Biology subjects

Benton, M. J.

Publications and source records attributed to Benton, M. J..

5 recordsLinked to original sources

bioRxiv2025

INDITEK-2.0: A Bayesian inverse eco-evolutionary modelling framework for reconstructing Phanerozoic biodiversity

O_LIMechanistic eco-evolutionary models are powerful tools for understanding how life diversified over geological timescales, yet estimating their parameters remains a key challenge. The high computational requirements of these models make probabilistic inversion methods unfeasible. C_LIO_LIWe address this challenge with INDITEK-2.0, a new, cost-efficient eco-evolutionary model that integrates a Bayesian inverse modelling framework for probabilistic estimation of parameters. C_LIO_LITo validate this framework, we conducted a proof-of-concept study. We first generated synthetic biodiversity data for marine invertebrates using INDITEK-2.0 with known parameter values. To mimic field data, some realistic random Gaussian errors were added to the data. We then used our Bayesian inverse modelling framework to recover these original (true) parameter values from the dataset of current biodiversity distributions after 500 million years of diversification. Our solution is a probability distribution on the parameter space, and we show that the method successfully recovered the target parameter values with a relatively low degree of uncertainity. C_LIO_LIINDITEK-2.0s ability to probabilistically infer underlying eco-evolutionary processes provides a new modelling tool for reconstructing the evolutionary history of biodiversity across Earths ecosystems and taxonomic groups. C_LI

ecology↗

bioRxiv2024

Estimating ancestral states of complex characters: a case study on the evolution of feathers

Feathers are a key novelty underpinning the evolutionary success of birds, yet the origin of feathers remains poorly understood. Debates about feather evolution hinge upon whether filamentous integument has evolved once or multiple time independently on the lineage leading to modern birds. These contradictory results stem from subjective methodological differences in statistical ancestral state estimates. Here we conduct a comprehensive comparison of ancestral state estimation methodologies applied to stem-group birds, testing the role of outgroup inclusion, tree time scaling method, model choice and character coding strategy. Models are compared based on their Akaike Information Criteria (AIC), mutual information, as well as the uncertainty of marginal ancestral state estimates. Our results demonstrate that ancestral state estimates of stem-bird integument are strongly influenced by tree time scaling method, outgroup selection and model choice, while character coding strategy seems to have less effect on the ancestral estimates produced. We identify the best fitting models using AIC scores and a leave-one-out cross-validation approach (LOOCV). Our analyses broadly support the independent origin of filamentous integument in dinosaurs and pterosaurs and support a younger evolutionary origin of feathers than has been suggested previously. More generally, our study highlights that special care must be taken in selecting the outgroup, tree and model when conducting ASE analyses. With respect to model selection, our results suggest that considering a LOOCV approach, may yield more reliable results than simply comparing AIC scores when the analyses involve a limited number of taxa.

paleontology↗

bioRxiv2023

AI in Paleontology

Accumulating data have led to the emergence of data-driven paleontological studies, which reveal an unprecedented picture of evolutionary history. However, the fast-growing quantity and complication of data modalities make data processing laborious and inconsistent, while also lacking clear benchmarks to evaluate data collection and generation, and the performances of different methods on similar tasks. Recently, Artificial Intelligence (AI) is widely practiced across scientific disciplines, but has not become mainstream in paleontology where manual workflows are still typical. In this study, we review more than 70 paleontological AI studies since the 1980s, covering major tasks including micro-and macrofossil classification, image segmentation, and prediction. These studies feature a wide range of techniques such as Knowledge Based Systems (KBS), neural networks, transfer learning, and many other machine learning methods to automate a variety of paleontological research workflows. Here, we discuss their methods, datasets, and performance and compare them with more conventional AI studies. We attribute the recent increase in paleontological AI studies to the lowering bar in training and deployment of AI models rather than real progress. We also present recently developed AI implementations such as diffusion model content generation and Large Language Models (LLMs) to speculate how these approaches may interface with paleontological research. Even though AI has not yet flourished in paleontological research, successful implementation of AI is growing and show promise for transformative effect on the workflow in paleontological research in the years to come. HighlightsO_LIFirst systematic review of AI applications in paleontology. C_LIO_LIThere is a 10 to 20-year gap between AI in paleontology and mainstream studies. C_LIO_LIRecent progress in paleontological AI studies is likely a result of lowering bar in training and deployment. C_LIO_LIFuture direction discussed for interactions between paleontology and AI. C_LI

paleontology↗

bioRxiv2019

Reptile-like physiology in Early Jurassic stem-mammals

There is uncertainty regarding the timing and fossil species in which mammalian endothermy arose, with few studies of stem-mammals on key aspects of endothermy such as basal or maximum metabolic rates, or placing them in the context of living vertebrate metabolic ranges. Synchrotron X-ray imaging of incremental tooth cementum shows two Early Jurassic stem-mammals, Morganucodon and Kuehneotherium, had lifespans (a basal metabolic rate proxy) considerably longer than comparably sized living mammals, but similar to reptiles, and that Morganucodon had femoral blood flow rates (a maximum metabolic rate proxy) intermediate between living mammals and reptiles. This shows maximum metabolic rates increased evolutionarily before basal rates, and that contrary to previous suggestions of a Triassic origin, Early Jurassic stem-mammals lacked the endothermic metabolism of living mammals.One Sentence Summary Surprisingly long lifespans and low femoral blood flow suggest reptile-like physiology in key Early Jurassic stem-mammals.View Full Text

paleontology↗

bioRxiv2017

150 million years of sustained increase in pterosaur flight efficiency

The long-term accumulation of biodiversity has been punctuated by remarkable evolutionary transitions that allowed organisms to exploit new ecological opportunities, and often resulted in large radiations of species. The Mesozoic flying reptiles - pterosaurs - which dominated the skies for over 150 million years (Myr), were the product of such a transition. The ancestors of pterosaurs were small and likely bipedal early archosaurs, which were certainly well adapted to terrestrial locomotion. More than 220 Myr ago, at some point in the Triassic, pterosaurs took flight and subsequently appear to have become capable and efficient flyers. However, the evolutionary processes that led to this efficiency remain enigmatic. Given the lack of proto-pterosaurs it is difficult to study how flight first evolved in this group, but we can test hypotheses about evolutionary changes to the energetics of locomotion following the transition to flight. Early pterosaurs were challenged by the c ...

evolutionary biology↗