The increasing population and changes in the climate in Africa demand a more sustainable approach to water usage for improved food and water security in the region. One of the key users of water, agriculture serves as the primary livelihood in Ghana, with a growing focus on cocoa production. To effectively implement sustainable water management strategies, it becomes imperative to conduct hydrological studies, including water balance components and water quality at sub-national and watershed scales. This would assist decision-makers in the proper planning and interventions for agriculture.

Livestock production in Tanzania remains overwhelmingly traditional, especially for ruminants, while domestic demand remains very much for products produced in traditional value chains. However, there are opportunities for upgrading value chains, especially in manufacturing leather and expanding productivity for milk and meat. Given the high potential climate impact of these livestock activities, it is important to understand their carbon dynamics and emission impacts.

This paper analyzes integrated crop-livestock farming systems in dryland regions of Senegal using household survey data and whole farm household modeling. It focuses on the Kaffrine and Thies regions, which exhibit differences in cultivated land area, staple crops grown, and livestock holdings. The analysis identifies region-specific opportunities to sustainably enhance productivity, resilience, and food security. The mechanistic model incorporates factors like crop mixes, livestock herd dynamics, climate impacts, economics, and labor to simulate entire farms.

The frequency and severity of extreme weather events are presenting substantial challenges to communities and nations worldwide. The already escalating impact of climatic hazards is expected to persist due to ongoing climate change. While strides have been made in enhancing forecasting capabilities and establishing early warning systems, global coverage remains inadequate, with just 40% of African countries reporting a multi-hazard early warning system in place as of 2022.

Inclusive landscape management (ILM) is a holistic approach to managing landscapes that considers the needs of all stakeholders, including local communities, indigenous peoples, and marginalized groups. This Inclusive Landscape Management Plan (ILMP) seeks to provide a framework for the sustainable management and development of landscapes in the Ahafo Ano Southwest District (AASWD) of Ghana.

This report is a comprehensive synthesis of insights, discussions, and recommendations stemming from Ukama Ustawi’s (UU’s), Learning Alliance's strategic session held during the Africa Day for Food and Nutrition Security (ADFNS) and the Comprehensive Africa Agriculture Development Programme (CAADP) Partnership Platform event in Zambia. The primary focus of the session was to explore practical strategies for operationalizing the Learning Alliance to achieve meaningful impact.

This study presents a comprehensive approach to developing an effective monitoring system for e- flow implementation in river ecosystems using high-resolution 3D modeling and modern sensor technology. The research focuses on the Limpopo and Incomati basins in Southern Africa.

The TAFSSA district food systems assessment aims to provide a reliable, accessible and integrated evidence base that links farm production, market access, dietary patterns, climate risk responses, and natural resource management in Bangladesh, India, and Nepal. It is intended to be a multi-year assessment. This data note summarizes data collected in March- April 2023 to describe what smallholder farmers are cultivating and what they do with the farm products produced. It is part of a pack of data notes that, together, provide a holistic picture of the food system in the district.

The importance of improving the FAIRness (findability, accessibility, interoperability, reusability) of research data is undeniable, especially in the face of large, complex datasets currently being produced by omics technologies. Facilitating the integration of a dataset with other types of data increases the likelihood of reuse, and the potential of answering novel research questions. Ontologies are a useful tool for semantically tagging datasets as adding relevant metadata increases the understanding of how data was produced and increases its interoperability.