The Bothnian coupled oroclines of the Svecofennian Orogen: a Palaeoproterozoic terrane wreck

The accretion of magmatic arcs gives rise to elongate, linear orogens and is a key process in forming new continental crust. Many Precambrian continents are, however, presently equidimensional or have large areas without any clear linearity, such as the central part of the Palaeoproterozoic Svecofennian Orogen (1.92–1.77 Ga). One way of forming an equidimensional continental domain is by buckling of a linear orogen about vertical axes of rotation into one or more coupled oroclines. Here, we reinterpret existing data and demonstrate the occurrence of coupled Bothnian oroclines in the Svecofennian Orogen. Palinspastic restoration of the southern and northern Bothnian oroclines brings a 1000‐km‐long segment of the Svecofennian Orogen into an originally linear, NW‐striking geometry that restores the lithological belts, metamorphic zones and structural vergences to a common direction, and which indicates that the orogen consists of a SW‐facing arc, which has been shortened along NE‐verging folds and thrust faults.     

Surficial geology indicates early Holocene faulting and seismicity,central Sweden

In Sweden, knowledge of the location and timing of glacially induced faulting and seismicity is critical to effective engineering of a long-term nuclear disposal facility. To improve understanding and modeling of the complex ice-induced and tectonic stresses associated with glacially induced faulting, field studies detailing the location and timing of movement of such structures are required. Although the fault has not been confirmed in the bedrock, multi-proxy surficial geologic evidence indicates that the recently discovered scarp in Bollnäs is such a structure. Machine-excavated trenches across the scarp reveal landsliding down the scarp and, in one location, faulted and vertically offset fine-grained glacial sediments. The presence of water-escape structures in trenches excavated on a topographic high strongly suggests a co-seismic origin derived from earthquake magnitudes >5.5. Numerous landslides in till exist in the region as well. Four slopes with landslides were examined in detail, and the factors of safety for these slopes indicate stable conditions and suggest a seismic trigger. Basal radiocarbon dates from peat bogs located stratigraphically above the landslides provide minimum limiting ages for the co-seismic landslides. The oldest date indicates sliding prior to 10,180 calendar years before the present. The proposed Bollnäs Fault is 400 km south of the so called Lapland Fault Province. To date, it is the southernmost confirmed glacially induced fault in Sweden. The results of this study are consistent with existing modeling results that indicate fault instability in this region of central Sweden following deglaciation.     

Classification of Soil Groups Using Weights-of-Evidence-Method and RBFLN-Neural Nets

Weights-of-Evidence (WofE) and Radial Basis Function Link Net (RBFLN) were applied to soil group mapping in eastern Finland. The data consisted of low altitude airborne geophysical measurements, Landsat 5 TM-satellite image, and digital elevation model (DEM) and slope information derived from it. Probability maps were constructed for each soil group one by one and combined into a prediction map of soil groups using maximum posterior probability (WofE) or pattern membership (RBFLN). Self-Organizing Map (SOM) and Sammon’s Mapping were applied for selecting the data sets for modeling and visualizing the data. The soil types belonging to each soil group used in the Arc-SDM modeling were defined by clusters revealed by the SOM and Sammon’s Mapping algorithms. The soil types with similar characters were collected in the same cluster. Numerical evaluation of the models’ performance was performed using the confusion matrix. The Ratio of Correct Classifications (RCC) for the best WofE model was 0.64 in the training area and 0.61 in the testing area. The RCC for the best RBFLN model was 0.62. Modeling of soil groups using Arc-SDM is time consuming because models need to be constructed for each soil group before combining them into a final prediction map. In this study a simple method was tested for combining the maps. In the future, more attention should be paid to combining the posterior probability models and also to selecting data sets used for modeling.