What Occurs within the Mangrove Ecosystems of the Douala Region in Cameroon? Exploring the Challenging Governance of Readily Available Woody Resources in the Wouri Estuary
Bibliographic record
Abstract
Mangrove ecosystems provide key ecosystem services in coastal areas. This study describes the riparian mangrove of the Wouri estuary, in the Douala region (Cameroon), emphasizing the changes in this ecosystem over the past decade and its current state. It highlights the different groups of actors who participate in the management and regulation of the resource. Finally, an analysis of the governance of the mangrove wood resource based on the theory of common goods by Elinor Ostrom (1990) is proposed by examining the results obtained from the previous points. The scientific interest lies in contributing to a better understanding of the socio-ecological changes in the mangrove in the context of increasing anthropogenic pressures, highlighting the governance challenges and conservation opportunities in a strategic region of Central Africa. This research reveals complex processes that characterize mangrove ecosystems on the Manoka and Cap Cameroon Islands. The lack of urbanization regulations, continued infrastructure growth, repeated flooding, and coastal erosion all have a negative impact on natural landscapes and forests. The use of wood for smoking and fishing, as well as coastal pollution resulting from deficient garbage management, also have a considerable influence. Strategic interventions are needed to ensure sustainable ecosystem management. Recommendations include the application of rules to prevent forest overexploitation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".