Integrated agroforestry system affects the dynamics of inorganic phosphorus fractions in the savanna of Brazilian Northeast
Bibliographic record
Abstract
The savanna (Cerrado) of northeastern Brazil has undergone significant transition in land use to expand agricultural activities. In this region, soils are highly weathered, with phosphorus (P) commonly bound to aluminum (Al) and iron (Fe), creating conditions that demand the supply of P fertilizers to build soil fertility. Conservation systems, such as integrated agroforestry, can increase the inorganic P lability. The aim of this study was to evaluate soil P availability in components of an integrated agroforestry system. Four systems were studied from a 3-year experiment: eucalyptus ( E. urophylla × E. tereticornis) rows (ER), sabiá ( Mimosa caesalpiniifolia) rows (SR), inter-planted maize, and inter-planted soybean in addition to an area of native Cerrado (NC) used as a control. Inter-planted soybean and maize components showed an increase in available P in relation to NC, as a response to a liming-induced increase in soil pH and phosphate fertilization. Eucalyptus and sabiá row components showed an increase in available P in soil because of higher P recycling promoted by forest species and lower P adsorption onto Fe and Al due to the high concentrations of organic matter. Phosphorus forms, following a descending order for all components of the agroforestry system, are P–Al > P–Fe > P–Ca. This information can be used to improve management and soil quality of agricultural production in the Cerrado of the Brazilian northeast region.
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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 | 0.000 | 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) | 0.001 | 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".