Genotypic variation among<i>Gammarus fasciatus</i>(Crustacea: Amphipoda) from the Great Lakes - St. Lawrence River: implications for the conservation of widespread freshwater invertebrates
Bibliographic record
Abstract
We examined the population genetic structure of the amphipod Gammarus fasciatus (Crustacea: Amphipoda) over two years from a total of 11 sites within the Great Lakes - St. Lawrence River system using allozyme electrophoresis. In 1995, we examined differences within the St. Lawrence River (Cornwall to Quebec City), and in 1996, we focused on larger scale, whole-system differences from Lake Superior to Lake Champlain. We found very low levels of genetic differentiation among sites (Wright's FST< 0.03). This was not unexpected for an active disperser in a relatively contiguous system. However, we also found low levels of genetic variability within sites (Hobs= 0.07- 0.15), a result that was not anticipated. We surveyed the available literature on gammarid and other amphipods and found that limited genetic variability is characteristic of continuously distributed taxa, contrary to the expectations of current conservation theory. This is potentially of concern, especially in light of recently reported declines of G. fasciatus at several locations within the St. Lawrence River and Great Lakes. Given the importance of species such as G. fasciatus in aquatic food webs, further work is clearly needed on the consequences of population genetic structure to species' responses to novel environmental changes (e.g., exotic species introductions).
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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 | 0.001 |
| 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) | 0.000 | 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".