Testing the impacts of invasive jumping worms at their northern range limit
Bibliographic record
Abstract
Earthworms can act as ecosystem engineers by altering soil structure, which impacts other organisms and ecosystem functioning. Jumping worms (family Megascolecidae) originating in Asia have been spreading in North America, extending their northern range limits to Ontario, Canada in the last decade and to New Brunswick in 2021. At the northern limits of their current range, little research has been done to examine the effects of jumping worms in these new habitats since their recent establishment. Our objectives were to evaluate: (1) how jumping worms impact soil nitrogen and soil carbon; (2) how their presence impacts the abundance of non-native European earthworms (family Lumbricidae); and (3) whether two sampling methods (i.e., mustard solution and wooden discs) are equally effective at detecting jumping worms. We sampled a residential property in Oromocto, New Brunswick, which was the first location where jumping worms were found in the province. Jumping worms did not have significant impacts on the abundance and biomass of European earthworms or soil carbon content in the top 5 cm of the soil, but they did significantly affect soil nitrogen levels. Both sampling methods were equally effective at detecting the presence of jumping worms. Further research is needed in managed landscapes, urban areas, and forests to determine the ecosystem impacts and invasion dynamics of jumping worms in Canada as this invasion progresses.
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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 | 0.000 | 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".