Ecology, Evolution, and Conservation of Lake‐Migratory Brook Trout: A Perspective from Pristine Populations
Bibliographic record
Abstract
Abstract Reintroduction or rehabilitation plans for fish populations in many systems (e.g., lakes) are complicated by limited data on ecological and genetic characteristics before human disturbances occurred. While no two lakes have identical physical and biological characteristics, a growing body of empirical evidence nevertheless indicates that parallel patterns of population structuring may evolve within northern temperate fish species. Examining the population structuring in undisturbed lakes of similar physical and biological characteristics may thus provide insight into the probable historical extent and causes of both population structuring and connectivity in human‐impacted lakes. Here, we review research on the population structuring and evolution of migratory brook trout Salvelinus fontinalis in a relatively undisturbed, postglacial lake (Mistassini Lake, Quebec). We provide information on lake habitat use, the morphology and life history characteristics of populations, diets, lakewide genetic population structure, seasonal migration characteristics between spawning and feeding areas, population evolutionary histories, and the prevalence of lake spawning. The biology of Mistassini Lake brook trout has a compelling number of similarities with what is known about that of the “coaster” form in Lake Superior and lake‐migratory brook trout elsewhere. Our review also has several implications for the rehabilitation of coaster populations with respect to (1) clarifying the degree of natural connectivity between populations; (2) predicting the likelihood of recolonization of vacant habitats; (3) choosing candidate source populations for translocations; and more broadly, (4) understanding the spatial scale of probable local adaptation. Mistassini Lake therefore provides a useful case study that applies to lake‐migratory trout elsewhere. We hope that our research will stimulate managers and biologists working on similar systems with pronounced human disturbances to consider the interplay between ecology and evolution in future conservation efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".