Earthworm services for cropping systems. A review
Bibliographic record
Abstract
Intensive agriculture is often criticized for negative impacts on environment and human health. This issue may be solved by a better management of organisms living in crop fields. Here, we review the benefits of earthworms for crops, and we present techniques to increase earthworm abundance. The major points are the following: (1) Earthworms usually improve soil structural stability and soil porosity and reduce runoff. (2) Earthworms modify soil organic matter (SOM) and nutrient cycling. Specifically, earthworms stabilize SOM fractions within their casts, and they also increase the mineralization of organic matter in the short term by altering physical protection within aggregates and enhancing microbial activity. (3) The positive correlation between earthworm abundance and crop production is not systematic, and contrasting effects on yields have been observed. Earthworms induce the production of hormone-like substances that improve plant growth and health. (4) Direct drilling increases earthworm abundance and species diversity, but the beneficial effect of reduced tillage depends upon the species present and tillage intensity. (5) Organic amendments enhance earthworm abundance. (6) Earthworms feeding at soil surface are the most exposed to pesticides and other agrochemicals. Finally, we discuss how to combine management practices, including inoculation, to increase the earthworm services. We conclude that using earthworm services in cropping systems has potential to boost agricultural sustainability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".