Sri Lanka's fisheries sector is important for jobs and food supply. Between 2019 and 2025, it faced several major problems at the same time, and how these events together affected fish production and prices is still not well understood. This study develops a framework to connect weather changes, major disruption events, fish production, and prices, with the goal of helping policymakers, traders, and supply chain managers make better decisions. Seasonal patterns are studied using STL decomposition. Spearman lag correlation is used to find delayed effects of climate on production. Interrupted Time Series (ITS) regression measures the impact of major events. SARIMAX models predict monthly production and prices. Hotspot detection identifies unusual patterns. The results show that marine and inland fisheries behave differently in terms of seasons and climate effects. Major disruptions caused different levels of impact, and in some cases, one sector helped compensate for another. These findings can support better planning, for example, improving infrastructure in high-risk areas, strengthening cold storage systems, and using early warning alerts for unusual events. Price forecasting tools should be used as decision-support tools, not as direct market signals.
Henry Bodwell, Hong Yang, John C. Simeone +7cs.IR cs.AI cs.CY
Illegal, unreported, and unregulated fishing (IUU) traditionally refers to fishing activities that violate applicable laws or occur in areas that lack applicable laws. We propose the term IUU+ to capture a broader suite of fisheries sector environmental and associated supply chain trade-related crimes and behaviors. Although IUU+ activity is widely recognized as a serious threat to marine ecosystems, markets, and livelihoods, a quantitative understanding of these incidents, e.g., their frequency, geography, species, actors, and patterns in the type of illicit activity, remains difficult to obtain. We propose IUU+DB, a large language model driven system for building a global incident database of IUU+ activity. The system ingests heterogeneous documents, classifies whether they describe relevant incidents, extracts key data elements such as actors, locations, species, vessels, violations, and enforcement outcomes, and supports deduplication and trend analysis. Case studies and validation results show that IUU+DB can help organize fragmented evidence, surface geographic and behavioral hotspots, support fisheries-domain specific research in academia and non-government organizations, assist source and species risk assessments for industry, and provide support for policy implementation and targeted enforcement efforts to government agencies.