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Title: Poaching in Uganda : a crime science and systems thinking perspective
Author: Hill, Joanna Florence
ISNI:       0000 0004 7660 8901
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Poaching is problematic in many developing countries but tackling the problem is severely hampered by a lack of data and resources to develop cost-effective solutions. In particular, a key conservation concern is that anti-poaching rangers are unable to provide complete spatial and temporal coverage of protected areas, which means that much poaching activity goes undetected. This affects understanding of poaching activities and the effectiveness of strategies based upon them. Guided by theoretical and practical techniques from the fields of crime science and systems thinking, the purpose of this thesis is to explore how agent-based modelling (ABM) and data collected through qualitative methods can help to understand and prevent poaching. The core empirical chapters describe a series of discrete but interconnected research activities that start with the construction of a preliminary agent-based model intended to explore poaching activities, followed by an 18-month fieldwork project conducted in Uganda to develop the behavioural rules used in the model and to fill in gaps in the empirical record. Two different but complementary qualitative approaches were used with communities that interact with wildlife in Murchison Falls Conservation Area. The research included the completion of 13 focus groups and 26 one-to-one interviews, followed by the collection of data concerning environmental factors that influence poacher decision making using three novel qualitative mapping exercises (sketches, jigsaw maps, simulation map) with eight individuals who poach wildlife. Overall, the thesis provides new insights into the situational factors that influence poaching, including the role of preventers and promoters, the methods people use to locate poaching opportunities and avoid detection, and also the spatial and temporal factors that facilitate poaching. It then discusses how these new data can be used to develop future poaching models for theory and policy testing.
Supervisor: Johnson, S. ; Borrion, H. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available