 fishing campaign (Järvalt et al. 2011) was converted into dry weight (DW) biomass (g DW m -2 ), carbon units (g C m -2 ) and respiration (g C m -2 d -1 ) using the conversion factors of 0.2, 0.492 and 0.033, respectively provided by Andersson and Kumblad (2006).

8. Cremona et al. Submitted to Aquatic Sciences phytoplankton bacterioplankton protozooplankton metazooplankton Dynamics of lake-wide planktonic functional groups biomass Results and discussion Typical of food webs dominated by microbial loop organisms (Welker and Walz 1999, Zingel et al. 2007)

9. Cremona et al. Submitted to Aquatic Sciences Gross primary production (GPP) Respiration (R) Dynamics of GPP lake and R lake GPP in Võrtsjärv comparable to other hemiboreal lakes (Canada Finlay et al 2010, Denmark Staehr & Sand-Jensen 2007 ) Results and discussion

10. Functional group Plankton C biomass (10 3 kg C) GPP (10 3 kg C day -1 ) R (10 3 kg C day -1 ) R/R lake (%) Bacterioplankton90 (0-187)-44 (0-90)17 (0-50) Metazooplankton20 (0-158)-6 (8-50)1.5 (0-8) Phytoplankton1 932 (14-6 048)164 (0-618)140 (3-362)36.5 (3-73) Protozooplankton137 (8-565)-55 (4-239)13 (1-52) Benthivorous fish--14 (10-23)8 (1-33) Piscivorous fish--3 (2-4)2 (0-5) Macrophytes-19 (0-122) 10 (3-22)4 (2-11) Epiphytes*-0.04 (0-0.2) Benthic invertebrates and bacteria - 49 (18-160)18 (5-38) Results and discussion Average calculated biomass, primary production and respiration of Lake Võrtsjärv functional groups during the 2009-2011 period (n = 1095) Cremona et al. Submitted to Aquatic Sciences

11. phytoplankton bacterioplankton protozooplankton metazooplankton Calculated lake-wide respiration of plankton functional groups Results and discussion

12. Cremona et al. Submitted to Aquatic Sciences Plankton metabolism Autotrophic (GPP > R) Heterotrophic (GPP < R) Results and discussion

13. Cremona et al. Submitted to Aquatic Sciences Solid line: del Giorgio & Peters (1993) Dashed line: present study Dotted line: Duarte & Agusti (1998) Comparison of plankton respiration Results and discussion

14. Cremona et al. Submitted to Aquatic Sciences Conclusions -Phytoplankton greatest primary producer and consumer. -Planktonic protozoans greatest contributors to consumer metabolism -Planktonic P/R planktonic food web is net heterotrophic and is sustained by macrophyte production -Whole-lake GPP and R values measured with ecosystem approach are the same order of magnitude than values obtained with empirical equations -Issues: ->GPP phytoplankton model does not consider under-ice GPP ->benthic respiration hard to assess ->fish data are not dynamic ->no error assessment