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.