Beyond GDP: Integrating the Total Economic Value of Wetland and Forest Ecosystem Services into Rwanda’s National Accounting System

Rwanda’s wetlands and forests deliver crucial socio-economic and environmental value, especially in building climate resilience and supporting livelihoods. Still, most of their macroeconomic contribution is omitted from national metrics like GDP, leading policies to focus on immediate economic returns, often to the detriment of these important natural infrastructures. To bridge this gap in measuring natural capital, we developed, established, and launched the Rwanda Integrated Valuation Framework (RIVF). This framework was developed and built by our research team to estimate the economic value of four large wetlands and six forests in Rwanda. Following UN SEEA protocols, our approach combines biophysical modelling with primary socioeconomic information. Our primary data was collected directly by our research team in a stratified random household sampling (n = 3,976). We applied Google Earth Engine with spatial data and utilised three InVEST 3.12.0 models (water yield, carbon storage, sediment delivery ratio) to model regulating services, while monetising social data through market and replacement cost methodologies. The study was officially approved by the National Council for Science and Technology (NCST) and the National Institute of Statistics of Rwanda (NISR) Research Visa Permit No. 0532/2024/10/NISR and follows ethical protocols. Estimates show that regulating services alone are worth more than 90% of the total annual value, with an aggregate value ranging between 386 and 545 billion RWF annually. Failing to capture the importance of these indicators could potentially contribute to unproductive economic growth in some key areas of Rwanda. Our results call for the formal inclusion of the estimates in macro-fiscal indicators as a means of advancing Rwanda’s Vision 2050, and eventually, in the medium- to long-term, transitioning towards a real-time National Ecosystem Intelligence System (NEIS) that is underpinned with convergent GeoAI and Internet of Things (IoT).