Footprints of drought in a montane grassland biome: a drought vulnerability index approach to drought conditions
Bibliographic record
Abstract
This study examines the impact of drought episodes during the summer and spring months on the socio-ecological livelihoods within the Maloti-Golden Gate Highlands. Given the increasing frequency and intensity of droughts worldwide, montane environments such as the Maloti remain under-researched despite their ecological significance. This study addresses this gap by utilizing MODIS-derived Vegetation Condition Index (VCI) retrieved from AppEEARS, specifically MOD13Q1 (2001–2020), alongside socioeconomic data obtained from Statistics South Africa (SSA) to assess drought vulnerability at a fine spatial scale. The results indicate a decreasing trend in precipitation over time, with 2015 being the driest year. Phuthaditjhaba was recognized as the most vulnerable region, closely followed by Kestell, due to demographic and economic factors. This study highlights the urgent need for localized drought mitigation strategies that consider environmental and socioeconomic components.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".