Population structure in anadromous lampreys: Patterns and processes
Bibliographic record
Abstract
Population structure can reveal the diversity, gene flow, and dispersal of a species. This information can be used to make management decisions and reveal fundamental aspects of an organism’s biology. Distinct intrinsic (e.g., biological characteristics) and extrinsic (e.g., geographical and historical events, environment, human pressures) factors can influence population structure, with significant differences among species. However, detection of population structure in migratory lamprey species can be difficult to detect due to their lack of natal homing; this is particularly the case for anadromous lampreys, with their potential for wide dispersal at sea during their parasitic feeding stage. We review phenotypic and genetic markers, as well as the methods that have been used to assess population structure in lampreys, and discuss the relative strengths and limitations of each. Structure has been detected in several anadromous species using some of these methods, even without homing in these species, but we briefly contrast the weak population structure observed in anadromous species with the stronger structure observed in freshwater-resident lamprey species (particularly non-migratory brook lampreys). We relate lamprey population structure to species-specific ecological traits, such as juvenile dispersal tendencies, and provide case studies of six species. Delineation of appropriate management units in migratory lamprey species is important for conservation and 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".