Participatory monitoring with VA’A canoes identifies key environmental factors driving microplastic distribution

Abstract

Microplastics (MP) distribution in coastal environments is influenced by a combination of environmental, spatial,

and temporal factors. Understanding these processes is essential to developing effective monitoring and miti- gation strategies. In this context, participatory research on plastic pollution that integrates water sports and

scientific research has great potential to contribute to environmental monitoring practices. In this study, the

assessment of MP abundance, composition and distribution in two coastal areas with contrasting levels of ur- banization was conducted using a low-cost participatory approach with Va’a canoes during water sports activ- ities. We applied a Boosted Regression Trees (BRT) model to infer the strongest local and environmental

predictors influencing MP density. A total of 23,159 MP was identified with a mean density of 0.47 items.m− 2 . The highly urbanized site exhibited higher density and variety of MP compared to the low-urbanized site. The

BRT model explained 66 % of the variance in cross-validation, highlighting the importance of local hydrody- namics, urbanization, and rainfall-driven runoff in MP distribution along the coast. The model showed that wind

speed was the strongest predictor of MP density, followed by site (high-urbanized vs. low-urbanized) and monthly rainfall. The use of Va’a canoes enabled robust data collection while simultaneously engaging water sports practitioners in citizen science. This approach not only extends monitoring capacity but also fosters local awareness and provides a scalable model that can be adapted to strengthen regional and global initiatives addressing microplastic pollution.