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IntroductionMarine particles form in the ocean surface sink through the water column into the deep ocean, sequestering carbon. Microorganisms inhabit and consume carbon in these particles. The East Pacific Rise (EPR) harbors both an Oxygen Deficient Zone (ODZ) and a non-buoyant plume region formed from hydrothermal vents located on the ocean floor, allowing us to explore relationships between microbial community and particle size between a range of environments. MethodsIn this study, we quantified microbial diversity using a fractionation method that separated particles into seven fine scale fractions (0.2–1.2, 1.2–5, 5–20, 20–53, 53–180,180–500, >500 μm), and included a spike-in standard for sequencing the 16S rRNA gene. Size fractionated organic carbon into the same fractions enabled the calculation of bacterial 16S rRNA copies per μg C and per liter. ResultsThere was a large increase in the bacterial 16S rRNA copies/ug C and copies/L on particles >180 μm between the upper water column and the deep water column. Though the total concentration of organic C in particles decreased in the deep water column, the density of bacteria on large particles increased at depth. The microbial community varied statistically significantly as a function of particle size and depth. Quantitative abundance estimates found that ostensibly obligate free-living microbes, such as SAR11 and Thaumarcheota, were more abundant in the free-living fraction but also common and abundant in the particulate size fractions. Conversely, ostensibly obligate particle attached bacteria such as members of Bacteroidetes and Planctomycetes, while most abundant on particles, were also present in the free living fraction. Total bacterial abundance, and the abundance of many taxonomic groups, increased in the ODZ region, particularly in the free-living fraction. Contrastingly, in the non-buoyant plume, there were highly abundant bacteria in the 5–20 and 20–53 μm fractions but reduced bacteria present in the 53–180 and 180–500 μm fractions. ConclusionQuantitative examination of microbial communities highlights the distribution of microbial taxa unburdened by compositional effects. These data are congruent with existing models which suggest high levels of exchange between particle-attached and free-living communities. 

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. 

Abstract. Recent earth system models predict a 10 %–20 % decrease in particulate organic carbon export from the surface ocean by the end of the21st century due to global climate change. This decline is mainly caused by increased stratification of the upper ocean, resulting in reducedshallow subsurface nutrient concentrations and a slower supply of nutrients to the surface euphotic zone in low latitudes. These predictions,however, do not typically account for associated changes in remineralization depths driven by sinking-particle size. Here we combinesatellite-derived export and particle size maps with a simple 3-D global biogeochemical model that resolves dynamic particle size distributions toinvestigate how shifts in particle size may buffer or amplify predicted changes in surface nutrient supply and therefore export production. We showthat higher export rates are empirically correlated with larger sinking particles and presumably larger phytoplankton, particularly in tropical andsubtropical regions. Incorporating these empirical relationships into our global model shows that as circulation slows, a decrease in export isassociated with a shift towards smaller particles, which sink more slowly and are thus remineralized shallower. This shift towards shallowerremineralization in turn leads to greater recycling of nutrients in the upper water column and thus faster nutrient recirculation into the euphoticzone. The end result is a boost in productivity and export that counteracts the initial circulation-driven decreases. This negative feedbackmechanism (termed the particle-size–remineralization feedback) slows export decline over the next century by ∼ 14 % globally (from −0.29to −0.25 GtC yr−1) and by ∼ 20 % in the tropical and subtropical oceans, where export decreases are currently predicted tobe greatest. Our findings suggest that to more accurately predict changes in biological pump strength under a warming climate, earth system modelsshould include dynamic particle-size-dependent remineralization depths. 

Abstract Models and observations suggest that particle flux attenuation is lower across the mesopelagic zone of anoxic environments compared to oxic environments. Flux attenuation is controlled by microbial metabolism as well as aggregation and disaggregation by zooplankton, all of which shape the relative abundance of differently sized particles. Observing and modeling particle spectra can provide information about the contributions of these processes. We measured particle size spectrum profiles at one station in the oligotrophic Eastern Tropical North Pacific Oxygen Deficient Zone (ETNP ODZ) using an underwater vision profiler (UVP), a high‐resolution camera that counts and sizes particles. Measurements were taken at different times of day, over the course of a week. Comparing these data to particle flux measurements from sediment traps collected over the same time‐period allowed us to constrain the particle size to flux relationship, and to generate highly resolved depth and time estimates of particle flux rates. We found that particle flux attenuated very little throughout the anoxic water column, and at some time points appeared to increase. Comparing our observations to model predictions suggested that particles of all sizes remineralize more slowly in the ODZ than in oxic waters, and that large particles disaggregate into smaller particles, primarily between the base of the photic zone and 500 m. Acoustic measurements of multiple size classes of organisms suggested that many organisms migrated, during the day, to the region with high particle disaggregation. Our data suggest that diel‐migrating organisms both actively transport biomass and disaggregate particles in the ODZ core.