Quantifying seeds egested by field-collected earthworms: a dynamic and overlooked pool in forest soil seed banks
Bibliographic record
Abstract
Although awareness of the influence of earthworms on soil seed banks in Canadian forests is growing, there have been few direct field measurements. We used a novel pairing of field-collected earthworms from a central Great Lakes forest in Ontario with a laboratory seed egestion assay to obtain a snapshot of the number of seeds passing through earthworms compared with seeds found in the surrounding soil. We identified a pool of seeds egested by earthworms that accounted for 2.4% of all seeds found in the earthworms and the top 0–10 cm of soil. Individual earthworms contained 0–5 seeds. The large-bodied adult anecic non-native Dew Worm or Common Nightcrawler (Lumbricus terrestris) egested a disproportionate number of seeds for its abundance (50% of egested seeds from 17% of earthworms), but smaller earthworms were also an important source of egested seeds (the other 50%). This small-scale proof-of-concept study demonstrates a method of directly measuring earthworm–seed interactions in the field. It can also detect seeds egested by earthworms below ground that would otherwise be missed by other seed accounting methods and it highlights the importance of granivory by non-surface casting earthworms.
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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 | 0.001 |
| 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 | 0.000 | 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".