Sustainability implications of Rwanda’s Vision 2050 long-term development strategy

Abstract

Improving livelihoods in Rwanda requires overcoming food insecurity and malnutrition. Vision 2050 is Rwanda’s long-term development strategy, yet little is known about its potential trade-offs for the country’s biodiversity, forest cover, and greenhouse gas (GHG) emissions. Scenario analysis can provide insights into how to achieve such goals more sustainably. Here, we use the Food, Agriculture, Biodiversity, Land-Use, and Energy (FABLE) Calculator, a simple integrated assessment tool, to explore potential sustainability implications by 2050 through two scenarios: (1) Current Trends and (2) Vision 2050. The Vision 2050 pathway incorporates components of the government’s long-term development strategy and associated national agricultural policy targets. It includes greater increases in crop productivity and decreases in post-harvest losses, and shifts to more sustainable diets, compared to the Current Trends pathway. Results show that the Vision 2050 pathway would, relative to Current Trends, lead to a greater decrease in agricultural land area and an increase in non-forested natural land-cover area, with consequent decreases in GHG emissions from agriculture, increases in carbon sequestration, and increases in the share of land that can support biodiversity conservation. Shifts to a healthier diet in the Vision 2050 pathway would only be compatible with national agricultural priorities if these diets favor consumption of foods that underpin sustainable livelihoods in Rwanda, such as beans, cassava, potatoes, sweet potatoes, banana, and corn. We discuss the potential for integrated land-use planning and adoption of agroecological farming practices to help Rwanda achieve food security, livelihood, biodiversity, and climate mitigation goals in tandem.

Integrated modeling to achieve global goals: lessons from the Food, Agriculture, Biodiversity, Land-use, and Energy (FABLE) initiative

“…In all countries, restoring more land to nature requires reducing the area used for other purposes, principally agriculture. FABLE's work shows that the best strategies for achieving this are shifting diets toward less land-intensive foods, and increasing crop and livestock productivity, freeing up land for restoration (Frank et al 2022;González-Abraham et al 2022;Jha et al 2022;Lehtonen and Rämö, 2022;Navarro Garcia et al 2022;Perez-Guzman et al 2022;Rasche et al 2022;Smith and Harrison et al 2022;Zerriffi et al 2022). Of note, some restoration efforts to date have promoted single or exotic species which do little to restore native ecosystem functioning.…”

Data-Driven Analysis and Machine Learning-Based Crop and Fertilizer Recommendation System for Revolutionizing Farming Practices

“…First, the system selects the major crops cultivated in Rwanda, such as maize, potatoes, beans, tomatoes, coffee, cassava, sweet potatoes, sorghum, onion, kidney beans, and banana. The selection criteria are based on familiarity with Rwanda's agricultural system, sustainability concerns, and empirical evidence from previous studies [45,46]. This process results in a comprehensive crop data collection relevant to the study objectives.…”