Distribution and Potential Spread of Japanese Knotweed (<i>Polygonum cuspidatum</i>) in Canada Relative to Climatic Thresholds
Bibliographic record
Abstract
Abstract Japanese knotweed (JK) is one of the most aggressive invasive plants known in the U.K., where its biology has been well-studied. It was introduced into Canada around 1900, but only recently has it become a serious concern in the province of British Columbia (BC). Climatic conditions, including annual degree days and mean-annual minimum temperatures at knotweed sites in British Columbia were modeled in BioSIM, using weather normals and long-term daily weather data, and compared to published thresholds (degree day = 2,505 DD, minimum temperature = −30.2 C, base temperature 0 C). The degree-day threshold was more limiting to JK in British Columbia than mean-minimum temperature (12.3% of province habitat was suitable for JK based on degree days compared with 26% for mean-minimum temperature). A new annual-precipitation threshold of 735 mm/year based on 95% of known knotweed sites in BC was identified. The best-fit logistic regression model included degree days and annual precipitation and predicted knotweed presence/absence with over 97% efficiency. Existing knotweed sites occupy just over half of the suitable habitat in BC, indicating there are still significant areas to be invaded. The limiting threshold for knotweed was reversed in Southern Ontario with between 35 to 53% of the habitat suitable based on minimum temperatures, whereas degree-day accumulations and annual precipitation were not limiting. Warmer temperatures from 2000 to 2008 resulted in an increase to 53% of the habitat in Southern Ontario being suitable for knotweed, compared to 35% when 1971 to 2000 weather normals were used. Different climatic thresholds among provinces might result in selection for different invasive knotweed genotypes. This could influence the success of biological control agents because of differential host suitability of knotweed genotypes. Habitat suitability maps generated will enable better targeting of knotweed surveys based on the risk of knotweed establishment.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".