SERVIR Applied Sciences Team Developing Tool to Evaluate Effectiveness of Forest Conservation in Mesoamerica

Although deforestation in Mesoamerica is a serious problem, resources available for protecting the region’s forests are limited. It is critical to ensure that existing resources are spent on effective policies.  However, conventional methods for assessing the effectiveness of conservation measures such as establishing protected areas and payments for environmental services are often inaccurate. A SERVIR Applied Sciences Team project led by Allen Blackman of Resources for the Future is developing a user-friendly web-based tool to help non-technical users conduct accurate evaluations using satellite data.

Protected areas (“parks”), a frontline conservation policy in Mesoamerica, provide a good example of the problem and the proposed solution. Conventional evaluation methods typically compare deforestation rates inside protected parks with deforestation rates outside and attribute the difference to the legal protections. But parks are usually located in remote places where deforestation rates are already low (Joppa and Pfaff 2009). Hence, the conventional approach to policy evaluation wrongly gives parks all the credit for their low deforestation rates, thereby dramatically overestimating their effectiveness. A similar story applies to community forestry, eco-certification, and payments for environmental services.

Over the past decade, a new, more rigorous method* has been developed for accurately evaluating such forest conservation policies.

“This method measures a policy’s effectiveness by comparing the rate of deforestation in areas affected by the policy to the rate in unaffected areas that are similar in terms of characteristics such as soil quality that drive deforestation,” explains Blackman. “In other words, this technique compares ‘apples-to-apples’.”

Unfortunately, the method’s complexity has precluded it from being widely adopted.

“It uses remote sensing deforestation data and incorporates statistical techniques to correct for the bias from conventional evaluation methods, but is data-intensive and requires technical expertise,” says Blackman.

The interactive web-based tool he and his colleagues are developing makes the new evaluation method more accessible to the non-technical user. All the required data is on-board and includes fine-scale GIS data on forest cover change and land characteristics that drive deforestation.  Examples of such factors are terrain, soil quality, population density, and distance to population centers.

Blackman and colleagues plan to (1) conduct workshops to train an initial set of key stakeholders to use the web-based tool, (2) create a virtual library of evaluations conducted with it, and (3) form a network of evaluators.

The Resources for the Future team hosted a workshop called “Decision Tools for Evaluating Forest Conservation Policy” on March 5, 2015, at Socio-Environmental Synthesis Center (SESYNC) headquarters in Annapolis, MD. Funded by SESYNC, the event’s objective was to garner expert feedback on the web tool.

Workshop participant Aaron Bruner, a Senior Economist at the Conservation Strategy Fund, had this to say: “I am very excited about the potential of what you are developing. Please let me know how I can support going forward.”

Blackman notes: “We hope our efforts lead to wider use of the new, improved policy evaluation method and ultimately to its increasing influence in choosing and implementing effective forest conservation policies in Mesoamerica.”

Notes:

*For more information, including a practical guide to this type of evaluation and a review of the literature using it, see: Evaluating forest conservation policies in developing countries using remote sensing data: An introduction and practical guide. Blackman and his colleagues are also developing a companion interactive web-tool called the Forest Conservation Targeting Tool (FCTT) to help Mesoamerican countries identify areas where forest conservation is most likely to yield the greatest benefits per dollar spent. Decision-makers can use that tool to quantify and visualize the returns expected from protecting specific forested regions and, based on that information, select the best areas for conservation.