Short Cruise Report - R/V MARIA S. MERIAN, MSM95 (GPF 19-2_05)

The main aim of the MSM95 research expedition was to investigate and map physical impacts on the arctic seafloor in two distinct and contrasting Arctic areas (The Svalbard shelf edge and the HAUSGARTEN time series stations in the FRAM strait) with a range of research equipment. A ‘nested’ data approach was conducted in each research area, with broad seafloor mapping conducted initially with the MARIA S. MERIAN onboard acoustic systems (The EM122 and EM712 bathymetric systems), followed by focused subsequent mapping conducted by PAUL 3000 automated underwater vehicle (AUV) sidescan and camera deployments, Ocean Floor Observation and Bathymetry System (OFOBS) towed sidescan and camera trawls and finally with very high resolution investigations conducted with a new mini-ROV launched directly from the OFOBS for close seafloor visual analysis. These data will be used to produce spatial distribution maps of iceberg and fishery impacts on the seafloor at three locations to the north, south and west of the Svalbard Archipelago, as well as maps of drop stone and topography variations across several of the HAUSGARTEN stations

PAPARA(ZZ)I : An open-source software interface for annotating photographs of the deep-sea

PAPARA(ZZ)I is a lightweight and intuitive image annotation program developed for the study of benthic megafauna. It offers functionalities such as free, grid and random point annotation. Annotations may be made following existing classification schemes for marine biota and substrata or with the use of user defined, customised lists of keywords, which broadens the range of potential application of the software to other types of studies (e.g. marine litter distribution assessment). If Internet access is available, PAPARA(ZZ)I can also query and use standardised taxa names directly from the World Register of Marine Species (WoRMS). Program outputs include abundances, densities and size calculations per keyword (e.g. per taxon). These results are written into text files that can be imported into spreadsheet programs for further analyses. PAPARA(ZZ)I is open-source and is available at http://papara-zz-i.github.io. Compiled versions exist for most 64-bit operating systems: Windows, Mac OS X and Linux

Benthic megafauna in the Arctic Ocean - Future dominion by sea cucumbers?

Benthic megafauna in the Arctic Ocean are important for the functioning of deep-sea ecosystems and influence the global carbon cycle. Food availability, as represented primarily by the phytodetrital flux from surface layers, influences the structure of benthic communities in the Arctic Ocean. Along the highly productive marginal sea-ice zones, benthic communities benefit from enhanced food supply. With the advance in climate change, marginal sea-ice zones are shifting and organisms at the seafloor are faced with changing environmental fluxes. This study was designed in order to deepen our understanding of benthic megafauna community dynamics in the Arctic Ocean, from which to infer predictions about the future. Benthic megafauna was quantified by annotating image data from 2016 to 2021. Image data was derived from three different stations, located in the north (N3), centre (HG-IV) and south (S3) of the HAUSGARTEN observatory in the Fram Strait, and was analysed in context with sea-ice coverage measurements. The benthic megafauna communities showed a shift in dominant functional traits, from sessile suspension feeders, to mobile deposit feeders at all stations over the study period. The dominance of mobile deposit feeders was attributed to one species, the sea cucumber Elpidia heckeri. This species showed increases in density of more than 20% across all three stations during the study period. Variations in phytodetrital quality and quantity are most likely the reasons for these strong density increases of the opportunistic sea cucumber. Additionally, a positive relationship between benthic megafaunal density and the extent of sea-ice coverage at N3 and HG-IV was indicated. From these data, into the future, similar strong variations in deposit feeding holothurian densities are expected, given their ability to quickly respond to changing phytodetrital fluxes. This research shows how valuable long-term image-based data studies are in order to detect trends in the future Arctic Ocean

Benthic megafauna in the Arctic Ocean - Dynamics in temporal community composition

Benthic megafauna in the Arctic Ocean plays a pivotal role in the functioning of deep-sea ecosystems and influences the global carbon cycle. The structure of benthic communities in the Arctic Ocean is primarily determined by food availability and therefore by phytodetrital flux from surface layers. Hence, highly productive marginal sea-ice zones provide high food supply for benthic communities. With the advance in climate change, marginal sea-ice zones are shifting and organisms are faced with changing phytodetrital fluxes. This study was designed to increase the understanding of benthic megafauna community dynamics in the Arctic Ocean and infer predictions about the future. Therefore, the benthic megafauna was quantified at three stations, with contrasting extent of sea-ice coverage, located in the north (N3), centre (HG-IV) and in the south (S3) of the HAUSGARTEN observatory in the Fram Strait. Image data from different years between 2016 and 2021 were annotated and analysed in context with sea- ice coverage measurements. The benthic megafauna communities showed a shift in dominant functional traits, from sessile suspension feeders, to mobile deposit feeders at all stations. The dominance of mobile deposit feeders was attributed to one species, the sea cucumber, Elpidia heckeri. Additionally, a positive relation between benthic megafaunal density and the extent of sea-ice coverage at N3 and HG-IV was indicated. Variations in phytodetrital quality and quantity are most likely the reasons for these strong density increases of the opportunistic sea cucumber. For the future, similarly strong variations in deposit feeding holothurian densities are expected, given their ability to quickly respond to changing phytodetrital fluxes. The results also indicate that benthic megafauna community composition as a whole is likely to exhibit strong variations in density and diversity. This research shows how valuable image data from time-series studies are in order to detect long-term trends in the future Arctic Ocean

Impact of returning scientific cruises and prolonged on-site presence on litter abundance at the deep-sea nodule fields in the Peru Basin

Marine litter can be found along coasts, continental shelves and slopes, down into the abyss. The absence of light, low temperatures and low energy regimes characterising the deeper habitats ensure the persistence of litter over time. Therefore, manmade items within the deep sea will likely accumulate to increasing quantities. Here we report the litter abundance encountered at the Pacific abyssal nodule fields from the Peru Basin at 4150 m depth. An average density of 2.67 litter items/ha was observed. Litter composed of plastic was the most abundant followed by metal and glass. At least 58 % of the items observed could be linked to the research expeditions conducted in the area and appeared to be mostly accidental disposals from ships. The data gathered was used to address temporal trends in litter abundance as well as the impact of human on-site presence and return cruises in the context of future deep-sea mining efforts

Gear-Induced Concept Drift in Marine Images and Its Effect on Deep Learning Classification

In marine research, image data sets from the same area but collected at different times allow seafloor fauna communities to be monitored over time. However, ongoing technological developments have led to the use of different imaging systems and deployment strategies. Thus, instances of the same class exhibit slightly shifted visual features in images taken at slightly different locations or with different gear. These shifts are referred to as concept drift in the domains computational image analysis and machine learning as this phenomenon poses particular challenges for these fields. In this paper, we analyse four different data sets from an area in the Peru Basin and show how changes in imaging parameters affect the classification of 12 megafauna morphotypes with a 34-layer ResNet. Images were captured using the ocean floor observation system, a traditional sled-based system, or an autonomous underwater vehicle, which is used as an imaging platform capable of surveying larger regions. ResNet applied on separate individual data sets, i.e., without concept drift, showed that changing object distance was less important than the amount of training data. The results for the image data acquired with the ocean floor observation system showed higher performance values than data collected with the autonomous underwater vehicle. The results from this concept drift studies indicate that collecting image data from many dives with slightly different gear may result in training data well-suited for learning taxonomic classification tasks and that data volume can compensate for light concept drift

Transects in the deep: Opportunities with tele-operated resident seafloor robots

Scientific, industrial and societal needs call urgently for the development and establishment of intelligent, cost-effective and ecologically sustainable monitoring protocols and robotic platforms for the continuous exploration of marine ecosystems. Internet Operated Vehicles (IOVs) such as crawlers, provide a versatile alternative to conventional observing and sampling tools, being tele-operated, (semi-) permanent mobile platforms capable of operating on the deep and coastal seafloor. Here we present outstanding observations made by the crawler “Wally” in the last decade at the Barkley Canyon (BC, Canada, NE Pacific) methane hydrates site, as a part of the NEPTUNE cabled observatory. The crawler followed the evolution of microhabitats formed on and around biotic and/or abiotic structural features of the site (e.g., a field of egg towers of buccinid snails, and a colonized boulder). Furthermore, episodic events of fresh biomass input were observed (i.e., the mass transport of large gelatinous particles, the scavenging of a dead jellyfish and the arrival of macroalgae from shallower depths). Moreover, we report numerous faunal behaviors (i.e., sablefish rheo- and phototaxis, the behavioral reactions and swimming or resting patterns of further fish species, encounters with octopuses and various crab intra- and interspecific interactions). We report on the observed animal reactions to both natural and artificial stimuli (i.e., crawler’s movement and crawler light systems). These diverse observations showcase different capabilities of the crawler as a modern robotic monitoring platform for marine science and offshore industry. Its long deployments and mobility enable its efficiency in combining the repeatability of long-term studies with the versatility to opportunistically observe rarely seen incidents when they occur, as highlighted here. Finally, we critically assess the empirically recorded ecological footprint and the potential impacts of crawler operations on the benthic ecosystem of the Barkley Canyon hydrates site, together with potential solutions to mitigate them into the future

Plastic microbeads from cosmetic products: an experimental study of their hydrodynamic behaviour, vertical transport and resuspension in phytoplankton and sediment aggregates

Hydrodynamic behaviour and the transport pathways of microplastics within the ocean environment are not well known, rendering accurate predictive models for dispersal management of such pollutants difficult to establish. In the natural environment, aggregation between plastic microbeads and phytodetritus or suspended sediments in rivers and oceans further complicate the patterns of dispersal. In this laboratory study, the physical characteristics and hydrodynamic behaviour of a selection of common plastic microbeads, as used in exfoliation skincare cosmetic products, were investigated. Additionally, the potential for aggregation of these microbeads with phytodetritus and suspended sediments, as well as the subsequent sinking and resuspension behaviour of produced aggregates, were investigated with roller tanks, settling columns and erosion chamber. Physical characteristics of the plastic microbeads showed great heterogeneity, with various densities, sizes and shapes of plastic material being utilised in products designed for the same purpose. The majority of the plastics investigated were positively buoyant in both freshwater and seawater. Aggregation between plastic microbeads and phytoplankton was observed to be swift, with even extremely high concentrations of plastics being rapidly scavenged by suspended algal material. Following aggregation to sizes of 300 to 4400 μm diameter, some formerly buoyant plastics were observed to settle through the water column and enter the benthic boundary layer with settling velocities ranging between 32 and 831 m day–1. These aggregates could be resuspended in the laboratory under critical shear velocities of 0.67–1.33 cm s–1 (free stream velocities of > 10 cm s–1). This rapid aggregation and subsequent settling indicates a potentially important transport pathway for these waste products, a pathway that should be considered when modelling discharge and transport of plastic microbeads and determining the ecosystems that may be at risk from exposure

Gear-Induced Concept Drift in Marine Images and Its Effect on Deep Learning Classification

Langenkämper D, van Kevelaer R, Purser A, Nattkemper TW. Gear-Induced Concept Drift in Marine Images and Its Effect on Deep Learning Classification. Frontiers in Marine Science. 2020;7: 506.In marine research, image data sets from the same area but collected at different times allow seafloor fauna communities to be monitored over time. However, ongoing technological developments have led to the use of different imaging systems and deployment strategies. Thus, instances of the same class exhibit slightly shifted visual features in images taken at slightly different locations or with different gear. These shifts are referred to as concept drift in the domains computational image analysis and machine learning as this phenomenon poses particular challenges for these fields. In this paper, we analyse four different data sets from an area in the Peru Basin and show how changes in imaging parameters affect the classification of 12 megafauna morphotypes with a 34-layer ResNet. Images were captured using the ocean floor observation system, a traditional sled-based system, or an autonomous underwater vehicle, which is used as an imaging platform capable of surveying larger regions. ResNet applied on separate individual data sets, i.e., without concept drift, showed that changing object distance was less important than the amount of training data. The results for the image data acquired with the ocean floor observation system showed higher performance values than data collected with the autonomous underwater vehicle. The results from this concept drift studies indicate that collecting image data from many dives with slightly different gear may result in training data well-suited for learning taxonomic classification tasks and that data volume can compensate for light concept drift