High diversity seabed habitats, such as shellfish aggregations, play a significant role in marine ecosystem sustainability but are susceptible to bottom disturbance induced by anthropogenic activities. Regular monitoring of these habitats with effective mapping methods is therefore essential. Multibeam echosounder (MBES) has been widely used in recent decades for seabed characterization due to its non-destructive manner and extensive spatial coverage compared to traditional methods like bottom sampling. Nevertheless, bottom sampling remains essential to link ground truth with acoustic seabed classification. Using seabed samples and MBES measurements, machine learning techniques are commonly employed to model their relationships and generate classification maps of an extended seabed. However, limited ground truth data, resulting from constraints in regulations, budget, or time, may impede the development of robust machine learning models. To address this challenge, we applied a semi-supervised machine learning method to classify seabed sediments of a blue mussel (Mytilus edulis) cultivation area in the Oosterschelde, the Netherlands. We utilized nine boxcore samples to generate pseudo-labels on MBES data. These pseudo-labels enlarged the training data size, facilitated the training of three comprehensive machine learning algorithms (Gradient Boosting, Random Forest, and Support Vector Machine), and helped to classify the study site into mussel and non-mussel areas. We found the geomorphological and backscatter-related features to be complementary for mussel culture detection. Our classification results were demonstrated effective through expert knowledge of this cultivation area and brought insights for future research on natural mussel habitats.

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To facilitate the conservation of seafloor habitats and planning of offshore activities, there is a growing need for mapping marine benthos in an effective and efficient way. Acoustic data acquired by multi-beam echosounders (MBES) have been extensively used for large-scale and high-resolution seafloor characterization. A deeper understanding of the relationship between backscatter data and sediment compositions can help to identify the benthos occurrence from the MBES data. With two multi-spectral MBES datasets collected near the western Wadden Sea islands in the North Sea, we investigated the potential of mapping marine benthos through backscatter classification. Two unsupervised classification methods, i.e., Bayesian classification, which mainly exploits the backscatter strength from incident angles larger than 20°, and hierarchical clustering of the backscatter strength at different angular ranges, were employed and the results were compared. The classification results from both methods showed a good correspondence with sediment properties such as the median grain size. Moreover, based on a principal component analysis of bottom sample properties, the hierarchical clustering results indicated a better distinction between contributions from the gravel content and benthos occurrence, e.g., sand mason worm density, than Bayesian classification, through involving the backscatter angular variations. Classification for multiple frequencies, on the other hand, showed little difference regarding the relationship with bottom sample properties. Although the backscatter difference between frequencies was also found to positively correlate with certain sample properties, using multi-spectral features for acoustic classification in this study did not reveal additional information compared to single-frequency classification results.@en

Detailed knowledge of both the sedimentological and ecological characteristics of the seafloor is essential when undertaking bottom-disturbing activities, but can be a challenge to obtain. Through backscatter data at different frequencies, collected with a multi-spectral multi-beam sonar, information on the structure of both the sediment surface and subsurface, and potentially also on the presence and distribution of benthic organisms, can be derived. We conducted two surveys at sea in summer 2021, in which we used an R2Sonic 2026 multi-spectral multi-beam sonar in the southern North Sea. Boxcore samples were taken to gather information on macrobenthos densities and sediment characteristics. The two studied areas were found to differ in seafloor morphology and correspondingly in the composition of the sediment composition and benthos distribution. Backscatter strength was used to classify the seafloor via the Bayesian method and via hierarchical clustering of angular variation. Relationships between the classification results for three frequencies and sediment and ecological variables were studied through redundancy analysis (RDA), for which hierarchical clustering of the angular variation in backscatter strength showed a higher model fit than Bayesian classification. We found that the density of the sand mason worm Lanice conchilega and percentages of dead shells, gravel and sand contributed most to the backscatter-based classification, with lower contributions of the percentages of mud and living bivalves. Our results suggest that acoustic backscatter can be used to delineate distinct seafloor regions, corresponding with concurrent gradients in ecological and sedimentological variables.

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Acoustic classification using single-beam and multi-beam echosounders has been widely applied in characterizing seabed sediments. Although previous studies have shown a better discrimination of fine and coarse sediments using multi-spectral echosounder data, analysis regarding comprehensive seabed sediment properties is still needed. In this study, we used single-beam data of 24 kHz, as well as multi-beam data of 90 and 300 kHz to investigate the benefits of multi-spectral backscatter data in describing sediment properties including median grain size; weight percentages of gravel, sand, and mud; volume percentages of stones, shell fragments, and living bivalves; as well as density of acoustically hard animals (molluscs and the tube-building worm Lanice conchilega). We classified data of each frequency in an unsupervised manner, using K-means clustering for the single-beam echo time series and Bayesian classification for the multi-beam backscatter. Compared with the top-layer sediment properties, we found classification of 90 and 300 kHz consistent with variations of median grain size and L. conchilega density, whereas classification of 24 kHz can also be related to the percentages of shell fragments and stones. In addition, one acoustic class of 24 kHz might indicate a higher gravel content in the subsurface of the study area. Although quantitative relationships between backscatter and sediment properties are still difficult to achieve given a limited number of samples, using multi-spectral backscatter data is a potential approach to characterize seabed sediments from various perspectives.

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Biological traits of benthic macroinvertebrates from a large area of the North Sea soft sediments were used to explore habitat occupancy within seascapes of contrasting hydrodynamics. The area, the Dutch sector of the North Sea, is mainly composed of 2 habitats: shallow dynamic bottoms of heterogeneous geomorphologies and deep homogeneous muddy bottoms. Higher within-habitat heterogeneity was hypothesized to more specifically select benthic life strategies according to environmental filtering, i.e. through the action of abiotic forces. Functional community patterns were explored through the RLQ method, which relates habitat and trait variables, at different spatial scales of specific seascape heterogeneity, and functional diversity indices were used to shed light on community assembly mechanisms. Locally, 3 associations between habitat characteristics and biological traits were shown to correspond with predictions of life history theories, whereas only 2 emerged when considering all types of seascapes. This spatial scaledependence was explained by abiotic alternations masked over the larger scale at which all the existing strategies could not be properly disentangled. The relative composition in strategies obeyed specific assembly rules as identified by functional diversity indices. Seascape geomorphology was locally discriminant of functional patterns, and could account for biodiversification, much beyond basic taxonomic counts. Whereas habitats of higher physical stability hosted the taxonomically richest communities, stress or disturbance frequency increased functional variations within communities due to different strategist habitat occupancies. This study proposes a generic mechanism of benthic community structuring in soft sediment shelves.

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Biogenic reefs form biodiversity hotspots and are key components of marine ecosystems, making them priority habitats for nature conservation. However, the conservation status of biogenic reefs generally depends on their size and stability. Dynamic, patchy reefs may therefore be excluded from protection. Here, we studied epibenthos and epifauna density, richness, and community composition of patchy, dynamic Sabellaria spinulosa (ross worm) reefs in the North Sea. This study was conducted by comparing boxcore (endobenthos) and video transect (epifauna) data from two research campaigns in 2017 and 2019 to the Brown Bank area on the Dutch Continental Shelf, where S. spinulosa reefs were first discovered in 2017. The Brown Bank area is characterized by dynamic, migratory bedforms at multiple scales which potentially affect biogenic reef stability. We showed that S. spinulosa habitats had a patchy distribution and alternated with habitats comprised of plain sand. Average S. spinulosa habitat patch size was 5.57 ± 0.99 m and 3.94 ± 0.22 m in 2017 and 2019, respectively (mean ± SE), which especially in 2019 closely resembled the small-scale megaripple bedforms. Contrary to the endobenthos communities that were unaffected by S. spinulosa, epifauna density and species richness were at least two times higher in S. spinulosa habitats compared to sandy habitats, resulting in different community compositions between the two habitat types. We showed that S. spinulosa persisted in the area for almost 2 years. Although the stability of individual patches remained unclear, we demonstrated that even patchy biogenic reefs may promote density and local biodiversity of mobile, epibenthic species, very likely as a result of increased habitat heterogeneity provided by reef habitat patches. This indicates that patchy biogenic reefs that occur in dynamic environments may also have high ecological value and their conservation status should be (re)considered to ensure their protection.

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Conflicts of interests between economic and nature conservation stakeholders are increasingly common in coastal seas, inducing a growing need for evidence-based marine spatial planning. This requires accurate, high-resolution habitat maps showing the spatial distribution of benthic assemblages and enabling intersections of habitats and anthropogenic activities. However, such detailed maps are often not available because relevant biological data are scarce or poorly integrated. Instead, physiotope maps, solely based on abiotic variables, are now often used in marine spatial planning. Here, we investigated how pointwise, relatively sparse biological data can be integrated with gridded, high-resolution environmental data into informative habitat maps, using the intensively used southern North Sea as a case-study. We first conducted hierarchical clustering to identify discrete biological assemblages for three faunal groups: demersal fish, epifauna, and endobenthos. Using Random Forest models with high-resolution abiotic predictors, we then interpolated the distribution of these assemblages to high resolution grids. Finally, we quantified different anthropogenic pressures for each habitat. Habitat maps comprised a different number of habitats between faunal groups (6, 13, and 10 for demersal fish, epifauna, and endobenthos respectively) but showed similar spatial patterns for each group. Several of these ‘fauna-inclusive’ habitats resembled physiotopes, but substantial differences were also observed, especially when few (6; demersal fish) or most (13; epifauna) physiotopes were delineated. Demersal fishing and offshore wind farms (OWFs) were clearly associated with specific habitats, resulting in unequal anthropogenic pressure between different habitats. Natura-2000 areas were not specifically associated with demersal fishing, but OWFs were situated mostly inside these protected areas. We thus conclude that habitat maps derived from biological datasets that cover relevant faunal groups should be included more in ecology-inclusive marine spatial planning, instead of only using physiotope maps based on abiotic variables. This allows better balancing of nature conservation and socio-economic interests in continental shelf seas.

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High-resolution surveying techniques of subtidal soft-bottom seafloor habitats show higher small-scale variation in topography and sediment type than previously thought, but the ecological relevance of this variation remains unclear. In addition, high-resolution surveys of benthic fauna show a large spatial variability in community composition, but this has yet poorly been linked to seafloor morphology and sediment composition. For instance, on soft-bottom coastal shelves, hydrodynamic forces from winds and tidal currents can cause nested multiscale morphological features ranging from metre-scale (mega)ripples, to sand waves and kilometre-scale linear sandbanks. This multiscale habitat heterogeneity is generally disregarded in the ecological assessments of benthic habitats. We therefore developed and tested a novel multiscale assessment toolbox that combines standard bathymetry, multibeam backscatter classification, video surveying of epibenthos and box core samples of sediment and macrobenthos. In a study on the Brown Bank, a sandbank in the southern North Sea, we found that these methods are greatly complementary and allow for more detail in the interpretation of benthic surveys. Acoustic and video data characterised the seafloor surface and subsurface, and macrobenthos communities were found to be structured by both sandbank and sand wave topography. We found indications that acoustic techniques can be used to determine the location of epibenthic reefs. The multiscale assessment toolbox furthermore allows formulating recommendations for conservation management related to the impact of sea floor disturbances through dredging and trawling.

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Backscatter data from multibeam echosounders are commonly used to classify seafloor sediment composition. Previously, it was found that the survey azimuth affects backscatter when small organized seafloor structures, such as sand ripples, are present. These sand ripples are too small to be detected in the multibeam bathymetry. Here, we show that such azimuth effects are time dependent and are useful to examine the orientation of sand ripples in relation to the flow direction of the tide. To this end, multibeam echosounder data at four different frequencies were gathered from the area of the Brown Bank in the North Sea. The acoustic results were compared to video and tide-flow data for validation. The sand ripples affected the backscatter at all frequencies, but for the lowest frequencies the effect was spread over more beam angles. Using the acoustic data made it possible to deduce the orientations of the sand ripples over areas of multiple square kilometers. We found that the top centimeter(s) of the seafloor undergoes a complete transformation every six hours, as the orientation of the sand ripples changes with the changing tide. Our methodology allows for morphology change detection at larger scales and higher resolutions than previously achieved.@en