Invasive Earthworms in the Crown of the Continent System and Implications for Land Management
Bibliographic record
Abstract
The United States contains invasive earthworms originating from Europe and Asia; the majority are European lumbricids. Direct introduction occurs primarily through human activity and, once established, earthworm populations are difficult to address. When exotic earthworms engage in bioturbation, they negatively alter subterranean food webs and nutrient cycling by disrupting soil layering systems. The most prominent form of physical alteration is the change and removal of the topmost organic layer. This disruption is associated with altered nitrogen and carbon cycling, as well as altered forest floor plant communities. The Crown of the Continent ecosystem is located in southwestern Alberta, southeastern British Columbia and northwestern Montana. This unique transboundary system is home to distinct biodiversity and is less altered by humans than many other ecosystems. The presence of exotic earthworms introduces new challenges for land managers and local soil systems. Current US policy offers an ineffective “innocent until proven guilty” attitude towards introduced species. Preventing spread and mitigating the effects of exotic earthworms is needed to preserve soil quality. Non-native earthworms and earthworm products could be banned and/or restricted by land managers to prevent further spread. Supplemental action, such as invasive species education programs, can enhance preventative practices.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".