Over 25 years ago, illegal fishing was seen as a significant threat to international fisheries. Extraordinary efforts, such as the adoption of the UN Fish Stocks Agreement and the UN Compliance Agreement, illustrated the importance of addressing illegal fishing at the global level. The countries in Latin America and the Caribbean (LAC) have a long history of addressing fisheries interests by leading global efforts. The Santiago Declaration of 1952 established a 200 nautical mile fisheries zone leading to the codification of the concept in the United Nations Convention on the Law of the Sea (UNCLOS). It also created a regional coordination mechanism, the Permanent Commission of the South Pacific (CPPS), which has recently begun efforts to establish a regional plan of action to combat illegal, unreported, and unregulated (IUU) fishing in accordance with the United Nations (UN) Food and Agriculture Organization (FAO) International Plan of Action on IUU. The intervening decades have seen i
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Overview
Overfishing is one of the greatest threats facing the ocean. In its 2020 biennial report on the status of the world’s fisheries, the United Nations Food and Agriculture Organization (FAO) noted that a third of fish stocks are overfished and that nearly 60 percent of the remaining stocks are unable to sustain further increases in fishing. Illegal, unreported, and unregulated (IUU) fishing exacerbates this threat, preventing accurate stock assessments and harming small-scale fishers and coastal communities through destructive fishing practices. The economic and food security implications are substantial: In some developing nations, IUU fishing accounts for more than 30 percent of fish taken from their waters, often due to limited capacity to monitor activity within exclusive economic zones.
An Agent-Based Model (ABM) is a category of a computational model for investigating actions and interactions of autonomous agents. The concept behind an ABM is the observation of simultaneous and multiple interactions of agents or programmed instructed entities through simulated environments. In developing these simulated environments, predictions of emergent phenomena can be evaluated. With an ABM, macro or high-level system properties can emerge from lower-level system interactions. Moreover, large scale state changes will emerge from micro-scale agent behaviors generated from system-level interactions. Such modeling techniques can be used to observe and evaluate new plant floor Machine-to-Machine (M2M) networked systems using Profibus or Modbus communication protocols. Also, thermodynamic materials properties of metals and plastics can be investigated using an ABM. In addition, NetLogo’s vast simulation library has an ABM of a Multilayer or Perceptron Artificial Neural Net tha