Illegal, Unreported, and Unregulated (IUU) fishing remains a major threat to marine ecosystems and coastal livelihoods, yet existing enforcement mechanisms rely on periodic inspections, manual reporting, or static financial incentives. We propose a novel closed-loop compliance-to-finance system in which multi-sensor vessel data are transformed into real-time financial signals that directly govern access to capital. In the proposed architecture, heterogeneous onboard and port-side sensors feed into an off-chain AI compliance model whose outputs are transmitted on-chain via decentralized oracle services. These compliance attestations programmatically adjust lending terms in Decentralized Finance (DeFi) protocols, dynamically reducing interest rates and increasing liquidity for compliant operators while restricting capital access for non-compliance. Loans are issued in USD-pegged stablecoins and overcollateralized using real-world fishing assets, including vessels, licenses, quotas, and contracts. Unlike prior approaches that treat sustainability incentives as external subsidies or reputational mechanisms, this system embeds regulatory compliance directly into the cost of capital, creating continuous, automated enforcement with minimum centralized intermediaries. We illustrate the feasibility of this architecture using existing low-cost sensing technologies, oracle infrastructure, and DeFi lending primitives, and discuss its potential to expand sustainable financing in small-scale and low-income fisheries where IUU fishing is most prevalent.
Jewel Das, Maheshwaran Govender, Haseeb Md. Irfanullah, Samiya Ahmed Selim · 5 authors
The ‘Ocean Decade’ focuses on ocean governance and management including ocean health and human well-being in line with the Sustainable Development Goals. Here, we use participatory network mapping to investigate perceptions of Blue Economy governance networks in Bangladesh. Representatives of four Blue Economy stakeholder categories (government, researchers, private sector and civil society, and non-governmental organizations) mapped who they perceived as Blue Economy actors and the relationships between these actors. The resulting “netmaps” highlight 83 actors and diverse perceptions of the composition, structure and dynamic of Blue Economy governance. Relations between governance actors were categorized as formal command, information and support, funding, and competition or obstruction. Information and support, followed by funding were the most frequently perceived Blue Economy governance interactions. The centrality and influence of government actors at different levels, the role of international agencies, and the marginalization of coastal resource users and communities emerged as key themes. A narrow view of the Blue Economy was found; this focused on fisheries, tourism, and shipping sectors indicating a risk of non-inclusive development. We find that Bangladesh’s Blue Economy governance needs to be more inclusive, collaborative, and decentralized and mainstream marginal actors, while carefully considering international actors’ motivations, roles and influence. We propose ‘blue equity’ to guide a holistic approach to Blue Economy governance which aims for a ‘Community of Practice on Blue Economy Governance’. In Bangladesh, such a policy shift requires an effective Blue Economy Cell of the Government that supports knowledge and capacity building, innovative financing, and research-guided policy.
Ecologists warn that the rapid evolution occurring as a result of high-intensity commercial fishing could have significant economic and ecological effects. So far, fishery managers do not take this rapid evolution (called fisheries-induced evolution or FIE) into consideration when determining fishery policy. I model the interactions between the genetics, population structure, and economics of the fishery in order to determine how beneficial altering the fishery managers decision framework to include fisheries induced evolution would be to fishery profit and yield. My model is based on North-East Arctic Cod, which are long lived and for which an abundance of information exists, including proof of FIE. I compare the steady state reached by a `myopic' fishery manager who sets effort and mesh size policy while ignoring evolution, to the steady state reached by a fishery manager who dynamically optimizes his strategy with the knowledge of how evolution will respond. This paper shows that accounting for evolution can increase steady state profits by 29-34%, however this benefit decreases and is eventually eliminated as the discount rate increases from zero. An important auxiliary benefit to accounting for evolution is the effect optimal management has on fishery biomass, maturation rates, and yield.