Predicting the exposure of coastal species to plastic pollution in a complex island archipelago. (September 2019) - Critchell, Kay; Hamann, Mark; Wildermann, Natalie; Grech, Alana
Abstract: Plastic pollution in the marine environment is a pervasive and increasing threat to global biodiversity. Prioritising management actions that target marine plastic pollution require spatial information on the dispersal and settlement of plastics from both local and external sources. However, there is a mismatch between the scale of most plastic dispersal studies (regional, national and global) and the scale relevant to management action (local). We use a fine-resolution hydrodynamic model to predict the potential exposure of coastal habitats and species (mangroves, coral reefs and marine turtles) to plastic pollution at the local scale of a management region (the 1, 700 km 2 Whitsunday Islands, Queensland, Australia). We assessed the potential exposure of mangroves, coral reefs and marine turtles to plastics during the two dominant wind conditions of the region; the trade wind and monsoon wind seasons. We found that in the trade wind season (April to September) all habitats and species had lower exposure than during the monsoon wind season (October to March). In both wind seasons we found a small proportion of coral reef habitat and large area of turtle habitat were in high potential exposure categories. Unlike coral reefs or marine turtles, mangroves had consistent hotspots of high exposure across wind seasons. Local scale management requires data at fine resolution to capture the variability that occurs at this scale. The outputs of our study can inform the development of conservation resources and local scale management action. Graphical abstract: Image 1 Highlights: Weather conditions strongly dictate plastic exposure patterns. Variable winds in the monsoon season lead to higher exposure of plastic. Strong south-easterly trade winds lead to plastic removal, therefore lower exposure. Plastic types have different accumulation patterns at a small geographic scale.