Shining Light on Data-Poor Coastal Fisheries

Abstract

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.

Transforming Biodiversity Governance

“…activities, biodiversity and socioeconomic needs; detailed consultations with the fishing dependent communities and management planning in which the communities proposed their own no-take zones, seasonally closed areas, gear-restricted zones and protected turtle nesting beaches (Exeter et al, 2021;WCS, 2018). Following this process, the area was officially accepted by the government in 2018 as Myanmar's first marine fisheries comanagement area (Latt, 2019).…”

Application of AIS‐ and flyover‐based methods to monitor illegal and legal fishing in Canada's Pacific marine conservation areas

“…Additional vessel tracking methods are important to capture fishing activity that is missed by AIS (see review by Iacarella et al, 2021). In particular, the utility of AIS for monitoring CAs is more limited for countries that do not mandate carriage by fishing or small vessels (Exeter et al, 2021; Kanjir et al, 2018), as well as in cases of illegal fishing where AIS message transmission may be blocked or falsified (Ford et al, 2018; Rowlands et al, 2019). A complementary approach to the AIS‐based method is the use of information collected on vessels by aerial surveillance (hereafter, “flyover”) programs.…”

AIS and VBD Data Fusion for Marine Fishing Intensity Mapping and Analysis in the Northern Part of the South China Sea

“…to conduct an in-depth study on illegal fishing in sensitive areas between North Korea, Japan, and Russia [33]. Exeter et al utilizes VIIRS boat detections (VBD) and GPS data to predict fishing effort, biomass and value, as well as the spatial and temporal distribution of catch [34].…”

“…It can be concluded that the existing studies have focused more on the analysis and mining of the fishing intensity characteristics of Marine fisheries by using a single data source [13,25]. Although there are cases in existing studies that have combined multiple sources of data, most of them have focused on illegal fishing at sea, and there are still no cases that combine the advantages of the two and explore fishing intensity information of Marine fisheries through their fusion [29][30][31][32]34].…”