Characterization of Fungal Pathogens Associated with White Pine Needle Damage (WPND) in Northeastern North America
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Eastern white pine is a crucial ecological and economic component of forests in the northern USA and eastern Canada, and is now facing an emerging problem in white pine needle damage (WPND). It is still unclear whether WPND results from one, or the combination of several fungal pathogens. Therefore, the first objective of this study was to characterize the fungi associated with WPND in the northeastern United States and document the damage being done to mature eastern white pine as a result of repeated defoliation. To date, 22 species of fungi, either cultured from diseased pine needles or formed fruiting bodies on pine needles were identified based on morphology and sequence data. Lecanosticta acicola and a putative new species of Septorioides were the species most frequently recovered from diseased needles, in addition to needle cast fungi Lophophacidium dooksii and Bifusella linearis, two obligate fungal pathogens that were frequently observed on pine needles in the northeast, but have not been known to cause excessive defoliation of eastern white pine. A second objective was to monitor yearly the health of 63 pairs of healthy and unhealthy trees in eight affected locations throughout New England. Since 2012, affected trees are increasingly and repeatedly chlorotic and defoliated every year. Trees that were initially healthy are now exhibiting symptoms. While L. acicola appears to be the primary pathogen causing WPND, several other common needle pathogens are being more frequently observed and the role of climate change may be important in the disease ecology of WPND. These defoliation events, while once a sporadic occurrence, have now become more frequent as observed in continued crown deterioration of eastern white pine in long-term monitoring plots followed during the course of this three-year study.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it