Spatial and temporal variation in fish assemblages in three small unpolluted estuarine rivers and associated lagoons in Kouchibouguac National Park, southern Gulf of St. Lawrence, Canada
Bibliographic record
Abstract
Estuaries have among the highest primary production rates of ocean waters and provide essential habitat for many organisms. Recognition of the need to conserve these critical habitats is coupled with the need for baseline data to allow assessment of ecosystem changes. This study compares natural variations in, and correlations between, the composition of fish assemblages and environmental factors at several sites over two years in three rivers emptying into estuaries in the southern Gulf of St. Lawrence, Canada. Fish diversity and abundance were determined by beach seining and related to water temperature, salinity, substrate, and vegetation. From May to September 2000 (14 sites) and May to August 2001 (15 sites), 20 fish species were collected, seven of which accounted for 98% of the total catch. The dominant species, Mummichog (Fundulus heteroclitus), represented 44% of the catch. Its abundance and that of the other dominant species — Threespine Stickleback (Gasterosteus aculeatus) 16%, Blackspotted Stickleback (G. wheatlandi) 13%, Banded Killifish (F. diaphanus) 12%, Fourspine Stickleback (Apeltes quadracus) 7%, Atlantic Silverside (Menidia menidia) 4%, and Ninespine Stickleback (Pungitius pungitius) 2% — differed significantly both spatially and temporally. Multidimensional scaling analysis showed a spatial gradient in abundance from upstream to lagoon sites and a temporal gradient from spring to fall. Upstream sites were low in salinity and had a higher organic content and a higher proportion of silt–clay in the sediment. Variation within fish populations was related to site and seasonal changes in environmental conditions and species’ tolerance of water temperature, salinity, vegetation coverage, and fine sediments.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".