Ecohydrological effects of grazing‐induced degradation in the Patagonian Monte, Argentina
Bibliographic record
Abstract
Abstract Water‐limited ecosystems have undergone rapid change as a consequence of changing land use and climate. The consequences of these changes on soil quality and vegetation dynamics have been documented in different regions of the world. In contrast, their effects on soil water, the most limiting resource in these environments, have received less attention, although in recent years increasing efforts have been made to relate grazing, soil water and vegetation functioning. In this paper, we present the results of field observations of plant phenology and soil water content carried out during two successive years at four sites along a degradation gradient caused by grazing in the Patagonian Monte, Argentina. We also developed a simplified soil water balance model to evaluate how changes in plant cover could affect water balance. Our field observations showed that the soil water content in the soil layer where roots of grasses are abundant (0–25 cm) was higher and the growing cycles were longer in degraded than in preserved sites. Similarly, our modelling approach showed that the deep soil (depth > 10 cm) was wetter in the degraded than in the preserved situation. Simulation also suggested a switch from transpiration to a direct evaporation dominance of water losses with degradation. Although reductions in plant cover related to grazing degradation were associated with a decrease in annual transpiration, the simulated soil water loss by transpiration was higher during summer in the degraded than in the well preserved situation. Thus, our field observations seem to be a consequence of ecohydrological changes causing an accumulation of water in the soil profile during the cold season and its transpiration during summer. In conclusion, our results showed that changes in plant cover caused by grazing disturbance can alter the soil water balance, which in turn can affect vegetation function.
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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 | 0.001 |
| 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".