Assessing the biological relevance of aquatic connectivity to stream fish communities
Bibliographic record
Abstract
Recent advances in the ability to quantify longitudinal connectivity of riverine systems is enabling a better understanding of how connectivity affects fish assemblages. However, the role of connectivity relative to other factors, such as land use, in structuring biological assemblages is just emerging. We assessed the relevance of a structural connectivity index to stream fish communities at a relatively large scale (across five watersheds of Lake Ontario) while controlling for confounding habitat variables, such as land use, elevation, and stream topology. The results were assessed to determine whether species’ sensitivities to connectivity are in accordance with expectations of life history. Our results indicated that at large scales, structural connectivity explains significant amounts of variation in community structure (1% to 5.4% as measured by Bray–Curtis similarity), but remains secondary to other habitat components. Connectivity also was significantly related to abundance in three of the seven species assessed. The lower explanatory power of our models compared with studies done at smaller scales suggests that the relevance of connectivity to fish communities is scale-dependent and diminishes relative to other environmental factors at larger spatial extents.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".