A fuzzy logic approach to spatial management of small-scale fisheries

• Main Author: Teh, Lydia Chi Ling
• Language: English
• Published: University of British Columbia 2011
• Online Access: http://hdl.handle.net/2429/39836

Fishers are an integral part of the marine ecosystem; where and how fishers allocate their fishing effort can directly affect biological outcomes. Nonetheless, the human dimensions of fisheries are often not well understood, even though the ability to anticipate fishers’ response to spatial regulations is a key aspect of successful management. My thesis addresses this challenge by developing a marine spatial management tool that balances both human and conservation variables. I conduct an empirical investigation of small-scale fishers’ spatial use patterns with the aim of understanding how fishers’ preferences and perceptions of the marine environment affect their selection of fishing locations. I find that fishers tend to fish within preferred resource spaces that are bounded by the extent of their mental maps, and that are always considered to be safe. I integrate fishers’ preferences in a fuzzy logic expert system that I develop for zoning marine spaces in data poor conditions. This system, the protected area suitability index (PASI), assesses the suitability of a site for being protected from fishing by balancing fishers’ preference for the site with the site’s conservation value. Sites that are considered to be highly suitable for protection are those that have low fisher preference and high conservation value. The PASI estimates site suitability scores that range from 0 to 10, where 10 indicates that a site is very suitable for protection. I applied the PASI in a case study of a proposed marine protected area in Sabah, Malaysia. At least 58% and up to 75% of the time, the PASI’s assessment of site suitability matched a zoning plan for no take areas that was designed through a collaborative community process. This demonstrates that the PASI is appropriate for conducting rapid site prioritisation in data poor regions of the world, and can be used as an alternative to data, time, and financially demanding spatial planning methods.