Using Cultural Algorithms to Learn the Impact of Climate on Local Fishing Behavior in Cerro Azul, Peru

Recently it has been found that the earth's oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2018 has become the warmest year on record for the earth's oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [1]. The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of warming and subsequent cooling of the Pacific Ocean that can last over a period of years. This cycle was first documented by Peruvian fishermen in the early 1600's. So it has been part of the environmental challenges that have been presented to economic agents throughout the world since then. It has even been suggested that the cycle has increased in frequency over the years, perhaps in response to the overall issues related to global warming. [2] [3] In this paper Cultural Algorithms are used to develop a multi-objective agent-based model of artisanal (traditional offshore) fishing behavior in coastal Peru, Cerro Azul. The data used to produce this model comes from the observation of fishing behavior over a four year period, 1982-1986. During this period over 6000 individual fishing trips were documented. This observation period overlapped with one of the largest ENSO activities ever recorded. As a result, it was possible to observe the changes in fishing behavior that were the result of this process. While the data is several decades old, the ENSO process was first observed in Peru in 1502. Thus, this data can be considered to reflect the adaptations that have been made to the process in the ensuing centuries. The model was used to produce Pareto curves that reflected tradeoffs in terms of fish quality and trip effort during each of three phases on the ENSO process. A version of Cultural Algorithms, CAPSO, was then used to compute whether these curves were significantly different from each other. The results suggested that they each represented a different phased response to the local climate change. During the warming phase fisherman had to exert less effort to secure quality fish than in the subsequent cooling off period. In that period there were more types of catches but they were distributed over a wider area. The final, back to normal phase reflected a compromise between the two, where fewer types of catches of slightly lower quality, but with lesser effort than in the previous phases.