An innovative ‘Forest and Trees Toolkit’ for reducing malnutrition in Africa

Introduction

Malnutrition affects one in three people across the world and is the number one risk factor in the global burden of diseases. Inadequate intake of fruits and vegetables is a key component of low-quality diets, especially in Sub-Saharan Africa. Trees are a source of nutrient-rich fruits and leafy vegetables – and research shows that one promising solution to Africa’s malnutrition problem is to increase the planting of trees that provide nutritious fruits and vegetables.

Current Initiatives

Currently, many countries in Sub-Saharan Africa are adopting large-scale tree planting programs as a climate mitigation strategy and to improve local livelihoods. As such, trees can provide a triple-win solution for nutrition, conservation, and climate goals.

Challenges

However, the agencies and NGOs implementing these tree-planting programs often lack the necessary research and knowledge on which species to plant to maximize benefits for both the environment and people.

Project Overview

Here, we will develop a ‘Forest and Trees Toolkit’ that can be used by extension workers and NGOs to make more targeted tree planting programs that also optimize people’s nutrition – thereby creating triple-win outcomes for nutrition, conservation, and climate goals.

Toolkit Components

The toolkit will consist of:

1. A knowledge platform hosting information on nutritionally important tree species across areas and contexts.
2. An app to generate tree species portfolios adapted to local contexts.
3. A user manual on how to use the app, including information on how to do live tree portfolio demonstration plots in community areas so that farmers can adopt the trees on their own farms.

Expected Outcomes

In short, the toolkit will be able to identify location-specific combinations of tree species that address month-on-month harvest (fruits and vegetables) and micronutrient gaps in local households’ diets.

Data Foundation

The development of the toolkit will be based on a unique high-quality interdisciplinary dataset that we have collected and compiled during the ERC project FORESTDIET.