Investigating birds as vectors of the nematode <i>Litylenchus crenatae</i> subsp. <i>mccannii</i> , the causal agent of beech leaf disease
Bibliographic record
Abstract
Abstract Beech leaf disease (BLD) is an emerging forest disease primarily affecting American beech ( Fagus grandifolia , Ehrh.) in North America. Tree mortality of sapling-sized trees has been observed within five to seven years of infection. The Litylenchus crenatae subsp. mccannii (Lcm) nematode is currently recognized as the major causal pathogen of BLD. Scientists first observed BLD in Ohio in 2012 and it has since spread and been detected in 15 states in the USA and one Canadian province. Understanding how this novel pathogen disperses is important for the development of management strategies and predictive models. The spread of BLD to new spatial areas may be due to the transportation of Lcm by animal vectors. We investigated birds as dispersal vectors of Lcm via ectozoochory (external) and endozoochory (internal). The ectozoochory objective was to determine if Lcm can be detected from ectoparasites and or feathers collected from wild birds caught in BLD areas. The endozoochory objectives were to determine if Lcm can be detected in the feces of wild-caught birds in BLD-infected areas, and if viable Lcm can be detected in feces from wild-caught birds kept in cages and fed Lcm nematodes. From 2021 to 2023 we collected 70 ectoparasite and feathers samples (ectozoochory) and 149 fecal samples (endozoochory) from 156 birds in areas in Ohio and Pennsylvania exhibiting BLD. We used molecular and microscopy methods to assess the presence of Lcm. Results confirmed Lcm presence in seven ectozoochory samples, and 14 endozoochory samples from six avian species: tufted titmouse ( Baeolophus bicolor ), black-capped chickadee ( Poecile atricapillus ), white-breasted nuthatch ( Sitta carolinensis ), dark-eyed junco ( Junco hyemalis ), American goldfinch ( Spinus tristis ), and downy woodpecker ( Dryobates pubescens ). These novel findings are among the first to detect plant parasitic nematode DNA in avian biological samples. The methods described in this manuscript could be applied to future BLD research as well as studies on animal vectors and forest pathogens. Understanding which bird species are vectors of Lcm will facilitate the creation of predictive models and develop preventative management strategies to protect uninfected American beech stands.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".