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Forster, Johanna 
ORCID: https://orcid.org/0000-0001-6729-9965, Turner, Rachel, Fitzsimmons, Clare, Peterson, Angelie, Mahon, Robin and Stead, Selina
(2017)
Evidence of a common understanding of proximate and distal drivers of reef health.
Marine Policy, 84.
pp. 263-272.
ISSN 0308-597X
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Abstract
Marine management has typically prioritised natural science methodological traditions as an evidence base for decision-making; yet better integration of social science methods are increasingly shown to provide a more comprehensive picture to base management decisions. Specifically, perceptions-based assessments are gaining support, as they can provide efficient and holistic evaluation regarding management issues. This study focuses on coral reefs because they are particularly threatened ecosystems, due to their ecological complexity, socio-economic importance, and the range of environmental drivers that impact them. Research has largely concentrated on assessing proximate threats to coral reefs. Less attention has been given to distal drivers, such as socio-economic and governance factors. A common understanding of threats related to coral reef degradation is critical for integrated management that takes account of peoples’ concerns. This study compares perceptions of drivers of reef health among stakeholders (n = 110) across different sectors and governance levels, in four Caribbean countries. Interview data identified 37 proximate and 136 distal drivers, categorised into 27 themes. Five sub-groups of themes connecting proximate and distal drivers were identified. Perceptions of two of these narratives, relating to ‘fishing and socioeconomic issues’ and ‘reef management and coastal development’, differed among respondents from different countries and sectors respectively. However, the findings highlight a shared perception of many themes, with 18 of the 27 (67%) mentioned by > 25% of respondents. This paper highlights the application of perceptions data for marine management, demonstrating how knowledge of proximate and distal drivers can be applied to identify important issues at different context-specific scales.
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