The Goldilocks effect of lake size on within-population diversity in stickleback
Bibliographic record
Abstract
Abstract Many generalist species consist of disparate specialized individuals, a phenomenon known as ‘individual specialization’. This within-population niche variation can stabilize population dynamics, reduce extinction risk, and alter community composition. But, we still only vaguely understand the ecological contexts that promote niche variation and its stabilizing effects. Adaptive dynamics models predict that intraspecific variation should be greater in environments with two or more equally-profitable resources, but reduced in environments dominated by one resource. Here, we confirm this prediction using a comparison of threespine stickleback in 33 lakes in on Vancouver Island, Canada. Stickleback consume a combination of benthic and limnetic invertebrates, focusing on the former in small lakes, the latter in large lakes. Intermediate-sized lakes support generalist populations, which arise via greater among-individual diet variation, not by greater individual diet breadth. These intermediate lakes exhibit correspondingly greater morphological diversity, while genomic diversity increases linearly with lake size. These results support the theoretical expectation that habitats with an intermediate ratio of resources are “just right” for promoting ecologically relevant intraspecific diversification.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".