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\begin{document}

\title{Spatial and temporal dynamics of water isotopes in the riverine-marine
mixing zone along the German Baltic Sea coast}



\author[1]{Bernhard Aichner}%
\author[1]{Timo Rittweg}%
\author[2]{Rhena Schumann}%
\author[3]{Sven Dahlke}%
\author[4]{Svend Duggen}%
\author[1]{David Dubbert}%
\affil[1]{Leibniz-Institute of Freshwater Ecology and Inland Fisheries in the Forschungsverbund Berlin eV}%
\affil[2]{University of Rostock}%
\affil[3]{University of Greifswald}%
\affil[4]{A. P. Møller Skolen}%


\vspace{-1em}



  
  \date{May 23, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
River estuaries are characterized by mixing processes between
isotopically depleted freshwater inflows and isotopically more enriched
marine water masses. Therefore, they often show linear correlation
between salinity and water isotopes (\selectlanguage{greek}δ\selectlanguage{english}18O and \selectlanguage{greek}δ\selectlanguage{english}2H values). Here we
evaluated spatial and seasonal isotope dynamics along three estuarine
lagoon transects at the northern German Baltic Sea coast. The data show
strong seasonality of isotope values even at locations located furthest
from the river mouths. They further reveal a positive and linear
salinity-isotope correlation in spring, but hyperbolic and partially
even reverse correlation in summers. We conclude that additional
physical processes, such as evaporation from the shallow lagoons,
overprint the two-phase mixing correlation during summers. Understanding
of those water isotope dynamics are crucial in context of ecological
studies, for example when interpreting oxygen and hydrogen isotope data
in aquatic organisms that depend on ambient estuarine waters.%
\end{abstract}%



\sloppy


\textbf{1. Introduction}

The water cycle, or hydrological cycle, refers to the movement of water
molecules throughout the globes geological, biological and ecological
compartments. Major constituents of this cycle are water evaporating
from the oceans, transportation of vapor to continental realms,
re-condensation to rain droplets, and flow back via groundwater and
surface flow towards the ocean. The varying physical properties,
specifically the different weights of stable oxygen and hydrogen
isotopes of the water molecule
(\textsuperscript{16}O,\textsuperscript{17}O, \textsuperscript{18}O,
\textsuperscript{1}H,\textsuperscript{2}H), lead to isotope
fractionation during all these processes (H. Craig, 1961; Dansgaard,
1964). As a consequence, the isotopic signature of water in both the
liquid and the vapor phase is characterized by spatial and temporal
variability, and in principal is depleted of the heavier isotopes in
water vapor and continental freshwater, compared to the ocean water
(Gat, Gonfiantini, \& (Eds), 1981). For this reason, mixing processes in
the transitional zone between the riverine/freshwater and marine/saline
realm lead to linear relationships between salinity and water isotopes
in those systems, as observed in multiple river estuaries around the
globe (Barrie, Worden, Barrie, \& Boyce, 2015; Chamberlayne, Tyler, \&
Gillanders, 2021; Ingram, Conrad, \& Ingle, 1996; Mohan \& Walther,
2015; Price, Skrzypek, Grierson, Swart, \& Fourqurean, 2012; Swart \&
Price, 2002).

In precipitation, isotopes exhibit a seasonal signal, with lower /
higher values in the cold and warm season, respectively (Bowen \&
Revenaugh, 2003). This seasonal partitioning of isotopes provides an
opportunity to model spatial dynamics of isotopes across a landscape,
riverscape, or seascape (Aron et al., 2021; Brennan, Cline, \&
Schindler, 2019; Orlowski, Kraft, Pferdmenges, \& Breuer, 2016).
Riverine and lacustrine systems reflect this signal (B. Aichner et al.,
2021; Dutton, Wilkinson, Welker, Bowen, \& Lohmann, 2005; Halder,
Terzer, Wassenaar, Araguas-Araguas, \& Aggarwal, 2015; Ogrinc, Kanduc,
Stichler, \& Vreca, 2008; Reckerth, Stichler, Schmidt, \& Stumpp, 2017),
but the seasonal amplitude is attenuated and timing of the signal
delayed by 1-3 months (Bittar et al., 2016; Jasechko, Kirchner, Welker,
\& McDonnell, 2016; Reckerth et al., 2017; Rodgers, Soulsby, Waldron, \&
Tetzlaff, 2005) . The reasons for the time delay between precipitation
and river/lake water isotopes, and the smaller seasonal amplitude of the
latter, can be attributed to multiple catchment characteristics and
processes. Crucial influencing factors on how fast a precipitation
isotope signal is transferred into fluvial systems are the flow regime
of rivers, and the area, topography and geology of their catchments
(Maloszewski, Rauert, Trimborn, Herrmann, \& Rau, 1992; McGuire et al.,
2005; Rodgers et al., 2005; Sklash, Farvolden, \& Fritz, 1976) .

In water bodies with high residence time of the water, such as large
and/or voluminous lakes or in the marine realm, the seasonal
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H variability decreases.
Instead mixing processes of water from different sources with variable
isotopic signatures, become more dominant on the actual isotopic
signature (Benetti, Reverdin, Aloisi, \& Sveinbjornsdottir, 2017; Harmon
Craig \& Gordon, 1965; Frew, Dennis, Heywood, Meredith, \& Boswell,
2000) . The North Sea, for example, is influenced by both North Atlantic
water with high salinity, entering the North Sea basin from the
northeast, and inflow of brackish water and freshwater, derived from the
Baltic Sea and from rivers, respectively (Harwood, Dennis, Marca,
Pilling, \& Millner, 2008). The Baltic Sea, in turn experiences
occasional inflow intrusion from the North Sea (higher
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values), but also
constantly receives freshwater discharge from rivers (lower \selectlanguage{greek}δ-\selectlanguage{english}values).
For these reasons water isotopes show a strong positive correlation with
salinity in both the Baltic Sea and North Sea (Ehhalt, 1969; Frohlich,
Grabczak, R\selectlanguage{ngerman}ô, \& bDski, 1988; Jefanova et al., 2020; Richter \& Kowski,
1990; Torniainen et al., 2017) .

Isotope signatures of the ambient water are mirrored in the local fauna
and flora, e.g. by plants or fish which depend on estuarine water. For
example, fish incorporate elements from ambient water into their body
structures, for example (ear bones) (Zanden, Soto, Bowen, \& Hobson,
2016). These structures form through precipitation from the water the
fish currently lives in, and as such, mirror to some extent the current
isotopic profile of the water (Patterson, Smith, \& Lohmann, 1993). In
recent years, oxygen isotopic ratios of otoliths have been commonly used
in studies of migration and geolocation of fish, by deriving predictive
surfaces, ie. isoscapes of large-scale water isotope data, in order to
retrospectively predict the whereabouts of migrating fish (Torniainen et
al., 2017; Trueman, Mackenzie, \& Palmer, 2012), and to assign fish to
discrete, geographically segregated stocks (Matta, Black, \& Wilderbuer,
2010). With respect to aquatic plants or algae, their cellular lipid
compounds have been shown to track the hydrogen isotopic signature of
the ambient water, but with a potential additional influence of varying
salinity (Bernhard Aichner, Hilt, Périllon, Gillefalk, \& Sachse, 2017;
Häggi, Chiessi, \& Schefuß, 2015; He, Nemiah Ladd, Saunders, Mead, \&
Jaffé, 2020; Ladd \& Sachs, 2015, 2017; Sachs \& Schwab, 2011; Schouten
et al., 2006). These dependencies have frequently been applied in
paleoclimatic studies, i.e. for reconstruction of past hydrological
conditions and salinities (e.g. (Bernhard Aichner et al., 2019; Leduc,
Sachs, Kawka, \& Schneider, 2011; Meer et al., 2007)).

Knowledge and understanding about water isotopic gradients has great
potential to facilitate application and interpretation of oxygen and
hydrogen isotopic compositions in biogenic carbonates and plant lipids.
In this study we analysed water isotope dynamics in estuarine river and
lagoon systems along the northern German Baltic Sea coast. Main
questions of this study are: 1) how far are seasonal isotope signals in
rivers transmitted into Baltic Sea estuarine systems? 2) what are the
major processes behind the observed gradients? 3) are water isotopes a
predictor for salinity in the riverine-marine mixing zone? The major aim
is to understand the underlying control mechanisms on seasonal and
spatial water isotope variability in this study area, which is essential
when fish and plant isotope data are interpreted in ecological and
biogeochemical studies.

\textbf{2. Study area}

The northeastern German coast of the Baltic Sea is basically a flooded
glacial moraine landscape. It is characterized by extensive bays,
shallow lagoons (the boddens) and marine inlets, which form the mixing
zone between rivers and the marine realm (Correns, 1977; Schwarzer,
Ricklefs, Bartholomä, \& Zeiler, 2008). These zones are characterized by
hydrologic events which in turn affect biochemical characteristics of
the ecosystem. For example they react sensitively both to discharge
pulses from rivers and inflow events from the marine side after storms
(Gocke, Rheinheimer, \& Schramm, 2003). Further, a dense net of water
management structures, such as water retention flaps, partially
attenuate freshwater flow from creeks into the lagoons. Here, automatic
ones will release water from creeks when the lagoons are low while some
manual flaps exist, which are operated by hand (Funkel, 2004) .

For this study, water samples were taken along three transects,
encompassing salinity gradients (Figs. 1 and 2; Supplementary Tables S1
and S2):\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Fig. 1: Transect sample points at a) Schlei, b) Dar\selectlanguage{ngerman}ß-Zingster Bodden
Chain (DZBC), and c) Eastern Transect (Stettiner Haff - Peenestream --
Greifswalder Bodden - Rügener Boddens). Red circles: time-series
sampling. Yellow circles: seasonal sampling. lB: Little Belt. gB: Great
Belt. S: øresund. Sampling points are listed in Supplementary Tables S1
and S2.

a) the Schlei estuarine (Figs 1 and 2a) is a flooded sub-glacial
channel, extending ca. 42 km from the major Baltic Sea coast line
towards the inlands. The inner Schlei comprises the two larger basins of
the ``Kleine Breite'' and ``Große Breite'', while the outer Schlei at
some sections resembles a wider river. Adjacent, several ``Noors'', i.e.
water bodies similar to lakes, are connected to the main Schlei often by
just narrow outlets. The Schlei has one medium sized inflow, the
Füsinger Au at Kleine Breite, and several small creeks entering along
the whole length of the water body. The salinity gradient is linearly
increasing from almost 0-3 psu at the inner Schlei (Burgsee and Kleine
Breite) towards values of ca. 15-20 psu near the outflow to the Baltic
Sea (Gocke et al., 2003; Grupe, Heinrich, \& Peters, 2009; LLUR.
Schleswig-Holstein, 2001; Seiß, 2014). This gradient is seasonally
influenced by relatively high freshwater discharge in winter and spring
compared to summers. Additionally, episodic sea level changes by ± 0.5
-- 1.5 m, caused by strong winds, lead to rapid movement of water masses
within the Schlei, which superimposes the salinity gradient (Schulz,
1979). Saltwater intrusion events, from the North Sea into the Baltic
Sea (Volker Mohrholz, 2018) (Fig 3) similarly have the potential to
increase salinity values in the outer Schlei, as visible for March 2020
in contrast to July 2020 (Fig. 2a).

b) the Darß-Zingst Bodden chain (DZBC) is a system of several shallow
water basins, which mostly do not exceed 2-3 m water depth (Figs. 1 and
2b). The rivers Recknitz and Barthe are major inflows and there are two
outflows towards the Baltic Sea, which lie close to each other at the
easternmost end of the Darß-Zingst peninsula. The salinity gradient is
covering the range from almost freshwater conditions near the Recknitz
and Barthe inflows to ca 10 psu near the outflows (Chubarenko,
Chubarenko, \& Baudler, 2005) . Those reflect the salinity values in the
adjacent Baltic Sea, which are lower than in the more western realms
(where the Schlei is situated), but likewise influenced by salt water
intrusion events (Fig. 2b). The DZBC can be divided into an inner /
western part (Saaler Bodden and Bodstedter Bodden), which is mainly
influenced by riverine inflows and an outer / eastern part (Barther
Bodden and Grabow) which is more susceptible to Baltic water inflow
during conditions of east winds (Schumann, Baudler, Glass, Dümcke, \&
Karsten, 2006). The two parts are connected by the Zingster Stream (ZS),
a narrow and deep water channel located in the central bodden chain.

c) the easternmost transect reaches from the Stettiner Haff, via the
Greifswalder Bodden to the multiple lagoons which form the western and
northern bodden chains around the isle Rügen (WRBC and NRBC) (Figs 1 and
2c). While the covered salinity gradient is similar than in the DZBC
(i.e. 0 -- ca. 10 psu), several inflows and connections to the Baltic
Sea create a more dynamic system, in exchange with marine water widely
overprinting the effects of freshwater inflow by rivers (Bachor, 2005;
Correns \& Jäger, 1979; H. Hübel \& Dahlke, 1999; Helmut Hübel, Wolff,
\& Meyer-Reil, 1998)). The Stettiner Haff is strongly under influence of
the Oder river, which contributes \textgreater{}95\% of the riverine
discharge along the northeastern German Baltic Sea coastline (Richter \&
Kowski, 1990). Salinity is gradually increasing between the Stettiner
Haff, along the Peene-Stream towards the Greifswalder bodden (Fig. 2c)
(Lampe, 1999). The latter is a larger basin of max 13.5 m depth which is
separated to the open Baltic Sea by the ``Greifswalder
Boddenrandschwelle'', a glacial terminal moraine which builds a just 1
-- 2.5m deep shallow. The Greifswalder Bodden is connected to the WRBC
by the Strela Sound, which terminates in the Vitter Bodden next to
Hiddensee island. The same bodden can be seen as terminal basin of the
inner or northern Rügen bodden chain (NRBC; reaching from Kleiner
Jasmunder Bodden via Großer Jasmunder, Breeger, and Wieker Bodden),
which is characterized by a salinity gradient from 0 to ca. 10 psu,
comparable as in the DZBC (Birr; Ulrich Schiewer, 2008).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Fig. 2: Salinity in March (left) and July (right) 2020, in the Schlei
(a), DZBC (b) and R\selectlanguage{ngerman}ügener boddens (c). Panels a -- c refer to subregions
as indicated in Figure 1. Blue circles A-I: sampling points for
time-series. Yellow circles \#1-68: shore samples. Green triangles
indicate LUNG monitoring point with data included into salinity
interpolation. Arrows indicate exchange points with Baltic Sea water.
SaB: Saaler Bodden. BoB: Bodstedter Bodden: BAT: Barther Bodden and
Grabow. WRBC: Western Rügen Bodden Chain. NRBC: Northern Rügen Bodden
Chain. GB: Greifswalder Bodden. P: Peene Stream. AW: Achterwasser.

\textbf{3. Material and methods}

\textbf{3.1 Water sampling}

Water samples were taken along transects (yellow dots in Fig. 1) in June
2019 (lower density of sampling points), March 2020, and July 2020. They
were collected close to shores with a pipette from ca. 40-60 cm below
water surface and directly transferred into a GC-vial. The vials were
instantly closed and stored in a cooling box, before being placed in a
fridge until further procession.

At selected spots, time-series were sampled 2-4 weekly (A: Schlei, A. P.
Møller Skolen Schleswig; E: Zingster Strom, Biological Station; I:
Vitter Bodden, Kloster/Hiddensee) or monthly (B-D, F-G: Zingster Bodden)
from March 2020 to March 2021. Samples from A and I were taken
accordingly to shore samples, while samples B-H were taken in deep parts
of the boddens, close to buoys marking long-term monitoring locations.
For the latter, a Limnos water sampler was used to obtain 2L samples
from 0.5-1.0 m depth below water surface, of which 1.5 mL were
transferred into GC vials.

\textbf{3.2 Water chemical parameters}

Water chemical parameters were measured in situ at shore transect and
time series sampling spots A and I, using a Multi 3630 IDS
multiparameter device (WTW, Weilheim, Germany), equipped with a WTW
TetraCon 925 electrical conductivity measuring cell. At the A. P. Møller
Skolen salinity and temperature was measured using a modular
multi-parameter probe (WTW multimeter 3440), mounted with TetraCon®
925-P and MPP 930 IDS electrical conductivity cells. Before each
application the cells were calibrated with E-Set Trace 0.01 M KCl
calibration solution based on PTB/NIST. For samples from DZBC-timeseries
(spots B-H), a WTW 1970i conductivity meter and TetraCon 325 measuring
cell were used to analyse electrical conductivity / salinity in the
laboratory\emph{.}

Salinity maps (Fig. 2) were produced in QGIS 3.14 using the inverse
distance weighted interpolation tool with a squared weighting
coefficient for the sampling periods March and July 2020. Herefore, the
in-situ measured salinity values were used for spatial interpolation, in
combination with data derived from monthly monitoring stations of local
authorities (LUNG; Landesamt für Umwelt, Naturschutz, Geologie of the
German State Mecklenburg-Vorpommern) (Fig. 2). For March 2020, some
additional values were derived from HOBO U24-002-C salinity loggers
(Onset, Bourne, USA), which were installed at different locations around
the Rügener boddens. Data were only interpolated within the
riverine-marine mixing zone, while the open Baltic Sea was excluded.

\textbf{3.3 Isotope measurement}

Water samples were filtered (0.2 \selectlanguage{greek}µ\selectlanguage{english}m cellulose acetate) prior to analysis
of stable isotopes (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H
values) in the water isotope lab at IGB Berlin, using a Picarro (Santa
Clara, CA, USA) L2130-i cavity ring-down spectrometer (CRDS).
Measurements were routinely checked for organic contamination using the
Picarro ChemCorrect software.

Isotope values and standard deviations are based on six replicate
measurements of each sample, discarding the first three measurements to
account for memory effects. In house criteria excluded all injections
with a water SD higher than 400 ppm or water amount deviation greater
than 3000 ppm to furthermore improve precision.

For instrument calibration we used 3 laboratory standards for each group
of 24 samples: L (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O -17.86 %0 and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H -109.91 %0), DEL (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O -10.03 %0
and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H -72.81 %0), H (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O 2.95 %0
and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H 0.29 %0). A fourth lab standard, M
(\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O -7.68 %0 and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H -56.70 %0), was
used as quality and drift control after every 6 samples. All lab
standards were referenced against primary measurement standards: VSMOW2
(Vienna Standard Mean Ocean Water 2), GRESP (Greenland Summit
Precipitation), and SLAP2 (Standard Light Antarctic Precipitation 2)
from the IAEA (International Atomic Energy Agency, Vienna International
Centre, A-1400 Vienna, Austria).

\textbf{4. Results and discussion}

\textbf{4.1 Seasonal control on water isotopes (time series)}

\emph{Schlei (Kleine Breite, Schleswig)}

At the inner Schlei, water isotopes show a seasonal trend (higher/lower
values in summer/winter) while in contrast salinities were relatively
constant (ca. 6 -- 7 psu) at most measuring days within the sampling
period (26\textsuperscript{th} March 2020 -- 16\textsuperscript{th}March
2021) (Fig. 3). Exceptions were two samples from 26\textsuperscript{th}
March 2020 and 19\textsuperscript{th} Feb 2021, which showed decreased
salinity values of 3.5 -- 4.3 psu. Those are mirrored by lower \selectlanguage{greek}δ-\selectlanguage{english}values
in water samples collected at those two days.

During, both February/March 2020 and February 2021, major storms lead to
increased precipitation and consequently higher surface runoff of rivers
and creeks discharging into the Schlei (Figs. 2a and 3). The sampling
spot A is located about 5 km west of the mouth of the river F\selectlanguage{ngerman}üsinger Au,
the annual freshwater input of which is about twice the total water
volume of the entire Schlei (Gocke et al., 2003). Further it is located
ca. 100 m eastwards the inflow of the small creek Mühlenbach, and
therefore susceptible to major discharge events, delivering freshwater
with lower \selectlanguage{greek}δ-\selectlanguage{english}values.

The maximum \selectlanguage{greek}δ-\selectlanguage{english}values are reached in September and early October (Fig.
3), i.e. 1-2 months delayed to maximum air and water temperatures. On
the other hand it is synchronous to maximum O\textsubscript{2}-depletion
(i.e. minimum O\textsubscript{2}-concentration) at the sampling spot.
The mechanistic relationship between phytoplankton blooms, local oxygen
depletion and oversaturation, carbonate precipitation, and pH values,
and their effects on oxygen isotopes in lacustrine waters have long been
debated (e.g. (Dietzel, Tang, Leis, \& K\selectlanguage{ngerman}öhler, 2009; Li et al., 2020;
Quay et al., 1995)). Likewise, an effect of this parameters on the
measured \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values at Schlei cannot be fully
excluded, but do not explain synchronous trends in \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H
values.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Fig. 3: Time series of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H / \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O
values in water samples collected between 26\textsuperscript{th} March
2020 to 16\textsuperscript{th} March 2021 at A. P. M\selectlanguage{ngerman}øller Skolen (APM
Skolen), Schleswig (Kleine Breite, Schlei; sampling point A; Fig. 2a),
in comparison to salinity, water temperature, pH. Data of daily mean
values of water discharge derived from the major inflowing river
Füsinger Au (LLUR, 2022). Major Baltic Sea salt inflow events at Great
Belt and Øresund from (V. Mohrholz, 2018).

\emph{Zingster Stream and boddens}

In contrast to the Kleine Breite (Schlei), at Zingster Stream (sampling
point E), the salinity values exhibited a more pronounced seasonal
trend, with lower \selectlanguage{greek}δ-\selectlanguage{english}values in winter/spring and higher values in summers
(Fig. 4). This is a common pattern in Baltic Sea lagoons and related to
the seasonal discharge pattern of inflowing rivers (Cyberski,
Wr\selectlanguage{ngerman}óblewski, \& Stewart, 2000) (Fig. 4). Short-term salinity fluctuations
on the other hand can be explained by influence of different water
masses from either the eastern or western side of the Zingster Stream,
which is controlled by wind direction and water level differences
(Schumann et al., 2006). The water isotope values mirror the seasonal
salinity trend throughout the studied time period
(24\textsuperscript{th} March 2020 -- 9\textsuperscript{th} March 2021;
Fig. 4), i.e. show lower values in winter/spring and higher in summers
(Fig. 4). Comparable to the Schlei, the correlations between water
isotopes and water / air temperature, as well as
O\textsubscript{2}-saturation cannot rule out effects of these
parameters onto \selectlanguage{greek}δ-\selectlanguage{english}values. This is especially true for lower temperatures
in the colder winter (2020/21) compared to the mild winter (2019/20),
which could explain the lower \selectlanguage{greek}δ-\selectlanguage{english}values in Jan-March 2021.

A similar seasonal trend in water isotopes as in Zingster Stream is
discovered at all sampling locations at the DZBC, i.e. from the inflow
of the Recknitz (sampling point B) to the outflow from the boddens
towards the Baltic Sea (sampling point H) (Fig. 5). The decreasing
influence of freshwater inflow along this transect is clearly visible at
increasing salinities, despite the actual seasonal salinity trends are
different in the outer boddens (F, G, H) compared to the innermost
boddens (B, C) (Fig. 5a). Close to the outflow towards the Baltic Sea
(point H), high salinities up to 14 psu were observed in February 2020
and March 2021. Those areas are more susceptible to salinity changes of
the Baltic Sea, which in turn are influenced by salt water intrusion
events from the North Sea, via the Little Belt, Great Belt and \selectlanguage{ngerman}Øresund
(Volker Mohrholz, 2018) (Fig. 1). Especially in February 2020 large
amounts of salt water was driven by two major storms into the Baltic Sea
(V. Mohrholz, 2018) (Fig. 3).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Fig. 4: Time series of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H / \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O
values in water samples collected between 24\textsuperscript{th} March
2020 and 9\textsuperscript{th} March 2021 at Biological Station Zingst
(Zingster Stream; sampling point E; Fig. 2b), in comparison to water
temperature and long-term trends of salinity. Water level at the bodden
outflow towards the Baltic Sea at Barh\selectlanguage{ngerman}öft (WSV, 2022). Riverine
discharge of Recknitz and Barthe (STALU, 2022) .\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Fig. 5: Time series of a) salinity and b) \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values
in water samples collected monthly at a transect along the Zingster
Bodden chain, reaching from buoys located near the inflow of the river
Recknitz (sampling spot B; LUNG monitoring point DB19) to those located
close to the outflow towards the Baltic Sea (sampling spot H; LUNG
monitoring point DB 1).

\emph{Vitter bodden (Hiddensee, Kloster)}

The outermost R\selectlanguage{ngerman}ügener boddens are characterised by complex dynamics
within multiple influencing water-masses: water is partially intruding
from the Baltic Sea, south and northeast of Hiddensee island (Bachor,
2005). Freshwater surface run off is derived from the NRBC (Helmut Hübel
et al., 1998) (Fig. 6). The bodden is further susceptible to large-scale
water exchange with eastward parts of the bodden coast, via the Strela
Sound (Birr, 1988; U. Schiewer \& Gocke, 1996).

At Vitter Bodden (Hiddensee/Kloster; sampling point I), water isotope
data exhibit similar seasonal trends than at the Schlei and DZBC
sampling spots (Fig. 6). The salinity measurements showed variable
values in the sampling period (18\textsuperscript{th} March 2020 --
3\textsuperscript{rd} March 2021), ranging from 7.5 to 11.2 psu (Fig.
6). Similar as in the outer boddens of DZBC, salt water intrusion events
(Fig. 3) are the reason behind maximum salinities in February 2020 and
2021. Fluctuating values at the end of the time series are probably
influenced by the partial appearance and melting of an ice-cover across
the boddens in February 2021.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

Fig. 6: Time series of \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H / \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O
values in water samples collected between 18\textsuperscript{th} March
2020 and 3\textsuperscript{rd} March 2021 at the ferry harbour Kloster,
Hiddensee (Vitter Bodden; sampling point I), in comparison to salinity
and water temperature. Water level from Strela Sound (Stralsund; point
\#40) provided by WSV (WSV, 2022). Monthly surface flow data from NRBC
to Vitter bodden (STALU, 2022).

\emph{Control mechanisms on water isotopes and salinity}

Water samples collected at the A. P. M\selectlanguage{ngerman}øller Skolen (Kleine Breite,
Schlei; sampling point A), Biological Station Zingst (Zingster Stream,
E), and Hiddensee/Kloster (Vitter bodden; I) all exhibit clear seasonal
isotopic variability (Figs. 3-6). The seasonal isotope amplitude is in
range of ca. 10 -- 5 \selectlanguage{english}%0 (\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H) and 2 -- 2.5 %0
(\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O), reaching minimum/maximum values in Feb/Mar and
Sep/Oct, respectively. Thus we suggest, that time-series data even at
sampling points in the outermost boddens still mainly reflect a delayed
and attenuated precipitation signal, i.e. a seasonality pattern as
previously observed in German rivers (Reckerth et al., 2017) and
northern German lakes (B. Aichner et al., 2021) . Those trends in
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values are not fully
mirrored by seasonal salinity changes, especially in the inner Schlei
(A), the outer Zingster boddens (F -- H), and the Vitter bodden (I).

This gives evidence, that other factors than mixing processes between
freshwater and marine water masses, exhibit additional control on local
water isotopes and salinity. For example, higher temperature
and/or\textsuperscript{18}O / \textsuperscript{2}H-enrichment due to
evaporation from lagoon surfaces are potential drivers behind higher
\selectlanguage{greek}δ-\selectlanguage{english}values in summers. This is plausible, since potential evaporation has
been estimated to be in range of annual freshwater supply by
precipitation, at least in the DZBC (Chubarenko et al., 2005). In
winters, lower \selectlanguage{greek}δ-\selectlanguage{english}values were observed in Feb/March 2021 compared to
Feb/March 2020. This could indeed be explained by temperature control,
i.e. the generally more cold conditions with partially ice-cover on all
sampling spots in winter / spring 2020/2021, compared to the relatively
mild winter/spring 2019/2020 (reflected in water temperatures; Figs 3 --
5).

\textbf{4.2 Water isotopes along the Schlei and bodden transects}

\emph{Spatial trends}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

Fig. 7: Interpolated \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values along the three
sampled transects for March (left) and July (right) 2020. Baltic Sea
excluded from interpolation. Panels a -- c refer to subregions as
indicated in Figure 1. Circles A-I: sampling points for time-series.
Circles \#1-68: shore samples. Arrows indicate exchange points with
Baltic Sea water. Abbreviations as in Fig. 2.

Similar to salinity gradients (Fig. 2), the water isotope values in
March 2020 increase from low to high at all three transects from river
inlets to the outflows to the Baltic Sea (exemplarily plotted for
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values in Fig. 7). In July 2020, most regions
show higher \selectlanguage{greek}δ-\selectlanguage{english}values compared to Spring (Fig. 7; interpolated maps with
isotope offsets in Supplementary Fig S1). Especially, the innermost
waterbodies, such as the inner Schlei, the Saaler Bodden at DZBC, and
the NRBC, exhibit relatively strong increase of isotope values.

Exceptions from these trends are areas under direct influence of Baltic
Sea water, such as the outflow regions of the Schlei and DZBC, which
show lower \selectlanguage{greek}δ-\selectlanguage{english}values in July compared to March (Fig. 7). The latter can
be explained by lower salinity and consequently lower isotope values of
Baltic Sea water in summer, compared to the high values after the
saltwater intrusion events in February and March 2020 (Fig. 3).

These dependencies lead to isotope gradients which are much less
pronounced than in March. Specifically the DZBC shows almost homogenous
isotope values along the whole bodden chain, with exception of the areas
directly adjacent to river inflows (Fig. 7b). In the following,
isotope-salinity correlations are closer examined.

\emph{Salinity -- isotope correlation}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

Fig. 8: Correlation between \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H values and salinity in June 2019, March 2020, and
July 2020. Linear and hyperbolic trendlines for Schlei (solid) and
combined Dar\selectlanguage{ngerman}ß-Zingster and Rügener Bodden (dashed) samples, under
exclusion of outliers as derived from lakes and the open Baltic Sea.

The spatial trends in water isotopes as visualized in Fig. 7 are
illustrated as correlation crossplots between \selectlanguage{greek}δ-\selectlanguage{english}values and salinities in
Fig. 8. Those reveal a positive correlation for samples from March 2020
(isotope amplitude ca. 30 %0 \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{2}H and 5.5 %0
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O over ca. 20 salinity units). In contrast, samples
from July 2020 reveal hyperbolic correlations between the two parameters
(Fig. 8). Here, \selectlanguage{greek}δ-\selectlanguage{english}values reach a plateau of maximum values for
salinities \textgreater{}7. For some samples, a reversal towards lower
\selectlanguage{greek}δ-\selectlanguage{english}values with increasing salinities is observable. A similar trend is
observable in samples from June 2019, which were taken in lower spatial
resolution (Fig. 8).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image9/image9}

\end{center}
\end{figure}

Fig. 9: Correlations between a) \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values and
salinity. Dashed grey trendline for March 20. Dashed black circle
indicate R\selectlanguage{ngerman}ügener Bodden and Baltic Sea samples; b)
\selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O values and latitude or longitude. Dashed
grey/black trendlines for March/July 20. Grey arrows indicate direction
of isotopic change from March to July; c) \selectlanguage{greek}Δ δ\selectlanguage{english}\textsuperscript{18}O
(March - July) and latitude or longitude; d) \selectlanguage{greek}Δ δ\selectlanguage{english}\textsuperscript{18}O
and \selectlanguage{greek}Δ \selectlanguage{english}Sal (March - July) for the three sampled transects. DZBC:
Dar\selectlanguage{ngerman}ß-Zingst Bodden Chain. East Transect comprises Stettiner Haff to GW
Bodden and Rügener Boddens.

When analysing the three transects individually and in more detail, they
all show a significant correlation between isotope values and salinity
in March 2020 (Fig. 9a). Especially in the Schlei, an almost linear
correlation between \selectlanguage{greek}δ-\selectlanguage{english}values and salinity is observable. Outliers with
significant higher \selectlanguage{greek}δ-\selectlanguage{english}values are samples taken from adjacent lakes and
noors, which not or only weakly connected to the Schlei (B\selectlanguage{ngerman}ültsee \#14,
Schnaaper See \#21, Ornumer Noor \#17, and Windebyer Noor \#19) (Fig.
7a). Further, a sample from the close-by Baltic Sea location Eckernförde
(\#21) might be influenced by local mixing process different than in the
Schlei system and its adjacent Baltic Sea outflow (e.g. \#27, \#29). In
the DZBC, the March 2020 samples can be assigned to two clusters: 1) low
saline samples taken from rivers or close to their outflows (\#30/\#31,
\#35/\#36) and from Saaler Bodden (\#32). 2) samples with salinity
\textgreater{}6 psu from all other locations (Fig. 9a and 7b). In the
Eastern Transect, again a linear salinity - isotope correlation is
observed from the Stettiner Haff to Rügener Boddens, with one outlier
(\#51) derived from the inner NRBC (Fig. 9a and 7c).

In contrast, in the Schlei and DCBZ, the two sampled summers (June 2019
and July 2020), reveal constant isotope values or even a reverse
correlation from salinities 4-6 psu and higher on (Fig. 9a). In the
eastern transect, however, a positive correlation along the Stettiner
Haff-Peenestrom-Greifswalder Bodden transect is observable, while
samples from the WRBC, NRBC and adjacent Baltic Sea samples show mixed
values clustering around -4.9 to -6.2 \selectlanguage{english}%0 \selectlanguage{greek}δ\selectlanguage{english}\textsuperscript{18}O and
salinity values 8.1 to 9.6 psu (dashed black circles in Fig. 9a and b).

These patterns come out more clearly when correlating \selectlanguage{greek}δ-\selectlanguage{english}values to
latitude / longitude, following their geographical orientations along
the transects (Fig. 9b), especially when considering the March-July
offset of isotope values (\selectlanguage{greek}Δδ\selectlanguage{english}) (Fig. 9c). This approach eliminates the
influence of larger salinity ranges in March compared to July, which is
strongest in the Schlei, and makes isotope values from specific spots
better comparable.

As noted above, most samples show isotope enrichment in the warmer
season (i.e. negative \selectlanguage{greek}Δδ \selectlanguage{english}March-July values) (Fig. 7). Exceptions are a
number of samples from the Baltic Sea, whose isotope signatures are
rather driven by mixing processes than by seasonal trends, or samples
under direct influence of Baltic Sea water (e.g. close to the outflows
of the Schlei and DZBC). In general, samples tendencially show stronger
isotope enrichment further inlands. Thus, they show increasing \selectlanguage{greek}Δδ
\selectlanguage{english}(March-July) values from the rivers inflow towards the Baltic Sea (Fig
9b, c; Fig. 7; interpolated salinity and \selectlanguage{greek}Δδ \selectlanguage{english}maps in Supplementary Figure
S1). Obviously, the shallow lagoons inlands (such as Kleine Breite at
the Schlei, and Saaler and Bodstedter Boddens at DZBC) are more
susceptible to undergo stronger isotopic enrichment in summers, than
locations more adjacent to the Baltic Sea. This is most pronounced in
the Schlei, here the \selectlanguage{greek}Δδ \selectlanguage{english}values are balanced (i.e. similar isotope values
in March and July) at ca. 75\% of the distance between the inner Schlei
and the outflow towards the Baltic Sea (Fig. 9c). Beyond this place
(which lies around the narrow passage aside the town Arnis, \#24/\#25),
\selectlanguage{greek}Δδ \selectlanguage{english}values become even positive due to lower \selectlanguage{greek}δ-\selectlanguage{english}values in July compared to
March. (Fig. 7a and Supplementary Figure S1a).

The major inference from these data set is, that sampling points that
undergo larger salinity changes between the maximum and minimum
freshwater inflows in spring and summers (i.e. most negative \selectlanguage{greek}Δ\selectlanguage{english}Sal
Mar-Jul) are also more susceptible to larger isotopic enrichment in the
summers (more negative \selectlanguage{greek}Δδ \selectlanguage{english}values Mar-Jul). This systematic is most
pronounced in the Schlei, which is characterized by the most linear
salinity gradient among the studied transects (Fig. 9d). A similar trend
is visible in the DZBC, but here it is weakened due to outliers as
mainly derived from the Barther Bodden and Grabow samples. In the
Eastern transect, no clear systematics between \selectlanguage{greek}Δ\selectlanguage{english}Sal and \selectlanguage{greek}Δδ \selectlanguage{english}could be
observed. While almost all samples show isotopic enrichment in summers
(negative \selectlanguage{greek}Δδ\selectlanguage{english}), the stronger influence of mixing processes of multiple
water sources (i.e. from rivers, inner R\selectlanguage{ngerman}ügen boddens, Baltic Sea water
intrusion from both the east and the north-west) can explain the
heterogenous isotope values in this study area. Here, increasing sample
density along sub-transects could potentially facilitate interpretation
of isotope data and the control mechanisms behind.

\textbf{5. Conclusions}

The time series data show that the studied estuarine systems exhibit a
clear seasonality within their water isotope values, which is comparable
NE German lakes rivers in both isotope amplitude and time succession.
The transect data further reveal complex isotope vs salinity
correlations: widely positive linear correlations were observed in March
2020 along all transects. In contrast, hyperbolic and partially inverse
correlations were found in the two samples summers (June 2019 and July
2020).

We hypothesize that this is triggered by increased susceptibility of the
mostly shallow inland water to evaporative isotope enrichment in
summers, causing higher \selectlanguage{greek}δ-\selectlanguage{english}values. Further, the discharge regime of
tributary rivers (lower \selectlanguage{greek}δ-\selectlanguage{english}values) and influence of water intrusion from
the Baltic Sea (higher \selectlanguage{greek}δ-\selectlanguage{english}values) obviously plays a role.

In summary, salinity is a fairly good predictor for water isotopes on
larger spatial scales. On regional scales, local effects overprint the
positive correlation between the two parameters especially in summers,
partly even leading to negative correlations. This seasonality of
salinity vs isotope correlation needs to be considered when interpreting
biogenic isotope data (of plants or animals) because those might be
similarly seasonally biased (often towards the warm/growing season).

\textbf{Acknowledgements}

Funding was provided by German Research Foundation (DFG) to B.A. (grant
Ai 134/3-1). We are grateful to Volker Reiff, Henry Hansen and Jan Droll
for help with sampling.

\textbf{Data availability}

All isotope and water chemical parameters in this manuscript are
available at PANGAEA (Aichner et al., 2021):
https://doi.org/10.1594/PANGAEA.937990

Until acceptance of the manuscript, this temporary and barrier free link
can be used to access the data
set:~https://doi.pangaea.de/10.1594/PANGAEA.937990

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