Individual variation in movement throughout the life cycle of a stream-dwelling salmonid fish
Bibliographic record
Abstract
Stream-dwelling fish populations have long served as important models of animal movement. Populations of adult stream-dwelling fishes are generally composed of a mix of relatively sedentary and mobile individuals. However, we do not know whether this pattern that we typically observe among adults is indicative of patterns of movement that occur throughout the life cycle. Therefore, we do not know whether we can apply these patterns to understanding or predicting processes such as migration and thus the potential for the evolution of genetic differences among populations. We test the general hypothesis that patterns of movement throughout the life cycle are consistent with patterns of movement inferred by indirect genetic methods and, more specifically, that the characteristics of the mobile fraction of the population are consistent with patterns of genetic differentiation. We used parentage analyses to infer the movements of alevin brook charr (Salvelinus fontinalis) in Freshwater River, Newfoundland, Canada, and a capture-recapture study of one cohort in this population to infer movement throughout the rest of the life cycle. We found that alevins move large distances shortly after emergence, primarily in the downstream direction, and that the population is composed of a mix of relatively sedentary and mobile individuals throughout all other intervals of the life cycle. In contrast, when we considered movements of individuals first captured as juveniles and eventually recovered as reproductively mature adults, we found relatively large and uniform distributions of net movement distance. Thus, heterogeneity in individual movement of adults is not representative of patterns of movement throughout the life cycle and therefore may provide only limited inference of population-level processes such as gene flow.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".