Non-native earthworm influences on ectomycorrhizal colonization and growth of white spruce
Bibliographic record
Abstract
Exotic earthworms are entering previously uninhabited soils of boreal forests, their invasion largely facilitated through human activities. As ecosystem engineers, earthworms are capable of causing dramatic changes in above- and belowground forest composition, but whether they have the same effects in all forests remains unclear. Forest compositional changes caused by earthworms may be mediated by interactions between earthworms and mycorrhizal fungi. Specifically, tree seedling growth may be altered by the presence of exotic earthworms and their subsequent impact on mycorrhizal fungi. In this study, we investigate the effects of exotic earthworms on ectomycorrhizal colonization and seedling growth of the conifer Picea glauca (white spruce) in gray luvisolic soils from the Boreal Plains. Anecic Lumbricus terrestris and epigeic Dendrobaena octaedra earthworms were added to mesocosms each containing a white spruce seedling in a greenhouse experiment. Impacts on the composition of ectomycorrhizal fungi in the mesocosms were determined using a combination of morphological and molecular techniques, and effects on seedling growth were assessed through above- and belowground measurements. The proportion of ectomycorrhizal root tips and ectomycorrhizal community composition did not vary as a function of earthworm species or density. Similarly, exotic earthworms had no significant effect on spruce seedling growth or survival.
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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 | 0.000 | 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) | 0.001 | 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".