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CIFOR–ICRAF publishes over 750 publications every year on agroforestry, forests and climate change, landscape restoration, rights, forest policy and much more – in multiple languages.

CIFOR–ICRAF addresses local challenges and opportunities while providing solutions to global problems for forests, landscapes, people and the planet.

We deliver actionable evidence and solutions to transform how land is used and how food is produced: conserving and restoring ecosystems, responding to the global climate, malnutrition, biodiversity and desertification crises. In short, improving people’s lives.

Adaptive business model development for community-based peatland restoration in Riau

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Livelihood on peatland often involves unsustainable practices such as drainage and extraction, causing peatland degradation. Indonesia's peatland restoration approach therefore includes interventions for livelihood revitalization and transformation. This paper describes lessons learned in facilitating sustainable livelihood transitions for restoring peatland using the Sustainable Business Model for Communities (SBMC) canvas as a tool. We utilized Participatory Action Research (PAR) methods, where we engaged in intensive focus group discussions, surveys and facilitation of the action or implementation of the business model. SBMC is a useful tool that facilitates the community mapping their ideas and exercising collective action for restoring peatland while generating green business for the community groups in Siak Regency, Riau Province. Our finding suggests that to successfully transform peatland practices and restore ecosystems, a business model should balance economic motives with restoration objectives, enhance community collective action, improve transparency, and increase adaptability. Embracing uncertainty and complexity in community-based peatland restoration can provide an opportunity for learning and improving the community's business model. Viewing business model development as an iterative process enables the community group to revisit and refine their model in response to landscape adaptation.
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DOI:
https://doi.org/10.1088/1755-1315/1315/1/012053
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