Salinity as a key control on the diazotrophic community composition in the southern Baltic Sea
- 1Department of Biology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
- 2Danish Institute for Advanced Study, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark
Correspondence: Christian Furbo Reeder (email@example.com)
Over the next decade, the Baltic Sea is predicted to undergo severe changes including decreased salinity due to altered precipitation related to climate changes. This will likely impact the distribution and community composition of Baltic Sea dinitrogen-fixing (N2-fixing) microbes, among which heterocystous cyanobacteria are especially adapted to low salinities and may expand to waters with currently higher salinity, including the Danish Strait and Kattegat, while other high-salinity-adapted N2 fixers might decrease in abundance.
In order to explore the impact of salinity on the distribution and activity of different diazotrophic clades, we followed the natural salinity gradient from the eastern Gotland and Bornholm basins through the Arkona Basin to the Kiel Bight and combined N2 fixation rate measurements with a molecular analysis of the diazotrophic community using the key functional marker gene for N2 fixation nifH, as well as the key functional marker genes anfD and vnfD, encoding for the two alternative nitrogenases.
We detected N2 fixation rates between 0.7 and 6 nmol N L−1 d−1, and the diazotrophic community was dominated by the cyanobacterium related to Nodularia spumigena and the small unicellular, cosmopolitan cyanobacterium UCYN-A. Nodularia was present in gene abundances between 8.07 × 105 and 1.6 × 107 copies L−1 in waters with salinities of 10 and below, while UCYN-A reached gene abundances of up to 4.5 × 107 copies L−1 in waters with salinity above 10. Besides those two cyanobacterial diazotrophs, we found several clades of proteobacterial N2 fixers and alternative nitrogenase genes associated with Rhodopseudomonas palustris, a purple non-sulfur bacterium. Based on principal component analysis (PCA), salinity was identified as the primary parameter describing the diazotrophic distribution, while pH and temperature did not have a significant influence on the diazotrophic distribution. While this statistical analysis will need to be explored in direct experiments, it gives an indication for the future development of diazotrophy in a freshening Baltic Sea with UCYN-A retracting to more saline North Sea waters and heterocystous cyanobacteria expanding as salinity decreases.
The Baltic Sea (Fig. 1) is a marginal, brackish sea characterized by a natural salinity gradient increasing from the northeast to the southwest. The Baltic Sea covers an area of 415 000 km2 with a permanent halocline in the Baltic Sea Proper, preventing vertical mixing, and oxygen (O2)-depleted waters in the deeper basins and coastal systems, accompanied by the occasional accumulation of hydrogen sulfide (H2S) and ammonium (NH) below the chemocline (Conley et al., 2002; Hietanen et al., 2012; Lennartz et al., 2014). It is further challenged by a high land-derived influx of phosphorus, leading to a substantial internal surface water and sedimentary phosphorus load (Gustafsson et al., 2017; Stigebrandt and Andersson, 2020). Prior studies have shown that the Baltic Sea experienced a 10-fold increase in O2-depleted areas over the last 115 years, covering an area of 12 000–70 000 km2, making it one of the ocean areas most severely affected by deoxygenation (Diaz and Rosenberg, 2008; Reusch et al., 2018). Between 1871 and 2013, the Baltic Sea showed an increase in temperature of 0.1 ∘C decade−1, exceeding the average global trend of about 0.06 ∘C decade−1 (Reusch et al., 2018; Rutgersson et al., 2014), and decreased salinity (1–2 kg−1) (Liblik and Lips, 2019). Nitrogen (N) deposition rates are now among the highest in marine areas (Reusch et al., 2018). The resulting eutrophication severely affects sensitive coastal areas, resulting in high pelagic production, frequent events of anoxia, and decreased biodiversity (Breitburg et al., 2018; Carstensen et al., 2014; Maar et al., 2016; Reusch et al., 2018; Rutgersson et al., 2014). In this context, the Baltic Sea has been described as a “time machine” for how future oceans will respond to climate change (Reusch et al., 2018), making it an ideal environment to investigate biological fixation of dinitrogen gas (N2 fixation) in response to such changes.
N2 fixation is the primary external source of new N to life in the ocean and plays a crucial role for primary production and thus carbon dioxide (CO2) uptake from the atmosphere (Carpenter and Capone, 2008; Gruber, 2005). Specialized organisms, called diazotrophs, carry out this highly energy-demanding process. The diversity of diazotrophs is not easy to describe, as those organisms spread across the microbial tree of life and are found in both the bacterial and archaeal domains (Zehr et al., 1998). N2 fixation is catalyzed by an enzyme complex, the nitrogenase, which exists in three different subtypes: the molybdenum (Mo) iron (Fe) type referred to as Nif, the vanadium (V) Fe type called Vnf, and an Fe–Fe type called Anf (Chisnell et al., 1988; Robson et al., 1986). The different metal cofactors are essential in the context of the redox sensitivity of the three nitrogenases. Mo is preferentially available in the presences of at least traces of O2 contrary to V and Fe, which are more soluble and thus available under anoxic conditions (Bennett and Canfield, 2020; Bertine and Turekian, 1973; Crusius et al., 1996; Dixon and Kahn, 2004; Morford and Emerson, 1999). The differential availability of those trace metals along redox gradients might have played a role in the evolutionary development of those nitrogenase types (Anbar, 2008; Mus et al., 2019), and their distribution might change in a future ocean impacted by acidification, deoxygenation (Keeling et al., 2010; Löscher et al., 2014; Schmidtko et al., 2017; Stramma et al., 2008), and desalination (Olofsson et al., 2020). To date, most studies focused mainly on Nif-type nitrogenases in the marine environment, while Vnf and Anf nitrogenases were often overlooked. Molecular detection of the nifH gene does not fully recover the diversity of vnfH and anfH, possibly resulting in an underestimation of alternative nitrogenases in the environment (Affourtit et al., 2001; Farnelid et al., 2009, 2013; Man-Aharonovich et al., 2007; Steward et al., 2004; Zehr et al., 1995). Nonetheless, the few available studies focusing on alternative nitrogenases identified them to be abundant and diverse and suggested them to play a role for N2 fixation in various ecosystems, including the upper water column of the ocean, O2-depleted waters, and Baltic Sea sediments (Bellenger et al., 2011, 2014; Betancourt et al., 2008; Christiansen and Löscher, 2019; Farnelid et al., 2009; Loveless et al., 1999; McRose et al., 2017; Tan et al., 2009; Zehr et al., 2003; Zhang et al., 2016).
In the Baltic Sea, N2 fixation is considered to mainly take place in sunlit surface waters carried out by three genera of heterocystous cyanobacteria: Aphanizomenon spp., N. spumigena, and Anabaena spp. (now referred to as Dolichosperum spp. (Klawonn et al., 2016; Wacklin et al., 2009), all of them containing the classic Nif nitrogenase (Janson et al., 1994; Leppanen et al., 1988) and contributing massively to N2 fixation with rates of up to 115–295 nmol N L−1 d−1 (Larsson et al., 2001). At the same time, cyanobacteria consume only a fraction of the N they fix with estimates in the range of 33.33–85.72 nmol N L−1 d−1 (Janson et al., 1994; Larsson et al., 2001; Wasmund, 1997). Using an approach based on elemental analyzer–isotope ratio mass spectrometry (EA-IRMS), Klawonn et al. (2016) measured N2 fixation rates up to 300 ± 216 nmol N L−1 d−1 and, based on cell-specific measurement of Aphanizomenon spp. and N. spumigena, revealed that they release up to 35 % of fixed N, translating into a substantial fraction of fixed N leaking out available for other primary producers (Ploug et al., 2010, 2011). In addition, low rates of N2 fixation (0.44 nmol N L−1 d−1) have been described in anoxic waters of the Baltic Sea (Farnelid et al., 2013). These rates were accompanied by a highly diverse Nif-containing heterotrophic diazotroph community at and below the chemocline in anoxic NH-rich waters (Farnelid et al., 2013). Heterotrophic diazotrophs were closely related to those in other O2-depleted marine system regions including the eastern tropical South (ETSP) and North Pacific (ETNP), the Arabian Sea (AS), and an anoxic basin in the Californian Bight (Fernandez et al., 2011; Hamersley et al., 2011; Jayakumar et al., 2012, 2017; Löscher et al., 2014). Non-cyanobacterial diazotrophs have been found to fix N2 actively. However, it is still inconclusive what regulates and controls their N2 fixation activity.
Over the last 3 decades, the Baltic Sea has experienced a trend of freshening in the range of 1–2 kg−1 in surface waters (Liblik and Lips, 2019) or between 0.4 and 1.2 (Saraiva et al., 2019). Earlier studies suggested that salinity impacts the diazotrophic community composition and the activity of nitrogenases in pure cultures of Azotobacter sp. marine microbial mats and estuaries (Dicker and Smith, 1981; Marino et al., 2006; Severin et al., 2012). Surface salinity in the Baltic Sea ranges between 0 and 10 (Fig. 1), making it one of the major drivers for microbial composition and distribution in the Baltic Sea (Dupont et al., 2014; Olofsson et al., 2020; Wulff et al., 2018). Typically, Aphanizomenon spp. dominate less saline waters (e.g., Bothnian Sea) and grow best with salinities around 5 (Lehtimäki et al., 1997). Aphanizomenon spp., however, have also been frequently reported to grow at salinities reaching up to 5–8 such as in the northern Baltic Proper (Olofsson et al., 2020). N. spumigena prefers the higher-salinity waters in the southern part (e.g., the southern Baltic Proper) with an optimum growth in salinities of 8–10 (Lehtimäki et al., 1997; Rakko and Seppälä, 2014). Additionally, the small, unicellular cyanobacterial symbiont UCYN-A has been detected in the Baltic Sea (Bentzon-Tilia et al., 2015). This cosmopolitan diazotroph has previously been shown to be abundant throughout most marine systems (Tang et al., 2019; Zehr et al., 2016) and to substantially contribute to N2 fixation rates (Martínez-Pérez et al., 2016; Mills et al., 2020). However, the factors controlling the biogeography of UCYN-A are poorly understood. However, the latest study suggested salinity as having a positive correlation with UCYN-A biogeography (Li et al., 2021). These observations indicate potential changes in the cyanobacterial composition in future freshening events (Olofsson et al., 2020; Wasmund et al., 2011). To now explore the impact and importance of salinity for diazotrophy in the Baltic Sea and in order to complement existing datasets on N2 fixation from high-productivity seasons, we carried out a survey including chemical profiling and rate measurements in the low-productivity fall season. The focus of this study is a molecular genetic assessment of the diazotrophic community diversity and genetic activity including heterocyst and unicellular cyanobacteria, heterotroph diazotrophs, and diazotrophs carrying alternative nitrogenase genes. In addition, we compared our data to those available to be able to predict the future distribution of Baltic Sea diazotrophs and N2 fixation rates.
2.1 Seawater sampling
Samples were collected during the cruise AL528 using the German research vessel RV Alkor from 17 to 28 September 2019 along a transect through the major basins of the Baltic Sea (see Fig. 1 for a cruise plan and Table S2 for an overview of all stations). Specifically, samples were collected at a station in the Kiel Fjord (KB06), one in the Arkona Basin (H21), four stations in the Bornholm Basin (BB08, BB15, BB23, BB31), and four in the eastern Gotland Basin (GB84, GB90a, GB107, GB108) at water depths between 3 and 115 m (m) using a 10 L Niskin bottle rosette equipped with a conductivity–temperature–depth (CTD) sensor. Water for dissolved inorganic nitrogen NOx (nitrate (NO) + nitrite (NO)) was collected from the Niskin bottles, filtered through an acid-washed 0.8 µm cellulose acetate filter (Sartorius™) using a syringe, and stored in 20 mL scintillation vials at −20 ∘C until analysis. Samples for PO analysis were filtered through a 200 µm mesh to avoid contamination with large zooplankton. Samples were filled in 20 mL scintillation vials and stored at −80 ∘C until analysis. NOx and PO samples were analyzed on a SKALAR SANplus analyzer (Thermo Fisher, Waltham, US) according to Grasshoff (1999) with a detection limit of 0.05 µmol N L−1 for NOx and 0.03 µmol P L−1 for PO. Nutrient samples were taken in triplicates and handled with nitrile gloves, and all equipment was rinsed with Milli-Q water between stations to avoid contamination. Samples for dissolved inorganic carbon (DIC) were collected by filling triplicates of 12 mL Exetainers bubble-free at stations KB06, H31, H21, and BB15. Samples were fixed with 20 µL of a saturated mercury chloride solution and stored at room temperature until analysis. DIC measurements were carried out using a 2 mM NaHCO3 solution as standard and as described previously (Hall and Aller, 1992). From all stations and depths 0.5 to 1 L of seawater was collected from Niskin bottles and immediately filtered onto 0.22 µm pore size membrane filters (Millipore, Bilaterica, USA; exact seawater volumes were constantly recorded); filters were stored at −80 ∘C until DNA extraction and further analysis.
2.2 15N2 and 13C seawater incubations
N2 and C fixation rates were determined using stable isotope labeling at KB06, H21, BB15, BB08, and GB107 at water depths between 3 and 41 m. We used the bubble addition method (Montoya et al., 1996) to ensure comparability to previous studies from the Baltic Sea. Triplicate water samples were filled from Niskin bottles into 2.4 L glass bottles until top-filled (Schott-Duran, Wertheim, Germany). To each incubation bottle, 1 mL 15N2 gas (15N2 98 % + lot no. I-16727, Cambridge Isotope Laboratories, Inc., USA) and 1 mL H13CO3 (1 g 50 mL−1 Sigma-Aldrich, Saint Louis Missouri US) was added through an airtight septum, and bottles were inverted to ensure mixing with final calculated concentrations of 0.8 atom % 15N2 and 10 µg mL−1 H13CO3 (approximately 3.8 atom %). After an incubation time of 24 h, samples were filtered onto pre-combusted GF/F filters (GE Healthcare Life Sciences, Whatman, USA). A parallel set of triplicate samples was collected from each sampling depth for determining the natural abundance of N and C isotopes in the particulate organic material. Filters were stored at −20 ∘C until further analysis. Filters were then acidified and dried in an oven at 65 ∘C. Dried filters were analyzed on an Elemental Analyzer Flash EA 1112 series (Thermo Fisher) coupled to an isotope ratio mass spectrometer (Finnigan Delta Plus XP, Thermo Fisher).
2.3 Molecular methods
For nucleic acid extraction, 0.22 µm pore size Millipore membrane filters (Millipore, Bilaterica, USA) were flash-frozen in liquid N and subsequently crushed. DNA was purified with the MasterPure Complete DNA and RNA purification Kit (Lucigen, Wisconsin, US) according to the manufacturer's protocol, with the minor modification of using 1 mL of lysis buffer to completely cover the filter pieces. RNA was purified using the Qiagen AllPrep DNA/RNA Mini Kit (Qiagen, Hilden, Germany). The remaining DNA was removed with the gDNA wipeout mix, and a cDNA library was constructed using the QuantiTect Reverse Transcription Kit (Qiagen, Hilden, Germany) with the supplied RT primer set. The nucleic acid concentration and quality were checked spectrophotometrically on a MySpec spectrofluorometer (VWR, Darmstadt, Germany).
A total of 15 DNA samples were amplified for nifH using nested PCR with primers and PCR conditions as described in Zani et al. (2000). The anfD and vnfD were amplified using a nested PCR with primers and conditions as described in Bellenger et al. (2014) and McRose et al. (2017). Amplicons were TOPO TA-cloned (Topo TA cloning Kit for sequencing, Thermo Fisher Scientific, Waltham, US) and Sanger-sequenced. Sequencing was carried out at the Institute of Clinical Molecular Biology in Kiel, Germany. Samples for nifH and anfD/vnfD amplification were the same as the ones for which N2 rate measurements were carried out (KB06, H21, BB15, BB08, and GB107 between 3 and 41 m; see Table S1).
Sequences were quality-checked and trimmed with BioEdit (Hall, 1999). The nifH sequences were trimmed to 321 bp and anfD/vnfD to 591 bp. This resulted in 182 nifH and 69 anfD/vnfD amplicon sequences. Sequences were BLASTX-searched against the NCBI database. A reference library was created, and sequences with lower than 80 % identity were discarded. Sequences were aligned in MEGAX (Kumar et al., 2018), and a maximum likelihood tree was constructed using 1000 bootstraps. To explore the overall microbial diversity, 23 samples from Kiel Fjord (station KB06, depth 5 and 10 m), Arkona Basin (station H2, depth 4, 12, 42 m; station H31, depth 4 and 12 m), Bornholm Basin (station BB23, depth 4, 48, 85 m; station BB15, depth 7, 41, 65 m; station BB08, depth 5 and 10 m), and eastern Gotland Basin (station GB84, depth 9, 29, 110 m; station GB107, depth 8, 40, and 112 m; station GB108, depth 10 and 115 m) were sent to amplicon sequencing of the 16s rDNA V1V2 region using Illumina HiSeq technology. Depths were chosen based on the water column chemistry (halocline, oxycline, oxygen minimum zones, and chlorophyll peaks). Sequencing was carried out by the Institute of Clinical Molecular Biology in Kiel, Germany. Raw reads were trimmed, quality-filtered in dada2 (v1.18) (Callahan et al., 2016), and taxonomically annotated using the SILVA database (v138) (Quast et al., 2013). Visualization of the cyanobacterial distribution was accessed with phyloseq (1.34.0) (McMurdie and Holmes, 2013).
Quantitative real-time PCRs were carried out targeting the nifH clade specifically for Nodularia, UCYN-A, and Gammaproteobacterial diazotrophs (gamma AO, gamma PO) as described previously (e.g., Boström et al., 2007; Langlois et al., 2008; Löscher et al., 2014). As standards, serial dilutions of plasmids (107 to 101 copies) containing the target nifH genes were used. Samples, standards, and non-template controls were run in duplicates on a Biorad qPCR machine (Biorad, Hercules, USA), and reactions were considered uncontaminated if no amplification could be detected in non-template controls after 40 qPCR cycles. To further ensure that no DNA contamination was present in our cDNA, we ran additional qPCR reactions of RNA samples. No amplification was observed. Sequences were submitted to GenBank with accession numbers MZ063808-MZ063873 and MZ063874-MZ064057 and 16S rDNA with accession number SAMN20309768-SAMN20309783.
2.4 Statistical methods
Principal component analyses (PCAs) on qPCR and environmental data were performed in R using the vegan package (Oksanen et al., 2020; R Foundation for Statistical Computing, 2017). The simper function (from the vegan package) was used to identify parameters with the highest impact on diazotroph abundance. A principal component analysis (PCA) was subsequently performed using prcomp and visualized with the factoextra package (Kassambara and Mundt, 2020). To maximize the amount of explained variance of the dataset, the figure included component 1 versus 2 (Fig. 8a) and component 1 versus 3 (Fig. 8b).
During the cruise, surface waters above 40 m water depth exhibited the typical Baltic Sea salinity gradient with salinities decreasing from southwest to northeast (10–24 in the Kiel and Arkona Basin and 7–9 in the Bornholm and eastern Gotland basins), accompanied by lower temperatures of 13–14 ∘C in the Bornholm and eastern Gotland Basin compared to slightly higher temperatures of 15–16 ∘C in the Kiel Fjord and Arkona Basin (Fig. 2). A thermocline was observed at 45 m in the Bornholm Basin and 65 m in the eastern Gotland Basin. The coastal station we sampled in the Arkona Basin showed a similar stratification pattern (Fig. 2) with a salinity of 10 on the surface and 17 below 30 m water depth. This stratification pattern is typical for the region and time of the year and could also be observed from annual data from the International Council for the Exploration of the Sea (ICES Copenhagen, 2020) (Fig. 1b). Surface waters were well-oxygenated with O2 concentrations above 156.31 µmol L−1 in the top 40 m of the water column. Low-O2 water masses with concentrations below 15 µmol L−1 were only observed in the Bornholm Basin in waters deeper than 65 m (Fig. 2).
Compared to the southwestern part, the DIC concentrations were lower in the upper water column of the eastern Gotland and Bornholm Basin, with concentrations of around 1.6 mmol L−1, and increased towards the southwestern part of the cruise track. An opposite trend was visible in nutrient distribution, with NOx (nitrite + nitrate) and phosphate (PO) decreasing from the northeastern part of the cruise track towards the southwestern part and with surface water concentrations of 9.04 µmol L−1 for NOx and 2.98 µmol L−1 for PO in surface waters of the eastern Gotland Basin and 0.27 µmol L−1 for NOx and 0.18 µmol L−1 for PO in the Kiel Fjord (Fig. 2). The observed nutrient concentrations were in the range of the Helsinki commission (HELCOM) dataset containing data from 2015 to 2020 and the HELCOM core indicator report (Helcom, 2018, Fig. S2). The somewhat higher nutrient concentrations detected in the Bornholm and eastern Gotland basins could result from a decaying phytoplankton bloom releasing nutrients including ammonia, decreased microbial activity, or increased eutrophication. High chlorophyll concentrations in the Bornholm Basin (3 µM Chl a in August and 2 µM Chl a in September), derived from the HELCOM dataset (from same areas as this cruise), indeed give evidence of a decaying phytoplankton bloom in the Bornholm Basin in September 2019 (Fig. S3). These values are in range with the HELCOM indicator report, with an average of 4 µM Chl a from June to September, and a previous study presenting a range between 2 and 6 µM Chl a (Helcom, 2018; Suikkanen et al., 2010).
Our dataset indicates an N:P ratio (µmol L−1 : µmol L−1) well below the Redfield ratio of 16:1 in surface waters along the cruise track, with excess P classically assumed to promote N2 fixation. However, NOx was still available to the phytoplankton and microbial community as supported by a positive intercept of the trend line, which might be considered unfavorable for N2 fixation (Fig. 3). Remaining NOx concentrations in the surface waters above 40 m thus speak for a limitation of primary production by either micronutrients, temperature, or light availability and less for a limitation by N or PO (Arrigo, 2005; Saito et al., 2008). Nitrogen repletion is supported by POC : PON ratios of 3.6 to 4.94 in the Kiel Fjord and Arkona Basin and 2.92 to 6.15 in the Bornholm and eastern Gotland basins (Fig. 3) (PON: particulate organic nitrogen, POC: particulate organic carbon), which are close to the Redfield ratio (Redfield, 1934). Altogether, nutrient concentrations do not strongly support a niche for N2 fixation.
3.2 Nitrogen fixation
While no clear niche for N2 fixation could be identified, we still detected N2 fixation rates in our samples from water depths between 3 and 41 m (Fig. 4). N2 fixation rates were between 0 and 6 ± 4.73 nmol N L−1 d−1 in the Arkona Basin, 0.7 ± 0.97 to 27.3 ± 38.21 nmol N L−1 d−1 in Bornholm Basin, and 0.67 ± 0.51 to 2 ± 0.4 nmol N L−1 d−1 in the eastern Gotland Basin (Fig. 4). In Kiel Fjord, N2 fixation rates were below the detection limit (0.03 nmol N L−1 d−1) of our method. One outlier was observed in the Bornholm Basin at a water depth of 5 m, with an N2 fixation rate of 27.3 nmol N L−1 d−1. This high rate was only detected in one out of our three replicates and was not included in our further analysis. Without this outlier, a conservative estimate of N2 fixation in the Bornholm Basin would be between 0.7 ± 0.97 and 5.27 ± 1.37 nmol N L−1 d−1. Though these rates are at the lower end of previous observations from the Baltic Sea (Table S3), they are comparable to a previous study from the same region but not the same season, with N2 fixation rates of 7.6 ± 1.76 nmol N L−1 d−1 from July and August (Farnelid et al., 2013). N2 fixation activity is supported by the δ15N–PON in our control samples, which was in the range of control samples and found to be 0.3 ‰ to 2 ‰ in samples from surface waters above 40 m from the eastern Gotland and Bornholm basins (Fig. 4). Values between −2 ‰ and +2 ‰ are considered indicative for N2 fixation (Dähnke and Thamdrup, 2013; Delwiche and Steyn, 1970).
Seasonal variations might explain the observed lower N2 fixation rates if compared to previous studies. N2 fixation rates are generally described as sensitive to low temperatures (Brauer et al., 2013; Church et al., 2009; Englund and Meyerson, 1974; Moisander et al., 2010; Stal, 2009), with the energetic costs of N2 fixation sharply rising at temperatures below 21 ∘C (Brauer et al., 2013). During our cruise, surface temperatures were between 12 and 16 ∘C and would most likely play a role in the low rates observed. Yet, growth of N. spumigena has been demonstrated at 4 ∘C, suggesting relevance during wintertime in the Baltic Sea (Olofsson et al., 2019). Additionally, lower light intensities during fall and winter could directly influence the abundance of cyanobacterial diazotrophs in the Baltic Sea (Dera and Woźniak, 2010; Staal et al., 2002).
N2 fixation rates were accompanied by low C fixation rates compared to rates in the micromolar range as typically detected in the Baltic Sea (e.g., Klawonn et al., 2016) (Fig. 4), which were, however, increasing over depth, with an average C fixation of 29.16 ± 10.89 nmol C L−1 d−1 in Kiel Fjord, 42.62 ± 7.86 nmol C L−1 d−1 the Arkona Basin, 40.52 ± 13.16 nmol C L−1 d−1 in Bornholm Basin, and 58.52 ± 15.42 nmol C L−1 d−1 in eastern Gotland Basin. Assuming Redfield stoichiometry, N2 fixation was sustained between 8.8 % and 108 % with an average of 43 % of C fixation during our cruise. These rates are comparable with the contribution of N2 fixation to C fixation in other oceanic regions, including the Atlantic (20 %–25 %) and Pacific Ocean (1 %–4 %), the Mediterranean Sea (8 %), and the Bay of Bengal (<1 %) (Church et al., 2009; Dore et al., 2002; Fonseca-Batista et al., 2019; Rahav et al., 2013; Saxena et al., 2020; Tang et al., 2019) (Table 1). The high contribution to primary production indicates that N2 fixation may promote or extend primary production into the fall season if only at low rates. Other sources, however, might include land or riverine input.
3.3 Diazotrophic community composition
We assessed the diazotrophic diversity based on nifH and anfD/vnfD amplicons (Figs. 5 and 6). Sequences belonging to N. spumigena (19 %) and UCYN-A (26 %) were dominant in the sequence pool. While Nodularia clades are classically abundant in the Baltic Sea waters (Boström et al., 2007; Farnelid et al., 2013; Klawonn et al., 2016; Larsson et al., 2001), only one previous report of UCYN-A from the Baltic Sea exists; it had been detected in waters of the Danish Strait and the Great Belt (Bentzon-Tilia et al., 2015). Moreover, we detected Pseudanabaena-like sequences representing 8 % of the sequence pool, consistent with previous studies (e.g., Acinas et al., 2009; Farnelid et al., 2013; Klawonn et al., 2016; Stal et al., 2003). Only 1.5 % of the sequences belonged to Aphanizomenon sp., a diazotroph known to dominate N2 fixation early in the season with salinity at 5–6 (Klawonn et al., 2016; Svedén et al., 2015). The low number found in this study might be seasonally related.
Notably, based on our nifH sequence analysis, we did not identify Dolichospermum spp., one of the common N2-fixing cyanobacteria for the Baltic Sea (Bentzon-Tilia et al., 2015; Boström et al., 2007; Farnelid et al., 2013). However, sequences related to A. lemmermannii were recovered from our 16S rDNA amplicon sequencing (Fig. S1). This discrepancy might speak for a bias against their specific nifH genes by our approach, or the clades we found in the 16S rDNA dataset might lack a nifH gene.
We detected Nodularia-like sequences (primer and probe constructed against N. spumigena and environmental Nodularia clusters; see Boström et al., 2007) in abundances of 3.37 × 105 to 4.06 × 107 copies L−1 at 3–5 m water depth and 8.64 × 104–4.46 × 106 copies L−1 at water depths of 20–41 m. Nodularia-specific nifH transcript abundance decreased over depth from 4.20 × 105 (5 m) to 3.5 × 102 (20 m) transcripts L−1 (Fig. 7). Nodularia followed the temperature–salinity gradient, with the highest abundance (up to 1.6 × 107 copies L−1) in waters with salinity at 10 or below (the Bornholm and eastern Gotland basins) and the lowest abundances (up 1.46 × 106 copies L−1) in waters with a salinity above 10 (Kiel Fjord and the Arkona Basin). Nodularia-specific nifH gene and transcript abundances were in the same range as previously described (106 gene copies L−1 and 105 transcripts L−1; Farnelid et al., 2013). UCYN-A was identified based on both nifH and 16S rDNA sequences and quantified using cluster-specific qPCR. UCYN-A was present in abundances of 3.73 × 103–9.97 × 107 copies L−1, similar to the one available previous study wherein the abundance of nifH specific for UCYN-A peaked in September (approximately 106 copies L−1) (Bentzon-Tilia et al., 2015) (Fig. 7). The same study showed nifH expression (roughly 103 transcripts L−1) of UCYN-A in the Baltic Sea surface waters (1 m). These transcript abundances are comparable with those obtained from our study, with transcript abundances between 2.98 × 102 and 3.73 × 102 transcripts L−1 at 5 m water depth and up to 3.71 × 105 transcripts L−1 at a water depth of 20 m (Fig. 7). Notably, the abovementioned study took place in the Danish Strait and thus in more saline waters (salinity of 13–17).
Contrary to Nodularia, UCYN-A reached the highest abundances (up to 4.52 × 107 copies L−1) in higher-salinity waters impacted by the North Sea (the Kiel Fjord and Arkona Basin) and the lowest abundance (up to 6.29 × 105 copies L−1) in low-salinity waters (Fig. 7, Supplement Fig. S1). UCYN-A is increasingly found throughout the oceans, often playing an important role in N2 fixation (e.g., Martínez-Pérez et al., 2016; Tang and Cassar, 2019). Over recent years, UCYN-A has been shown to have a crucial part in N2 fixation and has been identified all over the globe from polar to tropical regions, tolerating between 4 and 30 ∘C (Gradoville et al., 2020; Harding et al., 2018; Martínez-Pérez et al., 2016; Mills et al., 2020; Short and Zehr, 2007; Tang and Cassar, 2019). Despite UCYN-A exhibiting the highest abundances in Baltic Sea waters with higher salinity, we found UCYN-A present and active across the salinity gradient.
Besides those cyanobacterial diazotrophs, we detected several clades of Proteobacteria related to Rhodopseudomonas palustris (4 %), Pelobacter sp. (9 %), and Gammaproteobacteria of the gamma AO clade (3 %, Langlois et al., 2008). We quantified gammaproteobacterial nifH in abundances between 1.78 × 104 and 1.82 × 105 copies L−1 (gamma AO) and their transcripts in abundances of 2.89 × 103–3.91 × 103 transcripts L−1. Despite lack of clones clustering with gamma PO, the group could be detected in abundances between 8.21 × 102 and 1.37 × 105 copies L−1 and their transcripts in abundances between 3.04 × 103 and 8.05 × 103 transcripts L−1, indicating a potential contribution to N2 fixation of those clades (Fig. 7). Diazotrophic Proteobacteria are common in the ocean; however, their role for N2 fixation is not fully understood (Benavides et al., 2018; Chen et al., 2019; Turk-Kubo et al., 2014). Diazotrophs related to Cluster III were dominated by Desulfovibrio-like (1.5 %), Opitutaceae-like (6 %), and Clostridium-like sequences (1.5 %). However, both nifH gene and transcript abundances were below the detection limit of our qPCR. Altogether, the gene and transcript abundances of cyanobacterial diazotrophs were 3 to 4 orders of magnitude higher than those of non-cyanobacterial clusters, suggesting that heterotrophic microbes may have only played a minor role for N2 fixation in Baltic Sea surface waters during our cruise.
In the pool of alternative nitrogenase sequences of the anfD type, we identified the purple non-sulfur bacterium Rhodopseudomonas palustris. We could not recover any vnfD sequences, which might be an adaptation to low vanadium concentrations in the Baltic Sea (Bauer et al., 2017). The role of alternative nitrogenases in the environment is poorly understood, partly due to a lack of data and detection systems. Our data, however, show the presence of alternative nitrogenases in the Baltic Sea surface water, which may sustain N2 fixation under certain conditions, for example in anaerobic micro-niches (Bertagnolli and Stewart, 2018; Farnelid et al., 2019; Paerl and Prufert, 1987; Pelve et al., 2017), including sinking particles (Chakraborty et al., 2021; Pedersen et al., 2018).
3.4 Factors impacting the diazotrophic distribution
To identify parameters impacting the distribution of diazotrophs during our cruise, we carried out a simper analysis. Interestingly, pH and temperature were less important for describing the diazotrophic distribution. The PCA suggested that depth and salinity explained the distribution of both the diazotrophic community and N2 fixation best (Fig. 8). Moreover, it revealed a correlation of N2 fixation and the Nodularia abundance and less of a correlation between N2 fixation and UCYN-A or other diazotroph clusters (Fig. 8). A decreasing salinity would thus not only promote the distribution of Nodularia-like diazotrophs and decrease UCYN-A abundances, but also promote N2 fixation rates in such a future scenario. Intuitively, it is of little surprise that our data (Fig. 8) and previous studies indicate salinity to be a key control for cyanobacterial distribution and N2 fixation in the Baltic Sea (Dupont et al., 2014; Olofsson et al., 2020; Rakko and Seppälä, 2014). A recent study also suggested a positive correlation between UCYN-A and salinity (Li et al., 2021), while a study based on a compiled dataset (1979–2017) indicated that salinity does not affect the biovolumes of the filamentous N. spumigena but rather species interactions (Karlberg and Wulff, 2013; Olofsson et al., 2020). Our study cannot evaluate such interactions and their impact of N2 fixation; however, our data do point towards Nodularia expanding into low-salinity waters in the future, thus complementing UCYN-A and possibly increasing N2 fixation rates in those waters.
Our analysis did not show temperature and pH to be major descriptors of N2 fixation during this cruise, consistent with previous findings with elevated CO2 concentrations not causing any response in N2 fixation in the Baltic Sea (Olofsson et al., 2019; Paul et al., 2016; Wulff et al., 2018). Moreover, a very recent study showed that ocean acidification has an impact on the diazotroph community composition and ecology and can decrease bulk N2 fixation rates in the subtropical Atlantic Ocean (Singh et al., 2021). Most likely, the contradicting results are due to other factors obscuring the stimulation by N2 fixation (Karlberg and Wulff, 2013; Wannicke et al., 2018). Besides pH, temperature has also been suggested as a control on diazotrophy, either directly or indirectly, by impacting O2 solubility (Stal, 2009).
Also, increasing nutrient loads in the Baltic Sea might further stimulate primary production, leading to increased anoxia and PO release from sediments (Ingall and Jahnke, 1997), which will, in turn, fuel N2 fixation and primary production (Canfield, 2006; Saraiva et al., 2019). Filamentous cyanobacteria benefit from excess PO (Olofsson et al., 2016); thus, excess PO resulting from progressive deoxygenation might stimulate blooms of Nodularia (Degerholm et al., 2006; Schoffelen et al., 2018).
In the case of a potential future freshening of the upper water column (Liblik and Lips, 2019) in combination with increased PO availability through both land-derived influx and phosphorus mobilization via bottom-water anoxia (Gustafsson et al., 2017; Ingall and Jahnke, 1997; Stigebrandt and Andersson, 2020; Vahtera et al., 2007), N2 fixation by, e.g., Nodularia will likely increase in the region covered by our cruise. This could lead to a scenario with increased bloom formations and expansion of such large heterocystous cyanobacteria across the Baltic Sea, as previously observed (Kahru et al., 1994; Kahru and Elmgren, 2014). An increased organic matter load would possibly lead to enhanced respiration by heterotrophic microbes, promoting the further expansion of O2-depleted waters. This could lead to increased denitrification, resulting in N loss and emission of N2O, fueling global warming with an increase in euxinic events as already observed in coastal Baltic waters (Breitburg et al., 2018; Carstensen et al., 2014; Lennartz et al., 2014). Further, blooms of Nodularia could lead to an increased load of Baltic Sea waters with the toxin nodularin (Sivonen et al., 1989), which can harm Baltic Sea biota and poison animals (Main et al., 1977; Nehring, 1993) and ultimately humans by impacting, e.g., the fishery industry (Karjalainen et al., 2007). The latest studies, however, show that projection of increased sea level rise counteracts freshening events in the Baltic Sea, making it uncertain whether salinity will increase or decrease in the future (Meier et al., 2021, 2022). Regardless, potential changes in salinity might impact the diazotrophic community as described above. The uncertainty in changing salinity makes it unclear to what extent diazotrophs might be impacted.
During our cruise, we explored the diazotrophic community composition and N2 fixation rates along the natural salinity gradient in the southern Baltic Sea in the fall season. N2 fixation rates were detectable but low for the Baltic Sea and sustained by a diazotrophic community dominated by the heterocystous cyanobacterium Nodularia and the small unicellular cyanobacterium UCYN-A. The two different types of cyanobacteria occupied two different niches defined by salinity ranges, with Nodularia dominating in lower-salinity waters (8–9) and UCYN-A in high-salinity waters (>10). Statistical analysis revealed that N2 fixation is quantitatively mainly driven by Nodularia clades and that both Nodularia abundances and N2 fixation rates are best explained by salinity. In the context of a predicted freshening of the Baltic Sea, the habitat of Nodularia-like heterocystous cyanobacteria would extend towards the southwestern part of the Baltic Sea, possibly replacing the community of UCYN-A and increasing N2 fixation in those waters. Enhanced N2 fixation might facilitate primary productivity, and organic matter export to waters below the euphotic zone and could thus have severe impacts on the Baltic Sea biogeochemistry including increased respiration, as well as O2 and N loss.
The datasets presented in this study can be found in online repositories. Accession number(s) can be found in NCBI with MZ063808-MZ063873 and MZ063874-MZ064057 as well as 16S rDNA with accession number SAMN20309768-SAMN20309783.
The supplement related to this article is available online at: https://doi.org/10.5194/os-18-401-2022-supplement.
CFR and CRL designed the experiments and CFR carried out the experimental work. JJ and IS designed the sampling strategy during the expedition and contributed essential datasets. CFR and CRL prepared the paper with contributions from all the co-authors.
The contact author has declared that neither they nor their co-authors have any competing interests.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
We thank the captain, crew, and chief scientist Jörg Süling of Alkor 528 for their support during the cruise. We thank Erik Laursen and Rikke Orloff Holm for their technical assistance. We thank Harri Kuosa and Malin Olofsson for reviewing the paper. Further support was received from the Nordcee labs at SDU and the GEOMAR-Helmholtz Centre for Ocean Research Kiel by providing access to their research vessel and facilities.
This research has been supported by the Villum Fonden (grant nos. 16518 to Donald Canfield and 29411 to Carolin Regina Löscher) and the European Union Horizon 2020 (GoJelly (grant no. 774499 to Jamileh Javidpour)).
This paper was edited by Markus Meier and reviewed by Malin Olofsson and Harri Kuosa.
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