Leafhoppers as vectors of phytoplasma diseases in Canadian berry crops: a review in the face of climate change
Bibliographic record
Abstract
Abstract Climate change has facilitated the introduction, establishment, and movement of invasive species in northern regions, enabling the colonization of previously unsuitable areas. While the responses of insects to these changes have been increasingly studied, our understanding of how such alterations impact trophic interactions still requires further research to make reliable predictions about the spread of diseases in a warming world. Phytoplasmas, a group of obligate parasitic unculturable Mollicutes, primarily rely on leafhoppers (Hemiptera: Cicadellidae) for transmission, spread, and survival. Phytoplasmas are associated with over 600 diseases affecting more than 1,000 plant species, including berries, grapevines, and other small fruits. In North America, diseases such as grapevine yellows, blueberry stunt, and strawberry green petal diseases have been linked to phytoplasma strains transmitted by known leafhopper species. However, the number of phytoplasma diseases has significantly increased in North America over the past decade, suggesting the presence of unidentified vectors or an abundance of leafhopper vectors. This short review provides an overview of the current knowledge on leafhoppers as vectors of phytoplasmas to berries, focusing on the last decade’s research in Canada. This paper also explores the potential implications of climate change on this pathosystem, including the anticipated range expansion of leafhopper species, changes in phytoplasma acquisition and transmission, and the risk of new leafhopper-transmitted plant-pathogen introductions through the arrival of new leafhopper species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".