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This study examines trends in PPE (masks, gloves) and disinfecting wipes over three years of the pandemic. The densities of discarded masks, wet wipes, and gloves (personal protective equipment: PPE), were quantified on the streets of Canakkale, Turkey during similar time periods in 2020, 2021 and 2022. Geotagged images of PPE on the streets and sidewalks were documented with a smartphone, while the track of an observer was recorded using a fitness tracker app along a 7.777 km long survey route in the city center, parallel to the Dardanelles Strait. A total of 18 surveys were conducted over three years, and the survey route was subdivided into three zones based on utilization patterns: pedestrian zone, traffic zone and a recreational park zone. The combined densities of all types of PPE density were high in 2020, lower in 2021 and highest in 2022. The within year trend showed an increase over the three study years. The average density of gloves declined from an initially high level in 2020, when the SARS-CoV-2 virus was thought to be transmitted by contact, to near zero in 2021 and to zero in 2022. Densities of wipes were similar in 2020 and 2021 and higher in 2022. Masks were initially difficult to procure in 2020, and their densities progressively increased during that year reaching a plateau in 2021 with similar densities in 2022. PPE densities were significantly lower in the pedestrian route relative to the traffic and park routes, which were not different from each other. The partial curfews implemented by the Turkish government and the effects of prevention measures taken on the PPE concentration in the streets are discussed along with the importance of waste management practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Recent research has revealed that shrimp sensory quality may be affected by ocean acidification but we do not exactly know why. Here we conducted controlled pH exposure experiments on adult tiger shrimp, which were kept in 1000-L tanks continuously supplied with coastal seawater. We compared survival rate, carapace properties and flesh sensory properties and amino acid composition of shrimp exposed to pH 7.5 and pH 8.0 treatments for 28 days. Shrimp reared at pH 7.5 had a lower amino acid content (17.6% w/w) than those reared at pH 8.0 (19.5% w/w). Interestingly, the amino acids responsible for the umami taste, i.e. glutamate and aspartic acid, were present at significantly lower levels in the pH 7.5 than the pH 8.0 shrimp, and the pH 7.5 shrimp were also rated as less desirable in a blind quality test by 40 volunteer assessors. These results indicate that tiger shrimp may become less palatable in the future due to a lower production of some amino acids. Finally, tiger shrimp also had a lower survival rate over 28 days at pH 7.5 than at pH 8.0 (73% vs. 81%) suggesting that ocean acidification may affect both the quality and quantity of future shrimp resources., (© 2021. The Author(s).)

The Deepwater Horizon spill is one of the largest environmental disasters with extensive impacts on the economic and ecological health of the Gulf of Mexico. Surface oil and coastal impacts received considerable attention, but the far larger oil spill in the deep ocean and its effects received considerably less examination. Based on 2017 ROV surveys within 500 m of the wellhead, we provide evidence of continued impacts on diversity, abundance and health of deep-sea megafauna. At locations proximal to the wellhead, megafaunal communities are more homogeneous than in unimpacted areas, lacking many taxonomic groups, and driven by high densities of arthropods. Degraded hydrocarbons at the site may be attracting arthropods. The scope of impacts may extend beyond the impacted sites with the potential for impacts to pelagic food webs and commercially important species. Overall, deep-sea ecosystem health, 7 years post spill, is recovering slowly and lingering effects may be extreme., Competing Interests: We declare we have no competing interests., (© 2019 The Authors.)

Despite the rapid increase in the number and applications of plankton imaging systems in marine science, processing large numbers of images remains a major challenge due to large variations in image content and quality in different marine environments. We constructed an automatic plankton image recognition and enumeration system using an enhanced Convolutional Neural Network (CNN) and examined the performance of different network structures on automatic plankton image classification. The procedure started with an adaptive thresholding approach to extract Region of Interest (ROIs) from in situ plankton images, followed by a procedure to suppress the background noise and enhance target features for each extracted ROI. The enhanced ROIs were classified into seven categories by a pre-trained classifier which was a combination of a CNN and a Support Vector Machine (SVM). The CNN was selected to improve feature description and the SVM was utilized to improve classification accuracy. A series of comparison experiments were then conducted to test the effectiveness of the pre-trained classifier including the combination of CNN and SVM versus CNN alone, and the performance of different CNN models. Compared to CNN model alone, the combination of CNN and SVM increased classification accuracy and recall rate by 7.13% and 6.41%, respectively. Among the selected CNN models, the ResNet50 performed the best with accuracy and recall at 94.52% and 94.13% respectively. The present study demonstrates that deep learning technique can improve plankton image recognition and that the results can provide useful information on the selection of different CNN models for plankton recognition. The proposed algorithm could be generally applied to images acquired from different imaging systems., Competing Interests: The authors have declared that no competing interests exist.

For thousands of years humankind has sought to explore our oceans. Evidence of this early intrigue dates back to 130,000BCE, but the advent of remotely operated vehicles (ROVs) in the 1950s introduced technology that has had significant impact on ocean exploration. Today, ROVs play a critical role in both military (e.g. retrieving torpedoes and mines) and salvage operations (e.g. locating historic shipwrecks such as the RMS Titanic), and are crucial for oil and gas (O&G) exploration and operations. Industrial ROVs collect millions of observations of our oceans each year, fueling scientific discoveries. Herein, we assembled a group of international ROV experts from both academia and industry to reflect on these discoveries and, more importantly, to identify key questions relating to our oceans that can be supported using industry ROVs. From a long list, we narrowed down to the 10 most important questions in ocean science that we feel can be supported (whole or in part) by increasing access to industry ROVs, and collaborations with the companies that use them. The questions covered opportunity (e.g. what is the resource value of the oceans?) to the impacts of global change (e.g. which marine ecosystems are most sensitive to anthropogenic impact?). Looking ahead, we provide recommendations for how data collected by ROVs can be maximised by higher levels of collaboration between academia and industry, resulting in win-win outcomes. What is clear from this work is that the potential of industrial ROV technology in unravelling the mysteries of our oceans is only just beginning to be realised. This is particularly important as the oceans are subject to increasing impacts from global change and industrial exploitation. The coming decades will represent an important time for scientists to partner with industry that use ROVs in order to make the most of these 'eyes in the sea'., (Copyright © 2018. Published by Elsevier B.V.)

Accumulation of marine debris is a global problem that affects the oceans on multiple scales. The majority of floating marine debris is composed of microplastics: plastic particles up to 5 mm in diameter. With similar sizes and appearances to natural food items, these small fragments pose potential risks to many marine organisms including zooplankton and zooplanktivores. Semi-enclosed seas are reported to have high concentrations of microplastics, however, the distribution and concentration of microplastics in one such system, the Gulf of Mexico, remains unknown. Our study documented and characterized microplastics in continental shelf waters off the Louisiana coast in the northern Gulf of Mexico, using bongo nets, neuston nets, and Niskin bottles. Additionally, we compared the size distributions of microplastics and zooplankton collected using the nets. Plastics were manually sorted from the samples, documented, and measured using digital microscopy. Confirmation of putative plastics was carried out by hydrofluoric acid digestion and a subsample was analyzed using FTIR microscopy. Estimated concentrations of microplastics collected on the inner continental shelf during this study are among the highest reported globally. Total microplastic concentrations ranged from 4.8 to 8.2 particles m -3 and 5.0-18.4 particles m -3 for the bongo and neuston samples, respectively. Niskin bottles collected smaller plastic particles than the nets and indicated total microplastic concentrations (primarily fibers) from 6.0E4 - 15.7E4 particles m -3 . Microplastic concentrations were greater than the abundances of all but four of the five most abundant taxa from bongo nets and were not statistically different from the abundances of any of the most numerous taxa from neuston nets. Sizes of microplastics and zooplankton partially or completely overlapped, suggesting the potential for confusion with natural prey., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups.

What are the greatest sizes that the largest marine megafauna obtain? This is a simple question with a difficult and complex answer. Many of the largest-sized species occur in the world's oceans. For many of these, rarity, remoteness, and quite simply the logistics of measuring these giants has made obtaining accurate size measurements difficult. Inaccurate reports of maximum sizes run rampant through the scientific literature and popular media. Moreover, how intraspecific variation in the body sizes of these animals relates to sex, population structure, the environment, and interactions with humans remains underappreciated. Here, we review and analyze body size for 25 ocean giants ranging across the animal kingdom. For each taxon we document body size for the largest known marine species of several clades. We also analyze intraspecific variation and identify the largest known individuals for each species. Where data allows, we analyze spatial and temporal intraspecific size variation. We also provide allometric scaling equations between different size measurements as resources to other researchers. In some cases, the lack of data prevents us from fully examining these topics and instead we specifically highlight these deficiencies and the barriers that exist for data collection. Overall, we found considerable variability in intraspecific size distributions from strongly left- to strongly right-skewed. We provide several allometric equations that allow for estimation of total lengths and weights from more easily obtained measurements. In several cases, we also quantify considerable geographic variation and decreases in size likely attributed to humans.

The Deepwater Horizon Oil Spill resulted in the release of a large quantity of oil and gas into the northern Gulf of Mexico from a bathypelagic source. Due to a lack of pre-spill quantitative data the baseline condition of the communities near the spill site is unknown. This makes it difficult to determine the impact of the spill on deepwater megafauna. Remotely operated vehicles were used to quantify megafauna at five study sites during August and September 2010:2000 m north, west, south, and east, and 500 m north of the Macondo well. Comparisons of animal abundances indicated that 2000 m-N and 2000 m-W had the greatest taxonomic richness and highest abundances while 2000 m-E had slightly lower values. In contrast 500 m-N and 2000 m-S had the lowest taxonomic richness and abundances. Our study also suggests that certain taxa were potentially more resistant or sensitive to the spill., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The deep-sea squid Grimalditeuthis bonplandi has tentacles unique among known squids. The elastic stalk is extremely thin and fragile, whereas the clubs bear no suckers, hooks or photophores. It is unknown whether and how these tentacles are used in prey capture and handling. We present, to our knowledge, the first in situ observations of this species obtained by remotely operated vehicles (ROVs) in the Atlantic and North Pacific. Unexpectedly, G. bonplandi is unable to rapidly extend and retract the tentacle stalk as do other squids, but instead manoeuvres the tentacles by undulation and flapping of the clubs' trabecular protective membranes. These tentacle club movements superficially resemble the movements of small marine organisms and suggest the possibility that G. bonplandi uses aggressive mimicry by the tentacle clubs to lure prey, which we find to consist of crustaceans and cephalopods. In the darkness of the meso- and bathypelagic zones the flapping and undulatory movements of the tentacle may: (i) stimulate bioluminescence in the surrounding water, (ii) create low-frequency vibrations and/or (iii) produce a hydrodynamic wake. Potential prey of G. bonplandi may be attracted to one or more of these as signals. This singular use of the tentacle adds to the diverse foraging and feeding strategies known in deep-sea cephalopods.

As part of the SERPENT Project, five observations of apparently healthy oarfish Regalecus glesne by remotely operated vehicles are reported from the northern Gulf of Mexico. Regalecus glesne were observed between 2008 and 2011 at depths from within the epipelagic and mesopelagic zones. These observations include the deepest verified record of R. glesne (463-492 m) and the first record of an arthropod ectoparasite (isopod)., (© 2013 The Authors. Journal of Fish Biology © 2013 The Fisheries Society of the British Isles.)

Zooplankton in the ocean respond to visual and hydro-mechanical cues such as small-scale shear in turbulent flow. In addition, they form strong aggregations where currents intersect sloping bottoms. Strong and predictable tidal currents over a sill in Knight Inlet, Canada, make it an ideal location to investigate biological behaviour in turbulent cross-isobath flow. We examine acoustic data (38, 120 and 200 kHz) collected there during the daylight hours, when the dominant zooplankters, Euphausia pacifica have descended into low light levels at ∼90 m. As expected, these data reveal strong aggregations at the sill. However, they occur consistently 10-20 m below the preferred light depth of the animals. We have constructed a simple model of the flow to investigate this phenomenon. Tracks of individual animals are traced in the flow and a variety of zooplankton behaviours tested. Our results indicate that the euphausiids must actively swim downward when they encounter the bottom boundary layer (bbl) to reproduce the observed downward shift in aggregation patterns. We suggest that this behaviour is cued by the small-scale shear in the bbl. Furthermore, this behaviour is likely to enhance aggregations found in strong flows at sills and on continental shelves.

High-frequency acoustic scattering techniques have been used to investigate dominant scatterers in mixed zooplankton populations. Volume backscattering was measured in the Gulf of Maine at 43, 120, 200, and 420 kHz. Zooplankton composition and size were determined using net and video sampling techniques, and water properties were determined using conductivity, temperature, and depth sensors. Dominant scatterers have been identified using recently developed scattering models for zooplankton and microstructure. Microstructure generally did not contribute to the scattering. At certain locations, gas-bearing zooplankton, that account for a small fraction of the total abundance and biomass, dominated the scattering at all frequencies. At these locations, acoustically inferred size agreed well with size determined from the net samples. Significant differences between the acoustic, net, and video estimates of abundance for these zooplankton are most likely due to limitations of the net and video techniques. No other type of biological scatterer ever dominated the scattering at all frequencies. Copepods, fluid-like zooplankton that account for most of the abundance and biomass, dominated at select locations only at the highest frequencies. At these locations, acoustically inferred abundance agreed well with net and video estimates. A general approach for the difficult problem of interpreting high-frequency acoustic scattering in mixed zooplankton populations is described.

An investigation of midwater zooplankton aggregations in a coastal fjord was conducted in November 2002. This study focused on quantitative comparisons between a calibrated, three-frequency (38, 120, and 200 kHz) vessel-based echo-sounder, a multinet towed zooplankton sampler (BIONESS), and a high-resolution underwater camera (ZOOVIS). Daytime layers of euphausiids and amphipods near 70-90-m depth were observed in lower parts of the inlet, especially concentrated by tidal flows around a sill. Quantitative backscatter measurements of euphausiids and amphipods, combined with in situ size and abundance estimates, and using an assumed tilt-angle distribution, were in agreement with averaged fluid-cylinder scattering models produced by Stanton and Chu [ICES J. Mar. Sci. 57, 793-807, (2000)]. Acoustic measurements of physonect siphonophores in the upper inlet were found to have a strong 38-kHz scattering strength, in agreement with a damped bubble scattering model using a diameter of 0.4 mm. In relatively dense euphausiid layers, ZOOVIS abundance estimates were found to be a factor of 2 to 4 higher than the acoustic estimates, potentially due to deviations from assumed euphausiid orientation. Nocturnal near-surface euphausiid scattering exhibited a strong (15 dB) and rapid (seconds) sensitivity to vessel lights, interpreted as due to changing animal orientation.