Towards a scientific community consensus on designating Vulnerable Marine Ecosystems from imagery.

Management of deep-sea fisheries in areas beyond national jurisdiction by Regional Fisheries Management Organizations/Arrangements (RFMO/As) requires identification of areas with Vulnerable Marine Ecosystems (VMEs). Currently, fisheries data, including trawl and longline bycatch data, are used by many RFMO/As to inform the identification of VMEs. However, the collection of such data creates impacts and there is a need to collect non-invasive data for VME identification and monitoring purposes. Imagery data from scientific surveys satisfies this requirement, but there currently is no established framework for identifying VMEs from images. Thus, the goal of this study was to bring together a large international team to determine current VME assessment protocols and establish preliminary global consensus guidelines for identifying VMEs from images. An initial assessment showed a lack of consistency among RFMO/A regions regarding what is considered a VME indicator taxon, and hence variability in how VMEs might be defined. In certain cases, experts agreed that a VME could be identified from a single image, most often in areas of scleractinian reefs, dense octocoral gardens, multiple VME species' co-occurrence, and chemosynthetic ecosystems. A decision flow chart is presented that gives practical interpretation of the FAO criteria for single images. To further evaluate steps of the flow chart related to density, data were compiled to assess whether scientists perceived similar density thresholds across regions. The range of observed densities and the density values considered to be VMEs varied considerably by taxon, but in many cases, there was a statistical difference in what experts considered to be a VME compared to images not considered a VME. Further work is required to develop an areal extent index, to include a measure of confidence, and to increase our understanding of what levels of density and diversity correspond to key ecosystem functions for VME indicator taxa. Based on our results, the following recommendations are made: 1. There is a need to establish a global consensus on which taxa are VME indicators. 2. RFMO/As should consider adopting guidelines that use imagery surveys as an alternative (or complement) to using bycatch and trawl surveys for designating VMEs. 3. Imagery surveys should also be included in Impact Assessments. And 4. All industries that impact the seafloor, not just fisheries, should use imagery surveys to detect and identify VMEs.

Zooplankton as a suitable tool for microplastic research.

In recent years, significant efforts have been dedicated to measuring and comprehending the impact of microplastics (MPs) in the ocean. Despite harmonization guidelines for MPs research, discrepancies persist in the applied methodologies and future challenges, mostly for the smaller fractions (< 100 µm). Whether intentional or accidental, ingesting plastic particles by zooplankton can lead to incorporating this pollutant into aquatic food chains. Therefore, zooplankton can serve as a suitable proxy tool for assessing the presence of plastic particles in ocean waters. However, reliable information is essential for conducting experimental laboratory studies on the impact of MPs ingestion by zooplankton organisms. Using zooplankton as a research tool for MPs offers numerous advantages, including similar sampling methodologies and study techniques as MPs and particle data integration over space and time. The scientific community can gain novel perspectives by merging zooplankton studies with MPs research. This review explores key aspects of using zooplankton as a tool for MPs research in water samples, encompassing various views such as particles ingestion in natural environments, particle quantification in zooplankton samples (past and future), ecotoxicological and toxicology model studies. By leveraging the potential of zooplankton research, advancements can be made in developing innovative techniques for MPs analysis.

Multimodal image and spectral feature learning for efficient analysis of water-suspended particles.

We have developed a method to combine morphological and chemical information for the accurate identification of different particle types using optical measurement techniques that require no sample preparation. A combined holographic imaging and Raman spectroscopy setup is used to gather data from six different types of marine particles suspended in a large volume of seawater. Unsupervised feature learning is performed on the images and the spectral data using convolutional and single-layer autoencoders. The learned features are combined, where we demonstrate that non-linear dimensional reduction of the combined multimodal features can achieve a high clustering macro F1 score of 0.88, compared to a maximum of 0.61 when only image or spectral features are used. The method can be applied to long-term monitoring of particles in the ocean without the need for sample collection. In addition, it can be applied to data from different types of sensor measurements without significant modifications.

A new subfamily of ulmarid scyphomedusae, the Santjordiinae, with a description of Santjordia pagesi gen. et sp. nov. (Cnidaria: Scyphozoa: Discomedusae: Semaeostomeae: Ulmaridae) from the Sumisu Caldera, Ogasawara Islands, Japan.

An undescribed species of ulmarid medusa was observed in situ and captured at 812 m depth within the Sumisu Caldera, Ogasawara Islands, Japan. Morphological and molecular evidence points to it being distinct from other ulmarid medusae and a new species (pagesi), genus (Santjordia) and subfamily (Santjordiinae) are herein erected to contain it. This new subfamily of semaeostome ulmarid medusae has both marginal and subumbrellar rhopalia, making it unique within the order Semaeostomeae. Although the combination of subumbrellar tentacles and the lack of branched canals should warrant the erection of a new family within the Semaeostomeae, a lack of information on the gonad structure and poor bootstrap support in the molecular phylogenetic tree cause us to relegate it to the catch-all family Ulmaridae, until greater taxon sampling and phylogenetic analyses are carried out for the Semaeostomeae.

Machine Learning for the Study of Plankton and Marine Snow from Images.

Quantitative imaging instruments produce a large number of images of plankton and marine snow, acquired in a controlled manner, from which the visual characteristics of individual objects and their in situ concentrations can be computed. To exploit this wealth of information, machine learning is necessary to automate tasks such as taxonomic classification. Through a review of the literature, we highlight the progress of those machine classifiers and what they can and still cannot be trusted for. Several examples showcase how the combination of quantitative imaging with machine learning has brought insights on pelagic ecology. They also highlight what is still missing and how images could be exploited further through trait-based approaches. In the future, we suggest deeper interactions with the computer sciences community, the adoption of data standards, and the more systematic sharing of databases to build a global community of pelagic image providers and users.

Unsupervised feature learning and clustering of particles imaged in raw holograms using an autoencoder.

Digital holography is a useful tool to image microscopic particles. Reconstructed holograms give high-resolution shape information that can be used to identify the types of particles. However, the process of reconstructing holograms is computationally intensive and cannot easily keep up with the rate of data acquisition on low-power sensor platforms. In this work, we explore the possibility of performing object clustering on holograms that have not been reconstructed, i.e., images of raw interference patterns, using the latent representations of a deep-learning autoencoder and a self-organizing mapping network in a fully unsupervised manner. We demonstrate this concept on synthetically generated holograms of different shapes, where clustering of raw holograms achieves an accuracy of 94.4%. This is comparable to the 97.4% accuracy achieved using the reconstructed holograms of the same targets. Directly clustering raw holograms takes less than 0.1 s per image using a low-power CPU board. This represents a three-order of magnitude reduction in processing time compared to clustering of reconstructed holograms and makes it possible to interpret targets in real time on low-power sensor platforms. Experiments on real holograms demonstrate significant gains in clustering accuracy through the use of synthetic holograms to train models. Clustering accuracy increased from 47.1% when the models were trained only on the real raw holograms, to 64.1% when the models were entirely trained on the synthetic raw holograms, and further increased to 75.9% when models were trained on the both synthetic and real datasets using transfer learning. These results are broadly comparable to those achieved when reconstructed holograms are used, where the highest accuracy of 70% achieved when clustering raw holograms outperforms the highest accuracy achieved when clustering reconstructed holograms by a significant margin for our datasets.

Life beneath the ice: jellyfish and ctenophores from the Ross Sea, Antarctica, with an image-based training set for machine learning.

BACKGROUND: Southern Ocean ecosystems are currently experiencing increased environmental changes and anthropogenic pressures, urging scientists to report on their biodiversity and biogeography. Two major taxonomically diverse and trophically important gelatinous zooplankton groups that have, however, stayed largely understudied until now are the cnidarian jellyfish and ctenophores. This data scarcity is predominantly due to many of these fragile, soft-bodied organisms being easily fragmented and/or destroyed with traditional net sampling methods. Progress in alternative survey methods including, for instance, optics-based methods is slowly starting to overcome these obstacles. As video annotation by human observers is both time-consuming and financially costly, machine-learning techniques should be developed for the analysis of in situ /in aqua image-based datasets. This requires taxonomically accurate training sets for correct species identification and the present paper is the first to provide such data. NEW INFORMATION: In this study, we twice conducted three week-long in situ optics-based surveys of jellyfish and ctenophores found under the ice in the McMurdo Sound, Antarctica. Our study constitutes the first optics-based survey of gelatinous zooplankton in the Ross Sea and the first study to use in situ / in aqua observations to describe taxonomic and some trophic and behavioural characteristics of gelatinous zooplankton from the Southern Ocean. Despite the small geographic and temporal scales of our study, we provided new undescribed morphological traits for all observed gelatinous zooplankton species (eight cnidarian and four ctenophore species). Three ctenophores and one leptomedusa likely represent undescribed species. Furthermore, along with the photography and videography, we prepared a Common Objects in Context (COCO) dataset, so that this study is the first to provide a taxonomist-ratified image training set for future machine-learning algorithm development concerning Southern Ocean gelatinous zooplankton species.

Stealthy tracking of deep ocean organisms with Mesobot.

Tracking deep ocean animals over their daily cycles will revolutionize our understanding of the largest biome on Earth.

Development of robust models for rapid classification of microplastic polymer types based on near infrared hyperspectral images.

Hyperspectral data in the near infrared range were examined for nine common types of plastic particles of 1 mm and 100-500 µm sizes on dry and wet glass fiber filters. Weaker peak intensities were detected for small particles compared to large particles, and the reflectances were weaker at longer wavelengths when the particles were measured on a wet filter. These phenomena are explainable due to the effect of the correlation between the particle size and the absorption of infrared light by water. We constructed robust classification models that are capable of classifying polymer types, regardless of particle size or filter conditions (wet vs. dry), based on hyperspectral data for small particles measured on wet filters. Using the models, we also successfully classified the polymer type of polystyrene beads covered with microalgae, which simulates the natural conditions of microplastics in the ocean. This study suggests that hyperspectral imaging techniques with appropriate classification models allow the identification of microplastics without the time- and labor-consuming procedures of drying samples and removing biofilms, thus enabling more rapid analyses.

A new southern record of the holopelagic annelid Poeobius meseres Heath, 1930 (Flabelligeridae).

BACKGROUND: The unusual holopelagic annelid Poeobius meseres Heath, 1930 (Flabelligeridae) was first collected from Monterey Bay, California and has been subsequently recorded across the northern Pacific from Japan to the Gulf of California. Rare occurrences in the eastern tropical Pacific have extended as far as 7° S off Peru. NEW INFORMATION: Using molecular phylogenetic analysis of a newly-collected specimen from the Salas y Gómez Ridge off Chile, we extend the known geographic range of P. meseres southwards by 2040 km. This subtropical specimen showed higher genetic similarity to a specimen from the type locality (< 1.5% pairwise COI distance) than to representatives from the Aleutian Islands and Japan (5-6%), establishing the first genetically-confirmed occurrence of this species in the Southern Hemisphere. The latitudinal range of P. meseres encompasses the sole collection locality, off Ecuador, of Enigma terwielii Betrem, 1925, a pelagic annelid which has been compared to P. meseres, but is indeterminable due to an inadequate description. We therefore suggest that the earlier sole record of E. terwielii may have been an occurrence of what is known now as P. meseres.

Deep-sea water displacement from a turbidity current induced by the Super Typhoon Hagibis.

Turbidity currents are the main drivers behind the transportation of terrestrial sediments to the deep sea, and turbidite deposits from such currents have been widely used in geological studies. Nevertheless, the contribution of turbidity currents to vertical displacement of seawater has rarely been discussed. This is partly because until recently, deep-sea turbidity currents have rarely been observed due to their unpredictable nature, being usually triggered by meteorological or geological events such as typhoons and earthquakes. Here, we report a direct observation of a deep-sea turbidity current using the recently developed Edokko Mark 1 monitoring system deployed in 2019 at a depth of 1,370 m in Suruga Bay, central Japan. A turbidity current occurred two days after its probable cause, the Super Typhoon Hagibis (2019), passed through Suruga Bay causing devastating damage. Over aperiod of 40 hours, we observed increased turbidity with turbulent conditions confirmed by a video camera. The turbidity exhibited two sharp peaks around 3:00 and 11:00 on October 14 (Japan Standard Time). The temperature and salinity characteristics during these high turbidity events agreed with independent measurements for shallow water layers in Suruga Bay at the same time, strongly suggesting that the turbidity current caused vertical displacement in the bay's water column by transporting warmer and shallower waters downslope of the canyon. Our results add to the previous few examples that show meteorological and geological events may have significant contributions in the transportation of shallower seawater to the deep sea. Recent technological developments pertaining to the Edokko Mark 1 and similar devices enable straightforward, long-term monitoring of the deep-seafloor and will contribute to the understanding of similar spontaneous events in the deep ocean.

Identification of microplastics in a large water volume by integrated holography and Raman spectroscopy.

A noncontact method to identify sparsely distributed plastic pellets is proposed by integrating holography and Raman spectroscopy in this study. Polystyrene and poly(methyl methacrylate) resin pellets with a size of 3 mm located in a 20 cm water channel were illuminated using a collimated continuous wave laser beam with a diameter of 4 mm and wavelength of 785 nm. The same laser beam was used to take a holographic image and Raman spectrum of a pellet to identify the shape, size, and composition of material. Using the compact system, the morphological and chemical analysis of pellets in a large volume of water was performed. The reported method demonstrates the potential for noncontact continuous in situ monitoring of microplastics in water without collection and separation.

A new small device made of glass for separating microplastics from marine and freshwater sediments.

Separating microplastics from marine and freshwater sediments is challenging, but necessary to determine their distribution, mass, and ecological impacts in benthic environments. Density separation is commonly used to extract microplastics from sediments by using heavy salt solutions, such as zinc chloride and sodium iodide. However, current devices/apparatus used for density separation, including glass beakers, funnels, upside-down funnel-shaped separators with a shut-off valve, etc., possess various shortcomings in terms of recovery rate, time consumption, and/or usability. In evaluating existing microplastic extraction methods using density separation, we identified the need for a device that allows rapid, simple, and efficient extraction of microplastics from a range of sediment types. We have developed a small glass separator, without a valve, taking a hint from an Utermöhl chamber. This new device is easy to clean and portable, yet enables rapid separation of microplastics from sediments. With this simple device, we recovered 94-98% of <1,000 µm microplastics (polyethylene, polypropylene, polyvinyl chloride, polyethylene terephthalate, and polystyrene). Overall, the device is efficient for various sizes, polymer types, and sediment types. Also, microplastics collected with this glass-made device remain chemically uncontaminated, and can, therefore, be used for further analysis of adsorbing contaminants and additives on/to microplastics.

A small, stainless-steel sieve optimized for laboratory beaker-based extraction of microplastics from environmental samples.

Removing non-plastic materials is a mandatory process for studying microplastics in environmental samples, and non-plastic materials, both inorganic and organic matter, are often removed chemically through sequential processes. In the multiple chemical treatment processes, the samples need to be collected and the reagent removed at the end of each chemical treatment before the samples are again exposed to a different reagent in a separate container. This leads to a loss of microplastics to some extent. Here, we developed a new, yet simple, small sieve made of stainless-steel that can fit in a laboratory beaker (e.g. 200 ml volume), allowing it to be transferred as-is between chemical treatments of environmental samples, even being soakable in a beaker of acid solution. The collection rates of microplastics were significantly higher in the small stainless-steel sieve than the commonly used filter method for different size of microplastic particles. The use of the new sieve means the processes of rinsing off and filtering samples can be abbreviated throughout the entire process of non-plastic matter removal from environmental samples, contributing to a lower chance of microplastic loss. The time consumed in the sieve method was also significantly lower than for the filtering method due to the elimination of the collection and rinsing steps, thus the use of this sieve can reduce processing time for the samples. The new method is innovative in terms of reducing both the microplastic loss and processing time during chemical treatment processes. •The method developed allows the lower chance of microplastic loss during chemical digestion process•The method reduces the time of sequential processes during chemical digestion.

Loss of metagenesis and evolution of a parasitic life style in a group of open-ocean jellyfish.

Loss or stark reduction of the free-swimming medusa or jellyfish stage is common in the cnidarian class Hydrozoa. In the hydrozoan clade Trachylina, however, many species do not possess a sessile polyp or hydroid stage. Trachylines inhabiting freshwater and coastal ecosystems (i.e., Limnomedusae) possess a metagenetic life cycle involving benthic, sessile polyp and free-swimming medusa. In contrast, the paradigm is that open ocean inhabiting, oceanic trachylines (in the orders Narcomedusae and Trachymedusae) develop from zygote to medusa via a free-swimming larva, forgoing the polyp stage. In some open-ocean trachylines, development includes a sessile stage that is an ecto- or endoparasite of other oceanic organisms. We expand the molecular-based phylogenetic hypothesis of trachylines significantly, increasing taxon and molecular marker sampling. Using this comprehensive phylogenetic hypothesis in conjunction with character state reconstructions we enhance understanding of the evolution of life cycles in trachyline hydrozoans. We find that the polyp stage was lost at least twice independently, concurrent with a transition to an oceanic life style. Further, a sessile, polypoid parasitic stage arose once, rather than twice as current classification would imply, in the open ocean inhabiting Narcomedusae. Our results also support the hypothesis that interstitial species of the order Actinulida are directly descended from direct developing, oceanic trachylines.

A new genus and species of the family Pennellidae (Copepoda, Siphonostomatoida) infecting the Pacific viperfish Chauliodus macouni.

A new genus and species of pennellid copepod, Protosarcotretes nishikawai n. g., n. sp., is described on the basis of an ovigerous female infecting a Pacific viperfish Chauliodus macouni collected from the deep-waters of Suruga Bay, Japan. The new genus exhibits the most plesiomorphic states in the first to fourth legs of pennellids, and is differentiated from two closely related pennellid genera Sarcotretes and Lernaeenicus by the morphology of the oral appendages. Two species of the genus Lernaeenicus are transferred to the new genus as Protosarcotretes multilobatus (Lewis, 1959) n. comb. and Protosarcotretes gnavus (Leigh-Sharpe, 1934) n. comb. The host specificity and life cycle of deep-sea pennellids are discussed. Sarcotretes scopeli Jungersen, 1911 and Cardiodectes bellottii (Richiardi, 1882) show low differentiated host-specificity, while P. nishikawai seems to be limited to the Stomiidae, which are rare hosts of pennellids, in contrast to the Myctophidae family. In the Pennellidae family, two patterns of the life cycle are found: with or without naupliar stages.

Megafauna of the UKSRL exploration contract area and eastern Clarion-Clipperton Zone in the Pacific Ocean: Annelida, Arthropoda, Bryozoa, Chordata, Ctenophora, Mollusca.

BACKGROUND: There is growing interest in mining polymetallic nodules from the abyssal Clarion-Clipperton Zone (CCZ) in the tropical Pacific Ocean. Despite having been the focus of environmental studies for decades, the benthic megafauna of the CCZ remain poorly known. To predict and manage the environmental impacts of mining in the CCZ, baseline knowledge of the megafauna is essential. The ABYSSLINE Project has conducted benthic biological baseline surveys in the UK Seabed Resources Ltd polymetallic-nodule exploration contract area (UK-1). Prior to ABYSSLINE research cruises in 2013 and 2015, no biological studies had been done in this area of the eastern CCZ. NEW INFORMATION: Using a Remotely Operated Vehicle and Autonomous Underwater Vehicle (as well as several other pieces of equipment), the megafauna within the UK Seabed Resources Ltd exploration contract area (UK-1) and at a site ~250 km east of the UK-1 area were surveyed, allowing us to make the first estimates of megafaunal morphospecies richness from the imagery collected. Here, we present an atlas of the abyssal annelid, arthropod, bryozoan, chordate, ctenophore and molluscan megafauna observed and collected during the ABYSSLINE cruises to the UK-1 polymetallic-nodule exploration contract area in the CCZ. There appear to be at least 55 distinct morphospecies (8 Annelida, 12 Arthropoda, 4 Bryozoa, 22 Chordata, 5 Ctenophora, and 4 Mollusca) identified mostly by morphology but also using molecular barcoding for a limited number of animals that were collected. This atlas will aid the synthesis of megafaunal presence/absence data collected by contractors, scientists and other stakeholders undertaking work in the CCZ, ultimately helping to decipher the biogeography of the megafauna in this threatened habitat.

A new species of clausophyid calycophoran siphonophore (Cnidaria: Hydrozoa), Kephyes hiulcus sp. nov., widely distributed throughout the world's oceans.

A new species of clausophyid siphonophore, Kephyes hiulcus sp. nov. is described. It can most easily be differentiated from its congener Kephyes ovata by the shape of the hydroecium in the anterior nectophore of the polygastric stage. This is open over the entire height of the nectophore in K. hiulcus sp. nov., and it is this character from which its specific name is derived. This species was found in the eastern and western Pacific Ocean, as well as the Celebes and Mediterranean Seas, indicating that this species is both relatively common and geographically widespread.

High Abundance of the Epibenthic Trachymedusa Ptychogastria polaris Allman, 1878 (Hydrozoa, Trachylina) in Subpolar Fjords along the West Antarctic Peninsula.

Medusae can be conspicuous and abundant members of seafloor communities in deep-sea benthic boundary layers. The epibenthic trachymedusa, Ptychogastria polaris Allman, 1878 (Hydrozoa: Trachylina: Ptychogastriidae) occurs in the cold, high latitude systems of both the northern and southern hemispheres, with a circumpolar distribution in Arctic and sub-Arctic areas, and disjunct reports of a few individuals from Antarctica. In January-February 2010, during benthic megafaunal photosurveys in three subpolar fjords along the West Antarctic Peninsula (Andvord, Flandres and Barilari Bays), P. polaris was recorded in Antarctic Peninsula waters. The trachymedusa, identified from megacore-collected specimens, was a common component of the epifauna in the sediment floored basins at 436-725 m depths in Andvord and Flandres Bays, reaching densities up to 13 m-2, with mean densities in individual basins ranging from 0.06 to 4.19 m-2. These densities are 2 to 400-fold higher than previously reported for P. polaris in either the Arctic or Antarctic. This trachymedusa had an aggregated distribution, occurring frequently in Andvord Bay, but was often solitary in Flandres Bay, with a distribution not significantly different from random. Epibenthic individuals were similar in size, typically measuring 15-25 mm in bell diameter. A morphologically similar trachymedusa, presumably the same species, was also observed in the water column near the bottom in all three fjords. This benthopelagic form attained abundances of up to 7 m-2 of seafloor; however, most P. polaris (~ 80%), were observed on soft sediments. Our findings indicate that fjords provide a prime habitat for the development of dense populations of P. polaris, potentially resulting from high and varied food inputs to the fjord floors. Because P. polaris resides in the water column and at the seafloor, large P. polaris populations may contribute significantly to pelagic-benthic coupling in the WAP fjord ecosystems.