Multi-vehicle adaptive 3D mapping for targeted ocean sampling.

Expanding spatial presentation from two-dimensional profile transects to three-dimensional ocean mapping is key for a better understanding of ocean processes. Phytoplankton distributions can be highly patchy and the accurate identification of these patches with the context, variability, and uncertainty of measurements on relevant scales is difficult to achieve. Traditional sampling methods, such as plankton nets, water samplers and in-situ vertical sensors, provide a snapshot and often miss the fine-scale horizontal and temporal variability. Here, we show how two autonomous underwater vehicles measured, adapted to, and reported real-time chlorophyll a measurements, giving insights into the spatiotemporal distribution of phytoplankton biomass and patchiness. To gain the maximum available information within their sensing scope, the vehicles moved in an adaptive fashion, looking for the regions of the highest predicted chlorophyll a concentration, the greatest uncertainty, and the least possibility of collision with other underwater vehicles and ships. The vehicles collaborated by exchanging data with each other and operators via satellite, using a common segmentation of the area to maximize information exchange over the limited bandwidth of the satellite. Importantly, the use of multiple autonomous underwater vehicles reporting real-time data combined with targeted sampling can provide better match with sampling towards understanding of plankton patchiness and ocean processes.

Flow-through imaging and automated analysis of oil-exposed early stage Atlantic cod (Gadus morhua).

Toxicology studies in early fish life stages serve an important function in measuring the impact of potentially harmful substances, such as crude oil, on marine life. Morphometric analysis of larvae can reveal the effects of such substances in retarding growth and development. These studies are labor intensive and time consuming, typically resulting in only a small number of samples being considered. An automated system for imaging and measurement of experimental animals, using flow-through imaging and an artificial neural network to allow faster sampling of more individuals, has been described previously and used in toxicity experiments. This study compares the performance of the automated imaging and analysis system with traditional microscopy techniques in measuring biologically relevant endpoints using two oil treatments as positive controls. We demonstrate that while the automated system typically underestimates morphometric measurements relative to analysis of manual microscopy images, it shows similar statistical results to the manual method when comparing treatments across most endpoints. It allows for many more individual specimens to be sampled in a shorter time period, reducing labor requirements and improving statistical power in such studies, and is noninvasive allowing for repeated sampling of the same population.

Contrasting phytoplankton-zooplankton distributions observed through autonomous platforms, in-situ optical sensors and discrete sampling.

Plankton distributions are remarkably 'patchy' in the ocean. In this study, we investigated the contrasting phytoplankton-zooplankton distributions in relation to wind mixing events in waters around a biodiversity-rich island (Runde) located off the western coast of Norway. We used adaptive sampling from AUV and shipboard profiles of in-situ phytoplankton photo-physiology and particle identification (copepods, fecal pellets and the dinoflagellate Tripos spp.) and quantification using optical and imaging sensors. Additionally, traditional seawater and net sampling were collected for nutrient and in-vitro chlorophyll a concentrations and phytoplankton and meso-zooplankton abundances. Persistent strong wind conditions (~5 days) disrupted the stratification in offshore regions, while stratification and a subsurface chlorophyll maximum (SCM) were observed above the base of the mixed layer depth (MLD ~30 m) in inshore waters. Contrasting phytoplankton and zooplankton abundances were observed between inshore (with the presence of a SCM) and offshore waters (without the presence of a SCM). At the SCM, phytoplankton abundances (Tripos spp., the diatom Proboscia alata and other flagellates) were half (average of 200 cell L-1) of those observed offshore. On the contrary, meso-zooplankton counts were ~6× higher (732 ind m-3 for Calanus spp.) inshore (where a SCM was observed) compared to offshore areas. In parallel, fecal pellets and ammonium concentrations were high (>1000 ind m-3 for the upper 20 m) at the SCM, suggesting that the shallow mixed layer might have increased encounter rates and promoted strong grazing pressure. Low nutrient concentrations (< 1µM for nitrate) were found below the MLD (60 m) in offshore waters, suggesting that mixing and nutrient availability likely boosted phytoplankton abundances. The size of the absorption cross-section (σPII') and yield of photosystem II photochemistry under ambient light (φPII') changed according to depth, while the depth-related electron flow (JPII) was similar between regions, suggesting a high degree of community plasticity to changes in the light regime. Our results emphasize the importance of using multiple instrumentation, in addition to traditional seawater and net sampling for a holistic understanding of plankton distributions.

A flow-through imaging system for automated measurement of ichthyoplankton.

Microscopic imaging and morphometric measurement of fish embryos and larvae is essential in environmental monitoring of fish populations and to evaluate larvae development in aquaculture. Traditional microscopy methods require time-consuming, repetitive work by human experts. We present a method for fast imaging and analysis of millimetre-scale ichthyoplankton suspended in seawater. Our system can be easily built from common and off-the-shelf components and uses open-source software for image capture and analysis. Our system obtains images of similar quality to traditional microscopy, and biological measurements comparable to those by human experts, with minimal human interaction. This saves time and effort, while increasing the size of data sets obtained. We demonstrate our approach with cod eggs and larvae, and present results showing biologically relevant endpoints including egg diameter, larval standard length, yolk volume and eye diameter, with comparison to similar measurements reported in the literature. • High throughput, microscope-scale imaging of fish eggs and larvae • Automated measurement of biologically relevant endpoints • Easily built from off-the-shelf components and open-source software.

Collaborating robots sample the primary production in the ocean.

Sampling genetic material from phytoplankton in open ocean eddies becomes more precise and efficient using a heterogeneous network of autonomous marine robots.

Toward adaptive robotic sampling of phytoplankton in the coastal ocean.

Currents, wind, bathymetry, and freshwater runoff are some of the factors that make coastal waters heterogeneous, patchy, and scientifically interesting-where it is challenging to resolve the spatiotemporal variation within the water column. We present methods and results from field experiments using an autonomous underwater vehicle (AUV) with embedded algorithms that focus sampling on features in three dimensions. This was achieved by combining Gaussian process (GP) modeling with onboard robotic autonomy, allowing volumetric measurements to be made at fine scales. Special focus was given to the patchiness of phytoplankton biomass, measured as chlorophyll a (Chla), an important factor for understanding biogeochemical processes, such as primary productivity, in the coastal ocean. During multiple field tests in Runde, Norway, the method was successfully used to identify, map, and track the subsurface chlorophyll a maxima (SCM). Results show that the algorithm was able to estimate the SCM volumetrically, enabling the AUV to track the maximum concentration depth within the volume. These data were subsequently verified and supplemented with remote sensing, time series from a buoy and ship-based measurements from a fast repetition rate fluorometer (FRRf), particle imaging systems, as well as discrete water samples, covering both the large and small scales of the microbial community shaped by coastal dynamics. By bringing together diverse methods from statistics, autonomous control, imaging, and oceanography, the work offers an interdisciplinary perspective in robotic observation of our changing oceans.

Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna.

Identification of benthic megafauna is commonly based on analysis of physical samples or imagery acquired by cameras mounted on underwater platforms. Physical collection of samples is difficult, particularly from the deep sea, and identification of taxonomic morphotypes from imagery depends on resolution and investigator experience. Here, we show how an Underwater Hyperspectral Imager (UHI) can be used as an alternative in situ taxonomic tool for benthic megafauna. A UHI provides a much higher spectral resolution than standard RGB imagery, allowing marine organisms to be identified based on specific optical fingerprints. A set of reference spectra from identified organisms is established and supervised classification performed to identify benthic megafauna semi-autonomously. The UHI data provide an increased detection rate for small megafauna difficult to resolve in standard RGB imagery. In addition, seafloor anomalies with distinct spectral signatures are also detectable. In the region investigated, sediment anomalies (spectral reflectance minimum at ~675 nm) unclear in RGB imagery were indicative of chlorophyll a on the seafloor. Underwater hyperspectral imaging therefore has a great potential in seafloor habitat mapping and monitoring, with areas of application ranging from shallow coastal areas to the deep sea.

Underwater hyperspectral imaging: a new tool for marine archaeology.

By applying an underwater hyperspectral imager (UHI) to a selection of archaeological artifacts, we have found spectral signatures that are representative of materials likely to be present at wreck sites. By successfully using the signatures to classify a subset of said artifacts placed on the seabed at 61 m depth, we demonstrate that it is possible to detect archaeological objects of interest in UHI data acquired by a remotely operated vehicle. Correct UHI classification of rust and glass bottles in situ on a historical wreck site further supports the viability of the method for marine archaeological applications.

Use of an Autonomous Surface Vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance.

Light is a major cue for nearly all life on Earth. However, most of our knowledge concerning the importance of light is based on organisms' response to light during daytime, including the dusk and dawn phase. When it is dark, light is most often considered as pollution, with increasing appreciation of its negative ecological effects. Using an Autonomous Surface Vehicle fitted with a hyperspectral irradiance sensor and an acoustic profiler, we detected and quantified the behavior of zooplankton in an unpolluted light environment in the high Arctic polar night and compared the results with that from a light-polluted environment close to our research vessels. First, in environments free of light pollution, the zooplankton community is intimately connected to the ambient light regime and performs synchronized diel vertical migrations in the upper 30 m despite the sun never rising above the horizon. Second, the vast majority of the pelagic community exhibits a strong light-escape response in the presence of artificial light, observed down to 100 m. We conclude that artificial light from traditional sampling platforms affects the zooplankton community to a degree where it is impossible to examine its abundance and natural rhythms within the upper 100 m. This study underscores the need to adjust sampling platforms, particularly in dim-light conditions, to capture relevant physical and biological data for ecological studies. It also highlights a previously unchartered susceptibility to light pollution in a region destined to see significant changes in light climate due to a reduced ice cover and an increased anthropogenic activity.

Tissue-associated "Candidatus Mycoplasma corallicola" and filamentous bacteria on the cold-water coral Lophelia pertusa (Scleractinia).

The cold-water coral Lophelia pertusa (Scleractinia, Caryophylliidae) is a key species in the formation of cold-water reefs, which are among the most diverse deep-sea ecosystems. It occurs in two color varieties: white and red. Bacterial communities associated with Lophelia have been investigated in recent years, but the role of the associated bacteria remains largely obscure. This study uses catalyzed reporter deposition fluorescence in situ hybridization to detect the in situ location of specific bacterial groups on coral specimens from the Trondheimsfjord (Norway). Two tissue-associated groups were identified: (i) bacteria on the host's tentacle ectoderm, "Candidatus Mycoplasma corallicola," are flasklike, pointed cells and (ii) endoderm-associated bona fide TM7 bacteria form long filaments in the gastral cavity. These tissue-bound bacteria were found in all coral specimens from the Trondheimsfjord, indicating a closer relationship with the coral compared to bacterial assemblages present in coral mucus and gastric fluid.

Phenotype-specific bacterial communities in the cold-water coral Lophelia pertusa (Scleractinia) and their implications for the coral's nutrition, health, and distribution.

The pseudocolonial coral Lophelia pertusa (Scleractinia, Caryophylliidae) is a eurybathic, stenothermal cosmopolitan cold-water species. It occurs in two color varieties, white and red. L. pertusa builds vast cold-water coral reefs along the continental margins, which are among the most diverse deep-sea habitats. Microbiology of L. pertusa has been in scientific focus for only a few years, but the question of whether the coral holds a host-specific bacterial community has not been finally answered. Bacteria on coral samples from the Trondheimsfjord (Norway) were characterized by the culture-independent 16S rRNA gene-based techniques terminal restriction fragment length polymorphism and sequence analysis. L. pertusa revealed a high microbial richness. Clone sequences were dominated by members of the Alpha- and Gammaproteobacteria. Other abundant taxa were Bacteroidetes, Actinobacteria, Verrucomicrobia, Firmicutes, and Planctomycetes. The bacterial community of L. pertusa not only differed conspicuously from that of the environment but also varied with both the location and color variety of its host. Therefore, the microbial colonization cannot be termed "specific" sensu stricto. However, similarities to other coral-bacterium associations suggest the existence of "cold-water coral-specific" bacterial groups sensu lato. L. pertusa-associated bacteria appear to play a significant role in the nutrition of their host by degradation of sulfur compounds, cellulose, chitin, and end products of the coral's anaerobic metabolism. Some coral-associated microbes were regarded as opportunistic pathogens. Dominance of mixotrophic members of the Rhodobacteraceae in white L. pertusa could explain the wider dispersal of this phenotype by supplementary nutrition.