Fishermen's perceptions of coastal fisheries management regulations: Key factors to rebuilding coastal fishery resources in Taiwan

Autor: Hsiang-Wen Huang, Chun-Pei Liao, Hsueh-Jung Lu
Rok vydání: 2019
Předmět:
Zdroj: Ocean & Coastal Management. 172:1-13
ISSN: 0964-5691
DOI: 10.1016/j.ocecoaman.2019.01.015
Popis: Although Taiwan has taken conservation measures for coastal and offshore fishery resources in recent years, the effectiveness of resources rebuilding is unclear. Many initiatives, such as marine protected areas (MPAs), are frequently opposed by fishermen. This research reviewed management measures and interviewed 313 fishermen by purposive stratification and snowball sampling. Data were analyzed by fishery, age, and vessel size to address the attitudes and perceptions of fishermen toward twelve fisheries management measures. Descriptive statistics, as well as chi-squared tests and independent t-tests, were used for basic analysis and differences comparison between groups. The results showed that illegal fishing vessels from China (71%), overfishing (69.5%), and ghost fishing (64%) are considered as major threats to Taiwan marine resources. The measures from voyage data recorders, larval anchovy, precious coral, and shark management result in higher satisfaction because of strict monitoring. The satisfaction measures for three net-type measures, i.e., trawler area closure, torch-light limitation, and gillnet limitation, were low. Line-type and small-scale vessel fishermen are more concerned with “small mesh size” and “ghost fishing”. Net-type, large-scale vessels and young fishermen were concerned about “climate change” and “inappropriate measures”. In conclusion, the priorities are to (1) establish a comprehensive scientific research framework; (2) strengthen enforcement to ensure resources rebuilding, especially for large-scale net fisheries; (3) promote public awareness and build communication between stakeholders to obtain support; and (4) communicate among policymakers and fishermen to increase mutual understanding.
Databáze: OpenAIRE