In aquatic environments, suspension-feeding bivalve molluscs are exposed to a manifold of natural and anthropogenically derived particles, including micro- and nanoplastics. Plastic particles interact with feeding and digestive organs and can produce negative effects. As a result of these effects and the potential transfer of microplastics to higher trophic levels, including humans, there has been renewed interest in the ingestion of plastic particles by different species of bivalves. Many recent studies, however, have ignored the ability of bivalves to select among particles both pre- and post-ingestively. Neglecting to consider the factors that mediate particle capture, ingestion, and egestion can lead to erroneous data and conclusions. This paper outlines the current state of knowledge of particle processing by bivalves, and demonstrates how it relates to studies utilizing plastic particles. In particular, the effects of particle size, shape, and surface properties on capture, preferential ingestion, post-ingestive sorting, and egestion are summarized. The implications of particle selection for the use of bivalves as bioindicators of microplastic pollution in the environment are discussed. Only through a full understanding of the types of plastic particles ingested and egested by bivalves can internal exposure, toxic effects, and trophic transfer of microplastics be assessed adequately.

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The capabilities of bivalve molluscs to feed selectively have been well documented, and physicochemical properties of particles have been implicated as possible factors in the selection process. In this study, the surface-property profiles of nine different microalgal species were determined by characterizing the surface charge, wettability (= contact angle), and surface carbohydrate moieties. Three fluorescein isothiocyanate (FITC) conjugated lectins were used to characterize carbohydrate moieties, including concanavalin A (ConA), Pisum sativum agglutinin (PEA), and wheat germ agglutinin (WGA). Distinct surface-property profiles were identified using linear discriminant analysis (DA) and used to design mixed-algal feeding experiments to assess particle selection by the blue mussel Mytilus edulis and the eastern oyster Crassostrea virginica. Results demonstrated preferential ingestion of some algal species over others, with strong rejection of some species (e.g. Pavlova lutheri and Prasinocladus marinus). These data were then used to develop DA and multiple linear regression models that considered the quantified surface properties and microalgal fates (rejected, ingested, or no selection) to examine determinants of selection. The DA model correctly classified 58% of the selection outcomes in mussels and 57% in oysters. Wettability was the most important factor in predicting selection in mussels, and surface charge was most important for oysters. In the multiple linear regression

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