Silent invaders: the hidden threat of asymptomatic phytobiomes to forest biosecurity
Bibliographic record
Abstract
Populations of diverse, unknown, and potentially pathogenic fungi and fungus-like organisms are continuously introduced into new locations via asymptomatic infections (e.g. as endophytes or latent pathogens) within internationally traded live plants. Interactions between these asymptomatic fungi and novel recipient host trees can be unpredictable, and urban introductions may act as bridgeheads into natural and managed forests. Historical examples of novel, highly destructive forest tree diseases highlight the potential threat of this pathway. As the trade in live plants continues to expand, the likelihood of high-impact incursions increases. This has led to calls for more proactive management, including more stringent treatment and regulatory standards, and even the phasing out of trade in plants determined to be an untenable risk to forest ecosystems. In this review, we discuss how biosecurity systems should consider advances in understanding the diversity and ecology of phytobiomes associated with asymptomatic plants and what measures can be considered to reduce this threat to global forest health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".