Distinct responses to warming within picoplankton communities across an environmental gradient.

Picophytoplankton are a ubiquitous component of marine plankton communities and are expected to be favored by global increases in seawater temperature and stratification associated with climate change. Eukaryotic and prokaryotic picophytoplankton have distinct ecology, and global models predict that the two groups will respond differently to future climate scenarios. At a nearshore observatory on the Northeast US Shelf, however, decades of year-round monitoring have shown these two groups to be highly synchronized in their responses to environmental variability. To reconcile the differences between regional and global predictions for picophytoplankton dynamics, we here investigate the picophytoplankton community across the continental shelf gradient from the nearshore observatory to the continental slope. We analyze flow cytometry data from 22 research cruises, comparing the response of picoeukaryote and Synechococcus communities to environmental variability across time and space. We find that the mechanisms controlling picophytoplankton abundance differ across taxa, season, and distance from shore. Like the prokaryote, Synechococcus, picoeukaryote division rates are limited nearshore by low temperatures in winter and spring, and higher temperatures offshore lead to an earlier spring bloom. Unlike Synechococcus, picoeukaryote concentration in summer decreases dramatically in offshore surface waters and exhibits deeper subsurface maxima. The offshore picoeukaryote community appears to be nutrient limited in the summer and subject to much greater loss rates than Synechococcus. This work both produces and demonstrates the necessity of taxon- and site-specific knowledge for accurately predicting the responses of picophytoplankton to ongoing environmental change.

Temperature dependence of parasitoid infection and abundance of a diatom revealed by automated imaging and classification.

Diatoms are a group of phytoplankton that contribute disproportionately to global primary production. Traditional paradigms that suggest diatoms are consumed primarily by larger zooplankton are challenged by sporadic parasitic "epidemics" within diatom populations. However, our understanding of diatom parasitism is limited by difficulties in quantifying these interactions. Here, we observe the dynamics of Cryothecomonas aestivalis (a protist) infection of an important diatom on the Northeast U.S. Shelf (NES), Guinardia delicatula, with a combination of automated imaging-in-flow cytometry and a convolutional neural network image classifier. Application of the classifier to >1 billion images from a nearshore time series and >20 survey cruises across the broader NES reveals the spatiotemporal gradients and temperature dependence of G. delicatula abundance and infection dynamics. Suppression of parasitoid infection at temperatures <4 °C drives annual cycles in both G. delicatula infection and abundance, with an annual maximum in infection observed in the fall-winter preceding an annual maximum in host abundance in the winter-spring. This annual cycle likely varies spatially across the NES in response to variable annual cycles in water temperature. We show that infection remains suppressed for ~2 mo following cold periods, possibly due to temperature-induced local extinctions of the C. aestivalis strain(s) that infect G. delicatula. These findings have implications for predicting impacts of a warming NES surface ocean on G. delicatula abundance and infection dynamics and demonstrate the potential of automated plankton imaging and classification to quantify phytoplankton parasitism in nature across unprecedented spatiotemporal scales.