Factors affecting colonisation success of the anecic earthworm Lumbricus terrestris (L.) in mesocosms on temperate pasture
Bibliographic record
Abstract
Changing precipitation patterns require climate adaptive measures to improve water regulation. Deep vertical earthworm burrows dug by the anecic species Lumbricus terrestris contribute to water infiltration rate and capacity, and deeper plant root growth. L. terrestris is considered a native species to western Europe, reaching its highest abundances in pastures. In pastures where the species is currently absent, water regulation could improve after inoculation with these earthworms. We conducted a field experiment to test the feasibility of introducing L. terrestris . Mesocosms were installed at two Dutch dairy farms. One farm had a resident L. terrestris population, the other did not. Subsequently, L. terrestris was introduced: half of the mesocosms received locally collected earthworms (NL), and the other half received commercially imported inoculum from Canada (CA). Twelve months later, the mesocosms were harvested and all earthworms were counted. The field experiment proved that L. terrestris can survive and produce offspring after introduction. At the location with a resident population, 15% of the L. terrestris introduced (tagged with Visible Implant Elastomer-tags) had survived, and at the L. terrestris -free site this was 26%. A hypothesised interspecific competitive relationship with Lumbricus rubellus (Hoffmeister) was not confirmed. Locally collected inoculum performed equal to or better than the commercial inoculum. Earthworm origin seems to influence chances of mesocosm colonisation success. VIE-tagging possibly interfered with survival. Future research could involve the role of pathogens and colonisation success in a non-enclosed set-up for a longer period of time.
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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".