We present the first documented complete mitogenomes of deep-sea Pennatulacea, representing nine genera and eight families. These include one species each of the deep-sea genera Funiculina, Halipteris, Protoptilum and Distichoptilum, four species each of Umbellula and Pennatula, three species of Kophobelemnon and two species of Anthoptilum, as well as one species of the epi-and mesobenthic genus Virgularia. Seventeen circular genomes ranged from 18,513 bp (Halipteris cf. finmarchica) to 19,171 bp (Distichoptilum gracile) and contained all genes standard to octocoral mitochondrial genomes (14 protein-coding genes, two ribosomal RNA genes and one transfer RNA). We found at least three different gene orders in Pennatulacea: the ancestral gene order, the gene order found in bamboo corals (Family Isididae), and a novel gene order. The mitogenome of one species of Umbellula has a bipartite genome ($13 kbp and $5 kbp), with good evidence that both parts are circular.

Black corals (Anthozoa: Antipatharia) are an ecologically and culturally important group of deep-sea cnidarians. However, as the majority of species inhabit depths >50 m, they are relatively understudied. The inaccessibility of well-preserved tissue for species of interest has limited the scope of molecular analysis, and as a result only a small number of antipatharian mitochondrial genomes have been published. Using next generation sequencing, 18 complete and five partial antipatharian mitochondrial genomes were assembled, increasing the number of complete mitochondrial genomes to 22. This includes species from six antipatharian families, four of which were previously unrepresented, enabling the first family-level, full mitochondrial gene analysis over the whole order. The circular mitogenomes ranged in size from 17,681 to 21,669 bp with the large range in size due to the addition of an intron in COX1 in some species and size variation of intergenic regions. All mitogenomes contained the genes standard to all hexacoral mitogenomes (13 protein coding genes, two rRNAs and two tRNAs). The only difference in gene content is the presence of the COX1 intron in five families. The most variable mitochondrial gene is ND4 which may have implications for future barcoding studies. Phylogenetic analysis confirms that Leiopathidae is sister to all other families. Families Antipathidae, Cladopathidae and Schizopathidae are polyphyletic, supporting previous studies that call for a taxonomic revision.

The term vulnerable marine ecosystem (VME) was introduced to facilitate the spatial management of deep-seas, identifying those habitats vulnerable to anthropogenic disturbance, such as trawling. Consistent interpretation of the VME definition has been hampered by an underlying paucity of knowledge about the nature and distribution of deep-sea habitats. Photographic and video platforms yield data rich, quantifiable imagery to address these knowledge gaps. A low-cost towed benthic video sled has been used to investigate deep-sea habitats and trawling impacts in west Greenland. A review of imagery from multiple cruises highlighted an area where benthic megafauna contributes to notable structural complexity on the continental slope of the Toqqusaq Bank. Quantitative analysis of imagery from this area provides the first description of a soft coral garden habitat and other communities. The coral garden and observed densities are considered in relation to the VME guidelines (FAO, 2009) and wider literature. The study proposes a 486 km 2 area spanning ∼60 km of continental slope as a VME. This has direct implications for the management of economically important deep-sea trawl fisheries, which are immediately adjacent. This furthers our knowledge and understanding of VMEs in North Atlantic, in a previously understudied region and demonstrates the utility of a low-cost video sled for identifying and describing VMEs.

We consider the opportunities and challenges associated with organizing a conference online, using a case study of a medium-sized (approx. 400 participants) international conference held virtually in August 2020. In addition, we present quantifiable evidence of the participants' experience using the results from an online post-conference questionnaire. Although the virtual meeting was not able to replicate the in-person experience in some aspects (e.g. less engagement between participants) the overwhelming majority of respondents found the meeting an enjoyable experience and would join similar events again. Notably, there was a strong desire for future in-person meetings to have at least some online component. Online attendance by lower-income researchers was higher compared with a past, similar-themed in-person meeting held in a high-income nation, but comparable to one held in an upper-middle-income nation. This indicates that online conferences are not a panacea for diversity and inclusivity, and that holding in-person meetings in developing economies can be at least as effective. Given that it is now relatively easy to stream contents of meetings online using low-cost methods, there are clear benefits in making all presented content accessible online, as well as organizing online networking events for those unable to attend in person.

1. Remote sensing is a powerful monitoring tool for seaweeds, providing large-scale insights into their ecosystem benefits and invasive impacts. Satellites and manned aircraft have been widely used for this purpose, but their spatial resolution is generally insufficient to map heterogeneous seaweed habitats. 2. In this study, the potential of low-cost and high-resolution drone imagery to map heterogeneous seaweed habitats was assessed on Azorean coasts, where an invasive and commercial species, Asparagopsis armata, is present. A Phantom Pro 3 drone equipped with a visible light sensor was used to create photomosaics in three sites on São Miguel island, and ground-truth data for various seaweed groups were collected with exploratory kayak sampling. The support-vector machine, random forest and artificial neural network algorithms were used to construct predictive models of seaweed coverage. 3. Wind, clouds and sun glint were the most significant factors affecting drone surveys and images. Exploratory sampling helped locate relatively homogeneous seaweed patches, however, the data were limited and spatially autocorrelated contributing to over-optimistic model evaluation metrics. Moreover, the models struggled to distinguish seaweeds deeper than three to four metres. 4. In conclusion, using drones to monitor heterogeneous seaweed habitats is challenging, especially in oceanic islands where waters are deep and weather is unpredictable. However, this study highlights the potential use of photo-interpretation to collect modelling data from drone imagery, instead of time-consuming exploratory ground-truth sampling. Future studies could assess drones to map seaweeds in less challenging conditions and use photointerpretation to improve collection of modelling data.