Oleinik, Anton

Analysis of fossilized Triceratops horridus remains within the Chicxulub Event Deposit of the uppermost Hell Creek Formation, and footprints of non-avian dinosaurs and flying reptiles from the excavated paleo surface underlying the Cretaceous-Tertiary (K/T) Boundary as marked by the Iridium anomaly, is used to interpret the very last moments of the terminal Cretaceous Period on the latest paleo surface available.
The research included characterization of the Triceratops’ bone histology and taphonomy, in addition to the preservation and diversity of the footprints. The data is used to interpret a “temporal snapshot” of the last days to weeks of the Late Cretaceous, offering insight to the site`s paleoenvironment immediately prior to the K/T impact event. Data from the Triceratops histological analysis indicates the animal died in the Spring, coinciding with the end of the Cretaceous. The tracks indicate a diverse non-avian dinosaur population composed of several families and breeding age individuals.

A nearshore ridge complex (NRC) sits less than 250 m from the coast of Pompano Beach in Southeast Florida, and the varied bottom types within this complex may represent critical habitat for benthic mollusks. In order to document the diversity of mollusks within the NRC, SCUBA-based roving surveys were conducted between 2011 and 2019. Between 2021 and 2022, sediment samples were also collected from each of the bottom types to study mollusk diversity patterns. This combination of survey methods resulted in the identification of 325 species of hard-shelled mollusks, representing 103 families and 4 classes. To test for differences in community structure between bottom types, relative abundance data from the sediment samples was used for multivariate analyses including NMDS ordination, ANOSIM, and hierarchical cluster analysis. Results indicated statistically significant differences in mollusk species composition between NRC bottom types.

Encrusters have a proven history as indicators of environmental conditions in nearshore habitats and are useful in both ecological and paleoenvironmental research within benthic ecosystems. Off the coast of Pompano Beach, Florida, a Holocene storm deposit contains large accumulations of subfossil Acropora palmata fragments with these same encrusting organisms attached to their surfaces. The objective of this research was to create an inventory of encrusters found within the storm deposit and document their successional outgrowth to determine the post-depositional history of sampled coral fragments. Foraminifera and coralline algae were the most common species found, and various sequences of successional outgrowth were observed that indicated fragments were either deposited gradually, immediately buried, or reworked after initial burial. This information is vital for understanding modern biodiversity on the Pompano coast, and the development of nearshore benthic marine ecosystems during the mid-late Holocene.

The legacy of monosodium methanearsenate (MSMA) application to golf courses is often arsenic concentrations above the EPA’s maximum contaminant level of 10 μg/L for drinking water and the FDEP soil cleanup target level of 2.1 mg/kg for residential areas. These concentrations pose a health risk and must be remediated for residential development. The objective of this study was to determine how arsenic concentrations vary spatially at a closed golf course poised for residential development. Groundwater and sediment arsenic concentrations were quantified and the controls on arsenic (As) mobility were characterized. The presence of nitrates and iron-(hydr)oxides at the studied golf course largely influenced putting greens having the least As in groundwater whereas roughs contained the most.

Traditional sand analysis is labor and cost-intensive, entailing specialized equipment and operators trained in geological analysis. Even a small step to automate part of the traditional geological methods could substantially improve the speed of such research while removing chances of human error. Digital image analysis techniques and computer vision have been well developed and applied in various fields but rarely explored for sand analysis. This research explores capabilities of remote sensing digital image analysis techniques, such as object-based image analysis (OBIA), machine learning, digital image analysis, and photogrammetry to automate or semi-automate the traditional sand analysis procedure. Here presented is a framework combining OBIA and machine learning classification of microscope imagery for use with unconsolidated terrigenous beach sand samples. Five machine learning classifiers (RF, DT, SVM, k-NN, and ANN) are used to model mineral composition from images of ten terrigenous beach sand samples. Digital image analysis and photogrammetric techniques are applied and evaluated for use to characterize sand grain size and grain circularity (given as a digital proxy for traditional grain sphericity). A new segmentation process is also introduced, where pixel-level SLICO superpixel segmentation is followed by spectral difference segmentation and further levels of superpixel segmentation at the object-level. Previous methods of multi-resolution and superpixel segmentation at the object level do not provide the level of detail necessary to yield optimal sand grain-sized segments. In this proposed framework, the DT and RF classifiers provide the best estimations of mineral content of all classifiers tested compared to traditional compositional analysis. Average grain size approximated from photogrammetric procedures is comparable to traditional sieving methods, having an RMSE below 0.05%. The framework proposed here reduces the number of trained personnel needed to perform sand-related research. It requires minimal sand sample preparation and minimizes user-error that is typically introduced during traditional sand analysis.

Severe weather events that accompany climatic changes have been the main focus of many studies that want to highlight the large processes that surround us every day. These studies are based on years of data collection and other studies to help aid their pursuits. An area of major focus is identifying proxies and supplementary materials that help refine climate records of the geologic past. This study aims to identify reliable proxies for obtaining a record of severe weather events. The research consists of studying a coral species Pseudodiploria strigosa colonies with the goal to document, interpret, and describe the burial and re-exposure of massive coral colonies by severe storm or hurricane events, as recorded in coral growth patterns through density patterns and the analysis of CT-scanned coral specimens.