Long-term application of organic matter based fertilisers: Advantages or risks for soil biota? A review
Bibliographic record
Abstract
The addition of organic matter rich materials to agricultural soil is currently a common practice to improve its quality and fertility. However, the input of organic matter rich waste materials into soils significantly impacts ecosystem functions. The potential contamination of soil by various chemical compounds is one of the many risks that should be taken into account. Recent environmental studies have assessed the introduction of potentially hazardous compounds from pharmaceutical and personal care products, heavy metals, and other sources. This review summarizes knowledge concerning the influence of long-term soil fertilisation on soil biota, with special attention to soil nematodes. The interaction between fertilisers and soil organisms is highly complex. Nematode communities can be used as an ecosystem assessment tool to provide a holistic measure of the biotic and functional status of soils. However, extensive investigation of nematode interaction with the affected soil, and the physicochemical characteristics of the soil, should elucidate their role as one of the components in the feedback cycle controlling ecosystem processes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.001 | 0.001 |
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".