bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/633008

The dynamics of stem and crown groups

Budd, G. E.·Mann, R. P.
View original source ↗Export metadata ↓

Abstract

ABSTRACTThe fossil record of the origins of major groups is of great interests to many biologists, especially when the fossil record apparently conflicts with timings based on molecular clock estimates. Here we model the diversity of “stem” (basal) and “crown” (modern) members of groups as seen in the fossil record, using a “birth-death model”. Under background conditions, the stem group members must diversify rapidly until the modern crown group emerges, at which point their diversity rapidly collapses, followed shortly by their extinction. Mass extinctions can disturb this pattern to create very diverse stem groups such as the dinosaurs and trilobites. Understanding these null-hypothesis patterns is essential for framing ecological and evolutionary explanations for how major groups originate and subsequently evolve.View Full Text

Source connections

Explore related subjects

paleontologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Budd, G. E., Mann, R. P.. 2019-05-09. The dynamics of stem and crown groups. https://doi.org/10.1101/633008

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Constraining Palaeogeography and Palaeotides for the Cambrian using cnidarian medusae

The ocean tides influence key Earth system processes at a range of spatial and temporal scales. It is known that the geometry of ocean basins is the leading controller of tidal energetics, so well-constrained palaeogeographic reconstructions and tidal properties for Earths past are imperative when investigating other Earth system processes. Here, we present a novel way to constrain both deep-time tidal model results and reconstructions, by combining palaeoecology with sedimentology. We compare new palaeo-tidal model simulations for the Cambrian period, significant for the early origin and radiation of major animal fauna, to tidal proxies. One of the most abundant soft-bodied organisms preserved during this time are cnidarian medusae (jellyfish). A total of 17 cnidarian medusae localities were obtained through the literature, which had an adequate global distribution and occurred at regular intervals throughout the period of study. In some locations there were also estimates of palaeo-tidal range. Our results show a good agreement between the simulations and proxy data. In the few locations where there is disagreement, it is proposed that the palaeogeographic reconstructions are missing details, e.g., island chains, and our results allow for the palaeogeographic reconstructions to be improved. The proxy method presented is promising and can be applied to other time-periods with different marine fossils, particularly at evolutionary and extinction periods where the marginal marine environment is of importance.

paleontology↗
bioRxiv2019

Automated Microfossil Identification and Segmentation Using a Deep Learning Approach

The applicability of computational analysis to paleontological images ranges from the study of the animals, plants and evolution of microorganisms to the simulation of the habitat of living beings of a given epoch. It also can be applied in several niches, such as oil exploration, where there are several factors to be analyzed in order to minimize the expenses related to the oil extraction process. One factor is the characterization of the environment to be explored. This analysis can occur in several ways: use of probes, extraction of samples for petrophysical components evaluation, the correlation with logs of other drilling wells and so on. In the samples extraction part the Computed Tomography (CT) is of importance because it preserves the sample and makes it available for several analyzes. Based on 3D images generated by CT, several analyzes and simulations can be performed and processes, currently performed manually and exhaustively, can be automated. In this work we propose and validate a method for fully automated microfossil identification and extraction. A pipeline is proposed that begins in the scanning process and ends in an identification process. For the identification a Deep Learning approach was developed, which resulted in a high rate of correct microfossil identification (98% of Intersection Over Union). The validation was performed both through an automated quantitative analysis based upon ground truths generated by specialists in the micropaleontology field and visual inspection by these specialists. We also present the first fully annotated MicroCT-acquired publicly available microfossils dataset.View Full Text

paleontology↗
bioRxiv2019

Saving Old Bones: a non-destructive method for bone collagen prescreening

Bone collagen is an important material for radiocarbon, paleodietary, and paleoproteomic analyses, but it degrades over time. Various methods have been employed to prescreen bone for collagen preservation, but these are often destructive and/or require exportation for analysis. Here we show that near-infrared spectroscopy can be used to determine bone collagen content quickly and non-destructively on site.rView Full Text

paleontology↗