Browsing by Author "Well, Lisa"

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    Using fishers’ local ecological knowledge for management of small-scale fisheries in data-poor regions: Comparing seasonal interview and field observation records in East Africa
    (Elsevier, 2023-08) Silas, Mathew; Semba, Masumbuko; Mgeleka, Said; Well, Lisa; Linderholm, Hans; Gullström, Martin
    Fishers, scientists and policy makers need to describe, understand and “agree on” variations in fish catches caused by exploitation and climate change for effective fisheries management. To achieve this, relevant data with sufficient spatiotemporal resolution is a necessity. In regions of the Global South, such as the Western Indian Ocean (WIO), fish catch data useful for management is scarce or non-existing. Still, the potential of local ecological knowledge to provide such information has not been fully utilised in these regions. In this study, we evaluated fishers’ local ecological knowledge (based on interviews) against detailed seasonal fish catch variability data based on catch per unit effort (CPUE) records. Because of the importance of the monsoon seasons for marine resource variability, differences in fish catches during the northeast (NE) and southeast (SE) monsoon seasons were investigated. Fishers’ perceptions generally agreed with catch data records, both showing that the NE monsoon season generally provides higher catch rates than the SE monsoon season. The fishers’ perceptions at two of the landing sites (Nyamisati and Shangani) contradict the recorded observations by showing highest fish catches during the SE monsoon season. It was clear, however, that fishers’ perceptions in these two sites focused on the most valuable target species (prawn and tuna in Nyamisati and Shangani, respectively) rather than total catches. In this particular case, fishers’ perceptions facilitated the significance of taking target species into consideration. The findings of this study highlight the importance of integrating local ecological knowledge into scientific research to help understand the complex dynamics of coastal fisheries and improve the management of data-poor fisheries.