A recently released voxel model quantifying aggregate resources of the Belgian part of the North Sea includes lithological properties of all Quaternary sediments and modelling-related uncertainty. As the underlying borehole data come from various sources and cover a long time-span, data-related uncertainties should be accounted for as well. Applying a tiered data-uncertainty assessment to a composite lithology dataset with uniform, standardized lithological descriptions and rigorously completed metadata fields, uncertainties were qualified and quantified for positioning, sampling and vintage. The uncertainty on horizontal positioning combines navigational errors, on-board and off-deck offsets and underwater drift. Sampling-gear uncertainty evaluates the suitability of each instrument in terms of its efficiency of sediment yield per lithological class. Vintage uncertainty provides a likelihood of temporal change since the moment of sampling, using the mobility of fine-scale bedforms as an indicator. For each uncertainty component, quality flags from 1 (very uncertain) to 5 (very certain) were defined and converted into corresponding uncertainty percentages meeting the input requirements of the voxel model. Obviously, an uncertainty-based data selection procedure, aimed at improving the confidence of data products, reduces data density. Whether or not this density reduction is detrimental to the spatial coverage of data products, will depend on their intended use. At the very least, demonstrable reductions in spatial coverage will help to highlight the need for future data acquisition and to optimize survey plans. By opening up our subsurface model with associated data uncertainties in a public decision support application, policy makers and other end users are better able to visualize overall confidence and identify areas with insufficient coverage meeting their needs. Having to work with a borehole dataset that is increasingly limited with depth below the seabed, engineering geologists and geospatial analysts in particular will profit from a better visualization of datarelated uncertainty.
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RBINS Staff Publications 2020
The anatomy of Cambaytherium, a primitive, perissodactyl-like mammal from the lower Eocene Cambay Shale Formation of Gujarat, India, is described in detail on the basis of more than 350 specimens that represent almost the entire dentition and the skeleton. Cambaytherium combines plesiomorphic traits typical of archaic ungulates such as phenacodontids with derived traits characteristic of early perissodactyls. Cambaytherium was a subcursorial animal better adapted for running than phenacodontids but less specialized than early perissodactyls. The cheek teeth are bunodont with large upper molar conules, not lophodont as in early perissodactyls; like perissodactyls, however, the lower molars have twinned metaconids and m3 has an extended hypoconulid lobe. A steep wear gradient with heavy wear in the middle of the tooth row suggests an abrasive herbivorous diet. Three species of Cambaytherium are recognized: C. thewissi (∼23 kg), C. gracilis (∼10 kg), and C. marinus (∼99 kg). Body masses were estimated from tooth size and long bone dimensions. Biostratigraphic and isotopic evidence indicates an age of ca. 54.5 Ma for the Cambay Shale vertebrate fauna, the oldest Cenozoic continental vertebrate assemblage from India, near or prior to the initial collision with Asia. Cambaytheriidae (also including Nakusia and Perissobune) and Anthracobunidae are sister taxa, constituting the clade Anthracobunia, which is sister to Perissodactyla. We unite them in a new higher taxon, Perissodactylamorpha. The antiquity and occurrence of Cambaytherium—the most primitive known perissodactylamorph—in India near or before its collision with Asia suggest that Perissodactyla evolved during the Paleocene on the Indian Plate or in peripheral areas of southern or southwestern Asia.
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