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Smart Fisheries for Sustainable Fisheries in Indonesia : A Study of Sardine Fishery in the Bali Strait

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In this study, a comprehensive strategy based on information and communication technology (ICT) for capture fisheries data digitalization, big data analysis, and decision support systems (DSS) was utilized to support and realize smart fisheries with the goal of promoting sustainable sardine capture fisheries in the Bali Strait, Indonesia. To establish smart fisheries, it is first necessary to create digital capture fisheries data: these data provide a basis for robust stock assessment and the generation of policies recommendations and adaptive fisheries management measures. In the Bali Strait, a broad ICT strategy was used, including the development of a platform for digital capture fisheries data by creating the MICT-L (Marine ICT- Landing) digital recorder application, the installation of loT (internet of things) GPS tracker devices, including 12 satellite-based and 20 cellular-based GPS tracking devices, and the establishment of an online database platform. To evaluate the total allowable catch (TAC) that ensures sustainable fisheries exploitation, a non- equilibrium surplus production analysis using a stock production model incorporating covariates (ASPIC) and a Bayesian surplus-production model (BSM) were conducted using catch time series data for 1980-2019. The MSY from ASPIC were introduced to the MICT-L system, and the model results revealed that the annual maximum sustainable yield (MSY) for Bali Strait sardines was 28,540 tons/year, effort at MSY was 10,790 trips per year, and sardine biomass level was 47,770 tons; consistent with previous studies, the sardine fisheries were classified as overexploited. To displaying the catch condition and fish stock resource exploitation status and increase stakeholder awareness of the landing and stock status, we developed an Android-based smart dashboard for daily monitoring. To understand the relationships between catch and environmental conditions and to develop catch and fishing ground predictions, we analyzed data from the capture fisheries database, environmental data from satellites (ie. the sea surface temperature and sea surface chlorophyll), and environmental indexes (i,e., the southern oscillation index, Niño 3.4, and dipole mode index (DMI) for the Indian Ocean). The most significant determinant of catch fluctuations was yearly factorial variation followed by monthly factorial and DMI parameter factorial variation, while CPUE fluctuation was strongly influenced yearly factorial variation followed by Niño 3.4. The models projected catch and CPUE with 57% accuracy. A spatial productivity analysis revealed monthly variation, and a further area-based analysis showed that fishing operations are frequently conducted in the northeastern Bali Strait, followed by the northwestern area. Most of the fishing operations were within the Bali Strait waters, with only several fishing fleets operating in areas in the southern part of the Bali Strait. Using the catch monitoring status from MICT-L and the model projection, simple decision-making scenarios were developed. This decision-making process was based on the conditions necessary to achieve the sustainable use of the sardine fish stock. This study provides a novel smart fisheries system based on local fishery characteristics to support decision-making by managers and other stakeholders and thereby to realize the sustainable use of the sardine stock and efficient data-based fisheries activity. Future work will be aimed at evaluating and improving DSS performance, user/stakeholder benefits, effective fisheries management, the impact of the SMART FISHERY system, and system sustainability. The full implementation and effectiveness of the system will require iterative dissemination and communication through broad channels to increase stakeholder understanding, awareness, and capacities and to support recommendations and the implementation of management measures.

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Availability

B23000138

DIS 639.222 MOH s

Archivelago Indonesia Marine Library - Perpustakaan Kementerian Kelautan dan Perikanan

Available

Detail Information

Series Title

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Call Number

DIS 639.222 MOH s

Publisher

: ., 2022

Collation

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Language

English

ISBN/ISSN

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Classification

639.222

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Capture Fisheries
Data Digitalization
Decision Support System
Smart Fisheries

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