The end-Devonian to mid-Mississippian time interval has long been known for its depauperate palaeontological record, especially for tetrapods. This interval encapsulates the time of increasing terrestriality among tetrapods, but only two Tournaisian localities previously produced tetrapod fossils. Here we describe five new Tournaisian tetrapods (Perittodus apsconditus, Koilops herma, Ossirarus kierani, Diploradus austiumensis and Aytonerpeton microps) from two localities in their environmental context. A phylogenetic analysis retrieved three taxa as stem tetrapods, interspersed among Devonian and Carboniferous forms, and two as stem amphibians, suggesting a deep split among crown tetrapods. We also illustrate new tetrapod specimens from these and additional localities in the Scottish Borders region. The new taxa and specimens suggest that tetrapod diversification was well established by the Tournaisian. Sedimentary evidence indicates that the tetrapod fossils are usually associated with sandy siltstones overlying wetland palaeosols. Tetrapods were probably living on vegetated surfaces that were subsequently flooded. We show that atmospheric oxygen levels were stable across the Devonian/Carboniferous boundary, and did not inhibit the evolution of terrestriality. This wealth of tetrapods from Tournaisian localities highlights the potential for discoveries elsewhere.

13The Lower Mississippian (Tournaisian) Ballagan Formation in SE Scotland yields tetrapod 14 fossils that provide fresh insights into the critical period when these animals first moved onto 15 land.

across the floodplain in seasonal rainfall episodes. These deposits are significant new sites that can be explored for the preservation of rare non-marine fossil material and provide unique insights into the evolution of early terrestrial ecosystems.

Glacigenic and fluvial deposits of variable lithological composition underlie many major cities in Europe and North America. Traditional geological mapping and 3D modelling techniques rarely capture this complexity as they use lithostratigraphic designations which are commonly based on genesis and age rather than lithological compositions.In urban areas, thousands of boreholes have been, and continue to be, drilled to facilitate the planning, design and construction of buildings and infrastructure. While these data may provide the basis for geological maps and 3D models based on lithological interpretation, they are too numerous for manual correlation to be undertaken efficiently. In this paper we explore the application of largely automated stochastic modelling techniques to develop predictive lithology models for glacial and fluvial deposits in the city of Glasgow, UK. These techniques are commonly used to assess facies variation in oilfield models and are applied here in an urban setting using over 4000 borehole records.Predictions derived from these methods have been evaluated by removing control data and rerunning the simulations. We demonstrate a moderate improvement in the prediction of lithology when using a lithologically-derived stochastic model compared with a conventionally interpolated lithostratigraphic model. It is possible to report uncertainty within the resulting models, either with probability maps or through a suite of plausible simulations of the lithologies across the study region. IntroductionThe growth and decay of high-and mid-latitude Pleistocene ice sheets has left 8% of the Earth's land surface, including one third of Europe and a quarter of North America, covered by glacigenic and fluvial deposits Gibbard, 2004a, 2004b). These deposits underlie many major cities and much of their associated infrastructure networks, and exert a significant influence on the groundwater system. Increasing urban development, and its demands (e.g. suitable foundation conditions, the need for waste storage, contaminant migration, drainage re-routing) requires that information about subsurface glacial deposits, which are often highly lithologically variable across short distances, is available for those involved in planning and construction (Campbell et al., 2010). A key challenge for the three-dimensional (3D) geological modelling community is therefore to represent these subsurface deposits in appropriate ways across large, city-wide areas (Culshaw, 2005;MacCormack et al., 2005;Kessler et al., 2009).In Glasgow, west central Scotland (Figure 1), the British Geological Survey (BGS), in partnership with Glasgow City Council and other local authorities, have used extensive borehole datasets to develop and successfully apply a suite of 3D Quaternary lithostratigraphic models (Merritt et al., 2007;Campbell et al., 2010) (Figure 2). A key strength of lithostratigraphic modelling is that it brings together the expertise of geologists and known geological relationships, enabling a geologically realistic r...

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Extensive evaporites in Lower Mississippian successions from palaeoequatorial regions are commonly used as evidence for an arid to semi‐arid palaeoclimate. However, in this article, detailed studies of evaporites and their context refute this interpretation. Detailed sedimentological and petrographical analysis of the Lower Mississippian of northern Britain, is combined with archived log data from more than 40 boreholes across southern Scotland, northern England and Northern Ireland, and published literature from Canada. Two key cores from the Tweed Basin and the northern margin of the Northumberland – Solway Basin contain 178 evaporite intervals and reveal twelve distinct forms of gypsum and anhydrite across seven facies that are associated with planar laminated siltstone and intercalated thin beds of ferroan dolostone. Nodular gypsum and anhydrite, typically in intervals <1 to 2 m thick, are integral components of the succession. Nodular evaporite occurs within about 1 m of a palaeosurface, but most evaporite deposits represent ephemeral brine pans to semi‐permanent hypersaline lakes or salinas on a floodplain that was subjected periodically to storm surges introducing marine waters. Formation of evaporites under a strongly seasonal climate in a coastal wetland is supported by palaeosol types and geochemical proxies, and from palaeobotanical evidence published previously. Although 65% of modern equatorial areas experience a strongly seasonal climatic regime, salinas and sabkhas are a minor component today in comparison with the evidence from these Lower Mississippian successions. This implies that the earliest terrestrial environments were complex and dynamic, providing a diverse range of habitats in which the early tetrapods became terrestrialized and represent a setting that is rarely preserved in the geological record.

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Abstract. Realistic representations of geological complexity are important to address several engineering and environmental challenges. The spatial distribution of properties controlling physical and geochemical processes can be effectively described by the geological structure of the subsurface. In this work, we present an approach to account for geological structure in geostatistical simulations of categorical variables. The approach is based on the extraction of information from a deterministic conceptualization of the subsurface, which is then used in the geostatistical analysis for the development of models of spatial correlation and as soft conditioning data. The approach was tested to simulate the distribution of four lithofacies in highly heterolithic Quaternary deposits. A transition probability-based stochastic model was implemented using hard borehole data and soft data extracted from a 3-D deterministic lithostratigraphic model. Simulated lithofacies distributions were also used as input in a flow model for numerical simulation of hydraulic head and groundwater flux. The outputs from these models were compared to corresponding values from models based exclusively on borehole data. Results show that soft lithostratigraphic information increases the accuracy and reduces the uncertainty of these predictions. The representation of the geological structure also allows a more precise definition of the spatial distribution of prediction uncertainty, here quantified with a metric based on Shannon information entropy. Correlations between prediction uncertainties for lithofacies, hydraulic heads and groundwater fluxes were also investigated. The results from this analysis provide useful insights about the incorporation of soft geological data into stochastic realizations of subsurface heterogeneity, and emphasize the critical importance of this type of information for reducing the uncertainty of simulations considering flux-dependent processes.3