By Greta Bindernagel, M. Trinidad Torres-Garcia, and Manuel Pacheco-Romero
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From landscapes to livelihoods: What we can learn from restoration projects worldwide
Ecosystem restoration is not only about bringing back plants, animals, and ecological functions, it should also be about supporting the people and communities who depend on, care for, and connect with these landscapes. While restoration is increasingly recognised as an important response to ongoing global degradation of nature, projects differ greatly in their approaches and outcomes. Understanding how some restoration efforts achieve wider benefits than others requires looking beyond environmental aspects alone and considering the social sphere in which restoration takes place.
We studied 30 restoration projects from around the world by collecting information on 58 characteristics, including their local context, the approaches and actions taken, and their outcomes across ecological, social, governance and economic dimensions. With a descriptive statistical analysis, we then grouped projects with similar approaches to identify common types and patterns and compared their broader contexts and outcomes.
Our findings highlight three important lessons. First, restoration needs to reflect local realities, including who has rights and responsibilities over land, existing power differences, historical inequalities, and the condition of the ecosystem being restored. Second, restoration is more successful when decision-making is flexible, inclusive, and involves local communities. Third, restoration should combine different forms of knowledge and actively consider fairness, ensuring that benefits and burdens are shared equitably.
There is no single recipe for successful restoration. However, our study shows that project types paying attention to both ecological and social dimensions are more effective, inclusive, and meaningful for people and nature. To support this, restoration initiatives need stronger long-term monitoring and consistent evaluation so that lessons can be learned and future efforts improved.
