Isotopic Structure of Lake Whitefish in Lake Huron: Evidence for Regional and Local Populations Based on Resource Use
Bibliographic record
Abstract
Abstract Lake Whitefish Coregonus clupeaformis is the most commercially valuable species in Lake Huron. The fishery for this species has historically been managed based on 25 management units (17 in Canada, 8 in the USA). However, congruence between the contemporary population structure of Lake Whitefish and management units is poorly understood. We used stable isotopes of carbon (δ13C) and nitrogen (δ15N), food web markers that reflect patterns in resource use (i.e., prey, location, habitat), to assess the population structure of spawning-phase Lake Whitefish collected from 32 sites (1,474 fish) across Lake Huron. We found large isotopic variation among fish from different sites (ranges: δ13C = 10.2‰, δ15N = 5.5‰) and variable niche size and levels of overlap (standard ellipse area = 1.0–4.3‰2). Lake Huron contained spawning-phase fish from four major isotopic clusters largely defined by extensive variation in δ13C, and the isotopic composition of fish sampled was spatially structured both within and between lake basins. Based on cluster compositions, we identified six putative regional groups, some of which represented sites of high diversity (three to four clusters) and others with less (one to two clusters). Analysis of isotopic values from Lake Whitefish collected from summer feeding locations and baseline prey items showed similar isotopic variation and established spatial linkage between spawning-phase and summer fish. Our results show that summer feeding location contributes strongly to the isotopic structure we observed in spawning-phase fish. One of the regional groups we identified in northern Georgian Bay is highly distinct based on isotopic composition and possibly ecologically unique within Lake Huron. Our findings are congruent with several previous studies using different markers (genetics, mark–recapture), and we conclude that current management units are generally too small and numerous to reflect the population structure of Lake Whitefish in Lake Huron. Received June 2, 2016; accepted October 3, 2016Published online January 3, 2017
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".