Although tropical deforestation in Mesoamerica continues to have severe environmental impacts, the human, financial, and technical resources available to curtail it are limited. Therefore, it is critically important that the resources we deploy are spent on policies that are effective. Unfortunately, however, credible evidence on policy effectiveness is quite scarce. We know little about whether and under what conditions community forestry, eco-certification, payments for environmental services, and other leading policies actually stem deforestation. A key reason is that the conventional approach to evaluating these policies is flawed and tends to generate overly optimistic results. Over the past decade, a new, more rigorous approach has been developed that relies on remotely sensed deforestation data along with statistical techniques that correct for the bias from conventional methods. Yet uptake by policymakers has been slow because this approach is data intensive and requires technical expertise. To overcome these barriers and to grow the evidence base on conservation policy effectiveness, the proposed project aims to:
- compile the requisite fine-scale spatial data for all of Mesoamerica;
- build a first-ever computational tool for evaluating forest conservation policies that is freely available, web-based, user-friendly, and that has the aforementioned data on-board;
- conduct a series of workshops to train an initial set of key stakeholders to use the tool; and
- build a virtual library of evaluations conducted with the tool, and a network of evaluators.