Life‐history variation along environmental and harvest clines of a northern freshwater fish: Plasticity and adaptation
Bibliographic record
Abstract
Plasticity, local adaptation and evolutionary trade-offs drive clinal variation in traits associated with lifetime growth. Disentangling the processes and determinants that cause these traits to vary helps to understand species' responses to changing environments. This is particularly urgent for exploited populations, where size-selective harvest can induce life-history evolution. Lake trout (Salvelinus namaycush) are an exploited fish with a life history adapted to low-productivity freshwaters of northern North America, which makes them highly vulnerable to ecosystem changes and overfishing. We characterized life-history variation across a broad and diverse landscape for this iconic northern freshwater fish and evaluated whether clinal variation was consistent with hypotheses for local adaptation or growth plasticity. We estimated growth-associated traits for 90 populations exposed to a diversity of environments using a Bayesian multivariate hierarchical model. We tested for clinal variation in their somatic growth, size at maturity and reproductive allocation along environmental gradients of lake productivity, climate, prey and exploitation clines under competing hypotheses of plasticity and local adaptation. Clinal life-history variation was consistent with growth plasticity and local adaptations but not harvest-induced evolution. Variation in somatic growth was explained by exploitation, climate and prey fish occurrence. Increased exploitation, from pristine to fully exploited conditions, led to increased somatic growth (from 32 to 45 mm/year) and adult life spans, and reduced age at maturity (from 11 to 8 years). Variation in size at maturity was explained by climate and, less certainly, prey fish occurrence, while reproductive allocation was explained by evolutionary trade-offs with mortality and other traits, but not environment. Lake trout life-history variation within this range was as wide as that observed across dozens of other freshwater species. Lake trout life histories resulted from evolutionary trade-offs, growth plasticity and local adaptations along several environmental clines. Presuming a plastic response, we documented ~1.4-fold growth compensation to exploitation-lower growth compensation than observed in many freshwater fishes. These results suggest that harvested species exposed to spatially structured and diverse environments may have substantial clinal variation on different traits, but due to different processes, and this has implications for their resilience and successful management.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".