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Abstract
Fishery research is useful in guiding conservation efforts and implementing quota restrictions based on assessments and simulations of the current state of stocks. Despite the availability of new approaches that account for environmental uncertainty and variability, policy design in small-scale fisheries still relies on a technical understanding of fish and fishermen populations alike (McIlgorm et al. 2010, Acheson and Wilson 1996, McGoodwin 1990). Ecosystem Based Fishery Models, Adaptive Management, and Socio-Ecological Systems perspectives often fail to incorporate the human dimensions of resource use and bottom- up behavioral approaches. In this dissertation, I study decisions about fishing efforts in a small tuna fishery in Ende, Flores, Eastern Indonesia through ethnographic (participant observation, semi-structure interviews, surveys), ecological (weather monitoring and coastal integrity assessments), and experimental tools (anthropometrics and probability judgment tasks). Relying on a socio-ecological and household-based approach, I use multilevel models, multivariate statistics and regression analysis techniques. My goal is to understand how environmental uncertainty influences fishing intensity and perceptions of catches, creating new behavioral responses that have consequences for the fishery as a whole. My objectives are to: 1) explore local narratives about luck and uncertainty; 2) describe the state of the stocks and present observational evidence to quantify statements of overfishing; 3) study decisions about fishing effort allocation taking into account the role of environmental uncertainty and its effects on the traditional moon cycle fishing calendar; and 4) characterize local perceptions of catchability and uncertainty and their impacts on fishing success. Results indicate that conservation policies need to: 1) understand the role of socioeconomic and environmental uncertainty in fishing effort and how it impacts household patterns of resource use before assuming that an area is overfished; 2) model individual decision making in terms of the economics of resource extraction and incorporate socio-environmental uncertainty to explain current level of fishing effort; 3) consider that fishermen can generate adequate representations that mimic probability distributions of ecological resources even when environmental probability is high; and 4) recognize that flexibility in strategies is a result of enabling structural responses in local communities that go beyond technical solutions.