Association between biogeographical factors and boreal lake fish assemblages
Bibliographic record
Abstract
Abstract Five regions in insular Newfoundland Canada, comprising 152 lakes, were studied to identify associations between species composition (presence and absence), geographical location and environmental variables (pH, area, depth, alkalinity, secchi disc depth and shoreline development factor). Correspondence analysis and canonical variate analysis were used to distinguish regional patterns. Five biologically and environmentally distinct areas were identified. The degree of association between biological, environmental and geographical distances were contrasted using Mantel's test. Regional fish community structure was significantly correlated with large‐scale geographical distance but not with environmental parameters or small scale distance. It was proposed that large scale processes such as post‐glacial dispersion, climate and recent species introductions are important determinates in structuring regional fish assemblages. Differences in individual lake character were important determinates in intraregional variability in fish assemblage type. Sampling strategies for regional modelling and management are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 teacher head, 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".