Response of Soil Mesofauna to Long‐Term Application of Feedlot Manure on Irrigated Cropland
Bibliographic record
Abstract
Long‐term application of feedlot manure to cropland may influence soil mesofauna. These organisms affect the health, structure, and fertility of soils, organic matter decomposition, and crop growth. The objective was to study the long‐term (16–17 yr) influence of feedlot manure type and bedding on soil mesofauna over 2 yr (2014–2015). Stockpiled or composted feedlot manure with straw (ST) or wood‐chip (WD) bedding (plus unamended control) was annually applied (13 Mg ha −1 dry wt.) to an irrigated clay loam soil with continuous barley ( Hordeum vulgare L. ). Intact cores were taken from surface (0–5 cm) soil in the fall, and the densities of Acari (mites) suborders and Collembola (springtails) families were determined. Manure type had no significant ( P > 0.05) effect on soil mesofauna density. In contrast, there was a significant two‐ to sixfold increase in density with WD‐ compared with ST‐amended soils of total Acari in 2014 and 2015, as well as total Collembola, total Acari and Collembola, oribatid mites, and entomobryid springtails in 2014. The bedding effect was attributed to significantly greater soil water content and lower bulk density for WD than ST. Density of soil mesofauna was not significantly greater in amended soils than in unamended soils. A shift by feedlot producers from stockpiled to composted feedlot manure application should have no effect on soil mesofauna density, whereas a shift from ST to WD bedding may increase the density of certain soil mesofauna, which may have a beneficial effect on soil. Core Ideas Manure type had no influence on soil mesofauna. Bedding material had a significant influence on soil mesofauna. Soil mesofauna densities were greater for wood‐ than straw‐amended soils. Bedding effect was due to greater soil water content and lower bulk density. Soil mesofauna density was not greater for amended than unamended soils.
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) | 0.000 | 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) | 0.000 | 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".