Relevance of data analytics in sustainable fisheries management: An evidence-based study
Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India
Schools of Social & Behavioral Sciences (Amritapuri & Coimbatore), Amrita Vishwa Vidyapeetham, India
AMMACHI Labs / Center for Women’s Empowerment and Gender Equality (CWEGE), Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India
College of Geography and Environment Science, Henan University, 475004 Kaifeng city-Henan Province, China
Data nadesłania: 21-10-2023
Data ostatniej rewizji: 23-11-2023
Data akceptacji: 23-11-2023
Data publikacji: 19-12-2023
Autor do korespondencji
Isaac Lukambagire   

Amrita School for Sustainable Futures, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India
Acta Sci. Pol. Formatio Circumiectus 2023;22(4):49-74
Aim of the study:
The value of fish resources to socioeconomic development is immense. However, there is growing evidence that loss of quality in the marine environments e.g. marine waters at sea and coastal freshwater zones is threatening the availability of livelihood resources e.g. fish resources evidenced by the dwindling fisheries resources that promote sustainable livelihood. Aware of this, several fisheries’ institutions, governments, and local users have come up with several strategies to boost marine water environment management and promote sustainable fishing. Unfortunately, most of the initiatives have not fully managed to eradicate unsustainable practices e.g. marine water pollution, which leads to loss of wild catches and to unsustainable fishing practices.

Material and methods:
Owing to this we use a mixed research methods approach involving a systematic literature review and field survey in Alappad to argue and present a case for governments and fishery management organizations to invest in data analytics as a new pathway that can give a comprehensive, near real-time view of both ocean resources and coastal fishing activities in light of the declining fish stocks and escalating environmental problems such as marine water quality loss due to pollution.

Results and conclusions:
Findings documented that by using data analytics, governments and fisheries management organizations/individuals may respond more swiftly to external forces such as climate change, and marine water quality loss, and implement new policies and regulations thus promoting sustainable fisheries management. Local perspectives of coastal communities could also guide the best data analytics tool or method to be used.

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