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The extensive chondrichthyan fossil record spans 400+ million years and has a global distribution. Paleontological studies provide a foundation of description and taxonomy to support deeper forays into ecology and evolution considering geographic, morphologic, and functional changes through time with nonanalog species and climate states. Although chondrichthyan teeth are most studied, analyses of dermal denticle metrics and soft tissue imprints are increasing. Recent methodological advances in morphology and geochemistry are elucidating fine-scale details, whereas large datasets and ecological modeling are broadening taxonomic, temporal, and geographic perspectives. The combination of ecological metrics and modeling with environmental reconstruction and climate simulations is opening new horizons to explore form and function, demographic dynamics, and food web structure in ancient marine ecosystems. Ultimately, the traits and taxa that endured or perished during the many catastrophic upheaval events in Earth's history contribute to conservation paleobiology, which is a much-needed perspective for extant chondrichthyans.▪The longevity and abundance of the chondrichthyan fossil record elucidates facets of ecological, evolutionary, and environmental histories.▪Though lacking postcranial, mineralized skeletons, dental enameloid and dermal denticles exquisitely preserve morphology and geochemistry.▪Technical advances in imaging, geochemistry, and modeling clarify the linkages between form and function with respect to physiology, diet, and environment.▪Conservation efforts can benefit from the temporal and spatial perspective of chondrichthyan persistence through past global change events. 

Shark teeth are one of the most abundant vertebrate fossils, and because tooth size generally correlates with body size, their accumulations document the size structure of populations. Understanding how ecological and environmental processes influence size structure, and how this extends to influence these dental distributions, may offer a window into the ecological and environmental dynamics of past and present shark populations. Here, we examine the dental distributions of sand tigers, including extant Carcharias taurus and extinct Striatolamia macrota , to reconstruct the size structure for a contemporary locality and four Eocene localities. We compare empirical distributions against expectations from a population simulation to gain insight into potential governing ecological processes. Specifically, we investigate the influence of dispersal flexibility to and from protected nurseries. We show that changing the flexibility of initial dispersal of juveniles from the nursery and annual migration of adults to the nursery explains a large amount of dental distribution variability. Our framework predicts dispersal strategies of an extant sand tiger population, and supports nurseries as important components of sand tiger life history in both extant and Eocene populations. These results suggest nursery protection may be vital for shark conservation with increasing anthropogenic impacts and climate change. 

Abstract Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.