Analysis of farmer risk perceptions is usually limited to production risks, with risk perception as a function of likelihood and severity. Such an approach is limited in the context of the many risks and other important risk attributes. Our analysis of the risk perceptions of farmers extends beyond production risks, severity of the risks, and their likelihoods. We first characterize agricultural risks and identify their main sources and consequences. We then analyze risk perceptions as a hierarchical construct using partial least squares path modelling.

Although agriculture is the backbone of the African economy, it has faced considerable challenges in the past sixty years. Africa has moved from being a self-sufficiency continent before the 1960s, to net food importers, with a handful of countries facing severe food shortages from drought, desertification, climate change and wars. In this article, we use the case of Northern Ghana to explore some of the salient dynamics that have resulted in the current crisis in the African agricultural sector over time.

Guyana has densely populated coastal regions and relatively inaccessible Hinterland and is highly vulnerable to climate change and climate variability. The agriculture sector requires a transformation towards climate-resilient agriculture systems. In order to respond to this priority, the Alliance of Bioversity International and CIAT, the Ministry of Agriculture of the Government of Guyana and local partners, joined efforts to develop and implement a Caribbean Development Bank (CDB) financed project, ‘Development of a Framework for Prioritizing Climate-Smart Agriculture (CSA)’.

Agricultural systems in Southeast Asia are rapidly transitioning from subsistence-oriented to market-oriented agriculture. Driven by the highly complex and variable decision processes of individual farm households, these transitions have produced a diverse landscape mosaic across the region. Elucidation and characterization of underlying decision-making processes, and the factors that influence land use choices, are thus essential for sustainable land use planning.

Link to the full toolkit: https://bit.ly/Foresight_Training_Toolkit
The Foresight for Future Planning Training Series is a four-part training series for applying foresight to address climate change impacts and uncertainties. The training series equips users to practically apply a range of foresight tools and methods for innovative research in development prioritisation, specifically assisting in strateg ic planning and policy formulation for climate-relevant transformation in agriculture and food systems.

Food systems must provide adequate, healthy, and sustainable diets to the growing and changing population whilst responding to shocks and stressors related to climate variability, urbanization, globalization, conflicts, and economic change. This study examined the national food systems of Cambodia, Myanmar, and the Philippines and the local food systems of complementary Climate-Smart Villages: Chhouk, Htee Pu, and Himbubulo Weste.

The objective of the baseline study was to evaluate conditions in the Sedhiou and Tambacounda Regions of Senegal for the AVENIR project. The study entailed observation of key trends, a household survey, and analysis of the biophysical characteristics of the project area and challenges for agriculture. Thereby, the study identified key lessons learned and documented challenges for agriculture development.

The Climate-Smart Agriculture Profile for Khyber Pakhtunkhwa, Pakistan, provides an overview of the agriculture sector in the Province along with the major climatic and non-climatic challenges impacting its development. Climate projections are used to support an assessment of future hazards likely to impact crop and livestock production.

The Crop and Spatial Modeling activity was part of the project ‘Development of an Evidence-Based, Gender Equitable Framework for Climate Smart Agriculture Interventions,’ carried out under the Ministry of Agriculture and in collaboration with the International Center for Tropical Agriculture (CIAT), the Hydrometeorological Service of Guyana, and the University of Guyana. The project required geospatial vulnerability assessment and crop modeling research and extends previous climate change studies and vulnerability and capacity assessments regarding Guyana’s agricultural sector.

County Climate Risk Profiles are a key tool to guide climate smart agriculture (CSA) investments and priorities at the county level in Kenya. These documents provide analyses of the underlying causes of vulnerability and on-going and potential climate change adaptation strategies. They also provide a snapshot of the enabling environment for building resilience by providing a synthesis of the policy, institutional and governance context.

This working paper summarizes the findings of a portfolio review conducted to explore the gender and youth responsiveness of climate-smart agriculture technologies tested across climate-smart villages. The innovative and integrative aspect of the Climate-Smart Village (CSV) approach can provide useful insights into how to decrease the gender gap in the context of climate change.