Hydrological factors controlling the spread of common reed (<i>Phragmites australis</i>) in theSt. Lawrence River (Québec, Canada)
Bibliographic record
Abstract
:The spread of Phragmites australis between 1980 and 2002 was documented from seven series of aerial photographs and remote sensing images covering the Grandes Battures Tailhandier (Boucherville Islands, St. Lawrence River, Québec, Canada). Over the 23-y period, the colonized surface rose exponentially from 0.86 to 32.6 ha, corresponding to an 18% annual increase. This increase resulted mostly from vegetative growth, although the establishment of new colonies — most likely resulting from seed germination — allowed longer-range dispersion. Hydrological factors, especially the water level and duration of flooding over the growth season (July 1 to October 31) of the previous year, favoured the spread of colonies. Gains were highest the year following low water-level conditions and in a southerly direction, whereas they were reduced when plants grew at more than 1.5 m above mean water level or when they were flooded for more than 100 d during the previous growing season. The rate of surface colonization observed at Boucherville Islands was compared to that recorded at four other fluvial sites. Between Cornwall and Trois-Rivières, the noticeable increase in the number of colonized sites since 1980 suggests that low water levels in 1995, 1999, and 2001 favoured the establishment of colonies of P. australis along the shores of the St. Lawrence River.
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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".