2.4 Stable isotope analysis
Isotope data are expressed in delta (δ ) notation:\(\delta^{i}E_{\text{sample}}=\frac{\left(\frac{i_{E}}{j_{E}}\right)_{\text{sample}}-\left(\frac{i_{E}}{j_{E}}\right)_{\text{ref}}}{\left(\frac{i_{E}}{j_{E}}\right)_{\text{Ref}}}\)For the element E, the ratio of heavy (i) to light (j) isotope are
measured in both sample and references (Coplen & Shrestha 2016). To
express the isotopic data as per mil (‰), they are multiplied by 1000.
The isotope ratios are expressed relative to international standards;
Vienna Pee Dee Belemnite (VPDB) for carbon and atmospheric air for
nitrogen.
All tissue samples for compound specific isotope analysis were freeze
dried and then hydrolyzed in 6 N HCl at 110°C for 20 h before
derivatizing the AAs to N -acetyl methyl esters (NACME, (Corr,
Berstan & Evershed 2007) following the protocols by (Larsen et
al. 2013; Larsen et al. 2016a). The samples were analysed at the
Leibniz Laboratory at Kiel University. The average standard deviation
for the samples, across all AAs was 0.3‰ for δ13C.
Elemental content and bulk isotope values were determined at the Stable
Isotope Facility of the Experimental Ecology Group, GEOMAR, Kiel. The
overall standard deviation for the measurement range 5.0-15.0 µg N and
10.0-140 µg C was ±0.2 ‰ and ±0.15‰, respectively. We did not perform
lipid extraction prior to stable isotope analyses of tissue samples
because this can affect δ 15N values (Svenssonet al. 2016). Instead, we applied lipid correction toδ 13C values with C/N values larger than 3.3
(indicating elevated lipid content) following Post et al. (2007).
For detailed CSIA and bulk SIA methods, see the Supplementary
Information. AA See Supplementary Table S2 for δ13C
values and Supplementary Table S3 for bulk δ13C and
δ15N values.
2.5 Statistical analyses
All statistical analyses were performed in R version 3.5.1
(R-Development-Core-Team 2018). To assess whether EAA in consumers
originate from bacteria, fungi or marine phytoplankton, we applied
linear discriminant function analysis (LDA) (R: MASS ) using
δ13CEAA training data from Larsenet al. (2013). To assess the power of differentiating among
functional groups and among species with
δ13CEAA data, we applied Principal
Component Analysis (PCA, R: vegan ) using mean-centred
δ13CEAA values to factor out baseline
isotope variability. The mean-centred values were calculated by
subtracting each individual δ13CEAAvalue from the mean δ13C values of all EAAs for each
sample. Prior to the PCA, we applied LDA to find the most effective set
of independent variables for predicting category membership. With this
set of independent variables, we performed covariance matrix PCA that
preserves variance as the range and scale of variables are in the same
units of measure. Using the first and second principal component scores,
we then applied Multivariate Analysis of Variance (MANOVA, R:manova ) in conjunction with Pillai’s trace to test the null
hypothesis that groups have a common centroid in a dependent variable
vector space. A rejection of this hypothesis entails that the groups
have significantly different δ13CEAApatterns or fingerprints. The MANOVA tests were performed on groups with
≥5 specimens. To remove the effect of a covariate factor, we applied
Multivariate Analysis of Covariance (MANOVA, R: jmv ). All data
for multivariate comparisons were first assessed for homogeneity of
variance by using Fligner-Killeen tests and visually checked for
departures from normality on Q-Q plots. To test for species-specific
δ13C differences for each EAA for consumers from Kiel
Bight and the Arkona Basin, respectively, we used a One Way ANOVA with
Tukey’s HSD test (R: aov;
TukeyHSD ). Using scatterplots, we also investigated the power of
differentiating niches with isotope values of the glycolytic AAs and
bulk carbon and nitrogen, respectively. We used linear modelling to test
the strength of linear associations (R: lm ).
3. RESULTS
3.1 Biosynthetic origins
of the essential amino acids
According to our LDA using training data of broad phylogenetic groups,
phytoplankton were the primary EAA source for all consumers in Kiel Bay
and Arkona Basin; contributions from bacteria and fungi were small or
possibly absent (Fig. 2). The discrete clustering of most functional
groups indicates that they were supported by different phytoplankton
sources, here listed in terms of association along the along the first
linear discriminant: suspension feeders, benthic flatfish, scavengers,
pelagic piscivores, planktivores and benthic predators.