Comparison between zooplankton data collected by the Continuous Plankton Recorder survey in the English Channel and by WP-2 nets at station L4, Plymouth (UK)

Zooplankton sampling has been carried out by the Continuous Plankton Recorder (CPR) survey since the 1930s enabling the study of long-term changes in plankton populations, the elucidation of seasonal patterns of abundance, and more recently providing zooplankton biomass estimates for ecosystem models. Data for zooplankton abundance collected by CPR tows in the Western English Channel (between 1988 and 1998) were compared to vertically integrated samples collected from station L4 off Plymouth, UK. Comparisons were made for locally abundant copepods (including Acartia, Calanus, Para/Pseudocalanus, Centropages, Oithona and Temora) collected by CPR and WP-2 nets. All dominant species recorded at L4 were also common to the CPR data. However, the position of the taxa in the two datasets was not equivalent. Seasonal cycles revealed by CPR data were significantly similar to those recorded throughout the water column at L4 for most taxa. However, absolute levels of abundance differed for the two datasets: abundances were underestimated by CPR samples when compared to those of vertically integrated samples by a factor of between 2 and 35, with the exception of Centropages. The differing mesh sizes (200 and 270 μm) of the WP-2 net and CPR mesh could only partially explain these differences in abundance, implying that the behaviour of individual taxa and their depth in the water column also influenced the abundance recorded.     

On the possibility of forecasting the long-term air temperature variability that determines the hydrophysical structure and ecology of the Black Sea waters

Periods and amplitudes of long-term temperature fluctuations were obtained using the methods of spectral analysis and filtration of secular time series of the air temperature at 13 hydrometeorological stations in the Black Sea region. The prognostic calculations of the long-term air temperature variability are based on the results of processing of time series. The calculations of the air temperature agree with the data of observations. The possibility of the long-term air temperature variability prediction is shown.     

A Linear Programming Model for Seabed Oil-Gas Pipe Network

This paper analyzes the pipe network system of oil-gas collection and transportation foroffshore oilfield development.A"0-1"integer linear programming model is constructed to optimize theinvestment of seabed pipe network.The mathematical model is solved by the spanning tree method ofgraph theory and network analysis.All spanning trees of a network graph compose all the feasible solu-tions of the mathematical model.The optimal solution of the model is the spanning tree with the minimumcost among all spanning trees.This method can be used to optimize the seabed pipe network system andgive a minimum cost plan for the development of offshore marginal oilfield groups.     

Study of the ice conditions in the Gulf of Ob

The results of theoretical studies of fracture lines in the ice floes of the Gulf of Ob as a function of the coefficient of internal sliding are presented in this paper. An estimate of the fractal dimensions of the emerging topological structures and the results of the calculation of stresses in the ice cover of the Gulf of Ob are presented as functions of different directions of external forcing caused by the joint action of winds and currents on the ice. The geographical locations of the zones of possible loads are shown, together with the estimates of the hummock sizes in the zones of the maximal compression of the ice floes in the Gulf of Ob.     

Prediction of hydrological phenomena using self-organizing mathematical models

The paper considers the application of self-organizing models, specifically, the method of grouped arguments consideration (MGAC), to forecast short and non-stationary time series of observations in the ocean. A sequence of operations for the treatment of observational series is suggested. To assess its efficiency, we have used mean monthly oxygen concentration data collected in the surface and near-bottom layers of the Taganrog Bay. It is shown that the application of the MGAC model allows one to reduce by two times the root-mean-square error of that of the series prediction by five points, in comparison with the Jenkins-Box regressional model. It has been concluded that the predictors' non-linear functions may be effectively used in the treatment of short samplings. Translated by Vladimir A. Puchkin.