The Provenance and Geochemical Alteration of Bermudan Eolianites

Large calcareous eolianites cover the remote island of Bermuda, accounting for more than 90% of the limestone bedrock. This study examines the sedimentology and geochemistry of these eolianites to better understand Pleistocene oceanography and the meteoric alteration of subtropical carbonate sediments. Cluster analyses reveal that the eolian carbonate sediments fall into two natural groups that represent lagoonal and reefal end members of marine sediment production. Coral fragments are uncharacteristically absent, possibly destroyed prior to their incorporation into eolian deposits by endolithic microboring organisms or broken up during transport. Sediment assemblages lead to the following interpretations of the Bermudan offshore environment: (1) the Ledge Flats reef system along the southwestern coast has been active since MIS 11, contributing coralline algal-rich sediment to the northern beaches of Sandy’s Parish and acting as an energy barrier in the south, allowing for low energy sedimentation in the quiet back- reef region; (2) on the northeastern coast, the low energy back-reef region landward of the Ledge Flats has thrived since MIS 11; (3) during MIS 5e, slightly warmer water temperatures led to the hindrance of coralline algal growth along the southern coast and in the North Lagoon. These are the first interpretations of Pleistocene marine assemblages on Bermuda. Meteoric fluids progressively transformed the pristine carbonate sediments into hardened limestones in a predictable solubility-dependent manner. The progressive alteration is coincident with: (1) divergence of δ18O and δ13C values from those similar to unaltered sediment towards those of calcrete, due to interaction with CO2-charged meteoric fluids; (2) depletion of elements with low partitioning coefficients and low meteoric concentrations, such as barium, boron, magnesium, potassium, sodium, strontium, and uranium; (3) enrichment of iron from Terra Rossa-hosted iron oxides; (4) enrichment of aluminum via detrital minerals sourced from protosol horizons; and (5) manganese concentrations that remain uncharacteristically low, owing to the lack of a consistent manganese source. Elemental correlations are useful for characterizing meteoric diagenesis, assuming the primary mineralogy is recognized, all components have been fully altered, and inter-particle cements are ubiquitous.

Karst hazard analysis towards the development of predictive karst models for southern Ontario

An investigation into karst hazard in southern Ontario has been undertaken with the intention of leading to the development of predictive karst models for this region. The reason these are not currently feasible is a lack of sufficient karst data, though this is not entirely due to the lack of karst features. Geophysical data was collected at Lake on the Mountain, Ontario as part of this karst investigation. This data was collected in order to validate the long-standing hypothesis that Lake on the Mountain was formed from a sinkhole collapse. Sub-bottom acoustic profiling data was collected in order to image the lake bottom sediments and bedrock. Vertical bedrock features interpreted as solutionally enlarged fractures were taken as evidence for karst processes on the lake bottom. Additionally, the bedrock topography shows a narrower and more elongated basin than was previously identified, and this also lies parallel to a mapped fault system in the area. This suggests that Lake on the Mountain was formed over a fault zone which also supports the sinkhole hypothesis as it would provide groundwater pathways for karst dissolution to occur. Previous sediment cores suggest that Lake on the Mountain would have formed at some point during the Wisconsinan glaciation with glacial meltwater and glacial loading as potential contributing factors to sinkhole development. A probabilistic karst model for the state of Kentucky, USA, has been generated using the Weights of Evidence method. This model is presented as an example of the predictive capabilities of these kind of data-driven modelling techniques and to show how such models could be applied to karst in Ontario. The model was able to classify 70% of the validation dataset correctly while minimizing false positive identifications. This is moderately successful and could stand to be improved. Finally, suggestions to improving the current karst model of southern Ontario are suggested with the goal of increasing investigation into karst in Ontario and streamlining the reporting system for sinkholes, caves, and other karst features so as to improve the current Ontario karst database.