Shining light on data-poor coastal fisheries

Exeter, Owen M., Htut, Thaung, Kerry, Christopher R., Kyi, Maung Maung, Mizrahi, Me'ira, Turner, Rachel A., Witt, Matthew J., and Bicknell, Anthony W.J. (2021) Shining light on data-poor coastal fisheries. Frontiers in Marine Science, 7. 625766.

PDF (Published Version) - Published Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview
View at Publisher Website:


Coastal fisheries provide livelihoods and sustenance for millions of people globally but are often poorly documented. Data scarcity, particularly relating to spatio-temporal trends in catch and effort, compounds wider issues of governance capacity. This can hinder the implementation and effectiveness of spatial tools for fisheries management or conservation. This issue is acute in developing and low-income regions with many small-scale inshore fisheries and high marine biodiversity, such as Southeast Asia. As a result, fleets often operate unmonitored with implications for target and non-target species populations and the wider marine ecosystem. Novel and cost-effective approaches to obtain fisheries data are required to monitor these activities and help inform sustainable fishery and marine ecosystem management. One such example is the detection and numeration of fishing vessels that use artificial light to attract catch with nighttime satellite imagery. Here we test the efficiency and application value of nighttime satellite imagery, in combination with landings data and GPS tracked vessels, to estimate the footprint and biomass removal of an inshore purse seine fishery operating within a region of high biodiversity in Myanmar. By quantifying the number of remotely sensed vessel detections per month, adjusted for error by the GPS tracked vessels, we can extrapolate data from fisher logbooks to provide fine-scale spatiotemporal estimates of the fishery’s effort, value and biomass removal. Estimates reveal local landings of nearly 9,000 mt worth close to $4 million USD annually. This approach details how remote sensed and in situ collected data can be applied to other fleets using artificial light to attract catch, notably inshore fisheries of Southeast Asia, whilst also providing a much-needed baseline understanding of a data-poor fishery’s spatiotemporal activity, biomass removal, catch composition and landing of vulnerable species.

Item ID: 69302
Item Type: Article (Research - C1)
ISSN: 2296-7745
Keywords: remote sensing, nighttime lights, data-poor fisheries, coastal fisheries, Myanmar, small-scale fisheries
Copyright Information: © 2021 Exeter, Htut, Kerry, Kyi, Mizrahi, Turner, Witt and Bicknell. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Funders: Darwin Initiative (DI), University of Exeter
Projects and Grants: DI grant (23-024)
Date Deposited: 07 Sep 2021 22:31
FoR Codes: 41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410401 Conservation and biodiversity @ 20%
41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410406 Natural resource management @ 35%
41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410404 Environmental management @ 45%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180507 Rehabilitation or conservation of marine environments @ 100%
Downloads: Total: 693
Last 12 Months: 15
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page