Disentangling beach litter pollution patterns to provide better guidelines for decision-making in coastal management

Abstract

Beach litter represents a worldwide problem impacting both terrestrial and aquatic environments. In the present study, we assessed beach litter pollution in a prominent touristic site in Brazil, the Jericoacoara National Park. In particular, we applied a delta-generalized additive modeling (GAM) approach in order to investigate pollution hotspots and to provide better guidelines for coastal environmental managers. A total of 7549 litter items were collected, resulting hard and flexible plastics the most abundant type. Our GAM analysis revealed that the distribution of each type of litter was affected by distinct drivers in the protected area, with the extension of the beach, tourist attractions, wind angle, and the distance to water bodies and villages as the most significant explanatory variables. Our model is suitable in predicting litter pollution hotspots on beaches, which is a valuable tool for future guidelines and effective management strategies to prevent beach pollution worldwide.