A portrait of a sucker using landscape genetics: how colonization and life history undermine the idealized dendritic metapopulation
Bibliographic record
Abstract
Dendritic metapopulations have been attributed unique properties by in silico studies, including an elevated genetic diversity relative to a panmictic population of equal total size. These predictions have not been rigorously tested in nature, nor has there been full consideration of the interacting effects among contemporary landscape features, colonization history and life history traits of the target species. We tested for the effects of dendritic structure as well as the relative importance of life history, environmental barriers and historical colonization on the neutral genetic structure of a longnose sucker (Catostomus catostomus) metapopulation in the Kogaluk watershed of northern Labrador, Canada. Samples were collected from eight lakes, genotyped with 17 microsatellites, and aged using opercula. Lakes varied in differentiation, historical and contemporary connectivity, and life history traits. Isolation by distance was detected only by removing two highly genetically differentiated lakes, suggesting a lack of migration-drift equilibrium and the lingering influence of historical factors on genetic structure. Bayesian analyses supported colonization via the Kogaluk's headwaters. The historical concentration of genetic diversity in headwaters inferred by this result was supported by high historical and contemporary effective sizes of the headwater lake, T-Bone. Alternatively, reduced allelic richness in headwaters confirmed the dendritic structure's influence on gene flow, but this did not translate to an elevated metapopulation effective size. A lack of equilibrium and upstream migration may have dampened the effects of dendritic structure. We suggest that interacting historical and contemporary factors prevent the achievement of the idealized traits of a dendritic metapopulation in nature.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".