Lin, Mingli; Liu, Mingming; Ma, Heidi; Turvey, Samuel T; Li, Songhai; (2024) Using local ecological knowledge to inform regional conservation prioritization for threatened marine megafauna. Ocean and Coastal Management , 255 , Article 107268. 10.1016/j.ocecoaman.2024.107268.

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Abstract

Due to high costs and time constraints, it can be difficult for traditional fieldbased methods to acquire sufficient data to identify priority species or areas in marine conservation planning. Local ecological knowledge (LEK) is increasingly used as an important source of information for evidence-based management strategies, but its usefulness for informing conservation prioritization for threatened marine species has rarely been assessed. Here, we conducted the first range-wide systematic survey of five marine megafauna (Indo-Pacific humpback dolphin, Indo-Pacific finless porpoise, dugong, whale shark, sea turtles) using interviews with fishers in the northern South China Sea (SCS), one of the richest marine biodiversity hotspots in the world, to assess the ability of LEK to highlight priority species and areas for conservation. Our results reveal that the dugong has become functionally extinct in China, while the Indo-Pacific finless porpoise, whale shark, and sea turtles have all experienced more severe declines compared to the Indo-Pacific humpback dolphin. Based on the sighting histories of these threatened species, regional conservation priorities and management activities should therefore focus on reducing disturbance pressure in the Beibu Gulf and eastern Guangdong for the Indo-Pacific finless porpoise and in eastern/southern Hainan Island for the whale shark and sea turtles. These findings challenge current conservation strategies that prioritize the Indo-Pacific humpback dolphin in the SCS, suggesting that coastal dolphins might not be good indicators of the population trends of sympatric marine megafauna. While LEK cannot provide precise abundance and habitat data for highly threatened marine species, we demonstrate that it offers comparable long-term population trend and wide-scale distribution data to inform the prioritization of conservation actions.

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