The end-Triassic mass extinction was among the most severe biotic crises of the Phanerozoic. It has been linked with the global expansion of marine anoxia, and the prolongation of these conditions within epeiric seas has been proposed as a cause for the suppression of biodiversity during the Hettangian. Testing this interpretation is complicated by spatially heterogenous patterns of local marine redox conditions within the western Tethys European Epicontinental Shelf. In this study we assess the redox state within this region by focusing on two carbonate successions in Italy. Based on I/Ca ratios, these locations record distinct local background redox conditions, with Val Adrara showing notably lower pre-extinction oxygen saturation state compared to Mount Sparagio. To better explain these differences, δ44Ca and trace element analyses were used to identify the roles of mineralogical and diagenetic effects on the preservation of primary redox signals. A framework of multiple elemental (Sr, Mg, Mn, I) and isotopic (δ13C, δ18O, δ44Ca, δ238U and δ34SCAS) ratios was developed to identify factors that could influence carbonate geochemistry. Both sites probably retain some primary variation in δ238U, δ34SCAS and I/Ca, but they are likely also shaped by changing mineralogy and early diagenetic conditions which complicates interpretations of the seawater composition. Where the redox signals are largely preserved, we interpret differences in pre-extinction I/Ca between the two sites to reflect distinct local oxygenation states. Model simulations show that ocean circulation and hydrological regime could have been important drivers of spatial heterogeneity in paleo-redox conditions across the European Epicontinental Shelf.

The end-Permian mass extinction event resulted in the loss of approximately 80% to 90% of marine animal species due to drastic changes in climate. Because warming was a major factor in the extinction, it has been theorized the organisms that did survive were able to do so because they moved to higher latitudes and this hypothesis is consistent with tetrapod data. We hypothesized that this relationship holds true for marine mollusks and arthropods as well. Using Changhsingian (Late Permian) and Induan (Early Triassic) data from the Paleobiology Database, we extracted occurrences of classes Bivalvia, Cephalopoda, Gastropoda, and Ostracoda, which had 2433, 395, 379, and 1717 genus occurrences, respectively. Then, we used the paleolatitude data for each genus occurrence to characterize the latitude distribution of each class before and after the Permian/Triassic transition. We compared the paleolatitude medians before and after the mass extinction for each class to quantify the latitude shift for each class: 23.18° for Bivalvia, 37.45° for Cephalopoda, 29.82° for Gastropoda, and 6.29° for Ostracoda. This finding indicates that each individual class had a different latitudinal shift, with all classes exhibiting a poleward shift north. We also conducted Welch t-tests to compare the differences in latitudinal ranges and found that they were significant (Bivalvia: p < 2.2e-16, Cephalopoda: p = 3.83e-6, Gastropoda: p < 2.2e-16, Ostracoda: p = 0.0030). In addition, we ran multiple randomized models to compare them with our original results and found a significant difference between them via the Kolmogorov-Smirnov test, which means that the northward migration could be a biological response. Moreover, the results of our study show that the overall latitudinal range of most classes contracted after the extinction event, with the exception of the Cephalopoda class.

From extracting nutrients to releasing energy, biological metabolism plays an integral role in determining evolutionary patterns of organisms through geologic time. A previous study depicted a positive relationship between metabolic rate and extinction probability for Mollusca within the Neogene period. We hypothesized that this relationship extends to other metazoan phyla during the Cenozoic Era. Using specific respiration rates measured from living organisms and body size data for fossil taxa, we estimated metabolic rates of animals across different phyla: Arthropoda, Brachiopoda, Echinodermata, and Mollusca. This analysis was performed at the class level by using the classes with the most data available to represent each phylum: Malacostraca, Ostracoda, Cirripedia, Rhynchonellata, Echinoidea, Bivalvia, Cephalopoda, and Gastropoda. We then used logistic regression to estimate the relationship between the calculated metabolic rates and extinction probability during each epoch of the Cenozoic Era. Results indicate that while each individual phylum has a different extinction probability across each epoch, the regression coefficients for the combination of all studied phyla illustrate no relationship since there is not enough evidence to reject the null hypothesis of no relationship between metabolic rate and extinction probability. Although this means that there is no significant correlation for most of the phyla, there are some exceptions where metabolism does affect extinction probability. During the Oligocene epoch, animals within the Mollusca phylum portray a clear negative correlation between metabolic rate and extinction probability. A negative relationship is also observed for Echinoderms during the Eocene epoch. Despite the crucial role that metabolism plays in species survival, our results indicate that more information is needed regarding specific environmental conditions in order to accurately predict the factors that ultimately affect species survival across marine animals within the Cenozoic Era.

Extinction within the Paleozoic era has been studied in the past, but there still lacks a comprehensive understanding of how extinction risk changed throughout it. Our research project aims to bridge this gap by exploring extinction risk in relation to major Paleozoic phyla and ecological characteristics. Using R, we analyzed the Stanford Earth Body Size dataset, which includes extensive data (n=8816) on Paleozoic marine animals. In Step 1, regression coefficients were formed, indicating whether being in one of the 6 phyla in each period of the Paleozoic era conferred greater or less extinction risk. In Step 2, the examined ecological characteristics included ocean acidification resilience, feeding patterns, body volume, length, surface area, motility, tiering, circulatory systems, and respiratory organ type. In Step 3, 6 binomial machine learning models were created using the traits from Step 2 to determine whether an individual genus went extinct in a particular period. Our Step 1 results confirm that within these timeframes, while certain phyla have greater extinction risk, extinction risk was not uniform across these groups. Our Step 2 results show certain traits provided advantages and disadvantages for an organism’s extinction risk. One interesting pattern was that the only consistently non-significant traits were body length, area, and volume. Likewise with Step 1, extinction risk for each ecological characteristic varied across the Paleozoic. Finally, in Step 3, the results were largely successful. Most of the six models had an accuracy above 80% with the highest being 92% in the Cambrian. The areas under the Precision-Recall and the Receiver Operating Characteristic Curves were all in the acceptable (<0.6) range, demonstrating that the model has low false positive/ negative rates and is able to distinguish between what trait indicates extinction or survival for each period. Our research project identified phyla at risk of extinction in each period of the Paleozoic, determined which natural traits incited greater extinction risk, and demonstrated machine learning models trained on fossil descriptors can predict when an individual genus became extinct. Our results confirmed that extinction risk is not consistently dependent on a singular factor nor is it constant across every period of the Paleozoic era.