Understanding how microplastic particles move and accumulate within estuarine and coastal waters requires consideration of primary inputs (e.g., raw materials from industrial zones) as well as secondary inputs resulting from fluvial processes (i.e., materials carried into coastal waters by rivers and streams). This study presents a novel approach to achieve this aim, by comparing the individual and combined ability of Particle Tracking Models (PTMs) and seasonal rainfall data, to explain observed inputs of microplastic pellets to the ocean beaches of Santos City (south-eastern Brazil). A Lagrangian PTM based on high-resolution hydrodynamic models was used to simulate seasonal patterns of pellet dispersal from five release points within the Santos Estuarine System (SES) and nearshore waters which are known contributors to the regions microplastic debris problem. Model outputs suggested that the debris field is likely to be small within the estuary (ranging from 3.6 to 8.1 km²), intermediate at the river mouth (mean 34 km²) and greatest for near- and offshore sites (ranging from 34 to 40 km²). The spatial footprints were strongly modulated by season (and rainfall), with simulations alone unable to reconcile daily inputs of pellets observed on the beaches of Santos Bay (ranging from 2 to 51 particles m² ⋅ d^–1). Given this discrepancy, a Generalized Additive Modeling approach was employed to integrate the PTM outputs with rainfall data to improve predictions of beached particles. Results confirmed that considering fluvial processes, could significantly improve the ability to predict rates of pellet accumulation (raising the explained deviance in observed inputs from 41 to 93%). Thus, the study highlights the potential to couple widely used dispersion models with metrics that describe fluvial forcing (rainfall and estuarine flushing) in order to better understand the spatio-temporal dynamics of microplastic debris transport and accumulation within dynamic coastal environments.

We compared the sensitivity of algae and hermit crabs to seasonal shifts in the dominance of continuous sewage discharge vs. pulsed inputs of terrestrial material to a subtropical bay. During periods of low rainfall, when sewage was proportionately more important than diffuse loads from adjacent catchments, algae and crabs provided comparable information on the spatial distribution of N pollution. Conversely, during the wet season, when diffuse nitrogen loads from the catchment were of greater importance, the isotope signal of algae decoupled from that of crabs, indexing a greater magnitude of change and a more pronounced spatial gradient. Overall, algae better indexed the short-term impacts of anthropogenic nitrogen pollution whereas the signals provided by crabs provided a longer-term integrated measure of N inputs. Our results demonstrate the value of including multiple taxa with variable traits when monitoring the spatial and temporal extent of nitrogen inputs to coastal waters.