Fragmentation and patch size shape genetic structure of brook trout populations
Bibliographic record
Abstract
We tested the relative influence of habitat patch size and connectivity on genetic structure and effective population size in eight brook trout (Salvelinus fontinalis) habitat patches in a watershed in Virginia, USA. Variation at eight microsatellite loci in 2229 young-of-the-year brook trout for two successive cohorts (2010 and 2011) was examined. Genetic differentiation across all populations was pronounced. Overall [Formula: see text] was 0.397 (95% CI: 0.322–0.525) and overall FSTwas 0.124 (95% CI: 0.096–0.159). Above-barrier patch size had a strong positive relationship with genetic diversity, [Formula: see text], and genetic differentiation. Our analysis is consistent with greater extinction risk in smaller above-barrier patches. Larger above-barrier patches contained greater genetic diversity but reduced [Formula: see text] relative to adjacent below-barrier patches. The primary effect of barriers may be to reduce available above-barrier spawning habitat, even for larger above-barrier patches. Below-barrier patches also showed evidence of reduced genetic diversity and lack of connectivity. Genetic monitoring focused at gaining a broader understanding of the relationships here will be necessary to fully evaluate local extinction risks.
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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".