Expanding agroforestry can increase nitrate retention and mitigate the global impact of a leaky nitrogen cycle in croplands
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The internal soil nitrogen (N) cycle supplies N to plants and microorganisms but may induce N pollution in the environment. Understanding the variability of gross N cycling rates resulting from the global spatial heterogeneity of climatic and edaphic variables is essential for estimating the potential risk of N loss. Here we compiled 4,032 observations from 398 published 15 N pool dilution and tracing studies to analyse the interactions between soil internal potential N cycling and environmental effects. We observed that the global potential N cycle changes from a conservative cycle in forests to a less conservative one in grasslands and a leaky one in croplands. Structural equation modelling revealed that soil properties (soil pH, total N and carbon-to-N ratio) were more important than the climate factors in shaping the internal potential N cycle, but different patterns in the potential N cycle of terrestrial ecosystems across climatic zones were also determined. The high spatial variations in the global soil potential N cycle suggest that shifting cropland systems towards agroforestry systems can be a solution to improve N conservation.
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.
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) | 0.000 | 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 it