Fatty acids reveal salmonine – prey relationships in Lake Michigan

Autor: Benjamin S. Leonhardt, Tomas O. Höök, Jacques Rinchard, Charles R. Bronte, Matthew S. Kornis, Benjamin A. Turschak, Christopher Maier, Harvey A. Bootsma, Austin Happel, Sergiusz J. Czesny
Rok vydání: 2020
Předmět:
Zdroj: Journal of Great Lakes Research. 46:1689-1701
ISSN: 0380-1330
DOI: 10.1016/j.jglr.2020.08.005
Popis: Lake Michigan salmon and trout populations are important species for recreational fisheries and food web management, and are largely supported through stocking efforts, with varying degrees of natural recruitment. Ongoing fisheries management of these salmonine populations is dictated by relationships between predator and prey abundance as well as community structure within the lake. However, while prey fish biomass has declined, and species composition has changed in recent decades, knowledge of prey consumption by the salmonine community has lagged. Herein, we explore trophic relationships using fatty acids profiles, which offer insights into the foraging habits and energy pathways relied on over weeks to months prior to collection. Fatty acids of the prey base for salmonines in Lake Michigan indicate a gradient of foraging habits that range from pelagic (typified by alewife and rainbow smelt) versus benthic (i.e., slimy sculpin and round goby) resource use. Fatty acids implied that there was more variation in foraging habits among individual lake trout and brown trout compared to Chinook salmon, coho salmon and rainbow trout, which appeared to all rely almost exclusively on pelagic prey. Fatty acid profiles also indicated size-based shifts in foraging habits; for example, larger lake trout consuming a greater proportion of benthic prey than smaller individuals. Data herein suggest that Chinook and coho salmon, as well as rainbow trout, are more likely to experience competitive interactions during times of low pelagic prey-fish abundance in Lake Michigan, whereas brown and lake trout are able to utilize benthic resources to a greater degree.
Databáze: OpenAIRE