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.

Tab. 2,3,4 Specific resistivity of calculated models for the soundings in Lapland

Geoelectrical soundings were carried out in 29 different places in order to find permafrost and to measure its thickness. In most places above timber Iine a permafrost thickness of 10-50 m was recorded. Permafrost was found at sites with thin snow cover during winter. Here, deflation phenomena on the summits of fjells indicate the occurence of permafrost, Vegetation type might be a good indicator of permafrost, too. It seems obvious that permafrost exists extensively on fjell summits of northern Finland.