Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region
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Abstract
Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.
Study Area
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region |
Series title | Journal of Great Lakes Research |
DOI | 10.1016/j.jglr.2017.01.007 |
Volume | 43 |
Issue | 2 |
Year Published | 2017 |
Language | English |
Publisher | Elsevier |
Contributing office(s) | Great Lakes Science Center |
Description | 11 p. |
First page | 359 |
Last page | 369 |
Country | Canada, United States |
Other Geospatial | Great Lakes |
Google Analytic Metrics | Metrics page |