Funders and donors from all walks of life find themselves in a pivotal moment. The flames have reached the front door, and there is a sense of urgency to invest in the now. How can philanthropy take a proven, systems-level approach to climate change-related disasters on the horizon? How can we pick each other up and ensure that no one gets left behind in the rebuilding processes currently underway?
Indigenous knowledge, which refers to the generations-spanning approaches and practices of a culture rooted in an advanced understanding of the local environment, is a crucial part of the answer. Many of GlobalGiving’s nonprofit partners are using this knowledge to reduce the vulnerabilities to natural disasters in their communities. We have much to learn from indigenous-led organizations, including these three that are protecting lives from the Americas to Indonesia.
- We don’t interact with our environment, we are the environment
- Building for the future requires traditional techniques
- Disaster preparedness as cultural practice
Rather than viewing the ongoing devastation of our environment as the “new normal,” imagine if philanthropy invested in proactively reducing community vulnerabilities. For too long, indigenous disaster risk reduction strategies have been passed off as inferior to modern science, even as billions of dollars are spent on disaster recovery each year. While all local contexts are different, studies have shown that integrating indigenous knowledge into disaster management can help to improve project performance, sustainability, and the community’s sense of ownership.
Now is the moment for funders to divert their attention to the indigenous-led approaches that have been proven to work at the intersection of environmental stewardship, mutual aid, and use of local resources. Managing the risks to our forests, our homes, and our environment will depend on a shift to include these missing links.
Read the full article about disaster risk reduction by Andrea Osorio at The Center for Disaster Philanthropy.