A first slight increase in 137Cs activity at a core depth of ∼14 cm and a peak at 11.75 cm were observed (**Figure 7**). At 9.5 cm, there was a steep rise in 137Cs, with fluctuating but still elevated activities toward the core top. 241Am activities were characterized by a clear maximum at a sediment depth between 14 and 11.5 cm, a single peak at 9.25 cm, and a peak between 7.75 and 8.25 cm. 206/207Pb values ranged from 1.17 to 1.21, with the lowest values at a sediment depth between ∼11 and ∼9 cm. The opal content was enriched in the topmost samples and between ∼6 and 8 cm.

# DISCUSSION

#### Temporal Dynamics and the Fate of Mn in the Gotland Deep After the MBI of 2014

The profiles of Mndiss obtained before the MBI in 2014 represent a first approximation of the conditions that prevailed during a stagnation period, that is, without the impact of substantial oxygenation events (**Figure 2**). Nonetheless, pronounced differences within the datasets were still discernible. The elevated Mndiss concentrations in the bottom water in July 2006 clearly represented the remnants of the re-established euxinic conditions and the coupled reduction of deposited Mn oxides after the MBI in 2003 (Feistel et al., 2003, 2004; Turnewitsch and Pohl, 2010; Häusler et al., 2018). Conversely, the decrease in Mndiss in the two lowermost samples from April 2007 was certainly due to a very short-term inflow of O2-containing waters, documented in the time-series at site 271 (**Figures 2**, **9**; ICES, 2015). Irrespective of the rising sulfide levels in deep water, possibly attributable to a decreasing pool of reactive Fe in the sediments that exacerbated the escape of sulfide into the open water column (Lenz et al., 2015), Mndiss concentrations were similar at least for the years 2008–2012 and thus suggestive of a balanced status. The Mndiss level was, however, ∼2-fold higher than that in February 2015, just before the major MBI pulse of 2014 reached the Gotland Basin (**Figures 2**, **3**). The even more pronounced difference in sulfide levels can be explained by the weak oxygenation event before the major MBI, as indicated by the O2 time series in the bottom waters from site 271 in spring 2014 (**Figure 9**; ICES, 2015). Although the average Mndiss concentration in euxinic waters of 9.0µM in August 2012 vs. 4.3µM in February 2015 indicated substantial Mn loss, a simple inventory estimate relativizes this finding. Thus, based on the hypsography of the Gotland Basin (**Figure 9A**; Seifert and Kayser, 1995; Supplementary Dataset), the upward shift of the redoxcline by ∼10 m (**Figures 2**, **3**) significantly increased the euxinic water volume enriched in Mn, from ∼209 km3 in 2012 to 288 km3 in 2015. After a basin-wide extrapolation of Mndiss concentrations from the water column profiles using the corresponding hypsography-based water volumes (**Figure 8**), the Mndiss inventories (∼1.5 × 109 mol) in the euxinic water bodies were identical during the 2 years, which argues against a sustained effect of the weak pre-MBI oxygenation, at least for Mn (see Supplementary Dataset).

Increased O2 and decreased Mndiss concentrations on 3 March 2015 represented the first signals of the approaching MBI from 2014 (**Figure 3**). This date accords with an O2 time series from a profiling mooring in the Gotland Deep (Prien and Schulz-Bull, 2016; Holtermann et al., 2017). In the following months, the main MBI phase caused the almost complete oxygenation of the water column, with only a thin remnant of the previously euxinic water body at around 120 m water depth (**Figure 3**). Correspondingly, Mndiss concentrations dropped to near nanomolar levels in these oxygenated waters, thereby enhancing the formation and downward deposition of particulate Mn oxides, as documented

indicate core parallelization based on Pb/Al ratios (Figure S3).

by the sediment trap (**Figure 4**). Although the position of the trap at a water depth of ∼186 m caused a bias between the detection of sinking Mn oxides and the onset of bottom water oxygenation, the steep increase in Mnpart fluxes in June 2015 reflected the considerable deposition of Mn oxides at the sediment surface. A temporal bias between the onsets of water column oxygenation and Mn oxide deposition was also apparent in the surface sediments taken close to station 271. Despite the presence of O2 in nearly the entire water column for more than a month, there was no sign of Mn enrichment in the uppermost fluffy sediments in May 2015 (**Figure 5**). By contrast, an analysis of the core taken in July 2015 showed strongly elevated Mn/Al ratios in the uppermost sample (**Figure 5**). Particle analysis by SEM-EDX revealed a relative abundance of >60% and further supported

used to identify time markers for event-stratigraphic dating of the sediment core (Supplementary Dataset).

the clear dominance of Mn oxide particles (**Figure 6C**). The similar morphologies of the Mn oxides and particles found in the sediment trap and in the pelagic redoxclines of the Baltic and Black Seas (**Figures 6A,B**; Dellwig et al., 2010) provide evidence of their origin in the water column. Because agglomeration with organic mucus reduces the density and consequently the sinking velocity of Mn oxides (<1 m d−1 ; Glockzin et al., 2014), the elevated current velocities resulting from the intruding water masses possibly have delayed the significant deposition of these particles (Holtermann et al., 2017).

Despite the prominence of O2 in nearly the entire water column, a first signal of the re-establishment of bottom water anoxia was already detected on 09 May 2015, by a slightly elevated Mndiss concentration in the supernatant water of the short core (**Figure 3**). This shift in the bottom water redox regime was even more pronounced in the Mndiss profiles from the cruises in July, September, October, and November 2015 (**Figure 3**). Elevated Mndiss concentrations in the supernatant water and a peak of 81µM in the pore water just below the Mn/Al peak at the sediment surface in July 2015 implied the onset of Mn oxide reduction and Mndiss escape into the open water column (**Figures 3**, **5**). Consequently, Mn enrichment in the surface sediment decreased and a further increase in the bottom and pore water concentrations of Mndiss occurred in October 2015. This liberated Mndiss, however, was trapped in the bottom waters below a depth of ∼210 m, as indicated by the enhanced Mnpart concentrations of SPM in July and October 2015 (**Figure 3**).

The return to pronounced bottom water euxinia was interrupted by a second inflow phase that occurred between the cruises of November 2015 and February 2016. According to the ICES Dataset on Oceanography, O2 (26µM) first appeared, at 239 m, on 3 December 2015, (**Figure 9**), but O2 concentrations decreased in the following cruise, to 7.6µM, and a slight presence of ∼4µM sulfide was even determined, on 8 January 2016. Therefore, the main onset of this second inflow pulse must have been between 8 January and 4 February 2016. While the intermediate water column in February 2016 was subjected to pronounced O2 consumption, the intruding O2 containing waters most likely caused an uplift of the former anoxic bottom water (**Figure 3**; Holtermann et al., 2017). The subsequent oxygenation of the water column again resulted in pronounced Mn oxide formation and deposition, as indicated by the increasing Mnpart fluxes in the sediment trap and the Mnpart enrichments in the surface sediments in February and June 2016 (**Figures 4**, **5**). Nevertheless, the rising concentrations of Mndiss and sulfide in the bottom and pore waters beginning in June 2016 (**Figures 3**, **5**) again suggested a comparatively fast switch to a reducing environment in the deeper Gotland Basin. Mnpart concentrations as high as 2.4µM were measured at a water depth of ∼210 m in October 2016 (**Figure 3**); however, these Mn oxides most likely dissolved in the deeper euxinic waters before reaching the seafloor, as also indicated by the absence of Mn enrichments in the corresponding surface sediments (**Figures 5**, **6**). Data from the final two cruises of February and March 2017 documented a progressive extension of euxinic bottom waters highly enriched in Mndiss and the final development toward pre-MBI-like conditions (**Figures 2**, **3**).

The strong Mndiss enrichments suggested a relatively rapid return to reducing near-bottom conditions within less than 3.5 months after each of the two oxygenation events. The reconstructed duration of bottom water oxygenation caused by the first inflow in winter 2014/2015 was about half as long as that determined from the instrumental O2 time series from the deep water (below 230 m water depth) of the Gotland Basin (**Figure 9**; ICES, 2015). This difference was due to the inclusion of the supernatant water samples from the short cores in our dataset,

to reflect the conditions very close to the SWI. Although the MBI in 2014 was the third strongest since 1880, with a strength roughly twice as high as the previous MBI, in 2003 (Mohrholz et al., 2015), oxygenation of the Gotland Deep bottom waters was less efficient (**Figure 9**; ICES, 2015). This discrepancy was unexpected, especially given the distinctly lower sulfide level in 2015 than in 2003. Neumann et al. (2017) suggested that the larger amounts of O2 that entered the Gotland Basin in 2003 were supported by several weaker inflows carrying additional O2 and that the strength of an MBI is not necessarily a measure of its oxidation capacity in the deeper parts of the Baltic Sea.

#### Mn Balance Calculations

The water column profiles obtained in the Gotland Deep within the course of the MBI from 2014 suggest substantial losses of Mndiss due to O2 inputs and the subsequent formation of particulate Mn oxides that sank toward the sea floor (**Figures 3**, **5**, **6**). However, the relatively fast re-establishment of anoxic conditions in the pore and bottom waters also caused a reduction of deposited Mn oxides and an elevated reflux of Mndiss into the water column.

Depending on the basin's topography, the water volume increases exponentially with decreasing water depth (**Figure 8A**) and concentration profiles alone cannot be used to construct elemental budgets. Nonetheless, by multiplying Mndiss concentrations by the corresponding volumes of the hypsography-based water depth intervals, we calculated Mndiss inventories for the entire Gotland Basin below a water depth of ∼70 m (**Figure 8B**; Supplementary Dataset). The estimates were based on the assumption that the water column profiles

obtained in the central deep were representative of the entire basin.

Compared with the pre-MBI situation, the inventory estimates indicated a loss of almost 90% of water column Mndiss within the first 2 months after the MBI reached the Gotland Basin in the end of February 2015 (**Figure 8B**). Although the deeper parts contribute only marginally to the entire basin volume, strong Mndiss enrichments in the bottom waters due to the re-establishing anoxia led to the fast recovery of the Mndiss inventory, with the amounts roughly half of the pre-MBI level in the following months. Apart from the somewhat longer time span until the recharge of Mndiss, a comparable behavior was also apparent after the second inflow pulse, in January 2016. The Mndiss inventories from the February and March 2017 cruises, which were entirely dominated by Mndiss enrichments in the deeper basin, were about two-thirds of the pre-MBI level. When considering the Mn oxides still present on surface sediments below the O2-containing water column (above ∼170 m water depth), it is more than likely that the Mndiss inventory of the Gotland Basin will further increase as euxinic conditions expand.

To allow a direct comparison between Mndiss inventories and Mnpart fluxes from the sediment trap, Mndiss inventories were also estimated for the water column above the trap (186–70 m water depth) with a base area of 1 m2 (**Figure 8C**; Supplementary Dataset). As expected, the temporal pattern of these Mndiss inventories generally resembled the total basin inventories, with two prominent phases of Mndiss loss after the two inflows pulses and subsequent replenishment (**Figures 8B,C**). An exception are comparatively low Mndiss values during the last two cruises in 2017 because the extension of reducing bottom waters enriched in Mndiss only marginally exceeded the water depth interval considered by the inventory calculation. Compared to the Mndiss inventories there was no clear relation to the Mnpart fluxes from the sediment trap. Thus, the delays between the increases in Mnpart fluxes and inflow-derived Mndiss losses can be explained by slowly sinking Mn oxides particles (Glockzin et al., 2014) affected by changing hydrodynamics within the course of the inflow (Holtermann et al., 2017). In addition, the cumulative amounts of Mnpart found in the trap until July 2015 (81 mM) were insufficient to explain the maximum Mndiss loss of ∼270 mM until May 2015. In contrast, after the second inflow pulse, Mndiss loss and the cumulative Mnpart flux were balanced for the period between February and the end of April 2016 (**Figure 8C**). However, the total cumulative Mnpart flux of 575 mM m−2 was even twice as high as the pre-MBI Mndiss inventory, which strongly argued against a simple vertical consideration of sediment trap-derived Mnpart fluxes.

An indication of the comparatively fast change in the bottom water toward reducing conditions causing Mn oxide dissolution came from pore water profiles that showed strong Mndiss enrichments close to the SWI in October 2015 and June 2016 (**Figure 5**). This suggested that the corresponding increases in bottom water Mndiss concentrations and inventories were strongly related to Mndiss pore water fluxes that were distinctly higher than those prior to the MBI in 2014 (**Figures 2**, **5**). Extrapolation of the highest pore water Mndiss flux of 1,253µM m−2 d −1 , which occurred in October 2015, to the area located below a water depth of 220 m (642 km2 ) and subjected to anoxic conditions resulted in an areal Mndiss flux of 8 × 108 mM d−1 . This areal pore water flux would need ∼55 days to achieve the calculated Mndiss inventory of 4.5 × 1010 mM in the water volume below 220 m (6.6 km3 ). Although this time span appears reasonable, pore water fluxes alone do not adequately explain the development of Mndiss inventories especially those measured toward the end of the observation period. Even if in October 2016 and March 2017 the Mndiss inventory was limited to the anoxic bottom waters below a water depth of 225 m (3.8 km3 ) and 190 m (38 km3 ), the time needed for the respective areal pore water fluxes (1.1 × 108 mM d−1 for 473 km2 and 1.4 × 108 mM d−1 for 1,499 km2 ) to achieve bottom water inventories of 1.3 × 108 and 8.8 × 1011 mM Mndiss would have increased to 1,240 and 6,308 days, respectively. The discrepancy is undoubtedly due to the fact that the pore water fluxes determined during those two cruises in the deepest part of the basin were no longer representative of the larger basin. Along with the lack of Mn oxides at the sediment surface, the pore water profile and Mndiss flux from the March 2017 cruise clearly approached pre-MBI conditions (**Figure 5**) at the deepest part of the basin. An important Mn source during these stages of the re-establishment and expansion of euxinic conditions was therefore the surface sediments from shallower water depths, where Mn oxides most likely persisted.

Several aspects strongly argue for substantial basin-internal transport of low-density Mn oxide particles (Glockzin et al., 2014) by lateral currents: (i) the temporal deviation between Mndiss loss in the water column and Mn oxide sedimentation (**Figure 8C**), (ii) the rapid replenishment of the water column Mndiss inventory, which cannot be explained by pore water Mn fluxes alone, (iii) the presence of Mnpart in oxygenated waters without a significant Mndiss source, e.g., in June 2016 (**Figure 3**), (iv) the highly fluctuating pattern of Mnpart fluxes of the sediment trap during the second inflow phase (**Figure 4**), and (v) the discrepancy between the Mndiss inventory of the water column and the Mnpart flux determined by the sediment trap samples (**Figure 8C**). If not already reduced by expanding euxinic waters, the enhancement of bottom currents by the MBI (Holtermann et al., 2017) most likely also re-suspended Mn oxides previously deposited in the shallower parts of the basin. Indeed, the Mn contents of the surface sediment samples from two shallower stations (MUC OD in 211 m and TrKl04 in 151 m water depth) west of site 271 (**Figure 1**) in October 2015 were 9.0and 3.1 wt%, respectively (Supplementary Dataset). The overall pathway of material transport toward the central basin finds support by several previous studies. Model results suggest an anti-clockwise direction of near-bottom currents with velocities decreasing toward the central basin (Hille et al., 2006). Along with the largest thickness of Littorina muds, the authors further report highest sedimentation rates in the deepest part of the Gotland Basin. Here, highest accumulation of TOC and heavy metals relates to physical forcing rather than biogeochemical processes (Emeis et al., 1998; Leipe et al., 2011). In addition to this physical transport of Mnpart, bottom currents likely also enhanced the geochemical focusing of Mndiss as suggested for lakes by Schaller and Wehrli (1997).

On the other hand, Mn oxide particles may also have left the basin with the intensified deep currents during the MBI. Lower salinity in the neighboring Fårö Deep during the MBI in 2014 (Holtermann et al., 2017), however, indicate that the connection to the Gotland Basin occurred mainly via comparatively Mnpoor water masses from water intermediate depths. This has also been suggested for the downstream connection to the Landsort Deep by Häusler et al. (2018). Along with the basin's topography surrounded by sill depths of ∼130 m and less, the current patterns in the deep Gotland Basin rather argue for a pronounced basininternal cycling of Mn (Hille et al., 2006; Holtermann et al., 2017).

#### Implications for Mn Carbonate Formation

Although the sediments of the deep basins of the Baltic Sea are the modern type-locality for exceptional Mn carbonate accumulation (Lenz et al., 2015; Häusler et al., 2018), our data argue against prominent Mn carbonate formation, at least in the central Gotland Deep subsequent to the MBI from 2014. Studies of the influence of previous MBIs on sedimentary Mn dynamics in the Gotland Deep require dating of the sediments to correlate instrumental time series from the water column with sediment signatures. This approach was first applied by Neumann et al. (1997), who compared dated Mn carbonate records of sub-recent sediments with the hydrographic long-term data available for the Gotland Basin. However, as recently shown for Mn-rich sediments from the Landsort Deep by Häusler et al. (2018), the application of CRS-based age modeling using 210Pb (Appleby and Oldfield, 1978) is strongly compromised by the ingrowth of authigenic Mn carbonate and scavenging processes at pelagic redoxclines (Wei and Murray, 1994; Swarzenski et al., 1999). To construct an age model for the short core obtained from site 271 in 2012, we used the event-stratigraphic dating method, previously successfully applied to Mn-rich sediments from the Landsort Deep (Häusler et al., 2018) and the eastern Gotland Basin (Moros et al., 2017). Several time markers were used for the linear interpolation (**Figure 7**): the radionuclides 137Cs and 241Am, reflecting the onset of nuclear bomb testing in 1954 and its peak in 1963, as well as the Chernobyl accident in 1986 (Koide et al., 1977; Appleby et al., 1991), stable Pb isotopes indicating maximum Pb pollution between 1970 and 1978 (Renberg et al., 2001), a basin-wide opal layer resulting from a massive diatom bloom between 1988 and 1990 (Wasmund et al., 2011; Kabel et al., 2012), and the Mn layers that formed after the MBIs in 1994 and 2003 (Moros et al., 2017).

The XRF scan of the dated short core showed two periods of strong Mn enrichment, around 1963 and 1970 (**Figure 9**). The parallel patterns of Mn/Ti and Ca/Ti were compatible with the pronounced presence of Mn carbonate (Ca-rich rhodochrosite). A comparison with instrumental O2/sulfide data (ICES, 2015) suggested a tight relationship between Mn carbonate and O2 containing bottom waters, in line with the widely accepted linkage between MBIs and Mn carbonate formation (Huckriede and Meischner, 1996; Neumann et al., 1997; Sternbeck and Sohlenius, 1997). The conceptual models of those studies were based on the assumption that massive Mn oxide formation caused by MBI-related bottom water oxygenation is followed by the transformation of deposited Mn oxides into Mn carbonates during the early stages of re-establishment of anoxia. However, as noted above for the MBI from 1993 (Heiser et al., 2001), MBIs do not necessarily result in substantial Mn carbonate formation, as was the case in our corresponding core, with its less pronounced Mn enrichments following the inflows in 1976, 1993, and especially 2003 (**Figure 9**). Although minor amounts of Mn carbonate crystals were identified in the surface sediment in June 2016 (**Figure 6F**), the fluffy layers of the cores from October 2016 and March 2017 were barren of any Mn enrichments (**Figures 5**, **6**). This finding argues against sustained Mn carbonate precipitation after the MBI from 2014. The disappearance of the freshly formed Mn carbonate in the fluffy layer samples may have been related to dissolution in the undersaturated bottom waters, as suggested by Heiser et al. (2001) for the partly missing Mn carbonate layers after the MBI in 1993.

In line with previous studies in the Gotland Basin and Landsort Deep (Neumann et al., 1997; Lenz et al., 2015; Häusler et al., 2018), the appearance of discrete Mn carbonate-rich layers in the laminated sediments implied the temporal coupling of their formation to the oxygenation events. Accordingly, a dispersed precipitation from pore waters supersaturated in Mn carbonate seems less likely. Indeed, calculation of the saturation indices for Mn carbonate from pore water data of the Gotland Deep suggests undersaturation at the SWI and supersaturation not before a sediment depth of 3–10 cm (Carman and Rahm, 1997; Heiser et al., 2001; Lenz et al., 2015). Although these studies were based on pore water data obtained during stagnation periods, with Mndiss concentrations similar to those measured in our August 2012 samples (**Figure 5**), the lack of a pronounced Mn carbonate presence in the surface sediments from October 2015, when pore water Mndiss concentrations were even higher close to the SWI, points to a more complex mechanism of Mn carbonate formation (**Figures 5**, **6D**), especially since fundamental changes in pore water chemistry during periods of intense (∼1960 and ∼1970) and weak to absent (e.g., the MBIs of 1993, 2003, 2014) Mn carbonate formation are rather unlikely (Lenz et al., 2015). Field data as well as experimental approaches suggest kinetic reasons and an inhibition by organics and/or phosphate as limitations on the precipitation of Ca-rich Mn carbonate in the Baltic Sea (Mucci, 1988; Jakobsen and Postma, 1989; Böttcher, 1998). Böttcher (1998) mentioned a potential role for microbial mediation, as demonstrated for other authigenic mineral phases, such as apatite and dolomite (Vasconcelos et al., 1995; Schulz and Schulz, 2005; Petrash et al., 2015).

The reduction of deposited Mn oxides as the initial step in Mn carbonate formation could occur by the upwards migration of pore water sulfide (e.g., Burdige and Nealson, 1986; Yao and Millero, 1993), but competing dissimilatory Mn reduction (e.g., Lovley, 1993) has to be considered as well. Indeed, the oxygen isotope signatures of Mn carbonates from the Gotland Basin indicated microbial involvement at least during Mn oxide reduction (Neumann et al., 2002). In incubation experiments, Aller and Rude (1988) observed the formation of Mn carbonate during microbially mediated Mn oxide reduction, in which Fe sulfides served as the reductants. In addition to Mn sulfide formation, Lee et al. (2011) reported the production of Mn carbonate by the facultative anaerobic Mn-reducing bacteria Shewanella oneidensis MR-1 in experiments that included Mn oxide in the medium. The enormous deposition of Mn oxides at the SWI during oxygenation events in the deeps of the Baltic Sea may therefore be accompanied by a shift in the bacterial community from sulfate- to metal-reducing phyla. A role for bacterial community dynamics during the re-establishment of anoxic conditions after the MBI from 1993 was documented by Piker et al. (1998). In that study, the sulfate reduction rates in the surface sediments (0–2 cm) in May 1995 reached distinct maxima compared to the previous oxygenated state of the bottom water in June 1994. Assuming bacterial mediation, the duration of noneuxinic conditions at the SWI may be crucial for Mn carbonate formation. In other words, the too rapid re-establishment of euxinia after a single inflow, due to excess sulfide production by sulfate-reducing bacteria, may also cause an unfavorable environment for Mn-reducing phyla potentially involved in Mn carbonate formation (Lee et al., 2011). Although there have been very few measurements allowing a description of the conditions directly at the SWI, the time series of O2 and sulfide in the water column covering the past ∼60 years (**Figure 9**) indicated a substantial difference between Mn carbonate-rich and Mn-carbonate-poor inflow periods. Along with distinctly lower sulfide levels, bottom water oxygenation was of considerably longer duration during the Mn carbonate-rich period between the 1960s and mid-1970s (around 20 MBIs; Mohrholz et al., 2015) than was the case during the sporadic inflows entering the Gotland Basin in 1993, 2003, and 2015. This temporal aspect accords with observations in the Landsort Deep, where massive Mn carbonate formations also occurred during longlasting periods of hypoxic (slightly oxygenated) but non-euxinic bottom water conditions (Häusler et al., 2018). In contrast to the comparatively short presence of O2 in the bottom waters after the MBI of 2014, which fostered a considerable Mndiss reflux, longerlasting oxygenation would prevent the escape of Mn to the open water column and thus ensure a high Mn abundance at the SWI.

Although ranked as the third strongest MBI since 1880 (Mohrholz et al., 2015), the inflow from 2014 is rather of short-term relevance for Gotland basin. This is especially true when considering the fast return to an euxinic situation, which paradoxically is even promoted by the inflow of O2 containing but also highly saline waters strengthening water column stratification. Whether this episode will have a lasting effect on nutrient and trace metal budgets remains unclear so far and asks for continuing studies. For instance, the tight relation of Mn, Fe, and P at pelagic redoxclines due to formation of mixed solid phases comprising Mn oxide, Fe oxyhydroxides, and adsorbed phosphate (Dellwig et al., 2010) was also relevant during the current inflow as indicated by elevated deposition of P- and Fe-rich particles between July 2015 and June 2016 (Figure S4). However, the absence of P enrichments at the SWI during re-establishing euxinia (October 2016 and March 2017) suggests considerable release of phosphate back into the water column. While Mn carbonates incorporate certain amounts of phosphate (Jilbert and Slomp, 2013), as seen by elevated P/Al values in older Mn-rich layers below 10 cm sediment depth (**Figure 5** and Figure S4), this P sink is currently missing.

The lack of Mn carbonate not only compromises its use as an indicator for past inflow events but also has important implications for other proxies related to Mn authigenesis. A prominent example is Mo and its isotopes, showing strong fractionation during scavenging by Mn oxides (Wasylenki et al., 2008). The possible conservation of the altered isotope signature by sedimentary fixation of Mo released from dissolving Mn oxides may therefore result in misleading redox interpretations (Noordmann et al., 2015; Kurzweil et al., 2016; Scholz et al., 2018). Complementing studies including trace metals are required to shed more light on the possible pitfalls that may be generated by inflow events like the one in 2014 because such oxygenation events should be also of relevance for other restricted basins and fjords as well as ancient epicontinental seas that were often subjected to pronounced O2-deficiency but also redox changes (Hein et al., 1999; Jenkyns, 2010).

#### CONCLUSIONS

The dynamics of Mn in the water column and sediments were studied in the Gotland Deep (central Baltic Sea) subjected to an MBI of 2014. The first signals of water column oxygenation due to the approaching inflow waters appeared at the beginning of March 2015. This was followed by an estimated loss of nearly 90% of the Mndiss inventory in the water column over the following 2 months, which caused a remarkable deposition of Mn oxides. However, increased Mndiss pore water concentrations and fluxes as well as elevated bottom water Mndiss levels suggested the re-establishment of reducing conditions at the latest after 3.5 months. A second inflow pulse in the beginning of 2016 interrupted this development, but after less than 4 months there was a shift back to reducing bottom waters as well.

Budget calculations indicated a Mndiss recovery of ∼70% of the pre-MBI level at the end of the observation period in winter 2017. The recovery could not be explained by pore water fluxes from the central basin alone. Along with the Mnpart fluxes determined from a sediment trap, these estimates further suggested a pronounced basin-internal cycling of Mn during and subsequent to the MBI, which may have benefitted from the circulation patterns in the Gotland Basin and concomitant sediment focusing, including the transport of solid Mn phases from shallower areas toward the central deep.

A comparison of a dated sediment Mn record with instrumental O2/sulfide data generally confirmed the close relationship between Mn carbonate and inflow-related bottom water oxygenation. However, compared to the longer-lasting oxygenation periods in the 1960s and early 1970s, the less pronounced or even absent Mn enrichments after the single inflows in 1976, 1993, and 2003 implied unfavorable conditions for Mn carbonate formation, possibly due to the too rapid shift back to euxinic conditions. Since there was no indication for substantial Mn carbonate formation after both oxygenation pulses in 2015 and 2016 within our study period of ∼2 years, it appears rather unlikely that intensive Mn carbonate formation will take place under the currently fast re-establishing euxinic situation. This assumption compromises the use of Mn carbonate layers as a simple proxy for the identification of past MBIs. For instance, scavenged trace metals imported to an increased extent by deposited Mn oxides may serve as complementing proxies if conditions at the SWI assure their fixation. Nonetheless, the combined consideration of a previous study in the Landsort Deep (Häusler et al., 2018) and the present work in the Gotland Basin emphasizes the suitability of the deeps of the Baltic Sea as modern analogs for oxygendeficient but comparatively dynamic systems in the geological past.

#### AUTHOR CONTRIBUTIONS

OD designed the study, performed ICP measurements, and wrote the manuscript. BS contributed the gamma spectroscopy data. DM organized sampling during several cruises and contributed oceanographic knowledge. FP was responsible for the sediment trap. KH contributed to the age model. HA was involved in the oceanography and the age model. All authors contributed to data analysis, discussion, and finalization of the manuscript.

# ACKNOWLEDGMENTS

We are indebted to the IOW cruise leaders M. Gogina, G. Jost, K. Jürgens, J. Kuss, V. Mohrholz, M. Naumann, R. Prien, M. Schmidt, L. Umlauf, J. Waniek, N. Wasmund as well as U. Lips (Tallinn University of Technology) and R. Schneider (University of Kiel) for enabling extra CTD casts, J. Donath for water sampling during monitoring cruises, and to the captains and crews of the RVs Alkor, Elisabeth Mann Borgese, Maria S. Merian, Meteor, Poseidon, Prof. A. Penck, and Salme. We thank R. Bahlo and S. Plewe for the SEM-EDX support, A. Köhler for the acid digestions, U. Hehl and R. Hansen for sediment trap deployment and analyses, and T. Leipe and M. Moros for MUCs from cruises MSM51 and 62. The authors thank two reviewers for constructive comments on an earlier version of the manuscript. This work was funded by the Leibniz Association through grant SAW-2017- IOW-2 649 (BaltRap) and the IOW monitoring program. The publication of this article was funded by the Open Access Fund of the Leibniz Association.

Special thanks to our bosun Dieter Knoll, who died in late 2017.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars. 2018.00248/full#supplementary-material

#### REFERENCES

Cariaco Basin: a significant midwater source of organic carbon production, Limnol. Oceanogr. 46,148–163. doi: 10.4319/lo.2<IP_ADDRESS>8

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Dellwig, Schnetger, Meyer, Pollehne, Häusler and Arz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Impact of a Major Inflow Event on the Composition and Distribution of Bacterioplankton Communities in the Baltic Sea

Benjamin Bergen1 , Michael Naumann1 , Daniel P. R. Herlemann1,2, Ulf Gräwe1 , Matthias Labrenz1 and Klaus Jürgens1 \*

1 Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany, 2 Centre for Limnology, Estonian University of Life Sciences, Tartu, Estonia

#### Edited by:

Elinor Andrén, Södertörn University, Sweden

#### Reviewed by:

Pradeep Ram Angia Sriram, UMR 6023, Laboratoire Microorganismes Génome Et Environnement (LMGE), France Anyi Hu, Institute of Urban Environment (CAS), China

\*Correspondence: Klaus Jürgens<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Marine Science

Received: 31 May 2018 Accepted: 28 September 2018 Published: 26 October 2018

#### Citation:

Bergen B, Naumann M, Herlemann DPR, Gräwe U, Labrenz M and Jürgens K (2018) Impact of a Major Inflow Event on the Composition and Distribution of Bacterioplankton Communities in the Baltic Sea. Front. Mar. Sci. 5:383. doi: 10.3389/fmars.2018.00383 Major Baltic inflow (MBI) events carry highly saline water from the North Sea to the central Baltic Sea and thereby affect both its environmental conditions and its biota. While bacterioplankton communities in the Baltic Sea are strongly structured by salinity, how MBIs impact the composition and distribution of bacteria is unknown. The exceptional MBI in 2014, which brought saline and oxygenated water into the basins of the central Baltic Sea, enabled the linkage of microbiological investigations to hydrographic and modeling studies of this MBI. Using sequence data of 16S ribosomal RNA (rRNA) and 16S rRNA genes (rDNA), we analyzed bacterioplankton community composition in the inflowing water and in the uplifted former bottomwater at stations reached by the MBI. Bacterial diversity data were compared with respective data obtained from previous, non-inflow conditions. Changes in bacterial community composition following the 2014 MBI were mainly apparent at the genus level. A number of specific taxa were enriched in the inflowing water, with large changes in the rRNA/rDNA ratios indicating the different activity levels between of the water masses. The relative similarity of the bacterial communities in the inflowing and uplifted waters as well as the results from an inflow-simulating numerical model showed that the inflowing water did not originate directly from the North Sea but mostly from adjacent areas in the Baltic Sea. This suggested that the inflow event led to a series of shifts in Baltic Sea water masses among the Baltic Sea basins and a gradual mixing of the water bodies. Dramatic changes in the bacterial community composition occurred when the bottomwater inflow reached the anoxic, sulfidic deep basins, resulting in an uplifting of the formerly anoxic bacterial community, dominated by Epsilonproteobacteria. Our study of the impact of MBIs on bacterioplankton communities therefore highlights two relevant underlying mechanisms that impact the distribution and possibly also the activities of planktonic bacteria in the Baltic Sea: (1) the successive dilution of inflowing North Sea water with ambient waters and (2) the uplifting of former bottom-water communities to higher water strata.

Keywords: bacterioplankton, Baltic Sea, Major Baltic inflow, saltwater intrusions, RNA, DNA

# INTRODUCTION

fmars-05-00383 October 24, 2018 Time: 15:1 # 2

In the land-locked Baltic Sea, water is exchanged only with the North Sea, via the straits of the Kattegat and Skagerrak. The low seawater inflow together with strong freshwater inputs from rivers, rain, and melt water accounts for the elongated, stable salinity gradient of the Baltic Sea, with high salinities in the Skagerrak (salinity > 25) and low salinities in the Gulf of Bothnia (salinity < 5) (Reissmann et al., 2009). Another result is a permanent halocline in the central Baltic Sea that prevents vertical mixing and leads to permanent stratification and subsequent oxygen deficiency in the deep basins (Reissmann et al., 2009).

Major Baltic inflow (MBI) events, forced by special atmospheric conditions, occur occasionally in the autumn and winter and carry a volume of saline water from the North Sea that is large enough to reach the central basins of the Baltic Sea (Matthäus and Franck, 1992). The inflowing water in winter typically has a higher salinity (17.5–19), a lower temperature (2–8◦C), and higher oxygen content than the Baltic bottom-water (Matthäus and Franck, 1992; Omstedt et al., 2004). Several studies have shown that these inflowing, oxygenated waters can give rise to chemically and microbially mediated transformations in the deep, stratified basins, thereby affecting methane oxidation (Schmale et al., 2016), mercury species distribution (Kuss et al., 2017), manganese cycling (Dellwig et al., 2018), nutrient release from the sediments (Hall et al., 2017; Sommer et al., 2017), and macrozoobenthos communities (e.g., Laine et al., 1997), However, the mechanisms and magnitude by which MBIs change the composition, activity, and distribution of planktonic microbial communities in the Baltic Sea are currently not understood.

Nonetheless, that the Baltic Sea salinity gradient is a structuring force acting on bacterial community composition has been convincingly demonstrated in several studies (Riemann et al., 2008; ; Herlemann et al., 2011, 2016; Bergen et al., 2014), which also more generally confirmed that salinity is one of the most important determinants of the structure of microbial communities in aquatic systems (Lozupone and Knight, 2007; Nemergut et al., 2011). In estuaries, the dominant bacterial phyla/classes shift from a prevalence of Betaproteobacteria and Actinobacteria in oligohaline regions to one of Alpha- and Gamma-proteobacteria in higher salinity areas (e.g., Bouvier and Giorgio, 2002; Kirchman et al., 2005; Fortunato and Crump, 2011). This pattern also characterizes the Baltic Sea (Herlemann et al., 2011), where the salinity gradient is much more stable than in most estuaries. Additionally, an adapted bacterial community thrives in the brackish waters of the Baltic Sea and its composition differs significantly from that of its freshwater and marine counterparts. Because MBIs result in a major disturbance of the salinity gradient, particularly in deeper layers, and in the natural ventilation of the central basins (Matthäus and Franck, 1992), they can be expected to impact the structure of the Baltic's bacterial communities.

In December 2014, an exceptionally strong MBI occurred after the long stagnation period that followed the last MBI, in 2003. The 2014 MBI ranked as the third strongest among the recorded MBIs (Mohrholz et al., 2015). Between December 13th and 25th, a total water volume of 358 km3 was pushed into the Baltic Sea by the continuous strong westerly winds. The inflowing water included a highly saline volume (salinity > 17) of 198 km3 and salt transport of 3.98 Gt. During the initial inflow phase, in December 2014, a mean salinity of 20.8, a mean temperature of 7.7◦C, and a dissolved oxygen concentration of 6.5 mL/L were measured in the Arkona Basin (Naumann et al., unpublished data). As previously demonstrated for other MBIs (Umlauf et al., 2007) on its way to the Baltic Sea, the highly saline inflow water mixed with ambient waters and raised the former bottom-waters, such that new and distinct water masses were formed. The large volume of highly saline water propagated quickly through the western Baltic Sea and Bornholm Basin, passing the Slupsk Sill already in February 2015. This fast propagation was supported by a series of weaker inflows that had occurred earlier in 2014. The final arrival of the water mass and the oxygenation of the Gotland Deep at 240 m water depth occurred after this study, in mid April 2015 (Naumann et al., unpublished data).

In this study, we took advantage of this strong MBI to investigate the effect of inflowing saline water on the composition of bacterioplankton within the water column. Specifically, we asked whether characteristic marine bacterial assemblages are transported by the inflow to the central basins or does the inflowing marine bacterial community become diluted through successive mixing with adjacent water masses. To answer this question, we analyzed the bacterial community composition of the inflowing and uplifted water and compared the results with data collected in 2009 under non-inflow (stagnant) conditions (Herlemann et al., 2016). Differences in community composition were determined by next-generation sequencing (NGS) of partial 16S ribosomal RNA (rRNA) and 16S rRNA genes (rDNA), which also allowed the identification of potentially active taxa. Numerical hydrodynamic modeling was used to estimate the most likely origin of the sampled water masses (Gräwe et al., 2015), and thus to identify the initial location of the bacterial community in the inflowing water masses, despite the high turbulent mixing rates. The results provided the first insights into the changes in the bacterioplankton communities that occurred in response to the different water masses during the MBI that began in 2014. Thus, we were able to show that (1) during its passage from the North Sea to the interior of the Baltic, the inflowing water mixed with adjacent water masses such that the inflowing bacterial communities became increasingly similar to those already present, and (2) the displacement (uplifting) of whole water masses caused the transport of formerly anaerobic bacterial communities into water depths where they normally do not occur.

# MATERIALS AND METHODS

#### Sampling

Samples were taken in the Arkona Basin, Bornholm Basin, Slupsk Channel and the southwestern part of the Eastern Gotland Basin (**Figure 1**) during a cruise with the RV Elisabeth Mann Borgese in February 2015 (cruise EMB 95). Temperature, salinity,

oxygen, and chlorophyll fluorescence were measured using a CTD SBE911+ combined with a bottle sampler rosette, which comprised 13 10-L free-flow bottles. Sampling depths were chosen at each station according to the characteristics of the physical water mass revealed in the CTD profiles. At each station, one sample was taken from the inflowing water body and one from the uplifted bottom-water body, distinguished by different salinities, temperatures, and oxygen concentrations (**Figure 2**).

Water samples (1 L) used for DNA and RNA analysis were filtered onto 0.22-µm pore-size white polycarbonate filters. DNA and RNA were extracted according to Weinbauer et al. (2002). Concentrations of inorganic nutrients were analyzed as described by Grasshoff et al. (1983). For bacterial enumeration, subsamples (100 mL) were fixed for 1 h with 400 µl of 1% paraformaldehyde and 0.5% glutaraldehyde, shock-frozen in liquid nitrogen, and stored at −80◦C until processed by flow cytometry. After staining with SYBR Green, the samples were analyzed on a FacsCalibur (Becton Dickinson) using a modification of the method of Gasol and del Giorgio (2000).

# Amplicon Sequencing and Sequence Processing

For cDNA synthesis, DNA was removed from the RNA extracts by DNase I (Ambion/Applied Biosystems, Huntington, United Kingdom) digestion, following the manufacturer's protocol. RNA samples were transcribed into cDNA by a reverse transcriptase step, using the iScript Select cDNA synthesis kit (Bio-Rad, Hercules, CA, United States) with the primer 1492r. The DNA extracts and the generated cDNA for bacterial diversity analysis were sent to LGC Genomics GmbH (Berlin, Germany) for further processing. There, the primers Bakt\_341F (CCTACGGGNGGCWGCAG) and Bakt\_805R (GACT ACHVGGGTATCTAATCC) (Herlemann et al., 2011) were used for PCR amplification and sequences were generated on the Illumina MiSeq V3 platform in a 2 bp × 300 bp paired-end run. Pairs of forward and reverse primer-trimmed sequences were combined using BBMerge 34.48 and processed using the SILVA NGS pipeline (Quast et al., 2013; Glöckner et al., 2017) based on SILVA release version 123 (Pruesse et al., 2007). SILVA NGS performs additional quality checks according to the SINA-based alignments (Pruesse et al., 2012) with a curated seed database in which PCR artifacts or non-SSU reads are excluded. The longest read serves as a reference for the taxonomic classification in a BLAST (version 2.2.28+) search against the SILVA SSURef dataset (Quast et al., 2013). The classification of the reference sequence of a cluster (98% sequence identity) is then mapped to all members of the respective cluster and to their replicates. Best BLAST hits were only accepted if they had a (sequence identity + alignment coverage)/2 ≥ 93 or otherwise defined as unclassified. The 16S rRNA and rDNA raw sequence data have been submitted to the European Nucleotide Archive (ENA) under the Accession No. PRJEB27018.

The bacterial community composition associated with the inflow event was compared with that of a typical situation, before the MBI, in approximately the same and adjacent areas of the

Baltic Sea. For this purpose, we used sequence data from the western and central Baltic Sea obtained in February 2009 (for the positions of the 2009 stations see **Supplementary Figure 1**), as reported in Herlemann et al. (2016). DNA from the reference samples from 2009 was amplified using the same primers (Bakt\_341F and Bakt\_805R) as described in Herlemann et al. (2011). DNA from the 2009 samples was sequenced by Eurofins MWG GmbH on a 454 GS-FLX sequencer (Roche). For a detailed description of the amplification and 454 sequencing procedures, see Herlemann et al. (2011, 2016). To allow comparisons of the reference and inflow sequences, all sequences were processed together using the Silva NGS pipeline with standard settings.

#### Statistical Analyses

As the Gotland Basin samples derived from anoxic conditions and thus harbored very distinct bacterial communities, they were excluded from statistical analyses aimed at distinguishing the different bacterial communities in inflowing and uplifted waters. For all statistical tests, samples were grouped according to their origin. Explicet (Robertson et al., 2013) was used for providing bootstrapped-based subsampling for normalizing OTU counts in the bacterial alpha diversity. For this analysis all samples were reduced to 1000 reads. The difference between the bacterial communities were visualized by non-metric multidimensional scaling plots based on the Bray–Curtis dissimilarity matrix, using the software PAST (Hammer et al., 2001). For these analyses, the sum-normalized OTU abundances were combined with data from the investigation conducted during stagnant conditions in February/March 2009 (Herlemann et al., 2016). A linear discriminant analysis (LDA) effect size (LEfSe) (Segata et al., 2011) 1 was used to test for discriminatory taxa in the different water masses, inflow and uplifted waters, based on relative rDNA and rRNA abundances. Based on a normalized relative abundance table, LEfSe applies the Kruskal–Wallis rank sum test to identify OTUs with significantly different abundances and performs an LDA to estimate the effect size of each feature. In this study, an alpha value of 0.05 and an effect size threshold of three were considered to indicate statistical significance.

#### Physical Numerical Model

To follow the inflowing water masses and quantify their transport pathways, a three-dimensional hydrodynamic model, the General Estuarine Transport Model (GETM), was used in a multi-nested downscaling framework extending from the North Atlantic (8 km resolution) to the Western Baltic Sea (600-m resolution). The numerical model provides hourly mean values of velocity, salinity, and temperature at every grid point and reproduced the 2014 MBI in detail (Gräwe et al., 2015; Mohrholz et al., 2015). Previous studies demonstrated the utility of the GETM in simulating inflow events and in allowing statistical analyses of inflows in the western Baltic Sea (Burchard et al., 2005; Gräwe et al., 2013). Our study used the same model setup as described in Gräwe et al. (2015). Based on the output of the hydrodynamic model, a particle-tracking tool was applied that enabled the water masses to be marked and followed, including tracking of the water masses back in time to estimate the potential sources and/or origins of distinct water parcels. Backtracking was started at the sampling stations in the Bornholm Gat (TF0145) and Slupsk Channel (TF0222) and was used to analyze the origin of the inflowing water masses in greater detail.

# RESULTS

#### Characterization of the Water Masses

The very strong inflow arising from the 2014/2015 MBI was clearly evident from the CTD profiles obtained from the Arkona Basin and Bornholm Basin; a representative example is shown in **Figure 2** (Bornholm Deep). The highly saline bottom layer (salinity > 17) in the Bornholm Basin was ∼34 m thick, with a clearly higher oxygen concentration and lower temperature (**Figure 2**, dashed box) than the uplifted former bottom-water (at 50–60 m depth). This mixture of inflow water and uplifted former bottom-water (>8 ◦C, salinity 12–17, 2–5 mL/L) passed the Slupsk Sill (58 m sill depth), which otherwise forms a natural barrier between the Bornholm and central Baltic basins, of which the Gotland Basin is the farthest to the northeast.

**Figure 3** shows a hydrographic cross-section reaching from the Darss Sill to the Eastern Gotland Basin, including the sampling stations and sampling depths and the general situation along the "Baltic thalweg" (Burchard et al., 2005;

1http://huttenhower.sph.harvard.edu/lefse/

Lilover et al., 2017) of water flowing into Baltic basins until the analyzed stage of the inflow event. During the sampling period, most of the MBI inflow water volume (about 90%) was estimated to be present in the Bornholm basin, below a water depth of 60 m (Naumann et al., unpublished data). The uplifted inflow water body, clearly apparent by its higher temperature (>7 ◦C), lower salinity (12–15), and a lower dissolved oxygen concentration (2– 4 mL/L), originated from a weak summer inflow in August of that year (Naumann et al., unpublished data). Anoxic/suboxic bottom-water in the Eastern Gotland Basin was clearly uplifted by this inflowing oxygenated, more saline water (station G1, **Figure 3C**), whereas deeper water (below 120 m depth) in the Gotland Basin remained anoxic and was not influenced at that stage of inflow propagation (station G2, **Figure 3C**).

An estimation of the flow pattern of the MBI along the stations sampled was obtained based on the features of the water masses determined from the CTD profiles and on information from previously published studies of this MBI (e.g., Gräwe et al., 2015; Mohrholz et al., 2015) (**Figure 1**). The stations first impacted by the MBI were those of the Arkoma Basin, A1 and A2, followed

by stations B1 and B2 of the Bornholm Basin. Thereafter, the MBI spread in different directions, with the central and southern stations B3 and B7 probably reached more or less simultaneously, due to the deflection of gravity currents to the right by the Coriolis force at the northern hemisphere, followed shortly thereafter by station B4, then stations B6 and S1, stations B5 and S2, and finally Gotland Basin station G1. At the bottom-water stations B5 and B6, the water probably consisted of the less-mixed original inflow water of December 2014 (temperature < 7.4◦C, salinity > 18, dissolved oxygen > 5.2 mL/L), whereas at the bottom of the sill stations S1 and S2 (temperature > 7.7◦C, salinity 16.6, dissolved oxygen < 4.3 mL/L) the water was composed of new inflow water strongly mixed with former bottom-water from the Bornholm Basin and Slupsk Channel, as evidenced by the higher temperatures and lower oxygen concentrations. At the time of sample collection, the inflowing water had not yet reached Gotland Basin station G2, which still had anoxic bottom-water.

As expected, salinity and temperature were higher in the inflow water and the uplifted bottom-water than in the reference water from the stagnation period in winter 2009 (**Table 1**). The higher temperature of the sampled water could be attributed to the August 2014 and December 2014 inflows. During these events, the warmed summer and autumn surface water of the Mecklenburg Bight (overflow August 2014) and Kattegat (inflow December 2014) penetrated the deep water of the Baltic basins and was warmer than the bottom-water of the previous stagnation period. The salinity and temperature values as well as the phosphate, silicate, nitrite, and nitrate concentrations of the uplifted bottom-water, especially that of the Arkona Basin, were between those of the inflow and reference waters of 2009. A comparison of the concentrations of dissolved nitrogen compounds in the Arkona and Bornholm Basins, as determined in samples from this study, with those of the reference samples from winter 2009 revealed that, due to the inflow water, the ammonia concentration was significantly lower in both basins, the nitrite concentration was lower in the Arkona Basin, and the nitrate concentration was higher in both basins (**Supplementary Figure 2**). Total prokaryotic cell numbers were in the same range, 6.6–8.0 × 105 mL−1 , with considerable variability between the stations but no apparent trend and with values roughly similar to those in samples from the stagnant period of 2009 (**Table 1**).

#### Back-Trajectory of the Water Masses

The origin of the sampled inflow water, estimated by numerical modeling and particle tracking, is depicted in the probability maps of **Figure 4**. According to the maps, the sampled water mass likely originated from a specific region in the western Baltic Sea. For the two sampling stations, located in the Bornholm Gat (A2) and Slupsk Channel (S2, see **Figure 1**), the maps show similar results for the two time slices: a main inflow period during December 13–25, 2014 and a pre-inflow stage that occurred in mid-October 2014. During the main inflow period (upper panels in **Figure 4**), the possible origin of both sampled water masses may have been the Arkona Basin and the southern Danish Belt Sea. Thus, there was a high probability that both samples were in contact with the inflowing saline water. Due to the high degree of mixing (lateral but also vertical) during the inflow, the initial start position of the sampled water masses could not be further specified. The lower maps show the position of the sampled water in October, the pre-inflow stage, and indicate an area spanning from the Skagerrak to the Danish Belt Sea, which is a common finding for such events. During this pre-inflow stage, the saline water of the Danish Belt Sea was pushed farther north into the Kattegat, due to a lowering of the water level in the Baltic Sea and the resulting outflow. Furthermore, because of the Earth's rotation, this outflowing water probably accumulated on the eastern side of the Kattegat. This specific pattern, illustrated in the lower panels of **Figure 4**, indicated that the water originated from the Danish Belt Sea and thus allowed an estimation of the origin of the sampled inflow water from this transition zone between the North Sea and the Baltic Sea.

# Taxonomic Composition of the Microbial Communities in the Different Basins and in the Inflowing and Uplifted Water Bodies

We compared the bacterial community compositions of all the samples from this study (excluding the anoxic Gotland stations) with reference samples from the stagnant situation in winter 2009, which covered also those area of potential inflow water origin (Skagerrak, Belt Sea, Western Baltic) as well as the same locations as in this study (Arkona and Bornholm Basins) (Herlemann et al., 2016). The nonmetric multidimensional scaling (NMDS) plot (Bray–Curtis dissimilarity) of the bacterioplankton community composition revealed a clear clustering of the respective bacterial communities according to their location (**Figure 5A**). The more saline stations from the Skagerrak, Kattegat, Belt Sea, and Western Baltic (reference 2009) were clearly separated from stations in the Arkona and Bornholm Basins. Samples from this study (**Figure 5A**, red symbols) clustered together for the Arkona and Bornholm Basins, slightly separated from samples from the reference study of 2009 (**Figure 5A**, blue symbols). The Bornholm samples from 2009 spread more widely whereas those from this study (including samples from the inflow and uplifted waters) were more tightly clustered (**Figure 5A**). A more detailed look at only the Bornholm Basin samples from this study showed the clear separation of the rRNA- and rDNA-based compositions on the first coordinate, with no overlap. Further, both the rRNAand rDNA- based bacterial community compositions of the inflowing and uplifted water bodies were separated on the second coordinate (**Figure 5B**). To visualize the relationship between the variability in the community composition and the features of the water mass, the physicochemical parameters were plotted in the NMDS ordination as fitting environmental variables (only the Bornhom Basin, **Supplementary Figure 3**). The variation in community composition correlated with differences in salinity and oxygen (higher in the inflow water) and partly also with nutrient levels (higher in the uplifted water). Alpha diversity was significantly higher in the samples from the Arkona and Bornholm Basins obtained in this study than in all reference samples from 2009 (**Supplementary Figure 4**). A direct

Mean values ± SD.

comparison of the inflowing and uplifted water masses revealed that for most stations diversity (OTU number and ShannonH) was slightly higher in the inflowing than in the uplifted water, both with the rDNA and the rRNA analyses (**Supplementary Figure 5**). Only the Gotland samples, containing anaerobic communities, deviated strongly from the other stations, showing a strongly reduced diversity (**Supplementary Figure 5**).

To elucidate the broad taxonomic changes that occurred between the inflowing and uplifted water bodies in the different basins, both 16S rDNA and 16S rRNA sequence data were examined. According to the analysis at the phylum/class level, in which the data for the different basins were pooled, 87–90% of the sequences could be assigned to these major phyla/classes; only 10–13% were unclassified or belonged to rare phylogenetic

FIGURE 5 | (A) Non-metric multidimensional scaling (NMDS) plots (Bray–Curtis dissimilarity, NMDS stress = 0.1133) of bacterioplankton community composition from different basins of the Baltic Sea, based on the rDNA analysis. The blue symbols represent samples from a reference study (Herlemann et al., 2016), which included the Skagerrak/Kattegat, Belt Sea, Western Baltic, Arkona and Bornholm Basins, and the red symbols samples from this study, including the Arkona and Bornholm Basins. (B) NMDS plot (Bray–Curtis dissimilarity, NMDS stress = 0.1046) of bacterioplankton community composition from the Bornholm Basin (this study only) based on rRNA and rDNA analyses. Full symbols indicate DNA-based and open symbols RNA-based bacterial communities. Dots represent the uplifted water masses and triangles the inflow water. The environmental variables inflow vs. uplifted water masses and rDNA vs. rRNA were added as post hoc vectors to the NMDS graph, representing the correlations between the environmental variables and NMDS scores.

groups (**Figure 6**). The bacterial composition at all stations until the inflow to station G1, including the Arkona Basin, Bornholm Basin, and Slupsk Channel, was comparable at this broad taxonomic resolution, and quite consistent between the rRNA- and rDNA-based analyses (**Figure 6**). Alpha- and Gammaproteobacteria were the most abundant groups in these samples, with an average relative abundance of 26 and 14%, respectively. Other important groups, with relative abundances of 5–10%, were Deltaproteobacteria, Bacteroidetes, Planctomycetes, Chloroflexi, and Actinobacteria. The rRNA- and rDNA-based compositions were only slightly different, with increased proportions of Firmicutes, Deltaproteobacteria and Chloroflexi, and decreased proportions of Bacteroidetes and Planctomycetes according to the rRNA data (**Figure 6**). The variations between the locations of the Arkona and Bornholm Basins and Slupsk Channel, and between the inflowing and uplifted waters, were rather small. However, in the Bornholm Basin, where the number of stations covered was sufficient to allow statistical tests, the inflowing and uplifted bacterial communities were significantly different at the phylum/class level (p < 0.01). A strikingly different community composition was apparent for the two Gotland basin stations G1 and G2, which were dominated by Epsilonproteobacteria. However, the water inflowing into station G1 (91 m depth), had a high overall similarity with the uplifted bottom-water from the Bornholm Basin, with a large proportion of Alphaproteobacteria, and only 6.8% Epsilonproteobacteria. By contrast, Epsilonproteobacteria constituted 59% of all sequences in the uplifted water at station G1 (82 m water depth). Station G2, which was not yet impacted by the MBI, was entirely dominated (85%) by Epsilonproteobacteria in the deeper waters (126 and

126 m, b: 120 m).

120 m) and contained only small proportions of the other phyla.

# Distribution and rRNA/rDNA Ratios of Dominant OTUs

For the most abundant OTUs (>0.5% relative abundance across all stations), the relative proportions at the different stations were visualized in heatmaps. Similar trends were detected in the data from the two analyses, at the rDNA (**Supplementary Figure 6**) and rRNA level (**Figure 7**), but the latter showed a more pronounced pattern for some dominant OTUs and is therefore presented here. ANOSIM revealed significant differences at the rDNA OTU level (R = 0.721) between the inflow-water and uplifted bottom-water communities. Fifteen OTUs from various phyla were determined to be significantly enriched in the inflowing water bodies across the stations sampled (**Supplementary Table 1**). For some OTUs a characteristic alternating sequence between inflowing and uplifted waters became visible, as best seen for the OTU "unclassified SAR202 clade," belonging to the Chloroflexi. In the inflowing water from the Arkona Basin this OTU was present in only modest abundance whereas it became the most abundant taxon in the uplifted water of the different stations in the Bornholm Basin, indicating that it dominated the bottom-waters of this basin, before being uplifted by the inflow. Alternating abundances in the inflowing and uplifted waters were also partly visible for other taxa such as the OTUs "unclassified Rhodospirillaceae" and "unclassified OM27." There were also OTUs, such as the alphaproteobacterial OTU "unclassified T9d," and the OTU "unclassified WCHB1," that showed a reverse alternating pattern, with a higher abundance in the inflowing and a lower abundance in the uplifted water (**Figure 7**). A third pattern was exemplified by the OTU "unclassified Nitrospina," a widespread marine nitrite oxidizer (Lücker et al., 2013). For this as well as a few other OTUs, a successive decline in relative abundance was determined, probably linked to the dilution of inflowing with existing water masses. The OTU "unclassified SAR86," belonging to a widespread marine gammaproteobacterial group, was successively diluted and no longer detectable at stations toward the end of the Bornholm Basin (**Figure 7**). By contrast, the OTU Nitrospina declined with inflow propagation but was still detectable in considerable abundance in the inflowing water bodies. The epsilonproteobacterial OTU Sulfurimonas was present only in the Gotland Deep stations, but with a relative abundance > 55%, accompanied by only few other taxa.

The rRNA/rDNA ratios for dominant bacterial OTUs in the different water masses and stations were determined, taking into account only those OTUs with a relative abundance of all sequence reads of >0.5% at both the rRNA and rDNA levels. The overall range in rRNA/rDNA ratios for the OTUs that met these criteria was quite large (**Supplementary Table 2**). Due to the variability between stations and because data were

not available for all inflow/uplift pairs, the mean values for all inflow water bodies were not significantly different from those of the uplifting water bodies for an of the OTUs (**Supplementary Table 2**). However, several OTUs underwent strong changes between the inflow and uplifted water at some stations. For example, at the two Arkona basin stations (A1, A2), in the uplifted water there was a large increase in the ratio for the OTUs "unclassified Rhodospirillaceae," "unclassified SAR116," and Nitrospina (**Supplementary Figure 7**). For the latter, the ratio first increased by a factor of 5–7, but it then decreased in the Bornholm basin and leveled off to values mostly in the range of 2–4.

### DISCUSSION

Bacterial communities in estuaries and coastal margins differ spatially in their composition because of the prevalent gradients in salinity, nutrients, and the other components needed for bacterial growth. However, most estuaries are shaped by hydrodynamic forces, which are responsible for the mixing and characteristic short retention times of their waters. By contrast, in the Baltic Sea, the long water residence time (>5 years) (Reissmann et al., 2009) allows the adaptation of freshwater bacteria to brackish conditions (Riemann et al., 2008) and the coexistence of marine and freshwater lineages, together with presumed brackish water clades, in waters with a salinity of around 7 (Herlemann et al., 2011). Although several studies have addressed the distribution of freshwater and marine bacterial lineages in the Baltic Sea (Riemann et al., 2008; Herlemann et al., 2011, 2014; Piwosz et al., 2013; Bergen et al., 2014), the extent to which MBIs transport typical marine bacterial communities into the brackish parts of the Baltic Sea is unknown, as is the impact of inflowing water masses of relatively high salinity on the composition, distribution and activity of bacterioplankton during the transit of inflow-driven water bodies into the central Baltic Sea. This study is the first to address these questions, by taking advantage of the large MBI of 2014, investigated in detail with respect to its magnitude and temporal development, to link microbiological investigations with the hydrographic and modeling studies. Our data on the bacterioplankton communities, obtained using both rRNA- and rDNA-based community analyses, indicate a high degree of mixing of the inflowing water with the former bottom-waters, a conclusion consistent with the numerical modeling results. Moreover, we were able to show that, among the different water masses, specific bacterial taxa undergo changes in abundance and in their rRNA/rDNA ratios. We were also able to document an example of the displacement by the inflowing water of an entire bacterial assemblage into other water layers.

## Characterization of the MBI Water Bodies

The development and dynamics of the 2014 MBI were investigated and followed in a series of cruises preceding our study. The data were complemented by CTD measurements of the permanent autonomous stations of the German Marine Monitoring network (MARNET), located at the Darss Sill and the Arkona Basin (Mohrholz et al., 2015), the autonomous Gotland Deep Environmental Sampling Station (GODESS) (Holtermann et al., 2017), and numerical modeling (Gräwe et al., 2015). The 2014 MBI is thus one of the best monitored MBIs in the Baltic Sea to date, with reliable estimates of inflow volume, as well as oxygen and salt transport. The data provided support for our proposed sequence of stations along which deep water transport and the uplifting of bottom-water presumably occurred (**Figure 1**).

An evaluation of the impact of the MBI on bacterioplankton communities required as a prerequisite a clear picture of the water mass transport through the western Baltic Sea and the deep basins. CTD measurements, in combination with an eddyresolving hydrodynamic model, reproduced the timing and pattern of the inflowing saline water and revealed its successive mixing with the stagnant bottom-water on its way toward the interior of the Baltic Sea (Gräwe et al., 2015). The temporal evolution of salinity and temperature suggested that already onethird of the inflowing water had been mixed away by the time it reached the Bornholm Channel (Gräwe et al., 2015), the first sampling site of this study. The back-trajectory of the water masses sampled in the Arkona and Bornholm Basins suggested that the origin of the inflowing water was in the area between the Skagerrak and Danish Belt Sea. The widespread pattern of potential origins (**Figure 4**) indicated a high degree of mixing, both vertical and horizontal. However, given the extraordinary size of this inflow event, this strong mixing was not surprising.

When saline water enters the basins and uplifts existing bottom-water, some mixing of these water masses has to be assumed. The effects on bacterial assemblages are two-fold: first, different bacterial communities from the two water bodies are mixed; second, inputs of substrates and/or electron acceptors (oxygen, nitrate) may change the growth conditions of some taxa and modulate their activities. For the Bornholm Basin during the 2014 MBI, the situation was more complex because the uplifted bottom-water was not identical to the bottom-water present during the prolonged stagnation period in the Baltic Sea (2003– 2014) that preceded the 2014 MBI. Rather, it already consisted of a mixture with the warmer water that derived from several smaller inflows into the Bornholm Basin earlier that same year (Naumann, 2015).

This study provides a snapshot of the MBI dynamics in February 2015, when the inflowing water had reached the southern edge of the Gotland Basin (station G1) but not yet the central basin. Later on, the MBI continued into the Gotland Basin and was followed by additional, smaller inflows, and two moderate MBIs in November 2015 and January–February 2016 (Naumann et al., unpublished data).

## Impact of the MBI on the Composition and Distribution of the Baltic Sea Bacterial Communities on a Broad Phylogenetic Level

The relatively stable Baltic Sea salinity gradient, ranging from marine conditions in the Skagerrak to nearly limnic conditions in the Gulf of Bothnia, is an ideal natural model system to

examine how salinity impacts the composition and functions of bacterioplankton communities. Studies within the last several years have revealed that Baltic Sea salinity determines the bacterial composition at broad phylogenetic levels, with Alphaand Gamma-proteobacteria dominating at more marine, and Betaproteobacteria and Actinobacteria at more limnic conditions (Herlemann et al., 2011). Community shifts at the phylum level occur in the brackish area of the Baltic Sea within a critical salinity range of 5–8 (Herlemann et al. (2011). Although strong seasonal shifts in bacterial composition have been documented (Andersson et al., 2009), data collected across the whole Baltic Sea imply that salinity provides a stronger phylogenetic signal in bacterial community composition than seasonality (Herlemann et al., 2016). Moreover, metagenomic analyses indicate that salinity-related changes in bacterial community composition are associated with changes in metabolic functions (Dupont et al., 2014).

These insights into bacterial composition along the salinity gradient suggest that any inflow of saline waters into the Baltic Sea will also import different (i.e., mainly marine taxa) bacterial communities into the central Baltic Sea. However, the continuous entrainment of overlying water during the passage of new, deep water from the North Sea into the Baltic Sea's basins also results in a successive dilution of the original communities. Therefore, the high similarity between the communities of the inflowing and former bottom-waters (uplifted) in the Arkona and Bornholm Basins, at least on a broad phylogenetic level (**Figure 6**), was not really surprising. This similarity was evident from not only the rDNA but also the rRNA analysis (**Figure 6B**); rRNAbased analyses have generally been used to assess the more "active" fraction of prokaryotes (e.g., Hunt et al., 2013). The successive dilution of inflowing water was also suggested by numerical modeling of the water transport (**Figure 4**). Other factors might also enhance the removal of imported marine taxa, such as inhibition due to more unfavorable conditions and losses due to viral lysis and grazing. Furthermore, the state of the deep water of the Bornholm Basin had probably already slightly changed compared to the previous stagnant conditions, due to smaller inflows of warmer water in 2014 that had mixed with old bottom-water. Despite these changes in the bottom-waters, the bacterial community compositions were rather similar to those of the reference data from 2009, as seen in the clustering of samples in the NMDS plots (**Figure 5A**). However, an inspection of only the Bornholm Basin stations, for which the most samples had been gathered, revealed obvious differences in the communities of the inflowing and uplifted water masses, both at the rDNA and the rRNA level (**Figure 5B**).

The most profound impact of the inflow water was visible in the Gotland Basin, which also represented the former stagnant water body and associated microbial communities because it had not been reached by the previous smaller inflows that occurred in 2004 (Naumann et al., unpublished data). In the Gotland Basin, a bacterial assemblage typical for the anoxic waters of the central Baltic Sea (e.g., Labrenz et al., 2007) was largely replaced by one that resembled the communities found in the adjacent oxygenated basins (Arkona, Bornholm) (**Figure 6**). Epsilonproteobacteria, which dominate near oxicanoxic interfaces in the Baltic Sea and depend on the availability of sulfide and nitrate for chemoautotrophic denitrification (Grote et al., 2012), were a good indicator of the former anaerobic community. The inflowing saline water mass uplifted the former oxygen-deficient bottom-water, and thus also its anaerobic bacterial community. Interestingly, Epsilonproteobacteria were found, in a small proportion (5–7%), also in the inflowing water of the southern Gotland station (G1) (**Figure 6**). As this bacterial group was not detected at the (oxic) stations before G1, its proportion can be considered indicative of the degree of mixing that occurred when the inflowing water uplifted the existing bottom-water. This observation demonstrates that in addition to ventilating the Baltic Sea's deep basins (Omstedt et al., 2004) MBIs can directly shift bacterial communities to water strata where they are normally not found.

## Impact of the MBI on the Composition and Distribution of the Baltic Sea Bacterial Communities on a Fine Phylogenetic Level

The Epsilonproteobacteria in the oxygen-deficient basins of the Baltic Sea consist nearly entirely of the Sulfurimonas group (Grote et al., 2012). In the oxic water column, Sulfurimonas spp. may serve as a strong indicator of displaced anoxic bottom-water, as this taxon is able to survive in the presence of oxygen but only proliferates around the oxic-anoxic interface (Grote et al., 2012). The previous appearance of Sulfurimonas in Baltic Sea surface waters, together with other anaerobic taxa, has been interpreted as the result of an upwelling event, that transported chemocline water to the surface (Lindh et al., 2015).

At a finer phylogenetic resolution (OTUs), further differences between the studied water masses became apparent, including the enrichment of several taxa in the inflow water compared to the former bottom-water (**Supplementary Table 1**). These taxa mainly belonged to Bacteroidetes, Chloroflexi, Planctomycetes, and Alpha-, Delta-, and Gamma-proteobacteria (**Supplementary Table 1**), with some of them related to known marine taxa (e.g., Brown et al., 2009). The SAR202 clade within the Chloroflexi is widespread in the mesopelagic and deep ocean (Morris et al., 2004) but has also been detected in high abundance in Baltic Sea sediments (Klier et al., 2018). This suggests an input of Chloroflexi cells from sediments into the water column, driven by the turbulence generated by inflowing water. The resuspension of sediments due to inflowing water has been observed (Naumann et al., unpublished data). Planctomycetes diversity was high in the inflow water. Members of this group have been found in the Baltic Sea, including two potential anaerobic ammoniumoxidizing phylotypes from the suboxic zone of the central Baltic (Brettar et al., 2012) and several related OTUs in the sea's brackish and marine areas (Herlemann et al., 2011). An analysis by Rieck et al. (2015) of the particle-associated bacterial communities in three salinity zones of the Baltic Sea showed a dominance of particle-associated Planctomycetes in the central Baltic. These Planctomycetes mainly consisted of the OTU CL500-3, which was also enriched in the inflow water of this study. The origin and

reason for the enrichment of this group in the inflow water are unclear but a broader distribution than previously recognized seems probable. The Alphaproteobacteria enriched in the inflow water mainly comprised Rhodobacteraceae and Rhodospirillaceae. Enriched Gammaproteobacteria were exclusively represented by Oceanospirillales. These groups have also been detected in marine areas of the Baltic Sea (Herlemann et al., 2011) and their immigration with the inflow water was therefore likely.

At the OTU level, interesting patterns along the inflow stations became apparent (**Figure 7**). Whereas some OTUs were successively diluted with progression of the inflow, others showed alternating abundances between the inflow and uplifted water bodies, indicating that they had occurred in higher abundance in the bottom-water and became uplifted by the inflow. The higher overall OTU richness (alpha diversity) in the Bornholm and Arkona Basins during our study compared to the reference samples from 2009, based on the rDNA analysis, also indicated that partial mixing of different water bodies with different bacterial communities increased the overall bacterial diversity (**Supplementary Figure 3**).

#### rRNA/rDNA Ratios

The parallel analysis of rDNA- and rRNA-based community composition also allowed calculation of the rRNA/rDNA ratios of the dominant OTUs. This ratio has been used to distinguish the different growth strategies of marine bacteria (oligotrophs vs. copiotrophs) (Lankiewicz et al., 2015), but also to decipher seasonal changes in the activity status of specific taxa as well as differences between free-living and particle-associated OTUs (Denef et al., 2016). The dominant bacterial OTUs for which a reliable sequence threshold was reached for both rRNA and rDNA all showed a considerable variation in this ratio, but within the range determined in other studies (e.g., Denef et al., 2016). Although the average values of these ratios did not significantly differ between inflowing and uplifted water bodies (**Supplementary Table 2**), the pattern across the stations suggested strong changes in some of the taxa between these water bodies (**Supplementary Figure 5**). This, together with the large changes in relative abundance along the stations (**Figure 7**) probably indicates different growth conditions in the different water bodies.

A striking example of differing rRNA/rDNA ratios was Nitrospina, for which large increases in its ratios in the uplifted water of the Arkona Basin were determined (**Supplementary Figure 5**). The genus Nitrospina is a widespread marine nitrite oxidizer, mainly below the euphotic zone and in sediments (Ngugi et al., 2015; Daims et al., 2016). This OTU may have been transported with the inflow water, and its potential activity (e.g., nitrite oxidation) was enhanced by the newly encountered nutrient conditions. Indeed, the concentrations of inorganic nitrogen compounds in the inflow water differed from those usually found in the study area (**Supplementary Figure 2**). The low concentrations of ammonia and nitrite and the high concentration of nitrate might have resulted from enhanced nitrification in the inflow water. Ammonia-oxidizing bacteria were not detected in higher abundance in our samples, but it is known that ammonia oxidation in the deeper waters of the Baltic Sea is dominated by ammonia-oxidizing archaea (Berg et al., 2015), which were not covered by our primers.

# CONCLUSION

This study is the first to describe the impact of an MBI on the composition and distribution of Baltic Sea bacterioplankton. Our results provide evidence of two major mechanisms that explain the observed impact on the bacterial communities of the central Baltic Sea basins: first, successive mixing of inflowing saline water along the transit through the Baltic Sea resulted in relatively similar bacterial assemblages between inflowing and former bottom-water communities on a broad phylogenetic level. Therefore, a typical marine bacterial assemblage did not arrive by the MBI in the central Baltic Sea. However, significant community changes were apparent at the OTU level, revealing the enrichment of certain taxa with the inflowing water, different patterns of changing abundance and varying rRNA/rDNA ratios in the different water bodies. Second, the uplifting of former bottom communities, with their key indicator taxa, resulted in their displacement into different water strata. This was best illustrated by the arrival of the 2014 MBI at a station in the Gotland Basin, where the former anoxic bottom community, dominated by Epsilonproteobacteria, was shifted to shallower water depths. The implications of these shifts in water masses and microbial communities for microbially mediated ecosystem functions are not yet fully understood. However, they can perhaps be determined in studies that examine the functional performance of key bacterial taxa and their physiological changes in response to mixing with inflowing water or to the uplifting to new water layers with different environmental conditions.

# ETHICS STATEMENT

All authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors.

# AUTHOR CONTRIBUTIONS

BB, MN, ML, and KJ planned, initiated, and conducted the study. MN gathered and provided hydrographic data. UG conducted the backtracking numerical model. DH helped with the analysis of bacterial diversity data. BB and KJ wrote the first draft of the manuscript. All authors discussed the results and edited the manuscript.

# FUNDING

This work was funded by the Deutsche Forschungsgemeinschaft (DFG) (projects JU367/15-1, JU367/16-1 to KJ and LA1466/8- 1 to ML). DH was supported by the European Regional Development Fund and the Estonian Research Council Mobilitas Plus Top Researcher grant "MOBTT24." UG was supported by the BMBF project "Hydrodynamic observations and simulations of munition in the sea," a subproject of the collaborative project "Environmental monitoring for the delaboration of munitions in the sea" (Grant No. #03F0747C).

#### ACKNOWLEDGMENTS

fmars-05-00383 October 24, 2018 Time: 15:1 # 13

We thank the captain and crew of the RV Elisabeth Mann Borgese for assistance in sampling during the EMB 95 cruise.

#### REFERENCES

The sampling campaign was done within the framework of the IOW's long-term data program, which was quickly adapted to take advantage of the special inflow situation with additional "task force inflow" sampling. We also thank Stephanie Mothes for technical assistance at sea.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars. 2018.00383/full#supplementary-material

ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196. doi: 10.1093/nar/gkm864

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Bergen, Naumann, Herlemann, Gräwe, Labrenz and Jürgens. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Understanding the Coastal Ecocline: Assessing Sea–Land Interactions at Non-tidal, Low-Lying Coasts Through Interdisciplinary Research

Gerald Jurasinski1,2† , Manon Janssen3† , Maren Voss1,4, Michael E. Böttcher1,5 , Martin Brede1,6, Hans Burchard1,7, Stefan Forster1,8, Lennart Gosch3 , Ulf Gräwe7 , Sigrid Gründling-Pfaff9 , Fouzia Haider8 , Miriam Ibenthal3 , Nils Karow6 , Ulf Karsten1,9 , Matthias Kreuzburg10, Xaver Lange7 , Peter Leinweber1,11, Gudrun Massmann12 , Thomas Ptak13, Fereidoun Rezanezhad14, Gregor Rehder1,10, Katharina Romoth15 , Hanna Schade8 , Hendrik Schubert1,15, Heide Schulz-Vogt1,4, Inna M. Sokolova1,8 , Robert Strehse11, Viktoria Unger2 , Julia Westphal5 and Bernd Lennartz1,3 \*

1 Department of Maritime Systems, Interdisciplinary Faculty, University of Rostock, Rostock, Germany, 2 Landscape Ecology, Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany, 3 Soil Physics, Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany, 4 Biological Oceanography, Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany, 5 Geochemistry and Isotope Biogeochemistry, Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany, 6 Fluid Mechanics, Faculty of Mechanical Engineering and Marine Technology, University of Rostock, Rostock, Germany, 7 Department of Physical Oceanography and Instrumentation, Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany, 8 Marine Biology, Faculty of Mathematics and Natural Sciences, University of Rostock, Rostock, Germany, 9 Phycology and Applied Ecology, Faculty of Mathematics and Natural Sciences, University of Rostock, Rostock, Germany, 10 Marine Chemistry, Leibniz Institute for Baltic Sea Research Warnemünde, Rostock, Germany, 11 Soil Science, Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany, 12 Hydrogeology, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany, 13 Department of Applied Geology, University of Göttingen, Göttingen, Germany, 14 Ecohydrology Research Group, Water Institute and Department of Earth & Environmental Sciences, University of Waterloo, Waterloo, ON, Canada, 15 Aquatic Ecology, Faculty of Mathematics and Natural Sciences, University of Rostock, Rostock, Germany

Coastal zones connect terrestrial and marine ecosystems forming a unique environment that is under increasing anthropogenic pressure. Rising sea levels, sinking coasts, and changing precipitation patterns modify hydrodynamic gradients and may enhance sea–land exchange processes in both tidal and non-tidal systems. Furthermore, the removal of flood protection structures as restoration measure contributes locally to the changing coastlines. A detailed understanding of the ecosystem functioning of coastal zones and the interactions between connected terrestrial and marine ecosystems is still lacking. Here, we propose an interdisciplinary approach to the investigation of interactions between land and sea at shallow coasts, and discuss the advantages and the first results provided by this approach as applied by the research training group Baltic TRANSCOAST. A low-lying fen peat site including the offshore shallow sea area on the southern Baltic Sea coast has been chosen as a model system to quantify hydrophysical, biogeochemical, sedimentological, and biological processes across the land–sea interface. Recently introduced rewetting measures might have enhanced submarine groundwater discharge (SGD) as indicated by distinct patterns of salinity gradients in the near shore sediments, making the coastal waters in front of the study site a mixing zone of fresh- and brackish water. High nutrient loadings,

#### Edited by:

Anas Ghadouani, The University of Western Australia, Australia

#### Reviewed by:

Sabine Schmidt, Centre National de la Recherche Scientifique (CNRS), France Helena Granja, University of Minho, Portugal

#### \*Correspondence:

Bernd Lennartz<EMAIL_ADDRESS>
†These authors have contributed equally to this work

#### Specialty section:

This article was submitted to Coastal Ocean Processes, a section of the journal Frontiers in Marine Science

Received: 30 April 2018 Accepted: 06 September 2018 Published: 26 September 2018

#### Citation:

Jurasinski G, Janssen M, Voss M, Böttcher ME, Brede M, Burchard H, Forster S, Gosch L, Gräwe U, Gründling-Pfaff S, Haider F, Ibenthal M, Karow N, Karsten U, Kreuzburg M, Lange X, Leinweber P, Massmann G, Ptak T, Rezanezhad F, Rehder G, Romoth K, Schade H, Schubert H, Schulz-Vogt H, Sokolova IM, Strehse R, Unger V, Westphal J and Lennartz B (2018) Understanding the Coastal Ecocline: Assessing Sea–Land Interactions at Non-tidal, Low-Lying Coasts Through Interdisciplinary Research. Front. Mar. Sci. 5:342. doi: 10.3389/fmars.2018.00342

**284**

dissolved inorganic carbon (DIC), and dissolved organic matter (DOM) originating from the degraded peat may affect micro- and macro-phytobenthos, with the impact propagating to higher trophic levels. The terrestrial part of the study site is subject to periodic brackish water intrusion caused by occasional flooding, which has altered the hydraulic and biogeochemical properties of the prevailing peat soils. The stable salinity distribution in the main part of the peatland reveals the legacy of flooding events. Generally, elevated sulfate concentrations are assumed to influence greenhouse gas (GHG) emissions, mainly by inhibiting methane production, yet our investigations indicate complex interactions between the different biogeochemical element cycles (e.g., carbon and sulfur) caused by connected hydrological pathways. In conclusion, sea–land interactions are far reaching, occurring on either side of the interface, and can only be understood when both long-term and event-based patterns and different spatial scales are taken into account in interdisciplinary research that involves marine and terrestrial expertise.

 Global climate change threatens this space, while the increasing population in coastal areas puts the coasts under pressure due to construction activities (including settlements, harbors, wind farms, and coastal protection structures such as dykes and levees), agriculture, and tourism (Nicholls et al., 2007; Doney, 2010; Kummu et al., 2016). These anthropogenic activities modify the water exchange processes between land and sea.

Shallow coasts at low-lying areas are characterized by a relatively wide ecocline from land to sea. Long-term changes in sea-level as well as periodic (tides) or episodic (storm surges) events can, thus, affect large areas on both sides of the shoreline. Our understanding of the sea–land connection is focused on extreme scenarios in which the ocean is flooding the land with often dramatic consequences to the people living on the coast. Studies of sea–land interactions are often focused on estuaries where large quantities of fresh water and solutes are mixing with ocean water (e.g., Newton et al., 2014). The impact of rivers on the coastal ocean is substantial and includes excess nutrient delivery (eutrophication) (Bollmann et al., 2010), transport of essential trace compounds (metals, silica) (Martin and Whitfield, 1983; Du Laing et al., 2009), and may lead to drastic environmental changes along the salinity gradient (Kemp et al., 2005). The coastline itself is rarely considered as an exchange interface for energy, water, and substances, yet this interface is very important as it operates continuously and may have far-reaching effects on (micro-)biological and hydro-biogeochemical processes on either side of the coast (e.g., Rullkötter, 2009; Gätje and Reise, 2012).

Sea level rise is a common process observable around the world, mainly caused by ongoing climate change (Church et al., 2013). Recent studies show a rapid increase of sea level worldwide (Nerem et al., 2018), that is amplified at the southern Baltic Sea by an ongoing isostatic subsidence of the coast (Johansson et al., 2014). Taking into consideration the possible scenario of a combination of sinking coasts (Hünicke and Zorita, 2016), the rising sea levels (Grinsted et al., 2015), and future increase of winter precipitation (BACC II Author Team, 2015), we can expect that sea–land connectivity will increase in the Southern Baltic Sea region in future as the area of the coastal system increases (Nicholls et al., 2007). Understanding of the prevailing physical, biogeochemical, and biological drivers as well as of potential tipping points of such coasts in transition is crucial for our ability to sustainably balance natural conservation and anthropogenic use of the coasts. Therefore, the overarching aim of the Baltic TRANSCOAST research training group is to enhance the fundamental understanding of the interconnected physico-chemical, biogeochemical, and ecological processes along the ecocline of the shallow coast using a southern Baltic coastal site, the Hütelmoor, as a model. The aim of the present paper is to outline the hypotheses and research questions of the interdisciplinary approach of Baltic TRANSCOAST and present the first results generated by this approach as a roadmap to gain deeper insight into processes across lowland coastal transects that can be applied to investigations of similar shallow coastal systems worldwide.

# THE BALTIC SEA AS A MODEL TO STUDY EXCHANGE PROCESSES AT SHALLOW COASTS WITH LOW-LYING LAND AREAS

The Baltic Sea is a young shelf sea in northern Europe (**Figure 1**) connected to the North Sea since the time of the Litorina

transgression about 8,000 years ago. The coastline of the Baltic Sea is roughly 2,000 km long (STALU-MM, 2010). The German coastal areas comprise 13,900 km2 currently mostly protected by dykes (Bollmann et al., 2010). Along the shoreline of the Baltic Sea, cliffs alternate with low-lying areas, with the latter often including peatlands. The extent of low-lying areas increases from West to East along the Baltic Sea coast in northeastern Germany (**Figure 1**).

At low-lying coastal areas, peatlands formed by the accumulation of organic material over millennia often constitute the interface between land and water bodies (**Figure 1**). They cover an area of approx. 40,000 ha in the northeastern German federal state of Mecklenburg-Western Pomerania and play a pivotal role in buffering the exchange of water and dissolved and particulate compounds. Fundamentally, two different processes contribute to formation of the two major types of coastal peatlands along the southern Baltic Sea coast, i.e., paludification (driven by very rare flooding when the water is hindered from leaving the flooded area) or episodic flooding (weekly to monthly) with flooded periods being generally shorter than non-flooded periods. Most coastal peatlands in Mecklenburg-Western Pomerania belong to the second, episodically flooded type. The sea–land transition zone is characterized by brackish water input into the terrestrial part of the coast through underground seawater intrusion or flooding. Submarine groundwater discharge (SGD) marks transport processes into the opposite direction delivering freshwater, dissolved organic matter (DOM), and nutrients to the sea, independent from riverine export and other point sources (e.g., Andersen et al., 2007; Knee and Paytan, 2011; Donis et al., 2017). SGD also encompasses recirculating seawater and mixtures of seawater with fresh waters (e.g., Böttcher et al., 2018). The direction of exchange across the coastline depends on the prevailing pressure gradients and their physically driven dynamics.

The natural dynamics at the coastline have been altered since centuries by flood control measures such as dykes and flood walls. The exchange of water across the sea–land interface is hampered by these structures, especially at low-lying coastal segments dominated by peatlands, which would be regularly flooded under natural conditions. The establishment of coastal protection measures allowed the artificial drainage of coastal peatlands for agricultural purposes. The resulting lowering of the groundwater tables modifies the prevailing physical and chemical gradients and hinders the possible land–sea connection. The necessity of coastal protection measures is controversial and much-debated. The need for protection of people and their possessions is indisputable. However, higher levels of protection and reduced exchange between land and sea increase the vulnerability of the coast and the potential for catastrophic events. Under sea-level rise, protection of low lying areas at shallow coasts may be an effective way for ensuring wealth and health of local residents, since they could be used as buffer zones for flooding events. Some of the coastal peatlands have been or will soon be rewetted by removing the dykes. The resulting exchange of water and compounds transported by water across the coastal interface has been perceived as a natural process worthy to be conserved or re-established. Likewise, the rewetting and restoration of wetand peatlands have become a societal priority because of the enormous ecological services restored peatlands may provide like carbon sequestration, and water and nutrient buffering (Vasander et al., 2003).

Future weather and climate scenarios obtained from downscaling of global climate models draw a differentiated picture for the southern Baltic Sea region. While dryer summers with more frequent and occasional extreme storm events are to be expected, the winters may become warmer and wetter in terms of total precipitation (BACC II Author Team, 2015). The winter half-year (i.e., November–April) is the dominant period of discharge generation in the region since in summer evapotranspiration typically causes a negative water balance. With the expected addition of precipitation in winter, more pronounced discharge rates and steeper hydraulic gradients are expected. Considering the many catchments located on the coast that do not drain through rivers (**Figure 1**), it is likely that

diffusive pathways from land to sea will become more important under future winter weather situations.

Elevated groundwater levels and associated steeper gradients toward the sea may provoke SGD (e.g., Church, 1996; Abarca et al., 2013). SGD is defined as 'any and all flow of water on continental margins from the seabed to the coastal ocean' (Burnett et al., 2003), originating, for instance, from fresh groundwater of modern terrestrial origin and/or recirculated seawater with the latter providing the main component of SGD in many places (e.g., Church, 1996; Burnett et al., 2003; Böttcher et al., 2018). Besides the hydro-geochemical measurements of dissolved substances, the patterns of Ra and other isotopes in surface waters are particularly helpful for identification and quantification of the benthic-pelagic coupling and source water contributions, respectively (e.g., Moore et al., 2011; Böttcher et al., 2014). Specifically, the pelagic presence of the short-lived 224Ra isotope, which is derived from thorium decay in the sediment, indicates a recent contribution of pore waters to the water column.

Submarine groundwater discharge as a pathway for the exchange of water and associated substances has been observed along the German coastline in tidal areas like the North Sea (e.g., Moore et al., 2011; Jeandel, 2016; Reckhardt et al., 2017) and non-tidal systems like the Baltic Sea (Piekarek-Jankowska, 1996; Massel, 2001; Peltonen, 2002; Kotwicki et al., 2014; Donis et al., 2017; Böttcher et al., 2018). Biological consequences of SGD have likewise been documented (e.g., Liu et al., 2017). Most significantly, the contribution of SGD to total input loads from the land into the sea has been considered as more important than that of riverine freshwater (Kwon et al., 2014). It remains challenging to prove the occurrence of SGD at low-lying coastal segments with small hydraulic gradients. In low-gradient systems, the geological substrate and the heterogeneity of hydraulic properties of individual sedimentary layers are crucial for the establishment of local groundwater fluxes.

The hydraulic properties of the marine sediments impact the near-ground circulation and thus solute dispersion in the shallow sea water. Furthermore, the sedimentary structures, such as ripple fields, have a direct influence on the turbulence dynamics and thereby on velocity and solute concentration profiles (Smyth et al., 2002). The hydraulic properties of marine sediments are considered highly changeable because of bioturbation. The connection between groundwater exfiltration, pore water transport, and near-ground circulation of solute spreading at the sediment–water interface remains as yet poorly described. Wave action and hydrodynamic processes at the watersediment interface cause pore water fluxes in and out of the sediment (Massel, 2001), bringing oxygen as well as organic material into deeper sediment layers, thereby modifying redox gradients and, consequently, affecting biogeochemical processes like denitrification and/or iron, manganese and sulfate reduction (Huettel et al., 1998, 2003; de Beer et al., 2005; Gao et al., 2012).

Coastal marine sediments are often characterized by coarser grains (sand and gravel), and are commonly less sorted than sediments in deeper waters (Forster et al., 2003). Sediments are often resuspended and transported along the shore; consequently, they are permeable and the upper sediment layers in coastal zones are physically unstable and very mobile habitats. Benthic-pelagic coupling in shallow water is close, and coupling becomes stronger with increasingly shallow waters. The primary production rates are typically high and occur predominantly in the pelagic zone (Schiewer and Schubert, 2004). However, benthic primary production has rarely been considered in these systems despite the micro-phytobenthos and benthic macrophytes being responsible for most of the primary production in shallow lagoons. It has been shown that seagrass and macroalgae production can exceed 100 g C m−2 a −1 (Gocke et al., 2012). Additionally, benthic diatoms may contribute up to 60 g C m−2 a −1 to primary production in the temperate climate of the northern hemisphere (Cahoon, 1999). For the southern Baltic Sea, even higher values have been measured, ranging from 75 to >100 g C m−2 a −1 (Meyercordt and Meyer-Reil, 1999). In the case of the southern Baltic Sea coast with its abundant coastal peatlands, the fluxes across the sediment water interface might be modified hydrodynamically by the presence of outcropping peat layers in the water, which may also serve as a source of carbon and nutrients to the shallow sea. These outcrops are the result of the receding shoreline over the past several thousand years because of sea-level rise (Harff et al., 2017).

# BALTIC TRANSCOAST APPROACH

The coastline appears to divide terrestrial from marine ecosystems, yet in reality it forms a unique sea–land transition zone due to the exchange processes between environmental compartments create a unique sea–land transition zone. Baltic TRANSCOAST aims to quantify the extent to which the sea influences terrestrial processes and assess how the shallow sea is affected by processes operating on land, thereby unraveling the system function of shallow coasts at low-lying land areas (**Figure 2**). We suggest a systematic and interdisciplinary research approach that considers the coast as a continuum of physical and biogeochemical processes that on the one hand influence marine and terrestrial biota, and on the other hand are impacted by this biota.

The research in Baltic TRANSCOAST addresses the following main hypotheses:

lines indicate the spatial coverage of the respective topic across the coastal ecocline. Arrowheads indicate that those topics have a specific focus on exchange in the

The research designed to test these hypotheses is arranged around three core thematic areas, i.e., hydro-physics, biogeochemistry, and biology with topics anchored in one of the thematic areas but extending into other areas (see **Figure 2**).

direction of the arrow. Non-arrowed topics consider two-way exchange processes instead.

#### Hydrophysics

In non-tidal systems, the water exchange between the sea and land is driven by vertical and horizontal exchange flows generated by wind, waves, and lateral density gradients (**Figure 2**). The hydraulic properties of the prevailing strata as well as exchange processes between porous media and the above lying water column are likewise influencing the linkage between the terrestrial and the marine compartment of the ecosystem. The hydro-physics thematic area in Baltic TRANSCOAST comprises oceanographic (sea side) and groundwater (land side) modeling as well as their coupling via water levels near the shoreline. The underlying hypothesis is that water fluxes between the land and the sea are substantial even at low lying coastal areas because of changing sea levels and variations in precipitation. These water fluxes are assumed to be enhanced locally, when the heterogeneity of the underground causes a concentration of flow pathways at specific locations.

Sea level dynamics are wind-driven in non-tidal systems and modeled in Baltic TRANSCOAST by interactively coupling a General Estuarine Transport Model (GETM) with a wind wave model (Moghimi et al., 2013). Near-shore hydrodynamics are determined by wind-driven transport and the plume of the adjacent Warnow River. The groundwater dynamics are represented using the MODFLOW code and measured groundwater levels along a land–sea transect. Compared to mineral substrates, organic soils forming the peatlands are often characterized by low bulk density, high porosity, and a non-rigid organic matrix. Hydraulic and solute transport properties are highly dependent on soil structure, and thus can change upon mechanical, hydraulic, and geochemical impacts (Rezanezhad et al., 2016). Hydraulic properties of the various substrates are either tested in situ or measured in the lab under varying salt concentrations. Hydrodynamic measurements and modeling are supported by geochemical stable (2H, 18O), non-stable isotope (Ra, 3H), and noble gas (He, Ne, Rn) analyses aimed at identifying flow pathways, benthic-pelagic coupling, SGD, and groundwater residence times.

#### Biogeochemistry

fmars-05-00342 September 25, 2018 Time: 18:18 # 6

Peat-dominated wetlands are typically water saturated and, therefore, have low redox potentials. Consequently, they have unique nutrient and carbon cycling patterns that may also alter the processes of surrounding soils and sediments. In coastal areas, the biogeochemistry of peatlands is likely altered when seawater intrudes into the peat body. For example, carbon release and/or sequestration rates may shift and/or additional sulfate may become available for alternative metabolic processes (e.g., during storm surges or via saltwater intrusion). Under the impact of SGD, biogeochemical processes, including greenhouse gas (GHG) emissions in the shallow sea, may differ substantially from non-impacted sites because of differing supplies of electron donors and acceptors (e.g., Böttcher et al., 2018). The availability and transformation of dissolved sulfate is particularly important for carbon and nutrient (e.g., nitrogen and iron) cycling. In Baltic TRANSCOAST, we investigate the pathways of carbon, nitrogen, phosphorus, and sulfate across the land-ocean interface to foster our understanding of the complex interactions of salinity, substrate availability, water and element exchange, and geochemical signal formation in soils and sediments.

We hypothesize that the occasional flooding of the peat body with brackish sea water modifies the degradation of the peat substrate and the release of DOM from the peat, with possible consequences for the reactive transport of different forms of carbon, nitrogen and phosphorus, dissolved inorganic carbon (DIC), and metals to the shallow coastal waters. The exchange of compounds between the Baltic Sea and the peatland (and vice versa) will affect microbial processes and the offshore generation and emission of trace gasses since electron acceptors and donors are transferred between the compartments (e.g., dissolved sulfate enters the peatland). Pore waters and sedimentary substrates are therefore analyzed on transects along the land– sea interface to investigate vertical profiles of concentrations and stable isotope compositions of various dissolved, solid, and gaseous compounds, as well as to characterize the underlying biogeochemical processes and the impact of microbial activities. In addition, the composition of surface waters in the peatland as well as in the shallow Baltic Sea allows for an estimate of the exchange of water and substances between the sediments/soils and the overlying water column (i.e., 'benthic-pelagic coupling').

#### Biology

The hydro-physical and biogeochemical conditions in the shallow coastal sea create specific environments for the biota. Salinity variations caused by freshwater input into the shallow coastal waters may impact the physiological performance, viability, biodiversity, and distribution of microbes, microand macroalgae, as well as zoobenthos including bioturbators such as polychaetes and/or bivalves. The input of recirculated seawater and freshwater and the nutrients therein can generate nutrient-enriched conditions in the vicinity of SGD, creating hot spots of biological productivity and shaping the local benthic communities as observed in, e.g., estuaries (Encarnação et al., 2013; Leitão et al., 2015). Changes in the activity or abundance of zoobenthos may in turn affect the sediments via feedback mechanisms such as shifts in hydraulic properties of the seabed because of a modified bioturbation activity. These processes and reactions are only poorly understood up to date and are, thus, given priority in the investigation in Baltic TRANSCOAST in the biological thematic area.

Submarine groundwater discharge and unique seabed properties (e.g., peat out-cropping) may affect the micro- and macro-phytobenthos communities. Frequent resuspension events will likely modify the benthic communities, the oxygen consumption in sediments, and the (re)growth of flora and fauna. We hypothesize that these disturbances may change the community composition of micro- and macrobenthos and influence rates of primary production by nutrient inputs from SGD and/or terrestrial runoff. In addition, benthic diatoms typically exhibit a high heterotrophic potential, and hence might benefit from DOM derived from terrestrial sources. Furthermore, direct impacts of salinity fluctuations on biota are one of the most intriguing aspects of this study. Even small changes in salinity are probably crucial for species composition in the shallow waters at the study site, with opposite effects on benthic and pelagic communities (for review see Telesh et al., 2013). Furthermore, salinity fluctuations can affect secondary productivity and energy fluxes in macrozoobenthic communities through the effects on energetic processes, oxygen consumption, and growth and bioturbation activities of key macrozoobenthos species. We test the hypotheses by determining the effects of salinity fluctuations on bioenergetics of common bioturbators (i.e., sediment-dwelling bivalves). We assess the tolerance thresholds beyond which the physiological impacts of salinity translate into reduced activity, growth and/or survival, thereby affecting the key ecological functions of bioturbation and bioirrigation. The physiological data are upscaled to community-level effects by developing physiologically realistic models of bioturbators' contributions to oxygen, nutrient, and water fluxes, as well as to the sediment reworking. The models consider the effects of environmental factors (such as temperature, salinity, or sediment characteristics) and biological traits (such as body size and/or bioenergetics status) of the bivalves.

# STUDY SITE AND INSTRUMENTATION

## Terrestrial Side: Low-Lying Land With Coastal Peatland

Baltic TRANSCOAST focuses on a common investigation site, the nature reserve 'Heiligensee und Hütelmoor' (in brief and in the following 'Hütelmoor'). It is located on the southern Baltic Sea coast in northeastern Germany, near the city of Rostock and the estuary of the river Warnow. The reserve stretches over an area of 540 ha with 315 ha covered by peatland. A local depression shaped by a former glacial stream (Kolp, 1957) served as basis for the development of a fen peatland that formed when the rising

sea level of the Baltic Sea caused rising groundwater levels on the landside. The climate is temperate in the transition zone between maritime and continental with an average annual temperature of 9.1◦C and an average annual precipitation of 645 mm (data derived from grid product of the German Weather Service, reference climate period: 1981–2010). The evapotranspiration amounts to 620 mm in open water and 581 mm a−1 in reed areas (Miegel et al., 2016).

The peatland type in this site can be classified as a coastal paludification fen, and the largest portion of the peatland is covered by 1–3 m thick layers of sedge and reed peat. Due to its low elevation (−0.1 to + 0.7 m HN), the site was influenced by intermittent flooding events, resulting in the formation of thin sand layers within the peat in some areas. In the surroundings of the Heiligensee, organic or mineral lake sediments are found at the basis of the peat. Underneath the peat, 3–10 m thick basin sands form an aquifer underlain by glacial till. The peatland is surrounded by forest on mineral soils. At the eastern boundary, the peat stretches up to 100 m into the forest featuring Alder carr.

As most peatlands in northern Germany, the Hütelmoor has been artificially drained. The main ditch was installed in the 18th century and mainly served for transporting wood from the surrounding forests to the harbor (Kolp, 1957). The ditch was connected to the lower reach of the river Warnow. Originally, the area had discharged directly into the Baltic Sea via a small brook cutting through the dunes; this connection was later blocked. In accordance with intensifying agricultural production in central Europe (van Diggelen et al., 2006), large parts of the wetland complex were intensively drained in the 1970s by open ditches and then used as grassland for fodder production (i.e., mown twice a year). As a result, the mean annual water level dropped to 1.60 m below ground surface.

In the 1990s, the study site was moderately rewetted and grasses were cut once a year to keep the vegetation open. Extensive mowing supported the aims of nature conservation to preserve a resting site for migratory birds while allowing the restoration of the typical fen vegetation. The mean growing season water level during that time was close to the surface (Koebsch et al., 2013). However, water levels dropped down to 70 cm below the surface during summers, which raised concerns about ongoing aerobic peat decomposition. Therefore, a ground sill was installed in the outflow of the catchment in winter 2009/2010 which initiated a year-round shallow flooding for most areas of the study site (mean growing season water level 37 cm, values indicate flooding). The discharge from the peatland averages 44 L s−1 , but stops during summer months when the water level drops below the ground sill (Miegel et al., 2016). Rewetting projects are common for much of the Baltic Sea coast where nature conservation has been given priority.

Currently, the vegetation is dominated by emergent macrophytes such as Common Reed [Phragmites australis (Cav.) Trin.]. Especially in the second part of the vegetation period submerged aquatic species like Soft Hornwort (Ceratophyllum submersum L.) dominate the relatively abundant areas of open shallow water. The typical brackish water emergent macrophyte Sea Clubrush (Bolboschoenus maritimus L.) was almost completely displaced, whereas another brackish water species, the Softstem Bulrush [Schoenoplectus tabernaemontani (C.C.Gmel.) Palla], was able to increase its cover considerably in the last decade (Koch et al., 2017). Dryer areas at the boundaries to the forest are mainly colonized by the Lesser Pond Sedge (Carex acutiformis Ehrh.) and the Common Rush (Juncus effusus L.).

Drainage and agricultural use led to aeration and mineralization of the peat resulting in a highly degraded top horizon. The soil type was identified as sapric histosol before rewetting. The remaining peat body is moderately to strongly decomposed with substantial heterogeneity of physical and chemical properties. Rewetting measures and permanently high water levels (above peat surface) have led to the sealing of the soil surface because of sedimentation of fine particles. The former soil surface now resembles a lake bottom surface, with the possible formation of a gyttja (a characteristic layer composed of either organic or mineral material that can be typically found beneath fen peats, which is considered as the initiation stage of fen peat formation). The ongoing sealing process at the soil surface limits the vertical infiltration, thus, possibly changing the hydraulic functioning of the entire wetland.

A dune dyke was installed at the coastline of the fen in 1903 for coastal protection of the nearby seaside resort Markgrafenheide and was reinforced in 1963 (Miegel et al., 2016). Already before 1903 there was a natural sand dune providing a barrier between the Baltic Sea and the Hütelmoor. Due to the artificial dune dyke the peatland has been almost completely cut off from the Baltic Sea. The last notable intrusion of brackish water occurred during a storm night in November 1995 (Bohne and Bohne, 2008). Afterwards, the dune dyke was rebuilt and strengthened. It is, however, not maintained anymore since the year 2000. It is anticipated that the natural impact of the sea including episodic flooding will re-establish in the near future likely resulting in repeated input of brackish waters (on decadal time scales) with possible consequences for hydro-physical and biogeochemical processes. A recent storm flood event in January 2017, which washed away considerable parts of the dune dyke at places where it was more than 20 m wide, failed to flood the study site.

### Marine Side: Shallow Coast of the Baltic Sea

A mosaic pattern of eroding cliffs and sand deposition areas are dominant along the western part of the Baltic Sea coast in northeastern Germany. Due to coastal erosion and isostatic sea level rise the coastline has shifted landwards at the study site exposing former land-based geological strata to the sea. The peat that once developed on land now extends to the sea, forming a unique habitat for micro- and macro-phytobenthos. Most of the coastal area between 0 and 10 m depth is covered by coarsegrained sediments with gravel and cobbles dominating at some sites. In the northern area of the study site, gravel and coarse sands are abundant on the sea bottom surface whereas in the south fine and medium sands dominate (for details and a map, see Kreuzburg et al., 2018). This is typical for sea floor near the coast because coastal waves and prevailing south-westerly winds generate longshore currents, displacing the small particles and

transporting them along the coast and toward greater depths. A few tens of meters away from the shoreline an underwater longshore bar has developed. This seems to be typical for the southern German Baltic coastline where no fine-grained sediments can be found (Tauber, 2012).

Roughly 10 km west from the study area, the Warnow estuary enters the Baltic Sea. The Warnow river basin is approximately 3,000 km2 in size with elevation differences of less than 100 m as is typical for lowland catchments mainly used for agriculture (Bahnwart et al., 1998; Deutsch et al., 2006). The river mouth is located 15 km landwards where a weir prevents sea water to travel further upstream. A gauging station is located at the weir and discharge is continuously recorded. The mean outflow rate is 16.5 m3 s −1 with a mean nitrate concentration of 1.78 mg N L −1 (or 127 µmol L−1 ) 1 . A small surface plume extends a few kilometers west – and northwards along the estuary while the salinity increases to the typical brackish values of 10–15 PSU. During the passage, inorganic nutrients are entirely consumed or mixed so that only recalcitrant substances like dissolved organic material of the plume are able to reach the study site off the Hütelmoor.

# Instrumentation and Field Data Acquisition

The investigations in Baltic TRANSCOAST are carried out on a well-developed research site, the study site Hütelmoor. Some analyses within the project are based on data recorded before the project started in 2016. The investigations on the landside in the peatland have already started in 2008 with closed chamber measurements and the installation of dip wells. In 2009 an eddy covariance tower measuring CO2 exchange was set up, which was equipped with a methane sensor in 2011 and is running continuously ever since.

In the course of Baltic TRANSCOAST, the study site has been instrumented both on land and in the sea (**Figure 3**). The investigations started in 2016 and are ongoing. The now used locations for chamber measurements are arranged in clusters around the Eddy tower (**Figure 3**) with replicates in different vegetation types including, e.g., stands of Common Reed and Common Sedge as well as areas with open water and are equipped with boardwalks and dip wells. In each cluster a peeper is installed that allows for regular sampling of pore and surface water at defined depths. GHG chamber measurements and water sampling are carried out monthly. The chambers are custom developed and flexible which allows for measuring vegetation up to 2m height while still allowing for efficient application in the field (Günther et al., 2014). During the campaigns GHG exchange (CH4 and CO2) is measured with either a Los Gatos Ultraportable GHG Analyzer or a Picarro GasScouter.

Groundwater monitoring wells were installed in transects across the peatland in 2016 (**Figure 3**). Each measuring point consists of up to three wells filtered in different depths (upper sand, peat, lower sand). All wells are equipped with self-registering pressure-temperature-salinity probes and are

1 lung.mv-regierung.de regularly sampled. The geology of the study site was assessed with 17 drillings, mostly down to the glacial till, and numerous additional peat probings. Undisturbed peat cores (250–450 cmł) for analyses of hydraulic conductivity and dissolved organic carbon (DOC) leaching in the lab were taken both in the peatland and in the peat layer cropping out into the Baltic Sea.