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In ocean waters, anaerobic microbial respiration should be confined to the anoxic waters found in coastal regions and tropical oxygen minimum zones, where it is energetically favourable. However, recent molecular and geochemical evidence has pointed to a much broader distribution of denitrifying and sulfate-reducing microbes. Anaerobic metabolisms are thought to thrive in microenvironments that develop inside sinking organic aggregates, but the global distribution and geochemical significance of these microenvironments is poorly understood. Here, we develop a new size-resolved particle model to predict anaerobic respiration from aggregate properties and seawater chemistry. Constrained by observations of the size spectrum of sinking particles, the model predicts that denitrification and sulfate reduction can be sustained throughout vast, hypoxic expanses of the ocean, and could explain the trace metal enrichment observed in particles due to sulfide precipitation. Globally, the expansion of the anaerobic niche due to particle microenvironments doubles the rate of water column denitrification compared with estimates based on anoxic zones alone, and changes the sensitivity of the marine nitrogen cycle to deoxygenation in a warming climate.

An in situ imaging technique has been used to show that large rhizarian plankton represent a much larger biomass than previously thought, meaning that they are likely to make an important contribution to ocean ecosystems. Rhizaria are major players in ocean ecology Ocean ecosystems are inhabited by planktonic organisms spanning a wide size range, with large zooplankton feeding on smaller species and thereby contributing to the marine food web and carbon cycling. However, our understanding of the role and contribution of fragile and large zooplankton to the marine ecosystem is limited. Using data collected by an in situ imaging system during the Tara Oceans global survey, Tristan Biard et al . quantified the respective contributions of Rhizaria (a broad phylogenetic group of marine protists) and other zooplankton larger than 600 μm, finding that they represent a much larger biomass than previously appreciated, contributing up to 5.2% of the total oceanic biota carbon reservoir. These findings highlight the important contribution of Rhizaria to plankton biomass, primary productivity and other biogeochemical processes in the oceans. Planktonic organisms play crucial roles in oceanic food webs and global biogeochemical cycles 1 , 2 . Most of our knowledge about the ecological impact of large zooplankton stems from research on abundant and robust crustaceans, and in particular copepods 3 , 4 . A number of the other organisms that comprise planktonic communities are fragile, and therefore hard to sample and quantify, meaning that their abundances and effects on oceanic ecosystems are poorly understood. Here, using data from a worldwide in situ imaging survey of plankton larger than 600 μm, we show that a substantial part of the biomass of this size fraction consists of giant protists belonging to the Rhizaria, a super-group of mostly fragile unicellular marine organisms that includes the taxa Phaeodaria and Radiolaria (for example, orders Collodaria and Acantharia). Globally, we estimate that rhizarians in the top 200 m of world oceans represent a standing stock of 0.089 Pg carbon, equivalent to 5.2% of the total oceanic biota carbon reservoir 5 . In the vast oligotrophic intertropical open oceans, rhizarian biomass is estimated to be equivalent to that of all other mesozooplankton (plankton in the size range 0.2–20 mm). The photosymbiotic association of many rhizarians with microalgae may be an important factor in explaining their distribution. The previously overlooked importance of these giant protists across the widest ecosystem on the planet 6 changes our understanding of marine planktonic ecosystems.

The tropical Atlantic upper-ocean circulation experiences multiannual to decadal changes associated with different climate modes and is simultaneously adjusting to climate warming. The most energetic current in the tropical Atlantic is the Equatorial Undercurrent (EUC), which flows eastwards along the Equator. On the basis of long-term moored observations, we show that the EUC strengthened by more than 20% from 2008 to 2018. The intensification of the EUC is associated with increasing subsurface oxygen concentrations and a thickening of the upper-ocean oxygenated layer in the equatorial Atlantic. These changes counteract climate-warming-induced deoxygenation in the region. The EUC strengthening is found to be mainly forced by trade wind changes in the western tropical North Atlantic. A 60-yr dataset reveals that the recent oxygen increase in the upper equatorial Atlantic is associated with multidecadal variability. This variability is characterized by low oxygen concentrations in the 1990s and early 2000s, and high oxygen concentrations in the 1960s and 1970s. The observed oxygen variability seems to be linked to a compression and expansion of the habitat of tropical pelagic fish, and must be accounted for when evaluating the possible consequences of deoxygenation for marine ecosystems and fisheries. Recent strengthening of the Equatorial Undercurrent counteracts warming-induced deoxygenation in the equatorial Atlantic, according to an analysis of long-term moored observations.

Anaerobic oxidation of ammonium (anammox) in oxygen minimum zones (OMZs) is a major pathway of oceanic nitrogen loss. Ammonium released from sinking particles has been suggested to fuel this process. During cruises to the Peruvian OMZ in April–June 2017 we found that anammox rates are strongly correlated with the volume of small particles (128–512 µm), even though anammox bacteria were not directly associated with particles. This suggests that the relationship between anammox rates and particles is related to the ammonium released from particles by remineralization. To investigate this, ammonium release from particles was modelled and theoretical encounters of free-living anammox bacteria with ammonium in the particle boundary layer were calculated. These results indicated that small sinking particles could be responsible for ~75% of ammonium release in anoxic waters and that free-living anammox bacteria frequently encounter ammonium in the vicinity of smaller particles. This indicates a so far underestimated role of abundant, slow-sinking small particles in controlling oceanic nutrient budgets, and furthermore implies that observations of the volume of small particles could be used to estimate N-loss across large areas. Up to 40% of the ocean’s fixed nitrogen is lost in oxygen minimum zones (OMZs) by anammox, but despite the importance of this process, nitrogen loss patterns in OMZs are difficult to predict. Here the authors show that ammonium release from small particles is a major control of anammox in the Peruvian OMZ.

In this work, we present MorphoCluster, a software tool for data-driven, fast, and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue to increase in the coming years. Still, this data requires interpretation. MorphoCluster augments the human ability to discover patterns and perform object classification in large amounts of data by embedding unsupervised clustering in an interactive process. By aggregating similar images into clusters, our novel approach to image annotation increases consistency, multiplies the throughput of an annotator, and allows experts to adapt the granularity of their sorting scheme to the structure in the data. By sorting a set of 1.2 M objects into 280 data-driven classes in 71 h (16 k objects per hour), with 90% of these classes having a precision of 0.889 or higher. This shows that MorphoCluster is at the same time fast, accurate, and consistent; provides a fine-grained and data-driven classification; and enables novelty detection.

Sea ice is permeated by small brine channels, which are characterised by sub-zero temperatures and varying salinities. Despite sometimes extreme conditions a diverse fauna and flora thrives within the brine channels. The dominant calanoid copepods of Antarctic sea ice are Stephos longipes and Paralabidocera antarctica. Here, I report for the first time thermal hysteresis (TH) in the haemolymph of a crustacean, S. longipes, whereas P. antarctica has no such activity. TH, the non-colligative prevention of ice growth, seems to enable S. longipes to exploit all available microhabitats within sea ice, especially the surface layer, in which strong temperature fluctuations can occur. In contrast, P. antarctica only thrives within the lowermost centimetres of sea ice, where temperature fluctuations are moderate. S. longipes possesses two isoforms of a protein with TH activity. A high homology to a group of (putative) antifreeze proteins from diatoms, bacteria and a snow mold and, in contrast, no homologs in any metazoan lineage suggest that this protein was obtained through horizontal gene transfer (HGT). Further analysis of available sequence data from sea-ice organisms indicates that these antifreeze proteins were probably transferred horizontally several times. Temperature and salinity fluctuations within the brine channel system are proposed to provide “natural transformation” conditions enabling HGT and thus making this habitat a potential “hot spot” for HGT.

In the Peruvian upwelling system, the mesopelagic oxygen minimum zone (OMZ) is the main vertically structuring feature of the pelagic habitat. Several zooplankton and nekton species undertake diel vertical migrations (DVMs) into anoxic depths. It has been argued that these migrations contribute substantially to the oxygen consumption as well as excretion of dissolved compounds (in particular ammonium) in subsurface waters. However, metabolic suppression as a response to low ambient oxygen partial pressure ($pO_2$) has not been accounted for in these estimates. Here, we present estimates of zooplankton- and nekton-mediated oxygen consumption and ammonium release based on vertically stratified net hauls (day/night, upper 1000m). Samples were scanned, followed by image analysis and size-/taxon-specific estimation of metabolic rates of all identified organisms as a function of their biomass as well as ambient temperature and $pO_2$. The main crustacean migrants were euphausiids (mainly \\textit{E. mucronata}) on offshore stations and the commercially exploited squat lobster \\textit{Pleuroncodes monodon} on the upper shelf, where it often undertakes migration to the seafloor during the day. Correction for metabolic suppression results in a substantial reduction of both respiration and ammonium excretion within the OMZ core. Ignoring this mechanism leads to tenfold higher estimate of DVM-mediated active export of carbon by respiration to below 100 m depth at deep-water stations. The DVM-mediated release of ammonium by euphausiids into the 200 to 400 m depth layer ranges between $0$ and $36.81\\ \\mu mol\\ NH_4\\ m^{-2} d^{-1}$, which is insufficient to balance published estimates of ammonium uptake rates due to anammox. It seems critical to account for the modulation of zooplankton metabolic activity at low oxygen in order to correctly represent the contribution of migrating species to the biological pump.

Image annotation is a time-consuming and costly task. Previously, we published MorphoCluster as a novel image annotation tool to address problems of conventional, classifier-based image annotation approaches: their limited efficiency, training set bias and lack of novelty detection. MorphoCluster uses clustering and similarity search to enable efficient, computer-assisted image annotation. In this work, we provide a deeper analysis of this approach. We simulate the actions of a MorphoCluster user to avoid extensive manual annotation runs. This simulation is used to test supervised, unsupervised and transfer representation learning approaches. Furthermore, shrunken k-means and partially labeled k-means, two new clustering algorithms that are tailored specifically for the MorphoCluster approach, are compared to the previously used HDBSCAN*. We find that labeled training data improve the image representations, that unsupervised learning beats transfer learning and that all three clustering algorithms are viable options, depending on whether completeness, efficiency or runtime is the priority. The simulation results support our earlier finding that MorphoCluster is very efficient and precise. Within the simulation, more than five objects per simulated click are being annotated with 95% precision.

Deep learning has been successfully applied to many classification problems including underwater challenges. However, a long-standing issue with deep learning is the need for large and consistently labeled datasets. Although current approaches in semi-supervised learning can decrease the required amount of annotated data by a factor of 10 or even more, this line of research still uses distinct classes. For underwater classification, and uncurated real-world datasets in general, clean class boundaries can often not be given due to a limited information content in the images and transitional stages of the depicted objects. This leads to different experts having different opinions and thus producing fuzzy labels which could also be considered ambiguous or divergent. We propose a novel framework for handling semi-supervised classifications of such fuzzy labels. It is based on the idea of overclustering to detect substructures in these fuzzy labels. We propose a novel loss to improve the overclustering capability of our framework and show the benefit of overclustering for fuzzy labels. We show that our framework is superior to previous state-of-the-art semi-supervised methods when applied to real-world plankton data with fuzzy labels. Moreover, we acquire 5 to 10% more consistent predictions of substructures.

The January 2022 eruption of the Hunga Tonga-Hunga Ha’apai (HTHH) volcano discharged 2,900 teragrams of ejecta, most of which was deposited in the South Pacific Ocean. Here we investigate its impact on the biogeochemistry of the South Pacific Gyre (SPG) using samples collected during the GEOTRACES cruise GP21 in February-April 2022. Surface water neodymium isotopes and rare earth element compositions showed a marked volcanic impact in the western SPG, potentially extending to the eastern region. Increasing trace metal concentrations in surface waters and chlorophyll-a inventories in euphotic layers between the eastern and western SPG further suggest that the volcanic eruption supplied (micro)nutrients potentially stimulating a biological response. We estimate that the HTHH eruption released up to 0.16 kt of neodymium and 32 kt of iron into the SPG, which is comparable to the annual global dust-borne Nd flux and the annual dust-borne Fe flux to the entire SPG, respectively. Surface water neodymium isotopes and rare earth element compositions reveal a marked impact from the January 2022 Hunga Tonga-Hunga Ha’apai eruption in the western South Pacific, with released trace metals potentially stimulating biological responses.