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Microbial community dynamics on sinking particles control the amount of carbon that reaches the deep ocean and the length of time that carbon is stored, with potentially profound impacts on Earth’s climate. A mechanistic understanding of the controls on sinking particle distributions has been hindered by limited depth- and time-resolved sampling and methods that cannot distinguish individual particles. Here, we analyze microbial communities on nearly 400 individual sinking particles in conjunction with more conventional composite particle samples to determine how particle colonization and community assembly might control carbon sequestration in the deep ocean. We observed community succession with corresponding changes in microbial metabolic potential on the larger sinking particles transporting a significant fraction of carbon to the deep sea. Microbial community richness decreased as particles aged and sank; however, richness increased with particle size and the attenuation of carbon export. This suggests that the theory of island biogeography applies to sinking marine particles. Changes in POC flux attenuation with time and microbial community composition with depth were reproduced in a mechanistic ecosystem model that reflected a range of POC labilities and microbial growth rates. Our results highlight microbial community dynamics and processes on individual sinking particles, the isolation of which is necessary to improve mechanistic models of ocean carbon uptake.

 

Autonomous sensors for gravitational carbon flux in the ocean are critically needed, because of uncertainties in the projected response of the biological carbon pump (BCP) to climate change, and the proposed, engineered acceleration of the BCP to sequester carbon dioxide in the ocean. Optical sediment trap (OST) sensors directly sense fluxes of sinking particles in a manner that is independent of, and complementary to, other autonomous, sensor‐derived estimates of BCP fluxes. However, limited intercalibrations of OSTs with traditional sediment traps and uncharacterized, potential biases have limited their broad adoption. A global field data set spanning three orders of magnitude in carbon flux was compiled and used to develop empirical models predicting particulate organic carbon flux from OST observations, and intercalibrating different sensor designs. These data provided valuable constraints on the uncertainty in the predicted carbon flux and showed a quantitative, theoretically consistent relationship between observations from OSTs with collimated and diffuse optical geometries. While not designed for this purpose, commercial beam transmissometers have been used as OSTs, so two models were developed quantifying the biases arising from the transmissometer's housing geometry and optical beam diameter. Finally, an algorithm for the quality control of beam transmissometer‐derived OST data was optimized using sensitivity tests. The results of this study support the expansion of OST‐based gravitational carbon flux measurements and provide a framework for interpretation of OST measurements alongside other gravitational particle flux observations. These findings also suggest key features that should be included in designs of future, purpose‐built OST sensors.

 

Surface phytoplankton communities were linked with the carbon they export into the deep ocean by comparing 18 S rRNA gene sequence communities from surface seawater and individually isolated sinking particles. Particles were collected in sediment traps deployed at locations in the North Pacific subtropical gyre and the California Current. DNA was isolated from individual particles, bulk-collected trap particles, and the surface seawater. The relative sequence abundance of exported phytoplankton taxa in the surface water varied across functional groups and ecosystems. Of the sequences detected in sinking particles, about half were present in large (>300 μm), individually isolated particles and primarily belonged to taxa with small cell sizes (<50 µm). Exported phytoplankton taxa detected only in bulk trap samples, and thus presumably packaged in the smaller sinking size fraction, contained taxa that typically have large cell sizes (>500 μm). The effect of particle degradation on the detectable 18 S rRNA gene community differed across taxa, and differences in community composition among individual particles from the same location largely reflected differences in relative degradation state. Using these data and particle imaging, we present an approach that incorporates genetic diversity into mechanistic models of the ocean’s biological carbon pump, which will lead to better quantification of the ocean’s carbon cycle.

 

To better quantify the ocean's biological carbon pump, we resolved the diversity of sinking particles that transport carbon into the ocean's interior, their contribution to carbon export, and their attenuation with depth. Sinking particles collected in sediment trap gel layers from four distinct ocean ecosystems were imaged, measured, and classified. The size and identity of particles was used to model their contribution to particulate organic carbon (POC) flux. Measured POC fluxes were reasonably predicted by particle images. Nine particle types were identified, and most of the compositional variability was driven by the relative contribution of aggregates, long cylindrical fecal pellets, and salp fecal pellets. While particle composition varied across locations and seasons, the entire range of compositions was measured at a single well‐observed location in the subarctic North Pacific over one month, across 500 m of depth. The magnitude of POC flux was not consistently associated with a dominant particle class, but particle classes did influence flux attenuation. Long fecal pellets attenuated most rapidly with depth whereas certain other classes attenuated little or not at all with depth. Small particles (<100 μm) consistently contributed ∼5% to total POC flux in samples with higher magnitude fluxes. The relative importance of these small particle classes (spherical mini pellets, short oval fecal pellets, and dense detritus) increased in low flux environments (up to 46% of total POC flux). Imaging approaches that resolve large variations in particle composition across ocean basins, depth, and time will help to better parameterize biological carbon pump models.

 

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set. 

Diatoms are highly productive single‐celled algae that form an intricately patterned silica cell wall after every cell division. They take up and utilize silicic acid from seawater via silicon transporter (SIT) proteins. This study examined the evolution of theSITgene family to identify potential genetic adaptations that enable diatoms to thrive in the modern ocean. By searching for sequence homologs in available databases, the diversity of organisms found to encodeSITs increased substantially and included all major diatom lineages and other algal protists. A bacterial‐encoded gene with homology toSITsequences was also identified, suggesting that a lateral gene transfer event occurred between bacterial and protist lineages. In diatoms, theSITgenes diverged and diversified to produce five distinct clades. The most basalSITclades were widely distributed across diatom lineages, while the more derived clades were lineage‐specific, which together produced a distinct repertoire ofSITtypes among major diatom lineages. Differences in the predicted protein functional domains encoded amongSITclades suggest that the divergence of clades resulted in functional diversification amongSITs. Both laboratory cultures and natural communities changed transcription of eachSITclade in response to experimental or environmental growth conditions, with distinct transcriptional patterns observed among clades. Together, these data suggest that the diversification ofSITs within diatoms led to specialized adaptations among diatoms lineages, and perhaps their dominant ability to take up silicic acid from seawater in diverse environmental conditions.