Among- and within-species variability in fatty acid signatures of marine fish and invertebrates on the Scotian Shelf, Georges Bank, and southern Gulf of St. Lawrence

Abstract

The fat and fatty acid compositions of 28 species of fish and invertebrates (n = 954) from the Scotian Shelf, Georges Bank, and the Gulf of St. Lawrence were determined. Discriminant analysis of the 16 most numerous species (n [Formula: see text] 18 each), using 17 major fatty acids, classified species with greater than 98% accuracy and grouped species into three general clusters (gadids, flatfish, and planktivores) with similar fatty acid compositions, and likely, similar diets. A number of species exhibited changes in fatty acid signatures with increasing size (multivariate analysis of variance), which corresponded with known dietary shifts reported from stomach contents analyses. Location effects were also observed among the three major geographical regions and were probably due to broad-scale variations in prey assemblages and phytoplankton composition in the northwestern Atlantic. Despite these effects, within-species variation was still substantially less than among-species variation. Thus, fatty acid signatures can be used to distinguish and characterize fish and invertebrate species in a given ecosystem, as well as to study finer-scale trophic interactions of these species. These data also have applications at higher trophic levels and will serve as a prey database for studying the diets of other fish and marine mammal predators using fatty acid signatures.

Fatty acid and stable isotope biomarkers suggest microbe‐induced differences in benthic food webs between depths

“…Our results concur with other studies showing that FA signatures of different groups of organisms are related to phylogeny (Budge et al 2002;Galloway et al 2012). Invertebrate taxa studied here clearly differed from each other regardless of depth and site variation (FA and MSI: p 5 0.0001; Fig.…”

“…If microbes are responsible for the v-3 declines in the aged, non-defended alga in our experiment (e.g., through selective consumption and catabolism of v-3 FA from their substrates) this could have important food web implications, as this category of FA is critical for heterotrophs (Mü llerNavarra 2008) and has been hypothesized as a limiting resource in food webs (Litzow et al 2006). Additional research is needed to further understand the roles that microbes, which can quickly colonize and abandon suspended POM (Kiørboe et al 2002), may play in diagenesis of POM and macrodetrital biomarker signatures (e.g., Budge et al 2001). The lack of significant differences in Agarum total v-3 FA and bacterial marker FA, when paired with the fact that microbe abundance did not increase on Agarum through time (Sosik 2012), implies a relationship between microbes and v-3 FA (Thiansilakul et al 2013) that warrants further research.…”

“…Wilmers et al (2012) estimated that 3-450 g C m 21 yr 21 of the production from kelp forests is not consumed in the SPE but is transferred out of the photic zone to the deep subtidal. The order of magnitude in the uncertainty of this flux estimate assumes that 1-50% of annual in situ kelp NPP is transported to DNSE (also see Buesseler et al 2007). These approaches (e.g., estimates of export-based NPP) do not account for dissolved organic carbon, which may account for up to 34% of the total annual energy production by kelps (Newell et al 1980).…”

“…FA can be used for qualitative assessment of trophic relationships (e.g., tracing presence of certain source-specific biomarkers), or for quantitative modeling of predator diet when FA signatures of all likely prey sources are known and fractionation of FA from diet to tissues of the consumer is accounted for (Iverson 2009). It is becoming increasingly evident that FA signatures are tied to species' phylogenetic relationships, e.g., in marine macrophytes (Galloway et al 2012), phytoplankton (Lang et al 2011), invertebrates, and fishes (Budge et al 2002).…”

Tracing aquatic food webs using fatty acids: from qualitative indicators to quantitative determination

“…For instance, while 22:1n-11 is the dominant isomer over 22:1n-9 in most marine ecosystems, 20:1n-9 is by far the dominant isomer over 20:1n-11 in the North Atlantic (e.g., Budge et al 2002) . However, several studies have shown the reverse in the Pacific, with 20:1n-11 dominating 20:1n-9 in fish and invertebrates (Saito and Murata 1998) .…”