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Miljø- og Fødevareudvalget 2024-25
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BRIEF RESEARCH REPORT
published: 21 August 2020
doi: 10.3389/fmars.2020.00705
Nitrogen and Phosphorous Content
in Blue Mussels (Mytilus spp.) Across
the Baltic Sea
Anna-Lucia Buer
1
*
, Daniel Taylor
2
, Per Bergström
3
, Lukas Ritzenhofen
1,4
and
Annemarie Klemmstein
1
1
Leibniz-Institute for Baltic Sea Research Warnemünde, Rostock, Germany,
2
Danish Shellfish Center, National Institute of
Aquatic Resources, Technical University of Denmark, Nykøbing Mors, Denmark,
3
Department of Marine Sciences, University
˙
of Gothenburg, Gothenburg, Sweden,
4
Marine Research Institute, Klaipeda, Lithuania
Edited by:
Jose Luis Iriarte,
Institute of Aquaculture, Austral
University of Chile, Chile
Reviewed by:
Caterina Faggio,
University of Messina, Italy
Huang Wei,
Second Institute of Oceanography,
Ministry of Natural Resources, China
Martyn Futter,
Swedish University of Agricultural
Sciences, Sweden
*Correspondence:
Anna-Lucia Buer
[email protected]
Specialty section:
This article was submitted to
Marine Fisheries, Aquaculture
and Living Resources,
a section of the journal
Frontiers in Marine Science
Received:
28 March 2020
Accepted:
03 August 2020
Published:
21 August 2020
Citation:
Buer A-L, Taylor D, Bergström P,
Ritzenhofen L and Klemmstein A
(2020) Nitrogen and Phosphorous
Content in Blue Mussels (Mytilus
spp.) Across the Baltic Sea.
Front. Mar. Sci. 7:705.
doi: 10.3389/fmars.2020.00705
To support the ongoing discussion about mussel farming and the potential to extract
nutrients from the sea, this study investigated the phosphorus (P) and nitrogen (N)
content of blue mussels (Mytilus spp.) under different abiotic and biotic parameters. The
focus of this survey was on the highly eutrophied Baltic Sea, where salinity ranges from 4
to 27 psu, and is a major contributing factor to differential mussel growth. We observed
that nutrient content was not linearly correlated to salinity, but if categorized, decreased
at higher salinities. Chlorophyll-a and temperature did not significantly correlate with
nutrient content, but season of harvest and mussel size did. Furthermore, habitat was a
strong driver of nutrient content, indicating higher nutrient density if mussels are grown in
mussel farms (i.e., in the water column) instead of on mussel culture beds or harvested
from wild beds (on the sea bed). Values of N and P averaged 5.85% N and 0.83% P
of tissue dry weight in mussels at the sea bed and 9.43% N and 0.96% P of tissue
dry weight in mussels from longline cultivation. These results will be useful in refining
estimations about mussel farming as a nutrient mitigation measure and the extraction
potential, as well as related costs.
Keywords:
Mytilus
spp., Baltic Sea, nitrogen, phosphorus, salinity
INTRODUCTION
The persistence and magnitude of eutrophication in the Baltic Sea requires cost-effective measures
to reduce nutrients and to achieve a good ecological status (GES) based on the Water Framework
Directive (WFD,
European Parliament, 2000)
and the Marine Strategy Framework Directive
(MSFD,
European Parliament, 2008).
Extensive mussel aquaculture on longlines or tube-net
systems (e.g., Smart Farm) is highly discussed as such a measure in the greater Baltic Sea (Lindahl
and Kollberg, 2008; Stadmark and Conley, 2011; Petersen et al., 2012, 2014, 2019; Nielsen et al.,
2016; Hedberg et al., 2018; Gren, 2019; Taylor et al., 2019; Kotta et al., 2020).
The amount of
nutrients that can hereby be removed depends on several parameters, such as nutrient content
of the mussels, growth rates, harvesting time, and farm set up (Capillo
et al., 2018; Taylor et al.,
2019).
These parameters drive the total mitigation potential and economic feasibility of mussel
farming as a eutrophication measure in different areas of the Baltic Sea. However, to the extent
which environmental parameters (salinity, chl-a, temperature) influence the nutrient content
within mussels has not been exhaustively investigated. Previous studies (Hedberg
et al., 2018;
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Buer et al.
Nutrients in Baltic Blue Mussels
Buer et al., 2020; Holbach et al., 2020; Kotta et al., 2020)
report
a fluctuating nutrient content of blue mussels across the Baltic
Sea but base their estimation of total mitigation potentials rather
on different growth rates and an average nutrient content.
Besides area-specific growth rates, it is important to evaluate
the parameters that affect the actual nitrogen and phosphorus
content stored in mussel tissue. Area-specific nutrient contents
can support further studies on the mitigation potential, cost
analyses and projections for Baltic-wide nutrient reduction.
The main objective of the present study was to document
the relationship between environmental conditions and
nutrient content in blue mussels across the Baltic Sea.
Therefore, we analyzed the nutrient content (nitrogen, N and
phosphorus, P) of blue mussels across the Baltic Sea in regards
to different environmental parameters (salinity, maxima of
water temperature, chlorophyll-a levels). Furthermore, nutrient
contents were related to mussel size, habitat, and season of
harvest. Providing the different environmental conditions across
the greater Baltic Sea, our hypothesis was that environmental
parameters would correlate with condition and nutrient contents
of mussels, and an analytical approach to test for associations
was followed.
MATERIALS AND METHODS
Mussel samples were collected from aquaculture farms and wild
stock as indicated in
Figure 1.
Samples along the Swedish west coast were collected at six
sites from natural mussel beds, taken at 0.5 m water depth, in the
spring of 2014. Mussels were divided into three size classes (5–
15, 20–30, and 40–50 mm) and the dry tissue of each individual
(n = 178) was analyzed separately for N and P content. After
freeze drying, a persulfate oxidation method was used for analysis
of nitrogen and phosphorous (Valderrama,
1995).
The age of the
mussels was estimated based on the mussel shell length.
Samples from the eastern Swedish coast (Grankullaviken,
Västervik and Hagby), the Latvian coast (Pâvilosta), and Estonia
(Vormsi Island) were harvested from test mussel farms within
the Interreg project
Baltic Blue Growth
(BBG). Mussel samples
from Greifswald Bay (GWB), Wieker Bay (WB), Nienhagen,
Kiel, and Flensburg (Germany), as well as the Danish sites
(Sallingsund, Skive, Dråby Vig, Mariager mid- and inner-fjord,
Vejle, As Vig), were collected at mussel farms within the BONUS
Optimus project. In Börgerende and Schilksee, DE, as well as
Gulf of Gda´ sk, PL, mussels were collected from natural hard
n
substrate. For all sites, mussels of different size, age and season
were sampled and frozen in sealed containers (−20
◦
C) for
further analyses. Subsequently, the shell length and total wet
weight of a minimum of 10–30 individuals was measured. After
dissection, tissue and shell of all individuals was pooled, freeze-
dried, and ground, before carbon and nitrogen were analyzed in
an auto-analyzer (Elementaranalysator EA 3000). Phosphorous
was determined in mussel ash using an alkaline persulfate
oxidation after
Hansen and Koroleff (1999).
Danish samples
cover seven sites, while some sites were sampled in different
seasons (n = 100 for each sampling event). The mussels were
processed after
ISO (1998)
6491 (1998) and
ISO (2009)
5983-2
(2009) for phosphorus and nitrogen determination, respectively.
The tissue-shell-ratio, also known as the condition index, was
calculated based on the dry weight of mussel tissue and shell.
CI
=
DW
tissue
[mg]
DW
shell
[mg]
Environmental data (salinity, temperature and chlorophyll-a
concentration) was collected by state authority monitoring
programs or modeled data (for Poland) for the upper water
FIGURE 1 |
Sampling sites along the Baltic Sea coast. Red circles indicate samples from longline collectors (in the water column), green circles indicate sampling
from wild stocks (off the ground).
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Buer et al.
Nutrients in Baltic Blue Mussels
layers (0.5 m depth)
1
. Chlorophyll-a was analyzed fluorometric
(665 nm) after filtration (GF/F, 0.7
µm),
extraction with ethanol
and acidification (ISO 10260:19922) following HELCOM –
Guidelines for monitoring of chlorophyll-a
2
.
Correlations of biometric data and environmental values
were evaluated by bootstrapping ordinary least squares linear
regression and mixed model effect leveraging by minimizing
AICc. Confidence intervals were determined by bootstrapping
and categorical comparison (habitat, season) was performed
by permutation ANOVA (1E5 permutations) with the vegan
package in R (Oksanen
et al., 2019).
Full factorial mixed
models were bootstrapped and used to evaluate interactions with
environmental variables. Normality of residuals was checked by a
normal QQ plot and the Shapiro-Wilk test. Finally, for nutrient
content of dry tissues, a full factorial interaction model of all
environmental parameters, habitat, and season was reduced by
elastic net regularization in the glmnet package in R by setting
the alpha parameter to 0.5 (Friedman
et al., 2010).
Additionally, data was pooled into three salinity categories:
below 15 psu (6–10 psu, based on sample availability), above
15 psu and above 20 psu. Salinities below 15 psu were expected
to have a strong effect on mussel condition and water content
(DW/WW-ratio) (Maar
et al., 2015).
As a bottleneck for water
exchange between the Kattegat and Baltic proper, the Great Belt
area provides a natural border between salinities above and below
20 psu and thereby, as a natural divider of samples (Feistel
et al.,
2009; Riisgård et al., 2012).
These categories were used to detect
potential differences in mussel N and P content (in tissue DW
and total WW) as well as differences in the tissue-shell-ratio.
RESULTS
Nutrients accumulate primarily in the bivalve tissues, only a
minor fraction is stored in the shell (ratio of 0.16
±
0.04 N in
DW). Therefore, phosphorous and nitrogen concentrations of
the mussel shell was not measured in all samples. To estimate
N and P-values of the total mussel wet weight (including shell),
measured N and P-values of the dry tissue were combined with
literature data for N and P in the dry shell, averaged water
contents and averaged shell-tissue-ratios. 0.04% P and 1% N of
dry shell mass were assumed for all sites based on literature
and our own data (Haamer,
1996; Ek Henning and Åslund,
2012; Petersen et al., 2014; Bucefalos, 2015; Palm et al., 2015;
Hedberg et al., 2018).
Water contents and shell-tissue-ratios
were averaged for samples at each site. Results are presented
in
Table 1.
Tissue-shell-ratios were not linearly correlated to average
salinity (R
2
= 1.7e-4,
p
= 0.84), although a weak trend toward
higher ratios in higher salinities appeared if categorically pooled
1
Swedish Meteorological and Hydrological Institute (SMHI, www.smhi.se.data);
Latvian Institute of Aquatic Ecology; Estonian Marine Institute; Dansih
Overfladevandsdatabasen
(ODA,
https://oda.dk);
SatBaltyk
IOPAN
(satbaltyk.iopan.gda.pl); Landesamt für Landwirtschaft, Umwelt und ländliche
Räume des Landes Schleswig-Holstein (LLUR); Landesamt für Umwelt,
Naturschutz und Geologie Mecklenburg-Vorpommern (LUNG).
2
https://helcom.fi/media/publications/Guidelines-for-measuring-chlorophyll-a.
pdf
(Figure
2A).
Average site temperature was equally poor in
explaining variation (R
2
= 0.007,
p
= 0.12) as well as chlorophyll-
a
(R
2
= 0.01,
p
= 0.05). Comparison of habitats exhibits a
higher ratio in mussels grown in the water column [Figure
2B,
F
(1,214)
= 56.61,
p
<
0.001]. This suggests that mussels grown
on suspended substrate in the water column have either thinner
shells or higher somatic tissue mass compared to mussels
from the sea bed. Nitrogen [F
(1,213)
= 610,
p
<
0.001] and
phosphorus [F
(1,213)
= 11.54,
p
<
0.001] contents were similarly
significantly higher in samples from mussel farms [9.55
±
0.73
(95
%CI:
9
.
30−9
.
78)
% N DW
tissue
, 0.96
±
0.17
(95
%CI:
0
.
89−1
.
01]
% P
DW
tissue
] compared to mussels from the sea bottom [5.85
±
0.83
(95
%CI:
5
.
72−5
.
96)
% N DW
tissue
, 0.82
±
0.22
(95
%CI:
0
.
79−0
.
85)
% P
DW
tissue
] (Figure
2C).
In a mixed model analysis of salinity
and habitat, habitat exhibited significant leverage (R
2
= 0.50,
p
<
0.001), but interaction between habitat and salinity was not
significant (p = 0.21). These results suggest position in the water
column or mode of attachment influences condition index to a
greater degree than salinity alone. Crossing all environmental site
averages was relatively effective in describing variability in the
tissue-shell ratio (R
2
= 0.38,
p
<
0.001), where chlorophyll-a,
temperature, and their interaction were the only significant
effects (p
<
0.01).
The nutrient content (N&P) within mussel dry tissue was
weakly correlated to average salinity (R
2
N
= 0.28,
R
2
P
= 0.08),
both exhibited negative slopes, indicating a general inverse trend
of nutrient content to salinity. After samples were pooled into
salinity categories, the phosphorus content showed significant
differences between the lowest (6–10 psu) and the intermediate
(15–20 psu) as well as the highest (20–30 psu) salinity (p
<
0.001)
but not between the latter (p = 1.000). The nitrogen content
followed the same pattern, and showed significant differences
between the lowest salinity and the two higher (p
<
0.001) but not
between the intermediate and high salinity categories (p = 0.179)
(Figure
3A).
Differences in nitrogen in total wet weight were
similar, but not significant (p
>
0.05). Phosphorus concentrations
in total wet weight were not significantly different based on
salinity (p
>
0.05) (Figure
3B).
No correlation was observed
between nutrient content in tissue dry weight to mean values of
chlorophyll-a concentration (Figure
3C)
nor to maximal water
temperatures (Figure
3D)
at each site. However, differences were
observed between seasons (Figure
3E,
samples of all study sites
included), indicating a significant lower nitrogen content in
spring compared to all other seasons [F
(3,211)
= 80.76,
p
<
0.001].
Phosphorus contents on the other hand were not different
between seasons [F
(3,211)
= 1.805,
p
= 0.1418] (Figure
3E).
Furthermore, nutrient content also differed between mussel sizes
(Figure
3F,
pooled samples of Swedish sites). Small mussels
(5–15 mm) had a significant higher nitrogen content in the
dry tissue compared to medium (20–30 mm,
p
= 0.009) and
large (20–50 mm,
p
<
0.001) mussels. On the contrary, the
phosphorus content increased with mussel size (p
>
0.001
between each group).
Reduction of the full factorial model for N in DW tissue,
with mean environmental parameters, habitat, and season,
included season
∗
habitat, season
∗
temperature
∗
chlorophyll-a,
season
∗
salinity, and habitat as significant effects (R
2
= 0.83,
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Nutrients in Baltic Blue Mussels
TABLE 1 |
Sample locations, bivalve habitat (LL, longline; SF,Smartfarm), environmental parameters, and N&P contents in dry tissue mass (DW) as well as total
wet weight (WW).
Lat
Site
As Vig, DK
Börgerende, DE
Dråby Vig, DK
Flensborg, DE
Grankullaviken, SE
Greifswald Bay, DE
´
Gulf of Gdansk, PL
Hagby, SE
Havstensfjorden, SE
Instö, SE
Kattvik, SE
Kiel, DE
Koster, SE
Kungsbacka, SE
Mariager inner-fjord, DK
Mariager mid-fjord, DK
Nienhagen, DE
Nienhagen, DE
Pâvilosta, LV
Sallingsund, DK
Schilksee, DE
Skive, DK
Stretudden, SE
Västervik, SE
Vejle, DK
Vormsi Island, EE
Wieker Bay, DE
(y)
55.7792
54.1539
56.8425
54.8774
57.3530
54.3172
54.4853
56.5600
58.2980
57.9054
56.4607
54.3797
58.8569
57.3645
56.6664
56.6990
54.1798
54.1798
56.9066
56.7849
54.4329
56.6706
58.3382
57.8450
55.7044
58.5190
54.6102
Long
(x)
10.0781
11.8983
8.8524
9.6408
17.1050
13.6270
18.8385
16.2580
11.7519
11.6571
12.7606
10.1683
11.1614
12.0130
9.9681
10.0618
11.9536
11.9536
21.0512
8.9153
10.1692
9.1262
11.4067
16.7570
9.6687
22.2550
13.2322
Habitat
LL, SF
Pier
LL, SF
LL, SF
LL
LL
Sea bed
LL
Sea bed
Sea bed
Sea bed
LL
Sea bed
Sea bed
LL, SF
LL, SF
Sea bed
LL
LL
LL, SF
Pier
LL, SF
Sea bed
LL
LL, SF
LL
LL
Temp
(
◦
C)
2.2–19.9
−0.3–22.8
2.0–23.9
0.5–23.3
−0.3–22
−0.4–25.2
−0.4–23.6
−0.1–22.3
0.3–22.9
−0.5–22
−1.1–22
0.1–19
−0.8–22.5
−0.2–21.7
−0.5–21.9
−0.9–19.6
−0.3–22.8
−0.3–22.8
−0.4–23.4
−0.8–23.4
−0.2–20.4
0.1–24.4.
−0.7–21.9
0.0–22.5
−0.9–23.7
1.4–27.8
0.3–24.0
Chl-a
(mg/m
3
)
0.3–63
0.1–16.5
0.3–40
0.3–73.7
0.1–8.8
1.0–54.3
0.2–18.1
0.7–20
0.1 -31.2
0.1–26.5
0.1–16.4
0–38.6
0.1–30
0.1–36.9
0.3–130
0.7–15
0.1–16.5
0.1–16.5
0.5–7.6
0.3–40
0–28.1
0.3–65
0.1–26.4
0.7–13
0.4–51
0.1–7.6
0.7–25.2
Sal [psu]
Mean
22.7
±
2.7
15.4
±
4.8
27.4
±
1.2
17.8
±
2.0
6.9
±
0.5
7.3
±
0.7
7.3
±
0.3
6.8
±
0.4
26.2
±
4.8
22.6
±
5.0
19.7
±
4.8
17.0
±
2.5
29.5
±
4.0
26.3
±
6.2
15.4
±
0.9
18.4
±
1.9
15.4
±
4.8
15.4
±
4.8
6.9
±
0.3
28.7
±
1.5
17.8
±
3.0
25.1
±
1.9
29.2
±
4.3
6.8
±
0.4
22.6
±
3.4
6.7
±
0.5
9.0
±
0.8
N
P
N
P
(%DW
tissue
)
9.3
8.6
9.7
8.4
9.9
9.5
9.0
8.4
5.9
5.6
5.8
8.7
6.0
5.7
9.0
10.3
11.1
8.5
9.4
9.5
7.8
9.6
6.0
10.4
8.9
11.1
9.7
0.8
1.0
0.9
0.7
1.1
1.0
1.4
1.1
0.8
0.9
0.8
0.8
0.7
0.9
0.8
1.1
0.9
0.7
1.0
0.8
0.9
0.9
0.7
1.2
0.8
1.2
1.1
(%WW
Total
)
1.3
0.9
1.3
1.2
1.5
0.8
0.9
1.1
1.1
1.0
1.0
1.1
0.9
1.1
1.4
1.4
1.0
1.1
1.5
1.2
0.7
1.2
1.1
1.4
1.4
1.2
0.9
0.09
0.07
0.10
0.09
0.13
0.06
0.10
0.09
0.10
0.10
0.09
0.09
0.07
0.11
0.11
0.13
0.06
0.08
0.14
0.09
0.07
0.10
0.09
0.13
0.10
0.09
0.08
FIGURE 2 |
Ratio of dry tissue to shell in regards to
(A)
salinity and
(B)
habitat of the mussel as well as
(C)
nitrogen and phosphorus content in dry tissue of mussels
from the sea bed and cultivated on longlines (LL).
p
<
0.05). For P in DW tissue, only habitat (p = 0.003) and
season (p = 0.006) had significant effects, but were weakly
correlated with the data (R
2
= 0.15). It should be noted that
habitat is correlated with chlorophyll-a, as longline (LL)
exhibited higher mean values [5.80
±
3.06
(95
%CI:
4
.
79−6
.
77)
] than
sea bed sites [2.05
±
0.39
(95
%CI:
1
.
99−2
.
11)
] [F
(1,213)
= 253.2,
p
<
0.001]. Furthermore, LL sites had higher mean temperatures
[10.45
±
0.99
(95
%CI:
10
.
14−10
.
78)
] than sea bed sites [9.91
±
0.31
(95
%CI:
9
.
87−9
.
96)
] [F
(1,213)
= 35.45,
p
= 0.003] and lower salinity
[15.59
±
8.55
(95
%CI:
12
.
87−18
.
29)
] than sea bed sites [25.07
±
3.65
(95
%CI:
24
.
55−25
.
61)
] [F
(1,213)
= 116.6,
p
<
0.001]. In sum, season
and habitat were the most influential effects on the variation in N
and P in DW tissue. When limiting to LL, as will be the habitat of
mitigation culture under current recommendations, none of the
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Buer et al.
Nutrients in Baltic Blue Mussels
FIGURE 3 |
Nitrogen (N, green, on the left) and phosphorus (P, red, on the right) content in tissue dry weight (DW) and total wet weight (WW) plotted over different
environmental parameters:
(A)
salinity categories (DW),
(B)
salinity categories (WW),
(C)
mean value chlorophyll-a (DW) and
(D)
maximal water temperatures (DW); as
well as nutrients over
(E)
season of harvest and
(F)
mussel size (in shell length, only Swedish samples).
environmental parameters were correlated with N or P content
in DW tissue, with the exception of weak negative correlation
of salinity and P content (R
2
= 0.1,
p
= 0.04). Season as a mixed
effect did not contribute to variation.
DISCUSSION AND CONCLUSION
Generally, the nutrient content within mussel tissue was not
strongly related to the environmental parameters: salinity,
average chlorophyll-a levels, or maximum water temperatures.
A lower dry weight nutrient content in mussels of the
eastern Baltic Sea by decreasing salinities was not observed.
Consequently, our original hypothesis that these environmental
parameters would account for most of the variability in mussel
nutrient content, was rejected. On the other hand, it was evident
that mussels cultivated on suspended substrate in the upper water
column exhibited considerably higher nutrient contents than
mussels on the sea bed. It has previously been demonstrated
that cultivation mode, or in general terms, position in the water
column, significantly influences the biochemical composition of
mussel tissues (Colombo
et al., 2016).
Interactions of parameters
suggested that simply season and habitat encompassed much
of the variability in N and P content; while it is acknowledged
that some of the associated variability within the environmental
parameters are built into habitat and season. Vertical gradients in
phytoplankton concentrations and stratification can exacerbate
food limitation in mussels at the sea bed (Wiles
et al., 2006;
Filgueira et al., 2018).
Prior work has demonstrated a relationship
between food concentration, composition, and mussel tissue
biochemistry (Pleissner
et al., 2012).
Two potentially important
implications of this habitat differentiation are: (1) samples from
wild mussel beds do not serve as reliable surrogates of nutrient
content when estimating potential nutrient yields in mitigation
culture; (2) nutrient content of DW tissue does not appear to vary
much in response to the salinity gradient.
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Nutrients in Baltic Blue Mussels
Harvest timing (seasonality) is an important parameter
when considering the potential nutrient extraction potential.
Low spring nitrogen contents in cultivated blue mussels are
consistent with primary gamete release (Pieters
et al., 1980;
Okumus and Stirling, 1998; Fernández et al., 2015). Taylor
et al. (2019)
recommended late autumn through winter harvests
in order to maximize nutrient extraction efficiency. This will
additionally avoid potential loss of nutrient content overlapping
with gamete release, and permit new spat collection in the late
spring/early summer.
Due to the low resolution of environmental parameters in time
and space, it was difficult to draw definitive conclusions from
observed relationships of nutrient content and environmental
conditions. These analyses could be improved by evaluating
interannual variation relative to position-specific high resolution
environmental data. Supplementing interpretations of nutrient
extraction potentials by energetic models may corroborate the
importance of environmental conditions to nutrient content
(Buer
et al., 2020).
In sum, these results suggest that variability in proportional
mussel nutrient content will be nominal when cultivated in the
water column if there is sufficient food available, and harvesting
timed to avoid the reproduction period. Total biomass,
therefore, will be the meaningful metric when estimating
nutrient extraction potential. Furthermore, although there is
reduced growth of blue mussels at low salinities, proportional
nutrient content is not significantly reduced in the summary
harvested dry materials.
contributed to data curation and manuscript writing. PB and DT
provided the data for nutrients in mussels of Sweden’s west coast
and Denmark, respectively, who also contributed to the text of the
manuscript. AK was involved in sample processing. All authors
contributed to the article and approved the submitted version.
FUNDING
The work was financially supported by the project BONUS
OPTIMUS (03A0020A). The project has received funding from
BONUS (Art 185) funded jointly by the European Union’s
Seventh Programme for research, technological development and
demonstration, and from Baltic Sea national funding institutions.
The publication of this article was funded by the Open Access
Fund of the Leibniz Association.
ACKNOWLEDGMENTS
We would like to thank the people who provided mussel
samples from around the Baltic: Juris Aigars (Latvian Institute
of Aquatic Ecology), Jonne Kotta (University of Tartu), Susanna
Minnhagen (Kalmar Municipality), Ksenia Pazdro (IOPAN), Tim
Staufenberger (Kieler Meeresfarm), and Florian Peine (LFA). For
the provision of environmental long-term data, we thank SMHI,
Latvian Institute of Aquatic Ecology, Estonian Marine Institute,
Danish Overfladevandsdatabasen, IOPAN, LLUR, and LUNG.
Furthermore, Regina Hansen, Anne Köhler, and Ines Scherff for
their support on CNP analyses, as well as Ivar Lund and Ulla
Sproegel for Danish nutrient analyses. Additionally, we would
like to thank the editor and the three referees for their critical
review and very valuable input.
DATA AVAILABILITY STATEMENT
All datasets generated for this study are included in the
article/Supplementary
Material.
AUTHOR CONTRIBUTIONS
A-LB was responsible for overall structure and writing of the
manuscript, data collection, and sample processing. DT and LR
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fmars.
2020.00705/full#supplementary-material
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Conflict of Interest:
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 © 2020 Buer, Taylor, Bergström, Ritzenhofen and Klemmstein. 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.
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