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Microscopic sessile suspension feeders live attached to surfaces and, by consuming bacteria-sized prey and by being consumed, they form an important part of aquatic ecosystems. Their environmental impact is mediated by their feeding rate, which depends on a self-generated feeding current. The feeding rate has been hypothesized to be limited by recirculating eddies that cause the organisms to feed from water that is depleted of food particles. However, those results considered organisms in still water, while ambient flow is often present in their natural habitats. We show, using a point-force model, that even very slow ambient flow, with speed several orders of magnitude less than that of the self-generated feeding current, is sufficient to disrupt the eddies around perpendicular suspension feeders, providing a constant supply of food-rich water. However, the feeding rate decreases in external flow at a range of non-perpendicular orientations due to the formation of recirculation structures not seen in still water. We quantify the feeding flow and observe such recirculation experimentally for the suspension feeder Vorticella convallaria in external flows typical of streams and rivers. 

Abstract Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab‐based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.