Carbon dioxide reduction by photosynthesis undetectable even during phytoplankton blooms in two lakes

Lakes located in the boreal region are generally supersaturated with carbon dioxide (CO2), which emerges from inflowing inorganic carbon from the surrounding watershed and from mineralization of allochthonous organic carbon. While these CO2 sources gained a lot of attention, processes that reduce the amount of CO2 have been less studied. We therefore examined the CO2 reduction capacity during times of phytoplankton blooms. We investigated partial pressure of CO2 (pCO2) in two lakes at times of blooms dominated by the cyanobacterium Gloeotrichia echinulata (Erken, Sweden) or by the nuisance alga Gonyostomum semen (Erssjön, Sweden) during two years. Our results showed that pCO2 and phytoplankton densities remained unrelated in the two lakes even during blooms. We suggest that physical factors, such as wind-induced water column mixing and import of inorganic carbon via inflowing waters suppressed the phytoplankton signal on pCO2. These results advance our understanding of carbon cycling in lakes and highlight the importance of detailed lake studies for more precise estimates of local, regional and global carbon budgets.

In Erssjön we found a typical summer phytoplankton community for a humic, mesotrophic lake (based on four sampling occasions in 2018).Dominant phytoplankton groups were green algae, cryptophytes and colonial cyanobacteria (20-45% of the total phytoplankton biomass).Phytoplankton biomass was high (8.77-13.54mm 3 L −1 ), with G. semen making up for 0.5-10% of the total phytoplankton community biomass (Supplementary material, Table S1).The number of species ranged from 24 to 30 and Shannon diversity (H') ranged from 0.5 to 1.1.No single species dominated the phytoplankton community during this time.The C phyto :TOC ratio (= phytoplankton share in total organic carbon) in summer 2018 ranged from 5-9%.
The phytoplankton community in Erken from June to October in 2018 was mainly comprised of diatoms, cryptophytes, dinoflagellates and cyanobacteria.Cryptophytes and dinoflagellates dominated the community in June and July, while cyanobacteria took over in August.Once autumn mixing started in mid-September, diatoms dominated the phytoplankton community up to 79% (2018-10-23, Supplementary material, Table S2).Total phytoplankton biomass (maximum: 2.9 mm 3 L −1 ) was 3-6 times lower compared to Erssjön.The number of species ranged from 20 to 43 and Shannon diversity was (H') ranged from 0.47 to 0.92.The C phyto :TOC ratio remained < 5% through all seasons.
Since a relationship between phytoplankton and pCO 2 might be non-linear, we also used an additional approach where we took a closer look at the three periods when algal blooms occurred: May/June and August 2017 (Erssjön) and August 2018 (Erken).Using the Kruskal-Wallis test, we compared pCO 2 during bloom periods (G.semen abundance and chlorophyll a maximum respectively) to pCO 2 sampled two weeks before (= pre-bloom) and after (= post-bloom) the blooms were detected.Applying this approach for Erssjön, we found that pCO 2 was similar before, during and after the G. semen bloom in May/June 2017 (Kruskal-Wallis test, chisquared = 7.62, df = 3, p value = 0.06, Fig. 3a).During the bloom in August 2017, pCO 2 appeared to be significantly higher after the G. semen bloom compared to before and during the bloom was observed (Kruskal-Wallis test, chi-squared = 8.74, df = 3, p value = 0.03, Fig. 3b).However, the post-hoc test revealed that pCO 2 during this bloom was no different from before and after the bloom (Dunn-test with Bonferroni correction for p values, all p values > 0.05, Fig. 3b), indicating that the significant result from the Kruskal-Wallis test was due to a type-I error.
Also, in Erken, pCO 2 remained the same before, during and after the G. echinulata bloom in August 2018 (Kruskal-Wallis test, chi-squared = 0.62, df = 2, p value = 0.72, Fig. 3c).Since chlorophyll a concentration was quite high two weeks before the G. echinulata bloom (2018-07-25, "pre-bloom" in Fig. 3c), we also ran a Kruskal-Wallis test including 2018-07-11 as the pre-bloom period, to account for either a longer bloom period or two separate blooms happening on 2018-07-11 and 2018-07-25.Still, neither the pre-bloom nor the post-bloom pCO 2 was higher or lower than pCO 2 during the blooms (Kruskal-Wallis test, chi-squared = 1.05, df = 3, p value = 0.79).pCO 2 and its relation physical lake variables.During sampling, water temperatures at 1-m depth in Erssjön ranged from 5 to 20 °C in 2017 and from 5 to 24 °C in 2018, with summer temperatures (June -August) > 16 °C (Supplementary material, Table S3).Air temperatures ranged from − 1 to 21 °C (2017) and − 1 to 28 °C (2018).Wind speed ranged from 0.2 to 8.4 m 1 s −1 (2017) and 0.2 to 6.4 m 1 s −1 (2018), the average wind speeds being 2.3 and 2.4 m 1 s −1 for 2017 and 2018 respectively.In Erken, water temperatures ranged from 6 to 24 °C (18 -24 °C between June-August), air temperatures from 2 to 27 °C and wind speed from 0.4 to 8.3 m 1 s −1 (average: 3.7 m 1 s −1 ).We observed no significant correlations between pCO 2 and any of the described above physical variables in the two lakes (Supplementary material, Table S4).In 2018, there was a trend towards decreasing pCO 2 with increasing wind speed in Erssjön, but very little of the overall variation in pCO 2 was explained by this (R 2 = 0.06).Furthermore, water column stability (expressed as the Schmidt number) and gas transfer velocity for water-air gas exchange (expressed as k 600 ) were not significantly correlated with pCO 2 either.

Discussion
In this study we investigated whether the occurrence of phytoplankton blooms can suppress pCO 2 in lakes.We studied two different lakes, one in which cyanobacterial (G.echinulata) blooms occurred (Erken), and another one in which we observed blooms of the raphidophyte G. semen (Erssjön).Contrary to what we expected the phytoplankton signal was not detectable as short-term fluctuations in pCO 2 during those times, which indicates that other factors are more important for pCO 2 in those lakes.
One criterium for phytoplankton to impact lake pCO 2 is a high enough biomass so that photosynthesis dominates over bacterial respiration and mineralization of carbon 10 .Available C phyto :TOC ratios were > 5% in Erssjön during summer of 2018.Since this is a threshold value for when phytoplankton biomass potentially can have a detectable effect on CO 2 10 , we would have expected that a phytoplankton bloom in this lake caused a decrease in pCO 2 .Since our hypothesis could not be supported, an interesting question in this context is the identity of the bloom forming phytoplankton species, especially the proportion of mixotrophic species.Erssjön's phytoplankton community is typical for a boreal brown water lake with a low pH, with cryptophytes, chrysophytes, euglenids and chlorophytes dominating in the summer of 2018.Some of these are mixotrophic species (Uroglena sp., Dinobryon sp., Gymnodium sp., Perdinium sp. and Ceratium sp. 25 , see Supplementary material, Table S5) and could potentially significantly contribute to heterotrophic respiration instead of autotrophic carbon fixation in boreal lakes 26 , especially in a warming climate 27 .This could be one contributing factor as to why CO 2 in many www.nature.com/scientificreports/boreal brown water lakes is seemingly not impacted by photosynthetic processes and remains supersaturated throughout the year, even though theses lakes demonstrate a high phytoplankton biomass with bloom conditions.In Erken, the total phytoplankton biomass remained relatively low (< 2 mm 3 L −1 ) during most of the year, which is below the C phyto :TOC ratio of 5% that Engel et al. 10 identified as a threshold for a detectable phytoplankton influence on lake CO 2 .However, a phytoplankton bloom still occurred (G.echinulata in August), where also chlorophyll a concentrations were higher than 10 µg L −1 (total phytoplankton biomass: 1.12 mm 3 L −1 ).However, again, these bloom conditions did not leave a detectable signal on the pCO 2 .The lack of a direct relation between phytoplankton and pCO 2 in Erken might be a result of measuring phytoplankton and pCO 2 at different sites.Erken is a relatively big lake that is strongly wind exposed with frequent lake water mixing, causing a patchy phytoplankton distribution, especially regarding large floating G. echinulata colonies.
Wind exposure is not only affecting the phytoplankton distribution in a lake but also pCO 2 .Previous studies have shown that wind-induced upwelling and vertical mixing affect the transport of CO 2 through the water column 28,29 , as well as the CO 2 flux to the atmosphere 30 .It is possible that wind suppresses the phytoplankton signal on lake pCO 2 , because CO 2 at the lake surface, where phytoplankton are photosynthesizing and, thus, consuming CO 2 , is mixed with CO 2 from waters from below.This may be especially true at Erken, which is highly susceptible to wind mixing, even causing perturbations in the thermal stratification during summer 31 .Furthermore, wind exposure may explain why lake pCO 2 does not increase in autumn after mixing starts in this lake, even though this is typically observed in eutrophic lakes when deep-water, CO 2 water mixes with surface oxygen-rich water 32 .
However, the G. echinulata bloom in Erken occurred mostly at low wind speeds (1.2-5.4 m 1 s −1 , mean: 2.9 m 1 s −1 ) when water mixing is low, as did the G. semen blooms in Erssjön (0.5-5.1 and 0.4 -2.8 m 1 s −1 in May and June respectively).Consequently, CO 2 import from deeper waters should be low.On the other hand, the gas transfer velocity of CO 2 from water to the atmosphere is lower at low wind speeds, which could lead to higher observed pCO 2 than would be expected during periods of high photosynthetic activity.Thus, the interaction between wind-controlled processes in the water column may be why pCO 2 and physical lake variables do not correlate in our study.
Besides mixing, inorganic carbon import via groundwater and river inflow could have affected pCO 2 in both lakes, which is common for lakes in the studied geographical region 3 .This could for example explain the increase of pCO 2 in Erssjön in autumn in 2017 and 2018, as this is when autumn mixing starts, precipitation events become more common and water in-and outflow from the lake increase.Furthermore, Erssjön is a rather small lake with a potentially shorter water retention time than Erken (7 years), so hydrological factors contributing to CO 2 supersaturation might be dominating over biological processes.
Even if blooms caused by G. semen or other phytoplankton species lead to a decrease in lake pCO 2 , it is unclear whether this would have a short-term or long-term effect on lake CO 2 emissions.Autochthonous carbon is preferably used by bacteria and often gets re-mineralized before it can sink to the lake bottom and contribute to the fixed carbon in the sediment 33,34 .Erssjön's pCO 2 increased in autumn in 2017 and 2018, indicating that phytoplankton biomass may contribute to internal lake carbon respiration and thus CO 2 emissions from the lake when being degraded.In order to understand the ecosystem effects, we would therefore need to monitor G. semen blooms and phytoplankton in general more closely, both regarding their biomass and the sedimentation of organic material before, during and after a bloom.
Sampling frequency is also critical for capturing times when G. semen migrates vertically through the water column during the day 35 .During migration, it easy to underestimate G. semen densities by sampling too early or too late during the day.It is also known that the carbon flux has high diel and seasonal variability 32,36 , with diel variations being especially pronounced during mixing events 32 .Even though the floating chambers were deployed for around 24 h, deployment and measurement times were not consistent between samplings (ranging from ~ 8:00 to 20:00, see Supplementary material, Table S6).This means that changes in pCO 2 during the day may not always have been captured completely.Thus, it is likely that the pCO 2 measurements at the surface of the lakes caused an under-or overestimation of pCO 2 for our sampling dates due to the time of sampling.
In summary, our results show that neither G. semen nor G. echinulata blooms were associated with decreases in pCO 2 in two Swedish boreal lakes.It is likely that physical factors, such as wind induced water column mixing and import of inorganic carbon via groundwater inflow and runoff, suppress the phytoplankton signal on pCO 2 .A higher sampling frequency is necessary to further study the dynamics between phytoplankton blooms and lake CO 2 concentrations, as phytoplankton blooms can occur rapidly and disappear within days.Further studies should focus on monitoring phytoplankton biomass and pCO 2 at higher frequency to capture diel variations, and include sedimentation rates of autochthonous organic matter and daily CO 2 fluctuations to determine if there is a long-term effect of phytoplankton on lake carbon fluxes.Another interesting aspect to study is the species composition of phytoplankton blooms, since the degree of mixotrophy could affect the relationship between phytoplankton and pCO 2 .

Methods
Sampling sites.Sampling was performed in a mesotrophic brown water lake (Erssjön) in the Bäveån catchment in Västergötland, Sweden (58°22′16.5"N,12°09′40.3"E)and in a mesotrophic non-humic lake (Erken) in the Broströmmen catchment in Uppland, Sweden (59°50′26.35"N,18°37′39.75"E).Background information about the two lakes are publicly available at the SITES website (https:// www.field sites.se/ en-GB/ sites-thema ticprogr ams/ lakes-in-sites-44856 978).Erssjön is situated 73 m above sea level, has an area of 0.061 km 2 and a maximum depth of 4.5-5 m.The surrounding area is mostly forest and some agricultural land.The lake is dimictic, with anoxic periods during summer stratification.Samples were taken from March to October in 2017 ( Erken is 13 m above sea level, has an area of 24 km 2 and a maximum depth of 21 m.The surrounding area is mostly forest, water and some agricultural land and pasture.The lake is dimictic.Samples were taken from June to October in 2018 (8 CO 2 samplings, every 2-4 weeks).Phytoplankton densities and chlorophyll a are monitored through weekly samplings conducted by the Erken Laboratory.CO 2 measurements.Carbon dioxide concentrations were measured with floating chambers designed according to Bastviken et al. 37 .In each lake, 4 floating chambers were set along 3 transects from the lake shore towards the center (Fig. 4, check Supplementary material, Table S7 for coordinates).The lake water depths below the floating chambers ranged from 0.3 to 1.9 m (Erssjön) and 0.6 -4.7 m (Erken).After a deployment of 18-28 h (Supplementary material, Table S6) a subsample of the headspace was taken with a syringe (3 × 60 mL) and transferred into a gas-tight, sealed glass vial through a needle (0.5 mm; 25 gauge).Samples were measured on a gas chromatograph autosampler.These headspace CO 2 concentrations should be close to equilibrium and pCO 2 was calculated according to Henry's Law.This data is publicly available upon request on the SITES website (www.field sites.se).

Phytoplankton bloom identification.
Phytoplankton blooms in lake surface waters were identified by analyzing chlorophyll a concentration, phytoplankton biomass and phytoplankton densities 38,39 .Sampling for those variables took place between 9:00 and 12:00 at the two lakes.A chlorophyll a threshold of 10 µg L −1 is often used to indicate a phytoplankton bloom 23,40 .In addition, phytoplankton biomass is often monitored to identify blooms of harmful algal species (HABs), e.g.toxic cyanobacteria 40,41 .To identify phytoplankton blooms in the two study lakes, we decided to use a chlorophyll a threshold of 10 µg L −1 to screen for phytoplankton blooms, as is recommended for moderately deep lakes in Europe 23 .For Erken, chlorophyll a data was available from the weekly monitoring program upon request (Erken Laboratory, Uppsala University, Sweden, https:// www.ieg.uu.se/ erken-labor atory/ lake-monit oring-progr amme/), and is now also available on the SITES Data portal: (https:// meta.field sites.se/ objec ts/ NT59B PT70C e7h1h uzA0x Sc1c).For chlorophyll analysis, water was filtered through a Whatman GF/C filter.Chlorophyll was extracted with 90% acetone and absorbance measured with a spectrophotometer at 750, 664, 647 and 630 nm according to the Swedish standard SS028146.
Since reliable chlorophyll a data from Erssjön was not available, we also identified blooms by determining densities of G. semen (qPCR) and G. echinulata (phytoplankton monitoring data).For densities the following thresholds for a bloom identification were used: 2,000 cells mL −1 or 0.2 mm 3 L −1 for G. echinulata which is the www.nature.com/scientificreports/lowest WHO threshold for dangerous cyanobacteria blooms 40 , based on the fact that these species are potentially toxic 42,43 , and 100,000 cells L −1 for G. semen since this species has an unusual big cell size 44 .
DNA analysis for the identification of G. semen densities.In Erssjön, a DNA sample was taken every 2-4 weeks from the Southern side of the mesocosm platform (N 58.371322°, E 12.161074°, see Fig. 4a) during 2017-05-15 -2017-10-16 and 2018-05-15 -2018-11-01.An integrated water sample (0-1 m) of 10 L was taken and a subsample of 2 L filtered through a membrane filter (0.2 µm pore size, 47 mm diameter).The filter was then folded, put into a 2 mL cryotube and stored at − 80 °C.DNA was extracted with the Qiagen DNeasy PowerSoil Kit according to the kit's instruction manual.The DNA concentrations were quantified using Pico-Green, measured on a Tecan Spark plate reader (Tecan, Switzerland) and found to be high enough for further analysis (~ 3-20 µg DNA µL −1 ).
For determining the G. semen abundance, we used qPCR with the specific primers developed by Johansson et al. 45 .The DNA was diluted 20 × and the master mix done with SYBR Green.The qPCR was run on a CFX96 Touch Real-Time PCR Detection System (Bio-Rad, USA) with the following cycle conditions: 2 min at 90 °C, 40 cycles at 95 °C for 15 s, 40 cycles at 60 °C for 15 s and 40 cycles at 72 °C for 15 s.For each sample, three technical replicates were measured and the average copy number per vegetative cell was used for quantification of G. semen cells.To determine the copy number per vegetative cell, we measured the extracted and 10 × diluted DNA of three samples of isolated and washed G. semen vegetative cells (40 cells per sample) from a G. semen culture established from a lake in Northern Uppland (Siggefora, culture SF1A8, established by Ingrid Sassenhagen).More details on this procedure is available in Münzner et al. 46 .The copy number per cell ranged from 171,500 to 304,770, with an average copy number of 243,596 (standard deviation: 54,605) per G. semen vegetative cell.

Phytoplankton community composition.
To get a better understanding on phytoplankton dynamics we also determined the phytoplankton biomass and community composition.In Erssjön we sampled during four dates in 2018 (July 10, July 24, August 14, September 1).Phytoplankton samples were taken from surface water samples (~ 0.5 m depth) and a subsample 100 mL was fixed with Lugol.Samples were stored at 4 °C in the dark before analysis.Phytoplankton samples were acclimatized to room temperature (24 h) and were counted with the Utermöhl method with an inverted microscope (Leica DMIL LED fluo) after settling for at least 12 h in a 10 mL chamber.We did a whole chamber count at 40 × magnification for phytoplankton > 100 µm (e.g.colonial algae), counts of diagonals (1 or 2) at 200 × magnification until a cell count of at least 200 cells (> 20 µm) was reached, and 10 random field counts at 400 × magnification.For each identified species, cell length and width were measured for one individual and used for biomass calculations.Phytoplankton shapes and biovolume formulas were determined according to Hillebrand et al. 47 .Phytoplankton diversity (H') and evenness (e h ) were calculated using the Shannon-Wiener Index.
For Erken, we used publicly available plankton data from the Erken Laboratory (Uppsala University, Sweden, https:// www.ieg.uu.se/ erken-labor atory/ lake-monit oring-progr amme/, data available upon request).Phytoplankton samples used in this data set were collected the following way: phytoplankton samples were collected at the deepest point of the lake with an integrated water sampler ("Ramberg tube") in 2 m intervals.The samples were mixed together according to their proportion to the total lake volume (all samples if the lake was fully mixed, epilimnion and hypolimnion samples mixed separately if the lake was stratified).Then, a 100 mL subsample of the integrated sample (only epilimnion sample if the lake was stratified) was taken, fixated with a few drops of Lugol and stored at 4 °C before further analysis.Phytoplankton were identified and quantified with an inverted light microscope according to the quality standards (SS- EN 15,204:2006) approved by the Swedish Environmental Protection Agency (EPA).
From the phytoplankton data we calculated the C phyto :TOC ratio to identify a previously described threshold when phytoplankton dynamics become detectable in lake waters 10 .For C phyto a conversion factor of 0.15 was chosen according to Engel et al. 10 .For TOC (total organic carbon) we used data on dissolved organic carbon (DOC).DOC has been shown to stand for 97% of the TOC in boreal lakes 48 , thus we assumed DOC to be equal to TOC in our study lakes.Since carbon monitoring data were not available for Erssjön, we used an average of previously reported values (22.33 mg DOC L −1 ) by Groeneveld et al. 49 .

Lake physical variables.
Publicly available data collected by SITES (SITES Data portal: https:// data.field sites.se/ portal/) of air temperature, water temperature at 1-m depth, wind direction and wind speed were used.For analyses, average values of those variables over the total deployment time of the chambers at each date were calculated.Schmidt number Sc was calculated according to Wanninkhof et al. 50, and for piston velocity k 600 , the formula for low wind speeds by Cole and Caraco 51 was used.

Statistics.
All data were analyzed with R 4.1.2.Group comparisons of CO 2 measurements within transects with the Kruskal-Wallis test (post-hoc test: Dunn-test with Bonferroni correction for p values) showed that pCO 2 was significantly higher in the chambers closest to the shore compared to the chambers further away from the shore, both in Erssjön (chi-square = 9.18, df = 3, p = 0.03) and Erken (chi-square = 8.43, df = 3, p = 0.04).However, even though pCO 2 decreased with increasing distance to the shore (linear regression analysis) in Erssjön (p < 0.001, R 2 = 0.02, n = 316) and Erken (p < 0.05, R 2 = 0.05, n = 104), almost none of the overall variation in pCO 2 was explained by that.Following this, we used the average pCO 2 of each transect for further analyses (n = 3 per lake per sampling).
Shown regressions and correlations are based on linear relationships.Since the distribution of all variables was skewed, they were log-transformed.Changes in pCO 2 over sampling dates in each lake for each year were assessed with the Kruskal-Wallis test.The Kruskal-Wallis test was also used for comparisons of pCO2 before,

Figure 1 .
Figure 1.Lake pCO 2 and G. semen densities based on qPCR results in Erssjön in 2017 (a) and 2018 (b).For each date, results from 3 sampling locations (pCO 2 measurements, 4 replicates per sampling spot) or one sampling location (G.semen abundance) are shown.The boxes symbolize 50% of the data and the line is the median.Boxplots = pCO 2 , grey triangles = G. semen abundance, dashed line = pCO 2 equilibrium (400 µatm), dotted line = cell number threshold indicating a phytoplankton bloom (100,000 cells L −1 ).Note the different scales in cell densities in (a) and (b).

Figure 2 .
Figure 2. Lake pCO 2 and chlorophyll a concentration in Erken in 2018.For each date in the figure, results from 3 sampling locations (pCO 2 measurements, 4 replicates per sampling spot) or one sampling location (chlorophyll a) are shown.The boxes symbolize 50% of the data and the line is the median.Chlorophyll a concentration was measured from an integrated water sample of either the epilimnion (2018-06-13 until 2018-09-09) or the whole water column after autumn stratification started (2018-09-28 -2018-10-26).Boxplots = pCO 2 , grey triangles = chlorophyll a, dashed line = pCO 2 equilibrium (400 µatm), dotted line = chlorophyll a threshold indicating an algal bloom (10 µg L −1 ).

Figure 3 .
Figure 3. Lake pCO 2 before, during and after observed and potential blooms of G. semen (Erssjön) and G. echinulata (Erken).In May 2017 in Erssjön, no G. semen density data is available for the potential pre-and postbloom periods.Letters signify the results of the post-hoc Test (Dunn-test, p values adjusted with the Bonferroni method) for the Kruskal-Wallis test results.bloom GS = G. semen bloom, bloom GL = G. echinulata bloom.