Agroforestry adoption and adaptation: A farmer-centric case study in Son La, Vietnam

Abstract

Agroforestry is promoted in northwestern Vietnam for enhancing environmental sustainability and supporting livelihoods, particularly in resource-constrained settings. By integrating trees into agricultural landscapes, agroforestry fosters beneficial economic and ecological interactions, offering a broad array of ecosystem services and environmental benefits. Despite these advantages, the adoption of agroforestry has not reached the level necessary to fully realize the potential benefits. This stagnation can be attributed to inherent uncertainties in agroforestry planning and implementation, which may pose risks for farmers considering its adoption. While research and development programs have concentrated on identifying and mitigating barriers to initial uptake, the adoption of agroforestry is recognized as a non-linear and dynamic process where farmers adapt practices based on their perceptions and circumstances. Using northwestern Vietnam as a case study, this dissertation investigates the multifaceted processes of agroforestry adoption, focusing on the dynamics influencing decision-making among resource-poor farmers and the implications for policy and practice. <br/> The research comprises four main studies, organized in four main chapters: <br/> • Chapter 2 integrates uncertainty into long-term benefit projections for agroforestry interventions by applying Decision Analysis and a probabilistic modeling approach. It reveals that while agroforestry offers promising long-term profitability, high upfront costs combined with uncertainties in discount rate, crop yields and prices significantly affect farmer preferences, often favoring annual monocultures over agroforestry. Addressing these knowledge gaps could enhance decision-making clarity for farmers and offer more targeted guidance for agencies promoting agroforestry adoption. <br/> • Chapter 3 examines the factors influencing agroforestry adoption decisions using an expert-informed Bayesian Network approach. It reveals a complex network of interrelated drivers, with markets and incentives playing a particularly strong role in shaping adoption. Through adoption pathway analysis, the study also explores the diverse trajectories farmers follow, highlighting the adaptive and non-linear nature of the adoption process. The findings underscore the importance of coordinated, holistic strategies, along with sustained support mechanisms that are responsive to farmers' evolving needs and decision-making contexts. <br/> • Chapter 4 employs Q methodology and systems thinking to explore farmers' perceptions and management decisions within the whole-farm context. The analysis reveals three dominant discourses among farmers regarding agroforestry and a shared mental model that reflects their systemic approaches to integrating agroforestry into farm operations. The study highlights the importance of understanding farmers' perspectives and reasoning processes deeply embedded in real-world contexts and offers insights that can inform innovation and policy development.<br/> • Chapter 5 adopts a participatory approach to develop a farm typology that differentiates farmers based on farm structure and agroforestry adoption behaviors. The study identifies three distinct farm archetypes, each characterized by specific constraints, opportunities and support needs related to agroforestry adoption. By combining these archetype profiles with insights gathered from participatory workshops, the study facilitates a more targeted understanding of farmer diversity. The work supports the design of context-specific strategies to address the varying needs of different agroforestry archetypes.<br/> This dissertation underscores the complexity of agroforestry adoption processes. Together, the four studies presented here offer strategic insights for designing support mechanisms that align with the dynamic and varied contexts of smallholder farmers in northwestern Vietnam.