Agricultural expansion into large forested and extensively-used areas, so-called forest frontiers, is a process with a long history and which is expected to continue in the future, driven by increasing global trade, affluence, and urbanization processes. A large part of this transition from extensive to intensive land use is taking place in montane areas where traditional “shifting cultivation”, the production of crops interspersed with long fallow periods, is being replaced with perennial plantations or annual crops aimed for export, also called cash crops. Agricultural transitions present important opportunities for rural development by raising household incomes, freeing up household labor, and enabling farmers to send their children to school. The construction of schools, as well as hospitals and other services, also hinges on the development of transport infrastructure, which in turn connects rural areas to regional and global markets. Such economic development can lift rural populations out of poverty, increase access to services, and expand the range of livelihood options. However, agricultural transitions can also have wide-ranging negative ecological and social implications. The loss of biodiversity in primary and secondary forests is compounded by the erosion, water pollution, and soil depletion that are frequently associated with intensive agricultural production. Land tenure regimes change from collective, shared, and informal, to private ownership associated with growing high-value crops. This process can result in an inequitable allocation of land, and in the emergence of a class of dispossessed persons in rural areas. The result can be a net loss of livelihood options, an increase in livelihood vulnerability, and a decrease in the ability to recover from shocks. The negative and positive outcomes frequently happen concurrently. When assessed at a local or regional level, rural areas are, on average, better off than before if they are better connected to services and markets, and average household incomes are higher. However, at the tail end of the income probability distribution are those who lose out. Agricultural transitions not only bring about vast socioecological changes, but frequently also happen abruptly in the form of so-called crop booms. Such booms are localized instances of very rapid agricultural expansion. The speed, abruptness, and intensity of change makes crop booms difficult to predict and understand. At the same time, it is precisely because of these characteristics that it is important to gain an understanding of these dynamics, since rapid change is known to compound negative socioecological outcomes. In northern Laos, the renewal of economic and political cooperation between Laos and China in the 1990s, coupled with new land use policies aimed at rural development and forest protection, as well as government-driven rural village relocations, created a conjuncture that has profoundly changed agricultural landscapes. The traditional system of shifting cultivation has been partially or entirely replaced by cash crop plantations in some areas, and rice production for household consumption has significantly decreased. Northern Laos’ Luang Namtha Province, bordering on China’s Yunnan Province, has seen a number of successive crop booms in the last decades, including the sugarcane boom in the late 1990s, the rubber boom starting around 2003, and the banana boom in 2011-2016. Importantly, these booms have largely been driven by smallholders and not by large scale agribusiness companies. Ethnic minority villages in these montane areas are seeing unprecedented levels of development and have now improved access to education, healthcare, and to larger and more distant markets. The reliance on cash crops for household income, which has been described as a dependence, makes households vulnerable to market volatility, especially if they rely on cash to buy food. However, prior to the advent of cash crops, traditional subsistence-oriented livelihoods were also subject to large risks and harvest failures. The aim of this work is two-fold. First, it aims to explain why crop booms happen. Second, it analyzes the impact of agricultural transitions on livelihoods. It focuses on two cases study areas and eleven villages in Luang Namtha Province. Empirical analysis is based on household surveys (n=110) and interviews with villagers, government officials, and investors, carried out between 2016 and 2017. Data collection focuses on household land use and socioeconomic trajectories since the late 1990s, and the reasons for those changes, including historical, institutional, economic, and biophysical. Within these spatial and temporal boundaries, this work aims to understand the causes of cash crop booms – with a focus on the rubber boom – and the implications of cash crop uptake on livelihood vulnerability. This work thus contributes to the field of Land System Science (LSS) by analyzing the dynamics and effects of land systems change. Chapter 2 uses a mix of qualitative and quantitative analysis to “tell the story” of the northern Laos rubber boom. The two case study areas under analysis underwent different trajectories of change. Whereas one experienced a full-fledged boom, rubber uptake was slower and lower in the other area, where other cash crops were planted as well, including cardamom, which is less lucrative but also less costly to plant. The comparison between the two case study areas offers insights about the triggers, drivers, and hindering factors that affected rubber adoption and expansion by smallholder farmers. By framing crop booms as land regime shifts, I explore the set of preconditions, triggers, and self-reinforcing factors that help explain the timing and the intensity of the boom. I focus on the decision-making processes underlying rubber adoption and expansion decisions. The household survey offers insight into the motivations for adoption and the influence of external factors, such as social relations and crop price information. The analysis is based, on the one hand, on descriptive statistics, for instance showing the proportion of the population that adopted rubber based on information versus imitation. On the other hand, it uses regression analysis to take into consideration, or control for, household characteristics and biophysical factors that affected rubber uptake. Chapter 3 is based on the insights generated in Chapter 2 and presents a more quantitative approach to the same question of rubber boom dynamics. Its aim is to elucidate the relative importance of drivers and hindering factors affecting rubber expansion, such as prices, imitation dynamics, accessibility, or protected area status. I define a price signal and a rubber conversion signal to represent the influence of commodity prices and imitation on land use decisions. I develop a model of land use change, which uses a probabilistic approach based on Bayesian Networks (BN), which allow the graphic representation of interlinked and correlated variables. In addition, regression analysis provides insights about such correlations, and about changes in relationships over time. Chapter 4 is focuses on livelihood vulnerability and explores the livelihood impacts of cash crop production compared to subsistence agriculture. A further aim is to analyze whether agricultural diversification reduces vulnerability, as is commonly proposed. The methodology applied is also based on a BN. BNs are well-suited for the analysis of risk and vulnerability because they quantify variables as probability distributions. Similarly, one way to quantify livelihood vulnerability is to analyze the probability distribution of a measure of well-being (e.g., income), in order to assess its mean and standard deviation, which influence how likely it is that a household will fall under a well-being threshold. By expressing all variables as probability distributions, this methodology allows to reflect “stressors” such as harvest failures or price drops. This is an innovative approach to measure household vulnerability, although the conceptual definition and calculation of vulnerability as a function of mean and standard deviation of a measure of well-being is not new. The model is run for different household types in both case study areas, comparing better off and poor households, as well as households with different levels of crop diversification. The limitations of this approach in terms of capturing the complexity of household vulnerability are discussed at length. Chapter 5 presents a discussion that goes back to the original questions: why do crop booms happen, and what is their implication for livelihood vulnerability. It analyzes crop booms as regime shifts but also as outcomes of relational processes, such as social relations and trade relations. It zooms in on the specific market dynamics that characterize crop booms, which are at the same time processes of agricultural and market expansion. The chapter also contrasts the findings from Chapter 4 with other work that has analyzed changing vulnerabilities in agricultural transition contexts. Finally, I discuss the suitability and the limitations of the methodology applied in the previous three chapters. Chapter 6 contains a reflection on the relevance of this work to society, including the research community and society at large. It also presents an outlook for future work – from low-hanging to exotic fruits – that could build on this research and address further questions. more...