My research examines how farmers navigate risk in the rapidly growing aquaculture sector in Sub-Saharan Africa, with a focus on Nile tilapia farming in Lake Victoria, Kenya. Aquaculture is inherently risky, shaped by volatile input markets, environmental shocks, and institutional gaps. Yet, how farmers perceive these risks often diverges from their actual financial exposure, creating inefficiencies that undermine both profitability and resilience.

In my recent research, I examined how farmers manage risk in Africa’s rapidly expanding aquaculture sector, with a focus on Nile tilapia farming in Lake Victoria, Kenya. Using surveys of more than 400 farmers, my research compares cage and pond systems to understand how risk perceptions shape management choices. Findings show that cage farmers, operating in capital-intensive, market-oriented settings, emphasize operational and market risks, while pond farmers, often subsidy-dependent, rank financial and climate risks higher. Despite these differences, farmers across both systems often misallocate resources, underinvesting in catastrophic ecological risks, such as fish kills, while overmanaging low-impact risks.

By combining econometric analysis and cost-effectiveness assessment, my work highlights where preventive strategies yield greater returns than reactive responses, and how better policies, financial tools, and extension services can align farmer behavior with economic realities. This research situates aquaculture within the broader economics of food systems, showing how risk, behavior, and institutions shape resilience and sustainability.

The quadrant plot above is one of the key results in my job market paper. Each point in this plot represents a risk source, plotted by its average management cost (x-axis) and average loss if unmanaged (y-axis). Each risk in pond and cage culture is labeled by a unique numeric ID corresponding to the adjacent reference key. Dashed lines represent the mean cost and mean loss across all risks in each system, dividing the plots into four quadrants. Risks in the top-left quadrant (high loss, low cost) represent high-priority targets for preventative intervention. Risks in the bottom-right quadrant (low loss, high cost) are economically unjustifiable. Risks in the top-right quadrant (high loss, high cost) are ideal targets for support as they are both expensive to manage with costly losses. Points are colored in pastel blue for ponds and pastel coral for cages. All costs data were collected from farm surveys in October/November 2024 and converted from KES to USD at a rate of 128:1 (2024 average exchange rate).

I integrate satellite data, machine learning, and field surveys to track the rapid growth of cage aquaculture in Lake Victoria and its ecological impacts. My research develops methods to classify cage farms from high-resolution imagery, monitor Harmful Algal Blooms(HAB), and link water quality conditions to economic and health outcomes. This brings a spatial systems perspective to food and water governance, connecting local livelihood risks with broader ecological processes.

I am developing methods that translate environmental risks in aquaculture into economic terms directly relevant to policy and community decision-making. Using production function approaches, I estimate the monetary value of livelihood losses resulting from degraded water quality, including reduced aquaculture yields and fisheries income. I also analyse the adaptation strategies households employ, relocating cages, diversifying income, or shifting fishing grounds, assessing their effectiveness and identifying vulnerable groups with low adaptive capacity. Finally, I evaluate the cost-effectiveness of monitoring systems, weighing the economic cost of inaction against the investment in proactive environmental management.