Citizen Participation and the Effectiveness of Mangrove Protection Measures in Cameroon: A Multidimensional Analysis

Cameroon’s mangroves play a crucial role in coastal protection, carbon sequestration, and local livelihoods. However, they face rapid degradation due to deforestation, urbanization, and pollution. Despite existing conservation policies and Cameroon’s commitment to international conventions, their effectiveness remains limited due to institutional fragmentation and weak citizen participation. This study examines how citizen participation influences the effectiveness of mangrove protection measures, adopting a polycentric and multidimensional approach. Using a mixed-methods approach (surveys, semi-structured interviews, focus groups, and spatial analyses), we analyzed conservation dynamics in the Wouri and Kribi estuaries. Findings reveal that citizen participation is predominantly passive (79%), limiting the impact of environmental policies. Polycentric governance, involving cooperation among citizens, local authorities, NGOs, and international institutions, emerges as a key driver for strengthening conservation efforts. The study identifies several challenges: lack of institutional coordination, weak transparency, and insufficient economic incentives. To address these challenges, we propose an integrated framework combining participatory governance, community empowerment, and the valuation of ecosystem services. The adoption of sustainable financing mechanisms, such as payments for ecosystem services and ecotourism, would enhance local engagement and ensure effective mangrove management. This research highlights the importance of an inclusive and adaptive approach to achieving sustainable coastal ecosystem conservation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-19
DOI
https://doi.org/10.5281/zenodo.15266721
Primary Topic
Imbalanced Data Classification Techniques
Type
article
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article

Citizen Participation and the Effectiveness of Mangrove Protection Measures in Cameroon: A Multidimensional Analysis

Zenodo (CERN European Organization for Nuclear Research)
Imbalanced Data Classification Techniques
article

Citizen Participation and the Effectiveness of Mangrove Protection Measures in Cameroon: A Multidimensional Analysis

article en

Abstract

Cameroon’s mangroves play a crucial role in coastal protection, carbon sequestration, and local livelihoods. However, they face rapid degradation due to deforestation, urbanization, and pollution. Despite existing conservation policies and Cameroon’s commitment to international conventions, their effectiveness remains limited due to institutional fragmentation and weak citizen participation. This study examines how citizen participation influences the effectiveness of mangrove protection measures, adopting a polycentric and multidimensional approach. Using a mixed-methods approach (surveys, semi-structured interviews, focus groups, and spatial analyses), we analyzed conservation dynamics in the Wouri and Kribi estuaries. Findings reveal that citizen participation is predominantly passive (79%), limiting the impact of environmental policies. Polycentric governance, involving cooperation among citizens, local authorities, NGOs, and international institutions, emerges as a key driver for strengthening conservation efforts. The study identifies several challenges: lack of institutional coordination, weak transparency, and insufficient economic incentives. To address these challenges, we propose an integrated framework combining participatory governance, community empowerment, and the valuation of ecosystem services. The adoption of sustainable financing mechanisms, such as payments for ecosystem services and ecotourism, would enhance local engagement and ensure effective mangrove management. This research highlights the importance of an inclusive and adaptive approach to achieving sustainable coastal ecosystem conservation.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 75%
Imbalanced Data Classification Techniques
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