Stanford explores new strategies against deforestation

Stanford explores new strategies against deforestation
Michelle Bhatia, Chief of Staff to the President — Stanford University
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Stanford researchers are working on new methods to reduce deforestation while increasing rural incomes. Their approach combines economic theory with practical trials to develop climate solutions.

In tropical regions, clearing forests for crops is often profitable for farmers in the short term. However, a Stanford team is exploring strategies to provide incentives for keeping trees intact without affecting farmers’ livelihoods. The research suggests tools like contracts that pay farmers based on the amount of forest they conserve and platforms that enable price transparency between farmers and buyers.

“This is about creating win-win solutions – approaches that are practical for farmers and effective for conservation,” said co-principal investigator Irene Lo, an assistant professor at the Stanford School of Engineering. “We’re finding that relatively simple changes to existing incentive structures can make a big difference.”

Traditional programs known as payment of ecosystem services (PES) require all forest on a farmer’s land to remain untouched in exchange for compensation. According to Lo and her colleagues, this approach often fails as many farmers find the terms too demanding.

“One of the most important priorities in nature conservation is to find ways to encourage landowners to conserve the biodiversity on their lands,” said project co-principal investigator Jim Leape, co-director of the Stanford Center for Ocean Solutions. “This research provides crucial insights into how to fashion incentives that work.”

Supported by Stanford Woods Institute’s Environmental Venture Projects program, researchers have designed PES contracts with payments scaled according to forest conservation levels—a simpler approach potentially increasing participation.

“Conditional contracts sound good in theory, but they’re often too stringent,” Lo said. “By offering payments that are proportional to conservation, we can encourage more farmers to engage and still achieve meaningful environmental benefits.”

The team also examines market forces in reducing deforestation by small-scale palm oil producers in Indonesia. Current supply chain inefficiencies push farmers toward quick cash from land clearing.

Research indicates platforms facilitating price transparency between farmers and buyers could improve incomes and profits while easing forest pressure. For instance, Pempem’s digital platform allows farmers access to daily prices from multiple buyers instead of relying on limited sources.

“These platforms offer dual benefits,” Lo said. “They help farmers secure better livelihoods and give buyers the information they need to make smarter sourcing decisions. That alignment of interests is key.”

Combining economic theory with supply chain management and field insights, graduate students play key roles in developing models based on interviews with Indonesian farmers.

Initial results have drawn interest from organizations like The Nature Conservancy and Pempem. Implementing these findings requires collaboration among researchers and organizations operationalizing payment schemes.

“Designing smart incentives is just the start,” said John Weyant, a professor at Stanford University. “The next challenge is making sure these ideas reach the people and institutions that can put them into action.”

Researchers plan further experiments testing incentive schemes within palm oil supply chains and integrating findings into broader climate models influencing deforestation rates and carbon emissions.

“This is one of those rare opportunities where smart policy design can deliver both economic and environmental gains,” Lo said.

Leape holds positions at both Stanford Woods Institute for the Environment and Stanford Doerr School of Sustainability; Weyant is also affiliated with Precourt Institute for Energy.

This story was originally published by Stanford Woods Institute for the Environment.



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