Bethany Allen

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Allen

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Bethany

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0000-0003-0282-6407

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Publications 1 - 10 of 15

The Greatest Extinction Event in 66 Million Years? Contextualising Anthropogenic Extinctions
Hatfield, Jack H.; Allen, Bethany; Carroll, Tadhg; et al. (2025)
Global Change Biology
Biological communities are changing rapidly in response to human activities, with the high rate of vertebrate species extinction leading many to propose that we are in the midst of a sixth mass extinction event. Five past mass extinction events have commonly been identified across the Phanerozoic, with the last occurring at the end of the Cretaceous, 66 million years ago (Ma). However, life on Earth has always changed and evolved, with most species ever to have existed now extinct. The question is, are human activities increasing the rate and magnitude of extinction to levels rarely seen in the history of life? Drawing on the literature on extinctions primarily over the last 66 million years (i.e., the Cenozoic), we ask: (1) what comparisons can meaningfully be drawn? and (2) when did the Earth last witness an extinction event on this scale? We conclude that, although challenging to address, the available evidence suggests that the ongoing extinction episode still falls a long way short of the devastation caused by the bolide impact 66 Ma, but that it has likely surpassed most other Cenozoic events in magnitude, with the possible exception of the Eocene–Oligocene transition (34 Ma), about which much uncertainty remains. Given the number of endangered and at-risk species, the eventual magnitude of the current event will depend heavily on humanity's response and how we interact with the rest of the biosphere over the coming millennia.
DeepDiveR—A software for deep learning estimation of palaeodiversity from fossil occurrences
Cooper, Rebecca B.; Allen, Bethany; Silvestro, Daniele (2025)
Methods in Ecology and Evolution
1. The incompleteness of the fossil record, in particular variation in preservation and sampling through space and time, presents a barrier to estimating changes in biodiversity which standard statistical methods struggle to account for. 2. Here we present DeepDiveR, an R package companion for the DeepDive Python program, facilitating estimation of biodiversity from fossil occurrence data. The method uses a simulation-trained deep neural network to generate predictions of biodiversity change through time, while accounting for temporal, spatial, and taxonomic heterogeneities in preservation and sampling. 3. DeepDive and DeepDiveR can be readily used to explore the extinct biodiversity of different clades. We demonstrate the pipeline to build and customise analyses in R, including consideration of changes in biogeography, before running them in Python. We also further develop the DeepDive model to integrate information about modern diversity in the case of extant clades and introduce a function that automatically adjusts the parameterisation of the simulations to generate training data that reflect the distribution of empirical datasets. 4. To demonstrate the software, we analyse the fossil record of the order Carnivora through the Cenozoic, finding a peak in diversity in the Late Miocene and a 31% species loss since the Pleistocene. Our implementation includes the generation of summary statistics and plots that allow for an evaluation of the model performance and diversity estimations, and a configuration file that captures all parameters required to guarantee the full reproducibility of the results.
How predictable are mass extinction events?
Foster, William J.; Allen, Bethany; Kitzmann, Niklas H.; et al. (2023)
Royal Society Open Science
Many modern extinction drivers are shared with past mass extinction events, such as rapid climate warming, habitat loss, pollution and invasive species. This commonality presents a key question: can the extinction risk of species during past mass extinction events inform our predictions for a modern biodiversity crisis? To investigate if it is possible to establish which species were more likely to go extinct during mass extinctions, we applied a functional trait-based model of extinction risk using a machine learning algorithm to datasets of marine fossils for the end-Permian, end-Triassic and end-Cretaceous mass extinctions. Extinction selectivity was inferred across each individual mass extinction event, before testing whether the selectivity patterns obtained could be used to ‘predict’ the extinction selectivity exhibited during the other mass extinctions. Our analyses show that, despite some similarities in extinction selectivity patterns between ancient crises, the selectivity of mass extinction events is inconsistent, which leads to a poor predictive performance. This lack of predictability is attributed to evolution in marine ecosystems, particularly during the Mesozoic Marine Revolution, associated with shifts in community structure alongside coincident Earth system changes. Our results suggest that past extinctions are unlikely to be informative for predicting extinction risk during a projected mass extinction.
Mechanistic phylodynamic models do not provide conclusive evidence that non-avian dinosaurs were in decline before their final extinction
Allen, Bethany; Volkova Oliveira, Maria V.; Stadler, Tanja; et al. (2024)
Cambridge Prisms: Extinction
Phylodynamic models can be used to estimate diversification trajectories from time-calibrated phylogenies. Here we apply two such models to phylogenies of non-avian dinosaurs, a clade whose evolutionary history has been widely debated. While some authors have suggested that the clade experienced a decline in diversity, potentially starting millions of years before the end-Cretaceous mass extinction, others have suggested that the group remained highly diverse right up until the Cretaceous-Paleogene (K-Pg) boundary. Our results show that model assumptions, likely with respect to incomplete sampling, have a large impact on whether dinosaurs appear to have experienced a long-term decline or not. The results are also highly sensitive to the topology and branch lengths of the phylogeny used. Developing comprehensive models of sampling bias, and building larger and more accurate phylogenies, are likely to be necessary steps for us to determine whether dinosaur diversity was or was not in decline prior to the end-Cretaceous mass extinction.
Estimating spatial variation in origination and extinction in deep time: a case study using the Permian–Triassic marine invertebrate fossil record
Allen, Bethany; Clapham, Matthew E.; Saupe, Erin E.; et al. (2023)
Paleobiology
Understanding spatial variation in origination and extinction can help to unravel the mechanisms underlying macroevolutionary patterns. Although methods have been developed for estimating global origination and extinction rates from the fossil record, no framework exists for applying these methods to restricted spatial regions. Here, we test the efficacy of three metrics for regional analysis, using simulated fossil occurrences. These metrics are then applied to the marine invertebrate record of the Permian and Triassic to examine variation in extinction and origination rates across latitudes. Extinction and origination rates were generally uniform across latitudes for these time intervals, including during the Capitanian and Permian–Triassic mass extinctions. The small magnitude of this variation, combined with the possibility of its attribution to sampling bias, cautions against linking any observed differences to contrasting evolutionary dynamics. Our results indicate that origination and extinction levels were more variable across clades than across latitudes.
Archosauromorph extinction selectivity during the Triassic-Jurassic mass extinction
Allen, Bethany; Stubbs, Thomas L.; Benton, Michael J.; et al. (2019)
Palaeontology
Many traits have been linked to extinction risk among modern vertebrates, including mode of life and body size. However, previous work has indicated there is little evidence that body size, or any other trait, was selective during past mass extinctions. Here, we investigate the impact of the Triassic–Jurassic mass extinction on early Archosauromorpha (basal dinosaurs, crocodylomorphs and their relatives) by focusing on body size and other life history traits. We built several new archosauromorph maximum-likelihood supertrees, incorporating uncertainty in phylogenetic relationships. These supertrees were then employed as a framework to test whether extinction had a phylogenetic signal during the Triassic–Jurassic mass extinction, and whether species with certain traits were more or less likely to go extinct. We find evidence for phylogenetic signal in extinction, in that taxa were more likely to become extinct if a close relative also did. However, there is no correlation between extinction and body size, or any other tested trait. These conclusions add to previous findings that body size, and other traits, were not subject to selection during mass extinctions in closely-related clades, although the phylogenetic signal in extinction indicates that selection may have acted on traits not investigated here.
palaeoverse: A community-driven R package to support palaeobiological analysis
Jones, Lewis A.; Gearty, William; Allen, Bethany; et al. (2023)
Methods in Ecology and Evolution
1. The open-source programming language ‘R' has become a standard tool in the palaeobiologist's toolkit. Its popularity within the palaeobiological community continues to grow, with published articles increasingly citing the usage of R and R packages. However, there are currently a lack of agreed standards for data preparation and available frameworks to support the implementation of such standards. Consequently, data preparation workflows are often unclear and not reproducible, even when code is provided. Moreover, due to a lack of code accessibility and documentation, palaeobiologists are often forced to ‘reinvent the wheel’ to find solutions to issues already solved by other members of the community. 2. Here, we introduce palaeoverse, a community-driven R package to aid data preparation and exploration for quantitative palaeobiological research. The package is freely available and has three core principles: (1) streamline data preparation and analyses; (2) enhance code readability; and (3) improve reproducibility of results. To develop these aims, we assessed the analytical needs of the broader palaeobiological community using an online survey, in addition to incorporating our own experiences. 3. In this work, we first report the findings of the survey, which shaped the development of the package. Subsequently, we describe and demonstrate the functionality available in palaeoverse and provide usage examples. Finally, we discuss the resources we have made available for the community and our future plans for the broader Palaeoverse project. 4. palaeoverse is a community-driven R package for palaeobiology, developed with the intention of bringing palaeobiologists together to establish agreed standards for high-quality quantitative research. The package provides a user-friendly platform for preparing data for analysis with well-documented open-source code to enhance transparency. The functionality available in palaeoverse improves code reproducibility and accessibility, which is beneficial for both the review process and future research.
Early Triassic super-greenhouse climate driven by vegetation collapse
Xu, Zhen; Yu, Jianxin; Yin, Hongfu; et al. (2025)
Nature Communications
The Permian–Triassic Mass Extinction (PTME), the most severe crisis of the Phanerozoic, has been attributed to intense global warming triggered by Siberian Traps volcanism. However, it remains unclear why super-greenhouse conditions persisted for around five million years after the volcanic episode, with one possibility being that the slow recovery of plants limited carbon sequestration. Here we use fossil occurrences and lithological indicators of climate to reconstruct spatio-temporal maps of plant productivity changes through the PTME and employ climate-biogeochemical modelling to investigate the Early Triassic super-greenhouse. Our reconstructions show that terrestrial vegetation loss during the PTME, especially in tropical regions, resulted in an Earth system with low levels of organic carbon sequestration and restricted chemical weathering, resulting in prolonged high CO2 levels. These results support the idea that thresholds exist in the climate-carbon system whereby warming can be amplified by vegetation collapse.
rmacrostrat: An R package for accessing and retrieving data from the Macrostrat geological database
Jones, Lewis A.; Dean, Christopher D.; Gearty, William; et al. (2024)
Geosphere
The geological record is a vast archive of information that provides the only empirical data about the evolution of the Earth. In recent years, concentrated efforts have been made to compile macrostratigraphic data into the online centralized database Macrostrat. Macrostrat is a global stratigraphic database containing information regarding surface and subsurface rock units and their respective ages, lithologies, geographic extents, and various other associated metadata. However, these raw data are currently directly accessible only through the Macrostrat application programming interface, which is a barrier to potential users that are less familiar with such services. This data accessibility hurdle currently prevents full capitalization of the value offered by Macrostrat, particularly its potential to improve understanding of the geological and biological evolution of the Earth. Here, we introduce rmacrostrat, an R package that interfaces with the Macrostrat database to access and retrieve a variety of geological, paleontological, and economic data directly into the R programming environment. In this article, we provide details about how the package can be installed, its implementation, and potential use cases. For the latter, we showcase how rmacrostrat can be used to visualize regional stratigraphic columns, produce regional geologic outcrop maps, and investigate temporal trends in macrostratigraphic units. We hope that this package will make geological data more readily accessible and in turn will facilitate new research utilizing Earth system data.
Projected future climatic forcing on the global distribution of vegetation types
Allen, Bethany; Hill, Daniel J.; Burke, Ariane M.; et al. (2024)
Philosophical Transactions of the Royal Society B: Biological Sciences
Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services.

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