Predicting Fisheries Productivity of Small‐Scale Vessels Under Climate Change in Indonesia

ABSTRACT Climate change is an urgent global challenge that transforms atmospheric and oceanographic conditions, impacts marine ecosystems through rising sea temperatures and sea levels, causes fish habitat to shift, and influences the dynamics of fisheries productivity. We developed an Artificial Neural Network (ANN) model to analyze the impact of climate change on capture fisheries production within a blue economy framework. Using data on the sea environment and fisheries production, the model predicted fisheries productivity and the risk of climate change to productivity. The best‐performing model (MAPE = 7.41%, MSE = 0.0024, MAE = 0.0370) accurately predicted productivity for vessels below 30 GT at the Pekalongan Fisheries Port on Java Island, Indonesia. Our findings highlight the potential of ANN models to support mitigation and adaptation efforts that contribute to fisheries sustainability and enhance resilience to climate change impacts.