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Abstract Particulate phases transport trace metals (TM) and thereby exert a major control on TM distribution in the ocean. Particulate TMs can be classified by their origin as lithogenic (crustal material), biogenic (cellular), or authigenic (formed in situ), but distinguishing these fractions analytically in field samples is a challenge often addressed using operational definitions and assumptions. These different phases require accurate characterization because they have distinct roles in the biogeochemical iron cycle. Particles collected from the upper 2,000 m of the northwest subtropical Atlantic Ocean over four seasonal cruises throughout 2019 were digested with a chemical leach to operationally distinguish labile particulate material from refractory lithogenics. Direct measurements of cellular iron (Fe) were used to calculate the biogenic contribution to the labile Fe fraction, and any remaining labile material was defined as authigenic. Total particulate Fe (PFe) inventories varied <15% between seasons despite strong seasonality in dust inputs. Across seasons, the total PFe inventory (±1SD) was composed of 73 ± 13% lithogenic, 18 ± 7% authigenic, and 10 ± 8% biogenic Fe above the deep chlorophyll maximum (DCM), and 69 ± 8% lithogenic, 30 ± 8% authigenic, and 1.1 ± 0.5% biogenic Fe below the DCM. Data from three other ocean regions further reveal the importance of the authigenic fraction across broad productivity and Fe gradients, comprising ca. 20%–27% of total PFe. 

Abstract Ocean ecosystem models predict that warming and increased surface ocean stratification will trigger a series of ecosystem events, reducing the biological export of particulate carbon to the ocean interior. We present a nearly three-decade time series from the open ocean that documents a biological response to ocean warming and nutrient reductions wherein particulate carbon export is maintained, counter to expectations. Carbon export is maintained through a combination of phytoplankton community change to favor cyanobacteria with high cellular carbon-to-phosphorus ratios and enhanced shallow phosphorus recycling leading to increased nutrient use efficiency. These results suggest that surface ocean ecosystems may be more responsive and adapt more rapidly to changes in the hydrographic system than is currently envisioned in earth ecosystem models, with positive consequences for ocean carbon uptake. 

Abstract Mesozooplankton is a very diverse group of small animals ranging in size from 0.2 to 20 mm not able to swim against ocean currents. It is a key component of pelagic ecosystems through its roles in the trophic networks and the biological carbon pump. Traditionally studied through microscopes, recent methods have been however developed to rapidly acquire large amounts of data (morphological, molecular) at the individual scale, making it possible to study mesozooplankton using a trait‐based approach. Here, combining quantitative imaging with metabarcoding time‐series data obtained in the Sargasso Sea at the Bermuda Atlantic Time‐series Study (BATS) site, we showed that organisms' transparency might be an important trait to also consider regarding mesozooplankton impact on carbon export, contrary to the common assumption that just size is the master trait directing most mesozooplankton‐linked processes. Three distinct communities were defined based on taxonomic composition, and succeeded one another throughout the study period, with changing levels of transparency among the community. A co‐occurrences' network was built from metabarcoding data revealing six groups of taxa. These were related to changes in the functioning of the ecosystem and/or in the community's morphology. The importance of Diel Vertical Migration at BATS was confirmed by the existence of a group made of taxa known to be strong migrators. Finally, we assessed if metabarcoding can provide a quantitative approach to biomass and/or abundance of certain taxa. Knowing more about mesozooplankton diversity and its impact on ecosystem functioning would allow to better represent them in biogeochemical models. 

Deficient myelination of the brain is associated with neurodevelopmental delays, particularly in high-risk infants, such as those born small in relation to their gestational age (SGA). New methods are needed to further study this condition. Here, we employ Color Spatial Light Interference Microscopy (cSLIM), which uses a brightfield objective and RGB camera to generate pathlength-maps with nanoscale sensitivity in conjunction with a regular brightfield image. Using tissue sections stained with Luxol Fast Blue, the myelin structures were segmented from a brightfield image. Using a binary mask, those portions were quantitatively analyzed in the corresponding phase maps. We first used the CLARITY method to remove tissue lipids and validate the sensitivity of cSLIM to lipid content. We then applied cSLIM to brain histology slices. These specimens are from a previous MRI study, which demonstrated that appropriate for gestational age (AGA) piglets have increased internal capsule myelination (ICM) compared to small for gestational age (SGA) piglets and that a hydrolyzed fat diet improved ICM in both. The identity of samples was blinded until after statistical analyses.