BackgroundThe highly derived morphology and astounding diversity of snakes has long inspired debate regarding the ecological and evolutionary origin of both the snake total-group (Pan-Serpentes) and crown snakes (Serpentes). Although speculation abounds on the ecology, behavior, and provenance of the earliest snakes, a rigorous, clade-wide analysis of snake origins has yet to be attempted, in part due to a dearth of adequate paleontological data on early stem snakes. Here, we present the first comprehensive analytical reconstruction of the ancestor of crown snakes and the ancestor of the snake total-group, as inferred using multiple methods of ancestral state reconstruction. We use a combined-data approach that includes new information from the fossil record on extinct crown snakes, new data on the anatomy of the stem snakes Najash rionegrina, Dinilysia patagonica, and Coniophis precedens, and a deeper understanding of the distribution of phenotypic apomorphies among the major clades of fossil and Recent snakes. Additionally, we infer time-calibrated phylogenies using both new ‘tip-dating’ and traditional node-based approaches, providing new insights on temporal patterns in the early evolutionary history of snakes.ResultsComprehensive ancestral state reconstructions reveal that both the ancestor of crown snakes and the ancestor of total-group snakes were nocturnal, widely foraging, non-constricting stealth hunters. They likely consumed soft-bodied vertebrate and invertebrate prey that was subequal to head size, and occupied terrestrial settings in warm, well-watered, and well-vegetated environments. The snake total-group – approximated by the Coniophis node – is inferred to have originated on land during the middle Early Cretaceous (~128.5 Ma), with the crown-group following about 20 million years later, during the Albian stage. Our inferred divergence dates provide strong evidence for a major radiation of henophidian snake diversity in the wake of the Cretaceous-Paleogene (K-Pg) mass extinction, clarifying the pattern and timing of the extant snake radiation. Although the snake crown-group most likely arose on the supercontinent of Gondwana, our results suggest the possibility that the snake total-group originated on Laurasia.ConclusionsOur study provides new insights into when, where, and how snakes originated, and presents the most complete picture of the early evolution of snakes to date. More broadly, we demonstrate the striking influence of including fossils and phenotypic data in combined analyses aimed at both phylogenetic topology inference and ancestral state reconstruction.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0358-5) contains supplementary material, which is available to authorized users.

The origin of the turtle shell has perplexed biologists for more than two centuries. It was not until Odontochelys semitestacea was discovered, however, that the fossil and developmental data could be synthesized into a model of shell assembly that makes predictions for the as-yet unestablished history of the turtle stem group. We build on this model by integrating novel data for Eunotosaurus africanus-a Late Guadalupian (∼260 mya) Permian reptile inferred to be an early stem turtle. Eunotosaurus expresses a number of relevant characters, including a reduced number of elongate trunk vertebrae (nine), nine pairs of T-shaped ribs, inferred loss of intercostal muscles, reorganization of respiratory muscles to the ventral side of the ribs, (sub)dermal outgrowth of bone from the developing perichondral collar of the ribs, and paired gastralia that lack both lateral and median elements. These features conform to the predicted sequence of character acquisition and provide further support that E. africanus, O. semitestacea, and Proganochelys quenstedti represent successive divergences from the turtle stem lineage. The initial transformations of the model thus occurred by the Middle Permian, which is congruent with molecular-based divergence estimates for the lineage, and remain viable whether turtles originated inside or outside crown Diapsida.

Planktonic foraminiferal species identification is central to many paleoceanographic studies, from selecting species for geochemical research to elucidating the biotic dynamics of microfossil communities relevant to physical oceanographic processes and interconnected phenomena such as climate change. However, few resources exist to train students in the difficult task of discerning amongst closely related species, resulting in diverging taxonomic schools that differ in species concepts and boundaries. This problem is exacerbated by the limited number of taxonomic experts. Here we document our initial progress toward removing these confounding and/or rate-limiting factors by generating the first extensive image library of modern planktonic foraminifera, providing digital taxonomic training tools and resources, and automating species-level taxonomic identification of planktonic foraminifera via machine learning using convolution neural networks. Experts identified 34,640 images of modern (extant) planktonic foraminifera to the species level. These images are served as species exemplars through the online portal Endless Forams (endlessforams.org) and a taxonomic training portal hosted on the citizen science platform Zooniverse (zooniverse.org/projects/ahsiang/ endless-forams/). A supervised machine learning classifier was then trained with~27,000 images of these identified planktonic foraminifera. The best-performing model provided the correct species name for an image in the validation set 87.4% of the time and included the correct name in its top three guesses 97.7% of the time. Together, these resources provide a rigorous set of training tools in modern planktonic foraminiferal taxonomy and a means of rapidly generating assemblage data via machine learning in future studies for applications such as paleotemperature reconstruction.

Abstract1. Large-scale, comparative studies of morphological variation are rare due to the time-intensive nature of shape quantification. This data gap is important to address, as intraspecific and interspecific morphological variation underpins and reflects ecological and evolutionary processes.2. Here, we detail a novel software package, AutoMorph, for high-throughput object and shape extraction. AutoMorph can batch image many types of organisms (e.g. foraminifera, molluscs and fish teeth), allowing for rapid generation of assemblagescale morphological data.3. We used AutoMorph to image and generate 2D and 3D morphological data for >100,000 marine microfossils in about a year. Our collaborators have used AutoMorph to process >12,000 patellogastropod shells and >50,000 fish teeth.