Estimates of lake trout (Salvelinus namaycush) diet in Lake Ontario using two and three isotope mixing models
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Abstract
Recent development of multi-dimensional stable isotope models for estimating both foraging patterns and niches have presented the analytical tools to further assess the food webs of freshwater populations. One approach to refine predictions from these analyses is to include a third isotope to the more common two-isotope carbon and nitrogen mixing models to increase the power to resolve different prey sources. We compared predictions made with two-isotope carbon and nitrogen mixing models and three-isotope models that also included sulphur (δ34S) for the diets of Lake Ontario lake trout (Salvelinus namaycush). We determined the isotopic compositions of lake trout and potential prey fishes sampled from Lake Ontario and then used quantitative estimates of resource use generated by two- and three-isotope Bayesian mixing models (SIAR) to infer feeding patterns of lake trout. Both two- and three-isotope models indicated that alewife (Alosa pseudoharengus) and round goby (Neogobius melanostomus) were the primary prey items, but the three-isotope models were more consistent with recent measures of prey fish abundances and lake trout diets. The lake trout sampled directly from the hatcheries had isotopic compositions derived from the hatchery food which were distinctively different from those derived from the natural prey sources. Those hatchery signals were retained for months after release, raising the possibility to distinguish hatchery-reared yearlings and similarly sized naturally reproduced lake trout based on isotopic compositions. Addition of a third-isotope resulted in mixing model results that confirmed round goby have become an important component of lake trout diet and may be overtaking alewife as a prey resource.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Estimates of lake trout (Salvelinus namaycush) diet in Lake Ontario using two and three isotope mixing models |
Series title | Journal of Great Lakes Research |
DOI | 10.1016/j.jglr.2016.03.010 |
Volume | 42 |
Issue | 3 |
Year Published | 2016 |
Language | English |
Publisher | International Association for Great Lakes Research |
Contributing office(s) | Great Lakes Science Center |
Description | 8 p. |
First page | 695 |
Last page | 702 |
Country | Canada, United States |
State | New York, Ontario |
Other Geospatial | Lake Ontario |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |