Exploiting exotic pathogens as mycoherbicides against invasive alien weeds: Japanese knotweed as a case study
Bibliographic record
Abstract
Plant species have been introduced increasingly into non-native ranges, where many have become exotic weeds with adverse impacts on native ecosystems, as well as on farming and other livelihoods. In biological control, the classical or inoculative approach is the one most commonly used for the management of invasive alien weeds and is based on the use of co-evolved natural enemies from the native range to control the invasive weed. Typically, the inundative or mycoherbicide approach targets problematic weeds using local plant pathogens that, in the case of introduced species, have 'jumped' onto the exotic host. The leaf-spot fungus, Mycosphaerella polygoni-cuspidati, co-evolved with its host, Reynoutria (Fallopia) japonica (Japanese knotweed), in Japan and has a unique history of being investigated both as a classical biological control agent and a mycoherbicide against this highly invasive weed in the United Kingdom and North America. Here, we highlight our research on M. polygoni-cuspidati as part of a biological control programme for Japanese knotweed and review the potential of mycoherbicides using exotic pathogens for the management of invasive alien weeds. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".