Carbon isotope fingerprinting of essential amino acids (EAA).This conceptional model depicts
δ13CEAA values of consumers feeding in
both estuarine and marine habitats. The consumers and their potential
food sources mirror δ13C baseline values along this
salinity gradient, and the δ 3CEAAintramolecular variability are from Larsen et al. (2015). The two
plots in the left pane (a and c ) are based on baseline
δ13CEAA values, and the two plots in
the right pane (b and d ) are based on
δ13CEAA values centred to the
δ13C mean across all EAA of a given sample.a , varying biogeochemical conditions across the
estuarine-marine gradient cause highly variable
δ13CEAA values. b , this
variability is greatly reduced within each food source when centring the
δ13CEAA values of each sample to the
mean of all five EAA. c , to find out which combination of
variables explain most of the variability among the three food sources,
we applied Principal Component Analysis (PCA), an unsupervised
dimensionality reduction method. Prior to the PCA we omitted lysine
because it is the least informative EAA for separating the three food
groups. Since the PCA is based on baseline δ13C
values, the PCA factor scores (PC1 and PC2 coordinates) are influenced
by both baseline and intermolecular δ13C variability.d , by using mean-centred data in the PCA, we have generated a
δ13CEAA fingerprint where the
resulting factor score variability within each group is reduced
substantially. By factoring out δ13C baseline
variability and instead using the source diagnostic power of
δ13CEAA fingerprinting, it is now
evident that regardless of habitat use all three consumers derive most
of their dietary EAA from Food-III. Abbreviations used on the x-axes ina and b : Ile = isoleucine, Leu = leucine, Lys =
lysine, Phe = phenylalanine, Val = valine.