Integrating Biophysical and Socioeconomic Data to Inform Forest Landscape Restoration Decisions: Proof-of-Concept of a Prototype Decision Support Tool in Uganda
Forest landscape restoration (FLR) involves a complex set of practical decisions related to choice of objectives (e.g., carbon sequestration, biodiversity conservation, sustainable wood production, poverty reduction, employment creation), restoration methods (e.g., natural regeneration, tree planting), and forest types (native or non-native species, single or multiple species). The complexity of the decision problem is compounded by the fact that all of these aspects can, and typically do, vary by location across the landscape due to differences in biophysical and socioeconomic conditions. As the global community prepares to scale up efforts in the UN Decade on Ecosystem Restoration, it is important to support decision-makers with practical tools to assess the FLR options that strike the right balance across different objectives, methods, and needs, helping them to achieve objectives in cost-effective and sustainable ways.
It is critical for the sustainability of FLR efforts to link them to the livelihood needs of local populations and the development of value chains that generate economic returns for those populations, thus giving them a stake in the long-term success of those efforts. Sustainable value chains can also expand funding for FLR by leveraging private-sector investment.
Building on an existing collaboration among FAO, the Spatial Informatics Group (SIG), SilvaCarbon, NASA SERVIR, and researchers at Peking University and Duke University to integrate socioeconomic suitability and impacts into forest restoration planning through a FAO Open Foris SEPAL Decision Support Tool, this project aims to develop a prototype of a country-level spatial optimisation tool to inform on Forest Landscape Restoration (FLR). By integrating biophysical and socioeconomic data, this initiative will enable decision-makers to identify cost-effective, sustainable FLR options for achieving priority objectives, identifying solutions that maximize socioeconomic and environmental benefits while accounting for specific constraints.
Uganda was chosen for the prototype because it is a priority country for FLR, has data available on socioeconomic benefits from long-running projects, a well established relationship with FAO, and skills and expertise to partner with IIS and FAO in this endeavor. The new tool developed in Uganda will extend IIS’s Atlantic Forest tool in several important ways, in particular by incorporating a broader set of potential objectives (e.g., sustainable wood production in addition to carbon and biodiversity), regeneration methods (planting in addition to natural regeneration), and forest types (plan also included in the project.