Forest health in the Anthropocene: the emergence of a novel tree disease is associated with poplar cultivation
Bibliographic record
Abstract
Abstract Plant domestication and movement are large contributors to the success of new diseases. The introduction of new host species can result in accelerated evolutionary changes in pathogens, affecting long-established coevolutionary dynamics. This has been observed in poplars where severe epidemics of pathogens that were innocuous in their natural pathosystems occurred following host domestication. The North American fungus Sphaerulina musiva is responsible for endemic leaf spots on Populus deltoides. We show that the expansion of poplar cultivation resulted in the emergence of a new lineage of this pathogen that causes stem infections on a new host, P. balsamifera. This suggests a host shift since this is not a known host. Genome analysis of this emerging lineage reveals a mosaic pattern with islands of diversity separated by fixed genome regions, which is consistent with a homoploid hybridization event between two individuals that produced a hybrid swarm. Genome regions of extreme divergence and low diversity are enriched in genes involved in host–pathogen interactions. The specialization of this emerging lineage to a new host and its clonal propagation represents a serious threat to poplars and could affect both natural and planted forests. This work provides a clear example of the changes created by the intensification of tree cultivation that facilitate the emergence of specialized pathogens, jeopardizing the natural equilibrium between hosts and pathogens. This article is part of the theme issue ‘Infectious disease ecology and evolution in a changing world’.
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 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".