Onset of deep drainage and salt mobilization following forest clearing and cultivation in the Chaco plains (Argentina)
Bibliographic record
Abstract
[1] Semiarid sedimentary plains occupied by dry forest ecosystems often display low groundwater recharge rates and accumulation of salts in the soil profile. The transformation of these natural systems to rain-fed agriculture has led to raising water tables and a slow, but steady, process of groundwater and soil salinization in vast areas of Australia. In the semiarid plains of Chaco (central South America), unprecedented deforestation rates are taken place. Based on deep soil sampling (0–6 m) in seven paired stands under natural dry forest, rain-fed agriculture and pasture, with different age of clearance (>30 years, 20 and 3 years) in Salta, Argentina, we provide evidence of groundwater recharge increase and onset of salt mobilization in areas where forests were replaced by annual croplands. Soils with higher water and lower chloride content are evidence of deep percolation and salt leaching. In Salta, stands subject to 30 years of rain-fed cultivation had profiles with 30–46% higher moisture content and 94% lower chloride stocks compared to dry forest (0.05 ± 0.04 kg/m2 versus 0.77 ± 0.4 kg/m2). Estimates of groundwater recharge based on the displacement of chloride peaks suggested values of 27–87 mm yr−1 for agricultural soybean stands, and 10.4 mm yr−1 for pastures. While hydrological shifts in the regional groundwater system are poorly monitored and understood, our findings show that it is potentially sensitive to land use changes and to salinization processes.
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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".