Opportunities to improve fisheries management through innovative technology and advanced data systems

Abstract

Fishery‐dependent data are integral to sustainable fisheries management. A paucity of fishery data leads to uncertainty about stock status, which may compromise and threaten the economic and food security of the users dependent upon that stock and increase the chances of overfishing. Recent developments in the technology available to collect, manage and analyse fishery‐relevant data provide a suite of possible solutions to update and modernize fisheries data systems and greatly expand data collection and analysis. Yet, despite the proliferation of relevant consumer technology, integration of technologically advanced data systems into fisheries management remains the exception rather than the rule. In this study, we describe the current status, challenges and future directions of high‐tech data systems in fisheries management in order to understand what has limited their adoption. By reviewing the application of fishery‐dependent data technology in multiple fisheries sectors globally, we show that innovation is stagnating as a result of lack of trust and cooperation between fishers and managers. We propose a solution based on a transdisciplinary approach to fishery management that emphasizes the need for collaborative problem‐solving among stakeholders. In our proposed system, data feedbacks are a key component to effective fishery data systems, ensuring that fishers and managers collect, have access to and benefit from fisheries data as they work towards a mutually agreed‐upon goal. A new approach to fisheries data systems will promote innovation to increase data coverage, accuracy and resolution, while reducing costs and allowing adaptive, responsive, near real‐time management decision‐making to improve fisheries outcomes.

Technological innovations in the recreational fishing sector: implications for fisheries management and policy

“…Smartphones are also a convenient interface with, and extension of, many of the technologies that are featured in this paper (e.g., cameras, ROVs, navigational equipment, smart devices). Particularly relevant to fisheries management and policy are the many applications (also known simply as “apps”) that support private or public catch logging, and specialized social networking (Venturelli et al 2017 ; Bradley et al 2019 ). Catch log fields vary among these apps (Venturelli et al 2017 ), but typically include date, time, location, conditions, method of fishing (e.g., boat vs. shore, type of lure), species, size, and fate.…”

“…Fish and Wildlife Service and the Fishbrain app ( www.fishbrain.com ) that encourages anglers to track invasive species ( www.landscapepartnership.org/news/fishbrain-and-u.s.-fish-and-wildlife-service-partner-to-create-app-powered-citizen-science-engagement-opportunity-tracking-endangered-species ). With enough research and participation, the rapid, two-way flow of information between anglers and agencies could even support an adaptive management approach that adjusts allowable harvest (fish size and number) in near real time based on the estimated impact of cumulative harvest on target reference points (Venturelli et al 2017 ; Bradley et al 2019 ). Although the emergence and success of such a management scheme is debatable, it illustrates the extent to which smartphones can re-shape fisheries management and policy.…”

Deep learning for smart fish farming: applications, opportunities and challenges

“…As shown in Figure 1, data-driven intelligence methods, including artificial intelligence and big data, have begun to transform these data into operable information for smart fish farming (Shahriar & McCulluch 2014;Olyaie et al 2017). Artificial intelligence, especially machine learning and computer vision applications, is the next frontier technology of fishery data systems (Bradley et al 2019). Traditional machine learning methods, such as the support vector machine (SVM; Cortes & Vapnik 1995), artificial neural networks (ANN;Hassoun 1996), decision trees (Quinlan 1986) and principal component analysis (Jolliffe 1987), have achieved satisfactory performances in a variety of applications (Wang et al 2018).…”

Assessing the viability of small aerial drones to quantify recreational fishers

“…The complimentary use of drones within fisheries management may be the optimal use of this technology, such as the rapid detection of passive fishing gear (Provost et al., 2020), or for assessing stocks to determine the effect of management decisions (Beckmann et al., 2019). Emerging technology enables the development of innovative techniques (Bradley et al., 2019), and the comparison of these to established methods is important to inform best practise and cost‐benefit analyses when designing surveys (Ezat, Fritsch, & Downs, 2018; Fernando et al., 2019; Flynn et al., 2018; Wood et al., 2016). Furthermore, simultaneous drone‐ and vessel‐based methods allowing for direct comparison of data in future studies are recommended (Desfosses, Adams, Blight, Smallwood, & Taylor, 2019).…”