Farmers’ Responses to Drivers of Forest Cover Change: The Case of Mae Chaem District, Thailand

Abstract

Empirical forest transition (shift from deforestation to reforestation) literature has historically struggled to establish a single universally-accepted forest transition “theory” due to various knowledge gaps hindering any efforts to do so. One such gap is the fact that very few studies have focused on how and why smallholder farmers respond to commonly accepted forest transition drivers, as well as how these responses impact forest cover and agricultural trends. Also, there remain many parts of the world where forest cover evolution has been insufficiently researched, as is the case of Mae Chaem district (Chiang Mai province, Thailand). Even though there are studies which claim forest loss occurred in the district between the 1990s and mid-2000s, there are few available records of forest cover evolution since then. To address these research needs, this thesis used secondary literature and spatial data, as well as semi-structured interviews and personal observations gathered during fieldwork in Mae Chaem district. It was first determined that forest cover in the district decreased between the 1990s and mid-2010s due to agricultural expansion. However, it appears that forest cover is expected to increase from 2016 to 2021 due to more strictly-enforced conservation measures set in motion by the Mae Chaem Model (a state-sponsored sustainable development model). These findings first suggest that the district might be currently in the early stages of a forest transition, its drivers being shifting forest policies and economic factors. Second, interviewed farmers resisted forest policies to optimize their crop productions before 2016, before beginning to develop more acceptant responses in early 2016 due to pressure from pro-conservation discourses and cognitive shifts regarding the value of protecting forest at the expense of agriculture. Also, farmers adopted ambiguous responses (motivated by their economic rationality) to pressure stemming from various economic factors, both prior and since 2016. With both environmental and socioeconomic issues deriving from these responses, the outputs from this study will hopefully help supplement existing forest transition studies on local populations responses to drivers of forest change. It is also expected to provide up-to-date information on existing and anticipated impacts of recent state development efforts, such as those deriving from the establishment of the Mae Chaem Model.