Preliminary identification of drivers and pathways of change in the Socio-Physical dynamics of the Western Indian Ocean Deltas
Bibliographic record
Abstract
<p>We present the output of a research combining field based, expert knowledge and remote sensing identification of the rates of change, pathways and drivers of these changes, during the past 35 years and more where possible, in four Western Indian Ocean River Deltas: Tana River and Delta (Kenya), Rufiji River and Delta (Tanzania), Limpopo River and Delta (Mozambique) as well as Betsiboka River and Delta (Madagascar). These findings are a set of preliminary results of the collaborative and multidisciplinary effort produced during the WIODER project () that brings together the National Museum of Kenya, Kenweb Kenya, University of Dar Es Salaam in Tanzania, University Eduardo Mondlane in Mozambique, Centre National de Recherches sur l'Environnement in  Madagascar, University of Southampton in UK, IHE Delft in the Netherlands, Institut de Recherches pour le Développement in France, and International Development Research Center in Canada and Kenya.</p><p>We highlight the similarities in the physical environment and, to some degree, also in the socio-economic-political environments that are leading the actual changes, affecting resilience of the local population and their sustainable development.</p><p>We focused on the substantial changes in the following aspects: precipitation seasonality and intensity, flooding patterns and frequency, land cover, dry forest cover, mangrove cover, crop production, soil erosion, fish population, human population, human migration flow, frequency of human conflicts within the delta population.</p><p>The IPCC foreseen changes in climate towards an aridification of the Southern Africa river basins and a wetter condition in the Eastern Africa region. Some signals of these climatic forecast are already recorded in both regions.</p><p>Assuming that these trends will continue for the next 10 years or so, we created and here we present two main scenarios of what will happen in these deltas: one with mainly climate change drivers, and another one with climate change and dam drivers.</p>
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".