Mapping socio-environmentally vulnerable hotspots in the Volta Delta of Ghana
Bibliographic record
Abstract
BACKGROUND: Many Delta residents are dependent on climate-sensitive resources for their survival. Nonetheless, these resources are susceptible to climatic change and variability. The Volta delta of Ghana is severely impacted by sea-level rise resulting in flooding, salinisation and permanent loss of lands, with relentless social and economic consequences. However, vulnerability assessments in the Volta Delta have primarily focused on sea level rise, with limited attention to communities' susceptibility to adverse socio-environmental impacts. This study maps socio-environmentally vulnerable hotspots in the Volta Delta, employing methods incorporating residents, stakeholders and experts' opinions. METHODS: Vulnerability is conceptualised based on the Intergovernmental Panel on Climate Change (IPCC) climate risk and socioeconomic vulnerability framework. The framework defines vulnerability as a function of sensitivity and adaptive capacity. Through stakeholder engagements, community support systems sensitive to climate-driven stressors, referred to as sensitivity dimensions, were identified. Those that enhance local communities' ability to adjust and mitigate the impacts of climate stressors, termed adaptive capacity dimensions, were also identified. Indicators for quantifying the dimensions were also identified through stakeholder engagements. Data for the analysis were extracted from multiple sources including Census, Landsat imagery, national land surveillance and Google Earth. Geospatial statistical techniques were used to analyse and map socio-environmental vulnerability hotspots. RESULTS: The findings show that vulnerable communities were predominantly agrarian communities clustered along the intersections of the South Tongu, North Tongu, and Akatsi districts as well as the Dangbe West and North Tongu districts. Communities along the eastern coastline of Keta and Ketu South Municipalities and the Dangbe West District were the least vulnerable. The results also show, that although communities along the coastal lines of the Keta, Ada East and Ada West districts were highly vulnerable to sea-level rise, access to vibrant cross-country economic and industrial activities at the Ghana-Togo border and the capital city of Accra and the port city of Tema contribute to their low socio-environmental vulnerability. CONCLUSION: Socioeconomic ability, particularly access to alternative economic activities has the potential to mitigate vulnerability to environmental stressors. The findings direct the need for area-specific targeted and concerted interventions for strengthening the socioeconomic ability and adaptation capacity of the Volta Delta residents.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".