Sediment organic matter, grain size, and results of prediction models from northern North Atlantic and Arctic Seas

Sediment samples and hydrographic conditions were studied at 28 stations around Iceland. At these sites, Conductivity-Temperature-Depth (CTD) casts were conducted to collect hydrographic data and multicorer casts were conductd to collect data on sediment characteristics including grain size distribution, carbon and nitrogen concentration, and chloroplastic pigment concentration. A total of 14 environmental predictors were used to model sediment characteristics around Iceland on regional geographic space. For these, two approaches were used: Multivariate Adaptation Regression Splines (MARS) and randomForest regression models. RandomForest outperformed MARS in predicting grain size distribution. MARS models had a greater tendency to over- and underpredict sediment values in areas outside the environmental envelope defined by the training dataset. We provide first GIS layers on sediment characteristics around Iceland, that can be used as predictors in future models. Although models performed well, more samples, especially from the shelf areas, will be needed to improve the models in future.

(Table 1) Stable carbon and nitrogen isotopic ratios of potential prey species of bearded seals (Erignathus barbatus), Svalbard

Changing patterns of sea-ice distribution and extent have measurable effects on polar marine systems. Beyond the obvious impacts of key-habitat loss, it is unclear how such changes will influence ice-associated marine mammals in part because of the logistical difficulties of studying foraging behaviour or other aspects of the ecology of large, mobile animals at sea during the polar winter. This study investigated the diet of pregnant bearded seals (Erignathus barbatus) during three spring breeding periods (2005, 2006 and 2007) with markedly contrasting ice conditions in Svalbard using stable isotopes (d13C and d15N) measured in whiskers collected from their newborn pups. The d15N values in the whiskers of individual seals ranged from 11.95 to 17.45 per mil, spanning almost 2 full trophic levels. Some seals were clearly dietary specialists, despite the species being characterised overall as a generalist predator. This may buffer bearded seal populations from the changes in prey distributions lower in the marine food web which seems to accompany continued changes in temperature and ice cover. Comparisons with isotopic signatures of known prey, suggested that benthic gastropods and decapods were the most common prey. Bayesian isotopic mixing models indicated that diet varied considerably among years. In the year with most fast-ice (2005), the seals had the greatest proportion of pelagic fish and lowest benthic invertebrate content, and during the year with the least ice (2006), the seals ate more benthic invertebrates and less pelagic fish. This suggests that the seals fed further offshore in years with greater ice cover, but moved in to the fjords when ice-cover was minimal, giving them access to different types of prey. Long-term trends of sea ice decline, earlier ice melt, and increased water temperatures in the Arctic are likely to have ecosystem-wide effects, including impacts on the forage bases of pagophilic seals.

Probabilistic models for the prediction of a ship performance in dynamic ice

We introduce two probabilistic, data-driven models that predict a ship's speed and the situations where a ship is probable to get stuck in ice based on the joint effect of ice features such as the thickness and concentration of level ice, ice ridges, rafted ice, moreover ice compression is considered. To develop the models to datasets were utilized. First, the data from the Automatic Identification System about the performance of a selected ship was used. Second, a numerical ice model HELMI, developed in the Finnish Meteorological Institute, provided information about the ice field. The relations between the ice conditions and ship movements were established using Bayesian learning algorithms. The case study presented in this paper considers a single and unassisted trip of an ice-strengthened bulk carrier between two Finnish ports in the presence of challenging ice conditions, which varied in time and space. The obtained results show good prediction power of the models. This means, on average 80% for predicting the ship's speed within specified bins, and above 90% for predicting cases where a ship may get stuck in ice. We expect this new approach to facilitate the safe and effective route selection problem for ice-covered waters where the ship performance is reflected in the objective function.

Framework for risk assessment for maritime transportation systems

Maritime accidents involving ships carrying passengers may pose a high risk with respect to human casualties. For effective risk mitigation, an insight into the process of risk escalation is needed. This requires a proactive approach when it comes to risk modelling for maritime transportation systems. Most of the existing models are based on historical data on maritime accidents, and thus they can be considered reactive instead of proactive. This paper introduces a systematic, transferable and proactive framework estimating the risk for maritime transportation systems, meeting the requirements stemming from the adopted formal definition of risk. The framework focuses on ship-ship collisions in the open sea, with a RoRo/Passenger ship (RoPax) being considered as the struck ship. First, it covers an identification of the events that follow a collision between two ships in the open sea, and, second, it evaluates the probabilities of these events, concluding by determining the severity of a collision. The risk framework is developed with the use of Bayesian Belief Networks and utilizes a set of analytical methods for the estimation of the risk model parameters. The model can be run with the use of GeNIe software package. Finally, a case study is presented, in which the risk framework developed here is applied to a maritime transportation system operating in the Gulf of Finland (GoF). The results obtained are compared to the historical data and available models, in which a RoPax was involved in a collision, and good agreement with the available records is found.