Submarine canyons as coral and sponge habitat on the eastern Bering Sea slope

Seagrass habitat suitability model for Redang Marine Park using multibeam echosounder data: Testing different spatial resolutions and analysis window sizes

Integrating Multibeam Echosounder (MBES) data (bathymetry and backscatter) and underwater video technology allows scientists to study marine habitats. However, use of such data in modeling suitable seagrass habitats in Malaysian coastal waters is still limited. This study tested multiple spatial resolutions (1 and 50 m) and analysis window sizes (3 × 3, 9 × 9, and 21 × 21 cells) probably suitable for seagrass-habitat relationships in Redang Marine Park, Terengganu, Malaysia. A maximum entropy algorithm was applied, using 12 bathymetric and backscatter predictors to develop a total of 6 seagrass habitat suitability models. The results indicated that both fine and coarse spatial resolution datasets could produce models with high accuracy (>90%). However, the models derived from the coarser resolution dataset displayed inconsistent habitat suitability maps for different analysis window sizes. In contrast, habitat models derived from the fine resolution dataset exhibited similar habitat distribution patterns for three different analysis window sizes. Bathymetry was found to be the most influential predictor in all the models. The backscatter predictors, such as angular range analysis inversion parameters (characterization and grain size), gray-level co-occurrence texture predictors, and backscatter intensity levels, were more important for coarse resolution models. Areas of highest habitat suitability for seagrass were predicted to be in shallower (<20 m) waters and scattered between fringing reefs (east to south). Some fragmented, highly suitable habitats were also identified in the shallower (<20 m) areas in the northwest of the prediction models and scattered between fringing reefs. This study highlighted the importance of investigating the suitable spatial resolution and analysis window size of predictors from MBES for modeling suitable seagrass habitats. The findings provide important insight on the use of remote acoustic sonar data to study and map seagrass distribution in Malaysia coastal water.

Long-distance influence of the Rhône River plume on the marine benthic ecosystem: Integrating descriptive ecology and predictive modelling

The Gulf of Lions (GoL) is among the most productive areas of the Mediterranean Sea, with the Rhône River contributing with as much as 90% of the liquid and solid materials (including anthropogenic chemicals) reaching the area. In this paper, we assessed whether classical descriptive ecology and MaxEnt predictive species distribution modelling were able to provide complementary information when analysing the long-distance influence of the river discharges on the GoL benthic ecosystem. Samples were collected in August 2014 from 12 stations covering the sedimentary plain of the deep submarine delta, from the Gulf of Fos to Gruissan. Sediments were mostly muddy with a high organic carbon and low P and N contents first decreasing and then increasing from east to west. The same pattern occurred for chlorophyll-a, particulate organic carbon and sea surface temperature, and was overall correlated with metal and pollutant contents derived from agricultural, port, urban and industrial sources driven by Rhône outputs. We observed a typical deltaic succession in the benthos, showing a relatively low diversity and including polychaetes (Sternaspis scutata) and holothurians (Oestergrenia digitata) known to be indicators of high sedimentation rates. Overall, benthos showed an inversed pattern regarding environmental variables, an evident consequence of the Rhône River influence. The suitability of some species was either positively or negatively correlated with some of the environmental variables, producing species-specific predicted distribution patterns, with the highest amount of information allowing to predict distributions being mainly provided by organic pollutants. Even with a limited number of available samples, our integrated approach reveals to be a very robust tool to highlight hidden patterns and contributes to improve our knowledge on how river-mediated anthropogenic discharges may influence biodiversity distribution and functional patterns in marine benthic ecosystems.

Multiple-Scale Variations of Sea Ice and Ocean Circulation in the Bering Sea Using Remote Sensing Observations and Numerical Modeling

The Bering Sea is located between the Aleutian Low and Siberian High, with strong seasonal variations in the oceanic circulation and the sea ice coverage. Within such a large-scale system, the physical processes in the Bering Sea carry interannual variability. The special topography in the Bering Sea traps a strong jet along the Bering Slope, whose instability enriches the eddy activity in the region. A Regional Oceanic Modeling System (ROMS), coupled with a sea ice module, is employed to study multiple-scale variability in the sea ice and oceanic circulation in the Bering Sea for interannual, seasonal, and intra-seasonal eddy variations. The model domain covers the whole Bering Sea and a part of the Chukchi Sea and south of Aleutian Islands, with an averaged spatial resolution of 5 km. The external forcings are momentum, heat, and freshwater flux at the surface and adaptive nudging to reanalysis fields at the boundaries. The oceanic model starts in an equilibrium state from a multiple year cyclical climatology run, and then it is integrated from years 1990 through 2004. The 15 year simulation is analyzed and assessed against the observational data. The model accurately reproduces the seasonal and interannual variations in the sea ice coverage compared with the satellite-observed sea ice data from the National Snow and Ice Data Center (NSIDC). Sea surface temperature and eddy kinetic energy patterns from the ROMS agree with satellite remote sensing data. The transportation through the Bering Strait is also comparable with the estimate of mooring data. The mechanism for seasonal and interannual variation in the Bering Sea is connected to the Siberia-Aleutian index. Eddy variation along the Bering Slope is discussed. The model also simulates polynya generation and evolution around the St. Lawrence Island.