Activity 4.1: Assess the socio-economic role of billfish in recreational, commercial, and artisanal fisheries
A multiple case study research design will be used to obtain data on recreational, artisanal, commercial fisheries that catch the flagship species. Information will include: Demographics, Socio-economic operator data, and drivers of perception and motivations to catch the selected species. The survey tool will include both quantitative and open-ended questionnaires. To analyze this data, we will use socio-economic performance indicators reported in the literature (e.g., Sumaila et al., 2012) including those reported by developed by FAO to assess the economic objective of a fishery, and the fisheries commercial viability.
These may include: Gross Revenue, Net Revenue, Financial Profit and Economic rent and economic impact (FAO, 1997; Kelleher et al., 2009; Dyck and Sumaila 2010; Sumaila et al., 2012) among other indicators. We will use questionnaire surveys focus group discussions, key informant interviews and secondary methods to develop a socio-economic profile of billfish fishers and traders in the case study areas. The questionnaire and checklist will focus on understanding billfish fishers and traders’ socio-economic characteristics; asset ownership; housing types; household livelihood activities and incomes; fishing behavior and patterns, and; expenditures and incomes accrued from billfish business. Where possible historical data will be collected in order to document trends of fishers and traders’ profiles. Participants for wealth ranking exercise in artisanal fishing communities will come from all stakeholders’ groups and consider gender, age, occupation, community status, and level of education. Aims of the exercise will be to: determine how wealth is defined among fishers, determine the mode of benefit sharing, and investigate non-fishing income and how they contribute to the resilience of fishers.
Activity 4.2: Develop value addition techniques for the marine products from the artisanal fishery (market research, processing, production level, and storage).
Social networks, their structural characteristics, and how they are formed in relation to billfish fishery and management. A participatory approach will be used to map out the value chain in the billfish fishery. Data will be collected through interviews, focus group discussions and on-site surveys. Data will include fishers’ dynamics, fish trade, the gear, type of craft, species caught, marketing structure, and capital investments.
The study will also investigate the political, social, cultural, and economic factors that may influence the value chain and preferences by different level of consumers. This data will then be used to answer socio-economic implications of mitigating bycatch of billfish. We will explore is the value chain analyses of a landed billfish in artisanal fisheries vs. a released billfish in recreational fisheries. This would in turn provide an understanding of the importance of recreational and artisanal billfish fisheries and the potential for sustainably developing recreational billfish fisheries (Golan et al., 2019).
Activity 4.3: Evaluate the socio-ecological implications of mitigating BY-CATCH of billfish
Data from all the four objectives will be collated through focused group discussions, semi-structured interviews and catch sampling. With this information we will identify the different factors that influence bycatch rates. Additionally, ecosystem-based risk assessments and management frameworks will be used to examine the influence of factors such as culture, the population pressure, climate change on bycatch rates.
Additionally, a Social-Ecological Systems (SES) framework (Ostrom, 2009) will be used to identify conditions under which the ecological, social, and economic outcomes of mitigating bycatch of billfish can be improved to provide benefits to resource users while sustainably managing the species. The wellbeing approach from a holistic standpoint which would identify the aspects of wellbeing amongst all the stakeholders would be applied and test how to measure this and prioritize them and understand how they relate to each other (Golan et al., 2019).
Activities 4.1 – 4.3 will be conducted at representative sites in Kenya, Tanzania, Mozambique, and Zanzibar.
Team leaders: Prof. Rashid Sumaila, assisted by collaborators Dr. Lydia Gaspare (Tanzania/Zanzibar), Dr. Emmanuel Sweke (Tanzania/Zanzibar), Dr. Sarah Glaser (Somalia), Dr. Nina Wambiji (Kenya).