Population Structure and Secondary Production of the Mediterranean Octocoral Lophogorgia ceratophyta (L. 1758)

Abstract. The gorgonian Lophogorgia ceratophyta thrives in turbid water at Tinetto Rock, La Spezia Gulf, Ligurian Sea. Its age structure suggests that the population is in a steady state; nevertheless, it is difficult to discern whether the main factors controlling this population are biological or event-related. Secondary production was estimated by means of an increment-summation method and yielded 0.54 g ash-free dry weight (AFDW)*m^-1 a^-1. This estimate does not take into account biomass losses due to reproductive output and non-lethal predation. Standing stock biomass was 5.44 g AFDW e m^-2. The annual P/B ratio was 0.10 and turnover time about 10a     

Growth of Five Species of Gorgonians (Sub-Class Octocorallia) in the Sedimented Waters of Singapore

Abstract. Annual growth rates of gorgonians in the Indo-Pacific region are reported ror the first tinie. A method of measuring gorgonian growth using periodic photographic monitoring that is sensitive to horizontal growth and changes in growth foci but that does not require tedious underwater measurements is applied. Growth parameters of five species of gorgonians from three Families ( Plexauridae. Melithaeidae . and Subergorgiidae ) were monitored over a period of 18 months using this method. Growth rates ranged from 2.30 cm a^-1 to 7.88 cm. a ^-1 in the highly sedimented waters of Singapore. The maximum number of branches added per year ranged from 1.7 to 14.5.     

The mysid Siriella armata as a test organism in toxicology: Effects of cadmium

A shrimp-like crustacean of the coastal Zooplankton in the north-western Mediterranean Sea, the mysid Siriella armata, offers a test organism whose life cycle is entirely controllable under laboratory conditions. The effects of the heavy metal cadmium were studied on adults and juveniles cultured in the laboratory including acute toxicity, bioaccumulation and effects on growth, ingestion and moult cycle.     

Directional spread parameter at intermediate water depth

The characteristics of directional spread parameters at intermediate water depth are investigated based on a cosine power ‘2s' directional spreading model. This is based on wave measurements carried out using a Datawell directional waverider buoy in 23 m water depth. An empirical equation for the frequency dependent directional spreading parameter is presented. Directional spreading function estimated based on the Maximum Entropy Method is compared with those obtained using a cosine power ‘2s' parameter model. A set of empirical equations relating the directional spreading parameter corresponding to the peak of wave spectrum to other wave parameters like significant wave height and period are obtained. It shows that the wave directional spreading at peak wave frequency can be related to the non-linearity parameter, which allows estimation of directional spreading without reference to wind information.     

Spatial structure and variability of fields of currents, attenuation factor of light, and temperature in the surface layer of the northwest part of the Black Sea

On the basis of the results of simultaneous observations of parameters of currents, attenuation factor of light, and temperature performed aboard a moving vessel, we established the main characteristics and features of the circulation of waters and the structure of transparency and temperature fields in the surface layer of the northwest part of the Black Sea. We investigate the correlation between the variability of fluid dynamics and redistribution of transparency and temperature fields. The measured currents are compared with those calculated using the actual field of atmospheric pressure during the time of observation. It is shown that the results obtained in the areas of steady currents in the west and central regions are in good agreement. Translated by Peter V. Malyshev and Dmitry V. Malyshev     

Physical and hydrological characteristics of climatic frontal zones in the Tropical Atlantic

Climatic frontal zones are selected in the thermohaline fields of the Tropical Atlantic by analyzing the many-year-average seasonal database reduced to the nodes of a one-degree grid. We determine physical characteristics of the frontal zones, study their spatial and temporal variability, and reveal basic regularities of the appearance of frontal zones in the fields of thermohaline characteristics. Translated by Peter V. Malyshev and Dmitry V. Malyshev     

High-resolution seafloor mapping using the DSL-120 sonar system: Quantitative assessment of sidescan and phase-bathymetry data from the Lucky Strike segment of the Mid-Atlantic Ridge

High-resolution, side-looking sonar data collected near the seafloor (100 m altitude) provide important structural and topographic information for defining the geological history and current tectonic framework of seafloor terrains. DSL-120 kHz sonar data collected in the rift valley of the Lucky Strike segment of the Mid-Atlantic Ridge near 37° N provide the ability to quantitatively assess the effective resolution limits of both the sidescan imagery and the computed phase-bathymetry of this sonar system. While the theoretical, vertical and horizontal pixel resolutions of the DSL-120 system are <1 m, statistical analysis of DSL-120 sonar data collected from the Lucky Strike segment indicates that the effective spatial resolution of features is 1–2 m for sidescan imagery and 4 m for phase-bathymetry in the seafloor terrain of the Mid-Atlantic Ridge rift valley. Comparison of multibeam bathymetry data collected at the sea-surface with deep-tow DSL-120 bathymetry indicates that depth differences are on the order of the resolution of the multibeam system (10–30 m). Much of this residual can be accounted for by navigational mismatches and the higher resolving ability of the DSL-120 data, which has a bathymetric footprint on the seafloor that is 20 times smaller than that of hull-mounted multibeam at these seafloor depths (2000 m). Comparison of DSL-120 bathymetry with itself on crossing lines indicates that residual depth values are ±20 m, with much of that variation being accounted for by navigational errors. A DSL-120 survey conducted in 1998 on the Juan de Fuca Ridge with better navigation and less complex seafloor terrain had residual depth values half those of the Lucky Strike survey. The quality of the bathymetry data varies as a function of position within the swath, with poorer data directly beneath the tow vehicle and also towards the swath edges.Variations in sidescan amplitude observed across the rift valley and on Lucky Strike Seamount correlate well with changes in seafloor roughness caused by transitions from sedimented seafloor to bare rock outcrops. Distinct changes in sonar backscatter amplitude were also observed between areas covered with hydrothermal pavement that grade into lava flows and the collapsed surface of the lava lake in the summit depression of Lucky Strike Seamount. Small features on the seafloor, including volcanic constructional features (e.g., small cones, haystacks, fissures and collapse features) and hydrothermal vent chimneys or mounds taller than 2 m and greater than 9 m² in surface area, can easily be resolved and mapped using this system. These features at Lucky Strike have been confirmed visually using the submersible Alvin, the remotely operated vehicle Jason, and the towed optical/acoustic mapping system Argo II.     

Interpolation of wave heights

Remote sensing of waves often necessitates presentation of data in the form of wave height values grouped over large time intervals. This restricts their use to long-term applications only. This paper describes how such data can be made suitable for short-term usage in the field. Weekly mean significant wave heights were derived from their monthly mean observations with the help of different alternative techniques. These include model-free neural network schemes as well as model-based statistical and numerical methods. Superiority of neural networks was noted when the estimations were compared with corresponding observations. The network was trained using three different training algorithms, viz., error back propagation, conjugate gradient and cascade correlation. The technique of cascade correlation took minimum training time and showed better coefficient of correlation between observations and network output.