Priming of carbon decomposition in 27 dairy grazed soils after bovine urine additions
Bibliographic record
Abstract
Context Soil organic matter (SOM) plays a vital role in carbon (C) storage and agricultural sustainability. Additions of bovine urine to soils can cause positive priming of soil C decomposition and represents a pathway for SOM loss. However, data is limited to a few soils. Aims We investigated the priming response to bovine urine of 27 dairy grazed pasture soils from the North Island of New Zealand. Methods Soils from Allophanic, Gley, Recent and Brown soil orders were collected. 14C-labelled dairy cow urine was applied (1000 kg N ha−1) to undisturbed soil cores and carbon dioxide (CO2) fluxes measured (25°C) for 21 days. Urine applications were repeated, and CO2 measured for a further 21 days (25°C). Water was the control treatment. Key results CO2 fluxes rapidly increased after both urine additions by 86 ± 1% 24 h after the first urine addition, and 68 ± 4% after the second. Positive, negative and no priming were observed, and the mean absolute deviation of priming ranged between 200 and 1000 μg C g−1, and variability was greater after the second urine addition. Urine induced changes in pH and electrical conductivity (EC) had no effect on priming, and soil C contents were correlated to cumulative CO2, but not priming, and varied over time. Conclusions Factors affecting soil priming remain elusive and priming was highly variable within and between soil types. Implications The impacts of bovine urine on C pools requires further investigation to determine if, or when, urine patches are potential pathways for soil C loss.
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 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".