Using a gradient in food quality to infer drivers of fatty acid content in two filter-feeding aquatic consumers

Aquatic Sciences
By: , and 

Links

Abstract

Inferences about ecological structure and function are often made using elemental or macromolecular tracers of food web structure. For example, inferences about food chain length are often made using stable isotope ratios of top predators and consumer food sources are often inferred from both stable isotopes and fatty acid (FA) content in consumer tissues. The use of FAs as tracers implies some degree of macromolecular conservation across trophic interactions, but many FAs are subject to physiological alteration and animals may produce those FAs from precursors in response to food deficiencies. We measured 41 individual FAs and several aggregate FA metrics in two filter-feeding taxa to (1) assess ecological variation in food availability and (2) identify potential drivers of among-site variation in FA content. These taxa were filter feeding caddisflies (Family Hydropyschidae) and dreissenid mussels (Genus Dreissena), which both consume seston. Stable isotopic composition (C and N) in these taxa co-varied across 13 sites in the Great Lakes region of North America, indicating they fed on very similar food resources. However, co-variation in FA content was very limited, with only one common FA co-varying across this gradient (α-linolenic acid; ALA), suggesting these taxa accumulate FAs very differently even when exposed to the same foods. Based on these results, among-site variation in ALA content in both consumers does appear to be driven by food resources, along with several other FAs in dreissenid mussels. We conclude that single-taxa measurements of FA content cannot be used to infer FA availability in food resources.

Study Area

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Using a gradient in food quality to infer drivers of fatty acid content in two filter-feeding aquatic consumers
Series title Aquatic Sciences
DOI 10.1007/s00027-017-0537-0
Volume 79
Issue 4
Year Published 2017
Language English
Publisher Springer
Contributing office(s) Upper Midwest Environmental Sciences Center
Description 11 p.
First page 855
Last page 865
Country Canada, United States
Other Geospatial Lake Erie, Lake Huron, Lake Michigan, Lake Ontario