PeskAAS: A near-real-time, open-source monitoring and analytics system for small-scale fisheries

• Published in: PloS one 2020-11, Vol.15 (11), p.e0234760-e0234760
• Main Authors: Tilley, Alexander, Dos Reis Lopes, Joctan, Wilkinson, Shaun P
• Format: Article
• Language: English
• Subjects: Animals; Biology and Life Sciences; Computer and Information Sciences; Conservation; Conservation of Natural Resources; Dashboards; Data collection; Data integration; Data mining; Decision making; Developing countries; Earth Sciences; Ecology and Environmental Sciences; Ecosystem; Engineering and Technology; Environmental monitoring; Fisheries; Fisheries - standards; Fisheries - statistics & numerical data; Fisheries management; Fishes - physiology; Fishing; Freeware; LDCs; Length-weight relationships; Low income groups; Methods; Nutrition; Open source software; People and places; Small-scale fisheries; Smartphones; Social Sciences; Software; Source code; Species Specificity; Systems Analysis; Technology application; Workflow
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0234760

Small-scale fisheries are responsible for landing half of the world's fish catch, yet there are very sparse data on these fishing activities and associated fisheries production in time and space. Fisheries-dependent data underpin scientific guidance of management and conservation of fisheries systems, but it is inherently difficult to generate robust and comprehensive data for small-scale fisheries, particularly given their dispersed and diverse nature. In tackling this challenge, we use open source software components including the Shiny R package to build PeskAAS; an adaptable and scalable digital application that enables the collation, classification, analysis and visualisation of small-scale fisheries catch and effort data. We piloted and refined this system in Timor-Leste; a small island developing nation. The features that make PeskAAS fit for purpose are that it is: (i) fully open-source and free to use (ii) component-based, flexible and able to integrate vessel tracking data with catch records; (iii) able to perform spatial and temporal filtering of fishing productivity by fishing method and habitat; (iv) integrated with species-specific length-weight parameters from FishBase; (v) controlled through a click-button dashboard, that was co-designed with fisheries scientists and government managers, that enables easy to read data summaries and interpretation of context-specific fisheries data. With limited training and code adaptation, the PeskAAS workflow has been used as a framework on which to build and adapt systematic, standardised data collection for small-scale fisheries in other contexts. Automated analytics of these data can provide fishers, managers and researchers with insights into a fisher's experience of fishing efforts, fisheries status, catch rates, economic efficiency and geographic preferences and limits that can potentially guide management and livelihood investments.