Making sense of variation in sclerochronological stable isotope profiles of mollusks and fish otoliths from the early Eocene southern North Sea Basin

Abstract

Stable isotope sclerochemistry of biogenic carbonate is frequently used for the reconstruction of paleotemperature and seasonality. Yet, few studies have compared intra-and inter-taxon isotope variability and variation within a single depositional environment. We measured seasonal changes in δ18O and δ13C compositions in multiple specimens of two carditid bivalve species, a turritelline gastropod species, and two species of otoliths from demersal fish, from two early Eocene (latest Ypresian, 49.2 Ma) coquinas in the inner neritic Aalter Formation, located in the Belgian part of the southern North Sea Basin (paleolatitude ~41°N). Results demonstrate considerable variation among taxa in the mean, amplitude, and skewness of δ18O and δ13C values from sequentially sampled growth series. We attribute this variation to factors including differences in seasonal growth over ontogeny, mixing of depositional settings by sediment transport, differences between sedentary and mobile organisms, and differences in longevity of the taxa in question. Growth cessation during winters in turritellines and fishes in particular lead to an incomplete representation of the seasonal cycle in their growth increments, in comparison to carditid bivalves. Ophidiid fish otolith isotope records appear to reflect environmental conditions over a wider range of habitats and environments, and we infer this is due to a combination of sedimentary transport, as these are small structures, and postmortem transport by free-swimming predatory fish. Our study highlights the potential variability encompassed by taxa in the shallow marine realm even when they are found in the same deposits. While this has significant implications for seasonality reconstructions based on conventional isotope profiles, we show that careful study of the ecology and ontogeny of multiple taxa and specimens within a death assemblage can reveal sources of variation and yield a close approximation of conditions in the setting of interest.