Vurdering av sårbare bunnhabitater i det nordlige Barentshavet; trålfangete bunndyr fra det årlige «øko-toktet»

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Modeling the Distribution of Habitat-Forming, Deep-Sea Sponges in the Barents Sea: The Value of Data

The use of species occurrence as a proxy for habitat type is widespread, probably because it allows the use of species distribution modeling (SDM) to cost-effectively map the distribution of e.g., vulnerable marine ecosystems. We have modeled the distribution of epibenthic megafaunal taxa typical of soft-bottom, Deep-Sea Sponge Aggregations (DSSAs), i.e., “indicators,” to discover where in the Barents Sea region this habitat is likely to occur. The following taxa were collectively modeled: Hexadella cf. dedritifera, Geodia spp., Steletta sp., Stryphnus sp. The data were extracted from MarVid, the video database for the Marine AREAl database for NOrwegian waters (MAREANO). We ask whether modeling density data may be more beneficial than presence/absence data, and whether using this list of indicator species is enough to locate the target habitat. We use conditional inference forests to make predictions of probability of presence of any of the target sponges, and total density of all target sponges, for an area covering a large portion of the Norwegian Barents Sea and well beyond the data’s spatial range. The density models explain 0.88), depending on the variables/samples used to train the model. The predicted surfaces were then classified on the basis of a probability threshold (0.75) and a density threshold (13 n/100 m2) to obtain polygons of “core area” and “hotspots” respectively (zones). The DSSA core area comprises two main regions: the Egga shelf break/Tromsøflaket area, and the shelf break southwest of Røst bank in the Træna trench. Four hotspots are detected within this core area. Zones are evaluated in the light of whole-community data which have been summarized as taxon richness and density of all megafauna. Total megafaunal density was significantly higher inside the hotspots relative to the background. Richness was not different between zones. Hotspots appeared different to one another in their richness and species composition although no tests were possible. We make the case that the effectiveness of the indicator species approach for conservation planning rests on the availability of density data on the target species, and data on co-occurring species.publishedVersio

Physical characterization and benthic megafauna distribution and species composition on Orphan Knoll and Orphan Seamount, NW Atlantic

Orphan Knoll (OK) is an 'orphaned' fragment of the North American continental crust that contains ~250 mounds of unknown composition ranging from 60 to 600 m of meters tall and 1 to 3 km wide. The adjacent “Orphan Seamount” (OS) is located 9 km NE of the SE portion of OK and is a volcanic seamount. The purpose of this study was to: determine the age and composition of the enigmatic OK mounds and OS, in an effort to better understand their origin and thus physical deep-sea habitat; to identify the distribution and abundance of the benthic megafauna of OK and OS; to examine the effects of bathymetry, oceanography and geology on deep-sea community composition. A multipurpose survey using the remotely operated vehicle (ROV) ROPOS was used to collect geological substrate samples, biological presence data (HD video), oceanographic data (conductivity, temperature and density (CTD)) and high and low resolution multibeam imagery. Rock samples on OS were identified as basaltic bedrock with limestone-filled vesicles (mid-Miocene aged through identification of Globigerina spp. and Orbulina spp. of pelagic foraminifera); thereby, identifying the OS as a volcanic seamount having been formed between the lower Cretaceous and the mid Miocene. Rock samples from the OK mounds identified mid-Miocene bedded pelagic limestone bedrock as the upper layer of limestone on top of the OK mounds. An unconformity was discovered between units 2 and 3 of the bedded OK mound limestone, identifying tilting of the faulted-blocks that are the Orphan Knoll mounds. The formation of the OK mounds possibly occurred through Neogene faulting through plate movements along the White Sail fault and quaternary faulting along the Charlie Gibbs Fracture Zone (CGFZ). On six ROV dives, 18 identified species of coral, 4 species of sponges, and 10 species of other deep-sea megafauna were identified. Amongst all of the recorded megafaunal species, 10 large concentrations (>20% area coverage) were grouped in an effort to further examine community turnover factors. Statistical analysis using gradientForest identified that bathymetry data of an intermediate scale (100 m spatial resolution) was the most accurate data to collect to explain megafaunal distribution and abundance through examining changes in community turnover along driver gradients in the deep-sea megafaunal species; however, surficial geology and oceanographic data were also important drivers in distribution and abundance of deep-sea megafauna. The variables depth, slope and aspect were found as being the most accurate descriptors when assessing changes in deep-sea megafaunal community turnover

Modelling benthic habitats and biotopes off the coast of Norway to support spatial management.

Habitat conservation, and hence conservation of biodiversity hinges on knowledge of the spatial distribution of habitats, not least those that are particularly valuable or vulnerable. In offshore Norway, benthic habitats are systematically surveyed and described by the national programme MAREANO (Marine AREAl database for NOrwegian waters). Benthic habitats and biotopes are defined in terms of the species composition of their epibenthic megafauna. Some habitats are of special conservation interest on account of their intrinsic value and/or vulnerability (e.g., long-lived species, rareness, to comply with international regulations such as OSPAR). In Norway, off Nordland and Troms, the following habitats of special interest can be found: Umbellula encrinus Stands, Radicipes sp. Meadows, Deep Sea Sponge Aggregations, Seapen and Burrowing Megafauna Communities, Hard Bottom Coral Gardens. In this paper, we used underwater video data collected within the MAREANO programme to define and describe benthic habitats and biotopes of special interest, and to map the geographic distribution thereof by means of habitat modelling. We first evaluated the community structure of each habitat in the list using a SIMPROF test. We determined that the class Deep Sea Sponge Aggregations, as defined by OSPAR, had to be split into at least three classes. We then re-defined seven new types of ecological features, including habitats and biotopes that were sufficiently homogeneous. Then we modelled the spatial distributions of these habitats and biotopes using Conditional Inference Forests. Since the purpose of the distribution maps is to support spatial planning we classified the heat maps using density thresholds. The accuracy of models ranged from fair to excellent. Hard Bottom Coral Gardens were the most rare habitat in terms of total area predicted (224 km2, 0.3% of the area modelled), closely followed by Radicipes Meadows (391 km2, 0.6%). Soft Bottom Demosponges (Geodid sponges and other taxa) represent the largest habitat, with a predicted area of 9288 km2 (14%). Distribution maps of classes defined by habitat-forming species (Hard Bottom Coral Gardens) were more reliable than those defined by a host of species, or where no single species was a clear habitat provider (e.g. Seapen and Burrowing Megafauna Communities). We also put forward that a scale of patchiness larger than the scale of observation, and homogeneity of the community both play a role in model performance, and hence in map usefulness. These along with density threshold values based on observed data should all be taken into account in marine classifications and habitat definitions

Predicting the Distribution of Indicator Taxa of Vulnerable Marine Ecosystems in the Arctic and Sub-arctic Waters of the Nordic Seas

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Using Spatial Validity and Uncertainty Metrics to Determine the Relative Suitability of Alternative Suites of Oceanographic Data for Seabed Biotope Prediction. A Case Study from the Barents Sea, Norway

The use of habitat distribution models (HDMs) has become common in benthic habitat mapping for combining limited seabed observations with full-coverage environmental data to produce classified maps showing predicted habitat distribution for an entire study area. However, relatively few HDMs include oceanographic predictors, or present spatial validity or uncertainty analyses to support the classified predictions. Without reference studies it can be challenging to assess which type of oceanographic model data should be used, or developed, for this purpose. In this study, we compare biotope maps built using predictor variable suites from three different oceanographic models with differing levels of detail on near-bottom conditions. These results are compared with a baseline model without oceanographic predictors. We use associated spatial validity and uncertainty analyses to assess which oceanographic data may be best suited to biotope mapping. Our results show how spatial validity and uncertainty metrics capture differences between HDM outputs which are otherwise not apparent from standard non-spatial accuracy assessments or the classified maps themselves. We conclude that biotope HDMs incorporating high-resolution, preferably bottom-optimised, oceanography data can best minimise spatial uncertainty and maximise spatial validity. Furthermore, our results suggest that incorporating coarser oceanographic data may lead to more uncertainty than omitting such data.publishedVersio

Diversity, structure and spatial distribution of megabenthic communities in Cap de Creus continental shelf and submarine canyon (NW Mediterranean)

The continental shelf and submarine canyon off Cap de Creus (NW Mediterranean) were declared a Site of Community Importance (SCI) within the Natura 2000 Network in 2014. Implementing an effective management plan to preserve its biological diversity and monitor its evolution through time requires a detailed character ization of its benthic ecosystem. Based on 60 underwater video transects performed between 2007 and 2013 (before the declaration of the SCI), we thoroughly describe the composition and structure of the main mega benthic communities dwelling from the shelf down to 400 m depth inside the submarine canyon. We then mapped the spatial distribution of the benthic communities using the Random Forest algorithm, which incor porated geomorphological and oceanographic layers as predictors, as well as the intensity of the bottom-trawling fishing fleet. Although the study area has historically been exposed to commercial fishing practices, it still holds a rich benthic ecosystem with over 165 different invertebrate (morpho)species of the megafauna identified in the video footage, which form up to 9 distinct megabenthic communities. The continental shelf is home to coral gardens of the sea fan Eunicella cavolini, sea pen and soft coral assemblages, dense beds of the crinoid Leptometra phalangium, diverse sponge grounds and massive aggregations of the brittle star Ophiothrix fragilis. The submarine canyon off Cap de Creus is characterized by a cold-water coral community dominated by the scleractinian coral Madrepora oculata, found in association with several invertebrate species including oysters, brachiopods and a variety of sponge species, as well as by a community dominated by cerianthids and sea urchins, mostly in sedimentary areas. The benthic communities identified in the area were then compared with habitats/biocenoses described in reference habitat classification systems that consider circalittoral and bathyal environments of the Mediterranean. The complex environmental setting characteristic of the marine area off Cap de Creus likely produces the optimal conditions for communities dominated by suspension- and filter-feeding species to develop. The uniqueness of this ecosystem and the anthropogenic pressures that it faces should prompt the development of effective management actions to ensure the long-term conservation of the benthic fauna representative of this marine area3,26

Epibenthic biodiversity, habitat characterisation and anthropogenic pressure mapping of unconsolidated sediment habitats in Algoa Bay, South Africa

Implementation of an ecosystem-based management approach for marine systems requires a comprehensive understanding of the biophysical marine environment and the cumulative human impacts at different spatio-temporal scales. In Algoa Bay, South Africa, this study describes the epibenthic communities occurring in unconsolidated marine habitats. It further investigates the potential abiotic factors that influence their distribution and abundance, compares epibenthic communities with existing habitat information and evaluates the protection status of the marine environment in the Bay. Seabed imagery, covering a total area of 171.4m², and sediment samples were collected from 13 stations from which 106 epibenthic species were identified. Multivariate analyses revealed two statistically distinct communities that did not align with the Algoa Bay benthic habitat types defined in the current National Biodiversity Assessment (NBA, 2012). Further assessment indicated that community differences were driven by the presence of rock substrate. A range of abiotic factors were tested against the epibenthic communities to explore patterns and identify potential drivers. The combination of abiotic factors depth, mean grain size, mean bottom temperature and mean bottom current explained 55% fitted variation in epibenthic data. The degree of long-term variability in several of these parameters were likewise identified as explanatory variables, including bottom temperature, current speed and dissolved oxygen. The link between abiotic factors and the epibenthic communities observed indicate that these variables can act as surrogates for habitat mapping in the future. The existing and proposed Marine Protected Area (MPA) in conjunction with the NBA 2012 habitat types does well in protecting the majority of habitats in the Bay, however there remain habitats that lack protection. Utilising the benthic communities and potential drivers identified in this study, the proposed MPA boundary delineations should be somewhat altered to include missing habitat types