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.

Benthic megafaunal biodiversity of the Charlie-Gibbs fracture zone: spatial variation, potential drivers, and conservation status.

The Charlie-Gibbs Fracture Zone (CGFZ) is a prominent geological feature offsetting the Mid-Atlantic Ridge (MAR), consisting of two parallel fractures, creating a highly variable seafloor bathymetry. It has been defined as the most important latitudinal biodiversity transitional zone on the MAR. Despite this recognition, the faunal communities living on the fracture zone have not been extensively described. A remotely operated vehicle (ROV) was utilised during the TOSCA (Tectonic Ocean Spreading at the Charlie-Gibbs Fracture Zone) survey. The survey included five ROV video transects at depths between 560 and 2900 m. The objectives of the study were to use this video footage to quantify benthic megafaunal density and biodiversity patterns on the CGFZ and their environmental drivers. Species accumulation curves and generalised additive modelling show that depth and the presence of hard substrates play an important role in explaining species richness and abundance at the CGFZ. Coral taxa showed highest abundance between depths of 1500 and 2000 m, while sponge taxa were more abundant between 1750 and 2250 m. A dense sponge aggregation was identified on a ridge feature at 2250 m depth. The high biodiversity and presence of dense sponge aggregations and coral gardens found in this study highlight the need for detailed surveys to help support decisions made by governing bodies on the protection status of the CGFZ. Supplementary Information: The online version contains supplementary material available at 10.1007/s12526-022-01285-1.

Author Correction: Species replacement dominates megabenthos beta diversity in a remote seamount setting.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Species replacement dominates megabenthos beta diversity in a remote seamount setting.

Seamounts are proposed to be hotspots of deep-sea biodiversity, a pattern potentially arising from increased productivity in a heterogeneous landscape leading to either high species co-existence or species turnover (beta diversity). However, studies on individual seamounts remain rare, hindering our understanding of the underlying causes of local changes in beta diversity. Here, we investigated processes behind beta diversity using ROV video, coupled with oceanographic and quantitative terrain parameters, over a depth gradient in Annan Seamount, Equatorial Atlantic. By applying recently developed beta diversity analyses, we identified ecologically unique sites and distinguished between two beta diversity processes: species replacement and changes in species richness. The total beta diversity was high with an index of 0.92 out of 1 and was dominated by species replacement (68%). Species replacement was affected by depth-related variables, including temperature and water mass in addition to the aspect and local elevation of the seabed. In contrast, changes in species richness component were affected only by the water mass. Water mass, along with substrate also affected differences in species abundance. This study identified, for the first time on seamount megabenthos, the different beta diversity components and drivers, which can contribute towards understanding and protecting regional deep-sea biodiversity.

New approaches to high-resolution mapping of marine vertical structures.

Vertical walls in marine environments can harbour high biodiversity and provide natural protection from bottom-trawling activities. However, traditional mapping techniques are usually restricted to down-looking approaches which cannot adequately replicate their 3D structure. We combined sideways-looking multibeam echosounder (MBES) data from an AUV, forward-looking MBES data from ROVs and ROV-acquired videos to examine walls from Rockall Bank and Whittard Canyon, Northeast Atlantic. High-resolution 3D point clouds were extracted from each sonar dataset and structure from motion photogrammetry (SfM) was applied to recreate 3D representations of video transects along the walls. With these reconstructions, it was possible to interact with extensive sections of video footage and precisely position individuals. Terrain variables were derived on scales comparable to those experienced by megabenthic individuals. These were used to show differences in environmental conditions between observed and background locations as well as explain spatial patterns in ecological characteristics. In addition, since the SfM 3D reconstructions retained colours, they were employed to separate and quantify live coral colonies versus dead framework. The combination of these new technologies allows us, for the first time, to map the physical 3D structure of previously inaccessible habitats and demonstrates the complexity and importance of vertical structures.

Landscape-scale spatial heterogeneity in phytodetrital cover and megafauna biomass in the abyss links to modest topographic variation.

Sinking particulate organic matter (POM, phytodetritus) is the principal limiting resource for deep-sea life. However, little is known about spatial variation in POM supply to the abyssal seafloor, which is frequently assumed to be homogenous. In reality, the abyss has a highly complex landscape with millions of hills and mountains. Here, we show a significant increase in seabed POM % cover (by ~1.05 times), and a large significant increase in megafauna biomass (by ~2.5 times), on abyssal hill terrain in comparison to the surrounding plain. These differences are substantially greater than predicted by current models linking water depth to POM supply or benthic biomass. Our observed variations in POM % cover (phytodetritus), megafauna biomass, sediment total organic carbon and total nitrogen, sedimentology, and benthic boundary layer turbidity, all appear to be consistent with topographically enhanced current speeds driving these enhancements. The effects are detectable with bathymetric elevations of only 10 s of metres above the surrounding plain. These results imply considerable unquantified heterogeneity in global ecology.

Vertical stratification of beetles (Coleoptera) and flies (Diptera) in temperate forest canopies.

Forest canopies support high arthropod biodiversity, but in temperate canopies, little is known about the spatial distribution of these arthropods. This is an important first step toward understanding ecological roles of insects in temperate canopies. The objective of this study was to assess differences in the species composition of two dominant and diverse taxa (Diptera and Coleoptera) along a vertical gradient in temperate deciduous forest canopies. Five sugar maple trees from each of three deciduous forest sites in southern Quebec were sampled using a combination of window and trunk traps placed in three vertical strata (understory, mid-canopy, and upper-canopy) for three sampling periods throughout the summer. Coleoptera species richness and abundance did not differ between canopy heights, but more specimens and species of Diptera were collected in the upper-canopy. Community composition of Coleoptera and Diptera varied significantly by trap height. Window traps collected more specimens and species of Coleoptera than trunk traps, although both trap types should be used to maximize representation of the entire Coleoptera community. There were no differences in abundance, diversity, or composition of Diptera collected between trap types. Our data confirm the relevance of sampling all strata in a forest when studying canopy arthropod biodiversity.

Automated image analysis for the detection of benthic crustaceans and bacterial mat coverage using the VENUS undersea cabled network.

The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada) deploys seafloor camera systems at several sites. Our objective in this study was to implement new automated image analysis protocols for the recognition and counting of benthic decapods (i.e., the galatheid squat lobster, Munida quadrispina), as well as for the evaluation of changes in bacterial mat coverage (i.e., Beggiatoa spp.), using a camera deployed in Saanich Inlet (103 m depth). For the counting of Munida we remotely acquired 100 digital photos at hourly intervals from 2 to 6 December 2009. In the case of bacterial mat coverage estimation, images were taken from 2 to 8 December 2009 at the same time frequency. The automated image analysis protocols for both study cases were created in MatLab 7.1. Automation for Munida counting incorporated the combination of both filtering and background correction (Median- and Top-Hat Filters) with Euclidean Distances (ED) on Red-Green-Blue (RGB) channels. The Scale-Invariant Feature Transform (SIFT) features and Fourier Descriptors (FD) of tracked objects were then extracted. Animal classifications were carried out with the tools of morphometric multivariate statistic (i.e., Partial Least Square Discriminant Analysis; PLSDA) on Mean RGB (RGBv) value for each object and Fourier Descriptors (RGBv+FD) matrices plus SIFT and ED. The SIFT approach returned the better results. Higher percentages of images were correctly classified and lower misclassification errors (an animal is present but not detected) occurred. In contrast, RGBv+FD and ED resulted in a high incidence of records being generated for non-present animals. Bacterial mat coverage was estimated in terms of Percent Coverage and Fractal Dimension. A constant Region of Interest (ROI) was defined and background extraction by a Gaussian Blurring Filter was performed. Image subtraction within ROI was followed by the sum of the RGB channels matrices. Percent Coverage was calculated on the resulting image. Fractal Dimension was estimated using the box-counting method. The images were then resized to a dimension in pixels equal to a power of 2, allowing subdivision into sub-multiple quadrants. In comparisons of manual and automated Percent Coverage and Fractal Dimension estimates, the former showed an overestimation tendency for both parameters. The primary limitations on the automatic analysis of benthic images were habitat variations in sediment texture and water column turbidity. The application of filters for background corrections is a required preliminary step for the efficient recognition of animals and bacterial mat patches.