Prediction potential fishing zones for Pacific saury (Cololabis saira): using two different approaches: GAM and Maxent
This scholarly work examines the prediction of fishing zones for Pacific saury (Cololabis saira) through two methodologies: GAM and Maxent. It details the implementation and comparison of these approaches to enhance habitat modeling in marine ecosystems, supporting informed fisheries management.
About This Book
This book presents a research investigation into predicting potential fishing zones for Pacific saury, scientifically known as Cololabis saira.
The analysis employs two distinct approaches: Generalized Additive Models (GAM) and Maximum Entropy (Maxent), to model and forecast suitable habitats.
By comparing these methods, the work highlights their applications in fisheries science and environmental modeling.
The findings contribute to sustainable fishing practices in oceanic regions.
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