Using fish landing sites and markets information towards quantification of the blue economy to enhance fisheries management

Abstract

Fisheries management uses important fish market information and information from Communication Technology (ICT) to improve fish trade by identifying inefficiencies, inequity and post‐harvest losses. The current study reports fisheries output using ICT at major landing sites and markets in Kenya and Uganda from the Kenya Marine and Fisheries Research Institute (KMFRI) Enhanced Fish Market Information Service (EFMIS) database for 2009 – 2017. Catch assessment survey data validated the use of market data in drawing conclusions. Regional Frame Survey data provided information before EFMIS, enabling comparisons of fish trade costings. The average quantity of fish traded in Kenya depended on seasons of active lake fishing, which occurs in January – March and August – October, while Uganda had an irregular pattern associated with fish trade throughout the year. The quantity of fish traded weekly depended on the average price of fish. Lower sales margins during the EFMIS project showed the merits of information sharing using ICT platforms for efficient and equitable fish trade. Such evaluation of fish market information is useful in fish trade policy formulation and for fisheries management and ecological sustainability in rural and peri‐urban communities.

Consequences of calamities and their management: The case of COVID-19 pandemic and flooding on inland capture fisheries in Kenya

“…A fluctuating trend was exhibited for Lake Victoria tilapia in the major landing sites and markets. This could be related to disruption of market because of movement restrictions from some towns such as Nairobi, which has been the major market ( Aura et al, 2019 ). A similar scenario was noted when China imposed lockdowns and travel restrictions ( Tester, 2020 , Dao, 2020 ).…”

“…The changes in fish landing and prices before and after flooding and Covid-19 were obtained by comparing data collected between 2009 and 2017 before (before 14th March 2020) and during (after 14th March 2020) using the Electronic Fish Market Information System (EFMIS). EFMIS is an ICT (Information and Communication Technology Authority) pilot project, being implemented around Lake Victoria in Kenya based on mobile phones to provide information on landings in terms of species and prices at fish landing sites and markets ( Aura et al, 2019 ).…”

“…The trend of the lake level was forecasted at 95% confidence interval using the Auto Regressive Integrated Moving Average (ARIMA) model for time series data and for predicting future points in the series ( Hyndman and Khandakar, 2008 , Asteriou and Hall, 2011 ). The EFMIS data was used to compare landings and prices for major commercial fish species before and during flooding and COVID-19 ( Aura et al, 2019 ).…”

“…Riparian communities in the African Great Lakes are marginalized, vulnerable, and highly susceptible to the rapid impact of social economic effects of mitigative measures such as those put in place to contain of COVID-19 ( FAO, 2020 , CFFA, 2020 ) and floods ( Njiru et al, 2012 ). This is because lakes and reservoirs are important income and employment generators in developing nations as they stimulate the growth of a number of subsidiary industries and are a high quality source of cheap and nutritious food besides being a foreign exchange earner for riparian communities and lacustrine stakeholders ( Hamerlynck et al, 2011 , Aura et al, 2019 , Nyamweya et al, 2020 ). More importantly, inland capture fisheries are a source of livelihood for a large section of an economically disadvantaged population in rural and peri-urban communities including women and young people ( Dugan et al, 2006 , Gangadhar, 2011 , Njiru et al, 2019 ).…”

Does Information Technology Help Fish Marketing? A Review for A Preferability Fish Marketing in North Sumatera, Indonesia

“…Then, [51] agreed that the employment of IT who is able to reduce price volatility in agricultural markets in enhancing the efficiency of agricultural markets. Researcher [52] reported that sharing information in IT platforms causing an efficient and equitable fish trade. Reducing the process number of middlemen have an impact on reducing wastage and volatility of fish prices.…”