Integrating Remote Sensing and Positive Deviance to Identify Scalable Forest Conservation Practices in Northern Ghana

Area of Science:

• Environmental Science
• Forestry
• Rural Development

Background:

• Climate resilience is linked to forest cover, yet factors enabling forest retention in rural communities facing constraints are understudied.
• Understanding local conservation practices is crucial for effective climate change adaptation strategies.

Purpose of the Study:

• To identify and analyze locally embedded forest conservation practices in Northern Ghana using the Data-Powered Positive Deviance (DPPD) framework.
• To explore the social, institutional, and behavioral factors influencing forest cover change in rural communities.

Main Methods:

• Application of the Data-Powered Positive Deviance (DPPD) framework.
• Geospatial analysis using satellite-derived vegetation indices to identify high and low forest-cover change communities.
• Comparative analysis and qualitative fieldwork to explore socio-institutional factors.

Main Results:

• Communities with higher forest retention exhibited a 'golden mix' of practices.
• Key practices include economic utilization of tree products, integrating trees into land boundary demarcation, and functional community forest governance.
• These practices demonstrate how livelihood strategies and local institutions can enhance forest conservation.

Conclusions:

• The study identifies practical, locally driven strategies for forest conservation and climate resilience in semi-arid regions.
• Combining geospatial data with community insights offers a robust approach to discovering context-specific conservation solutions.
• Findings from Northern Ghana can inform similar initiatives in comparable environmental and socio-economic settings.