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Microeconomic relationships between and among fishers and traders influence the ability to respond to social-ecological changes in a small-scale fishery
Ist Teil von
Ecology and society, 2017-06, Vol.22 (2), p.26, Article art26
Ort / Verlag
Ottawa: Resilience Alliance
Erscheinungsjahr
2017
Link zum Volltext
Quelle
PAIS Index
Beschreibungen/Notizen
Understanding the cross-scale nature of how natural resource trading links to local extraction patterns remains a topic of great relevance to stewardship and sustainable use of ecological systems. Microeconomic influences on a society’s pattern of small-scale natural resources utilization can exacerbate resource overuse, especially under increased population pressure. In many rural communities that are based on a limited diversity of resource industries, quantifying the response of extractors and traders to market and environmental fluctuations is critical to understanding management constraints. We examine the fishing practices of a small lake in Uganda, East Africa, from the dual perspectives of the traders and the fishers using a Bayesian Belief Network approach based on detailed interview surveys. Fishers in this small lake target Nile perch (Lates niloticus) and Nile tilapia (Oreochromis niloticus), two fish species of high commercial and food security significance in East Africa. We combined data on financial, social, and ecological systems to understand how aspects of trading quantitatively relate to fish extraction patterns in Lake Nabugabo Uganda. Importantly, we find that the patron-client type relationships generate incentives to extract specific fish, whereas “freelancer” independent fishers are able to create responsive and flexible extraction practices that match market and environmental fluctuations. Management of fishing administered by local Beach Management Units will likely have a higher probability of success when in synchrony with trading relationships and ecological dynamics. We use this study in Uganda to reflect on methodological challenges and opportunities of combining multiple types of data sets for cross-scale analysis of social-ecological system dynamics.