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Abstract In vitro incubations using natural marine communities can provide insight into community structure and function in ways that are challenging through field observations alone. We have designed a minimal metal incubation system for controlled and repeatable experimentation of microbial communities. The systems, dubbed Pelagic Ecosystem Research Incubators (PERIcosms), are 115 L, conical tanks designed to sample suspended, settled, and wall associated material for month long periods. PERIcosms combine some of the ecological advantages of large volume mesocosm incubations with the experimental ease and replication of bottle incubations, and their design is accessible for use by researchers without specialized training or travel to a designated incubation facility. Here, we provide a detailed description for the construction and implementation of PERIcosms and demonstrate their potential to promote replicable, diverse communities for several weeks under clean conditions using time‐series results from two field experiments. One field experiment utilized coastal waters collected from Santa Catalina Island, CA and the other oligotrophic waters collected offshore of Honolulu, HI. Biomass metrics (chlorophyll a and particulate carbon) along with 16S/18S DNA based community composition assessments were conducted to show that communities contained within PERIcosms remained alive and diverse for several weeks using a semi‐continuous culturing approach. We detail trace metal clean techniques that can be used to minimize external contamination, particularly for low dissolved iron environments. PERIcosms have the potential to facilitate natural community incubations which are needed to continue advancing our understanding of microbial ecology and geochemistry. 

Abstract Marine protists and their metabolic activities are intricately tied to the cycling of nutrients and the flow of energy through microbial food webs. Physiochemical changes in the environment, such as those that result from mesoscale eddies, may impact protistan communities, but the effects that such changes have on protists are poorly known. A metatranscriptomic study was conducted to investigate how eddies affected protists at adjacent cyclonic and anticyclonic eddy sites in the oligotrophic ocean at four depths from 25 to 250 m. Eddy polarity impacted protists at all depths sampled, although the effects of eddy polarity were secondary to the impact of depth across the depth range. Eddy‐induced vertical shifts in the water column yielded differences in the cyclonic and anticyclonic eddy protistan communities, and these differences were the most pronounced at and just below the deep chlorophyll maximum. An analysis of transcripts associated with protistan nutritional physiology at 150 m revealed that cyclonic eddies may support a more heterotrophic community, while anticyclonic eddies promote a more phototrophic community. The results of this study indicate that eddies alter the metabolism of protists particularly in the lower euphotic zone and may therefore impact carbon export from the euphotic zone. 

Abstract Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. In addition, the GAM transformation increased the predictive power (F1 score) of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results. 

Sinking particles are a critical conduit for the export of organic material from surface waters to the deep ocean. Despite their importance in oceanic carbon cycling and export, little is known about the biotic composition, origins, and variability of sinking particles reaching abyssal depths. Here, we analyzed particle-associated nucleic acids captured and preserved in sediment traps at 4,000-m depth in the North Pacific Subtropical Gyre. Over the 9-month time-series, Bacteria dominated both the rRNA-gene and rRNA pools, followed by eukaryotes (protists and animals) and trace amounts of Archaea. Deep-sea piezophile-like Gammaproteobacteria, along with Epsilonproteobacteria, comprised >80% of the bacterial inventory. Protists (mostly Rhizaria, Syndinales, and ciliates) and metazoa (predominantly pelagic mollusks and cnidarians) were the most common sinking particle-associated eukaryotes. Some near-surface water-derived eukaryotes, especially Foraminifera, Radiolaria, and pteropods, varied greatly in their abundance patterns, presumably due to sporadic export events. The dominance of piezophile-like Gammaproteobacteria and Epsilonproteobacteria, along with the prevalence of their nitrogen cycling-associated gene transcripts, suggested a central role for these bacteria in the mineralization and biogeochemical transformation of sinking particulate organic matter in the deep ocean. Our data also reflected several different modes of particle export dynamics, including summer export, more stochastic inputs from the upper water column by protists and pteropods, and contributions from sinking mid- and deep-water organisms. In total, our observations revealed the variable and heterogeneous biological origins and microbial activities of sinking particles that connect their downward transport, transformation, and degradation to deep-sea biogeochemical processes.