Molecular timescales estimate that early animal lineages diverged tens of millions of years before their earliest unequivocal fossil evidence. The Ediacaran macrobiota (~574 to 538 million years ago) are largely eschewed from this debate, primarily due to their extreme phylogenetic uncertainty, but remain germane. We characterize the development of Charnia masoni and establish the affinity of rangeomorphs, among the oldest and most enigmatic components of the Ediacaran macrobiota. We provide the first direct evidence for the internal interconnected nature of rangeomorphs and show that Charnia was constructed of repeated branches that derived successively from pre-existing branches. We find homology and rationalize morphogenesis between disparate rangeomorph taxa, before producing a phylogenetic analysis, resolving Charnia as a stem-eumetazoan and expanding the anatomical disparity of that group to include a long-extinct bodyplan. These data bring competing records of early animal evolution into closer agreement, reformulating our understanding of the evolutionary emergence of animal bodyplans.

Global diversity patterns in the fossil record comprise a mosaic of regional trends, underpinned by spatially non-random drivers and distorted by variation in sampling intensity through time and across space. Sampling-corrected diversity estimates from spatially-standardised fossil datasets retain their regional biogeographic nuances and avoid these biases, yet diversity-through-time arises from the interplay of origination and extinction, the processes that shape macroevolutionary history. Here we present a subsampling algorithm to eliminate spatial sampling bias, coupled with advanced probabilistic methods for estimating origination and extinction rates and a Bayesian method for estimating sampling-corrected diversity. We then re-examine the Late Permian to Early Jurassic marine fossil record, an interval spanning several global biotic upheavals that shaped the origins of the modern marine biosphere. We find that origination and extinction rates are regionally heterogenous even during events that manifested globally, highlighting the need for spatially explicit views of macroevolutionary processes through geological time.

How much of evolutionary history is lost because of the unevenness of the fossil record? Lagerstätten, sites which have historically yielded exceptionally preserved fossils, provide remarkable, yet distorting insights into past life. When examining macroevolutionary trends in the fossil record, they can generate an uneven sampling signal for taxonomic diversity; by comparison, their effect on morphological variety (disparity) is poorly understood. We show here that lagerstätten impact the disparity of ichthyosaurs, Mesozoic marine reptiles, by preserving higher diversity and more complete specimens. Elsewhere in the fossil record, undersampled diversity and more fragmentary specimens produce spurious results. We identify a novel effect, that a taxon moves towards the centroid of a Generalized Euclidean dataset as its proportion of missing data increases. We term this effect ‘centroid slippage’, as a disparity-based analogue of phylogenetic stemward slippage. Our results suggest that uneven sampling presents issues for our view of disparity in the fossil record, but that this is also dependent on the methodology used, especially true with widely used Generalized Euclidean distances. Mitigation of missing cladistic data is possible by phylogenetic gap filling, and heterogeneous effects of lagerstätten on disparity may be accounted for by understanding the factors affecting their spatio-temporal distribution.

1. The open-source programming language ‘R’ has become a standard tool in the palaeobiologist’s toolkit. Its popularity within the palaeobiology 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 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 the future plans for the broader palaeoverse project.4. palaeoverse is the first community-driven R package in 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.

1. Fossil occurrence databases are indispensable resources to the palaeontological community, yet present unique data cleaning challenges. Many studies devote significant attention to cleaning fossil occurrence data prior to analysis, but such efforts are typically bespoke and difficult to reproduce. There are also no standardised methods to detect and resolve errors despite the development of an ecosystem of cleaning tools fuelled by the concurrent growth of neontological occurrence databases.2. As fossil occurrence databases continue to increase in size, the demand for standardised, automated and reproducible methods to improve data quality will only grow. Here, we present semi-automated cleaning solutions to address these issues with a new R package fossilbrush. We apply our cleaning protocols to the Paleobiology Database to assess the prevalence of anomalous entries and the efficacy and impact of our methods.3. We find that anomalies may be effectively resolved by comparison against a published compendium of stratigraphic ranges, improving the stratigraphic quality of the data, and through methods which detect outliers in taxon-wise occurrence stratigraphic distributions. Despite this, anomalous entries remain prevalent throughout major clades, with often more than 30% of genera in major fossil groups (e.g. bivalves, echinoderms) displaying stratigraphically suspect occurrence records. 4. Our methods provide a way to flag and resolve anomalous taxonomic data before downstream palaeobiological analysis and may also aid in the automation and targeting of future cleaning efforts. We stress, however, that our methods are semi-automated and are primarily for the detection of potential anomalies for further scrutiny, as full automation should not be a substitute for expert vetting. We note that some of our methods do not rely on external databases for anomaly resolution and so are also applicable to occurrences in neontological databases, expanding the utility of the fossilbrush R package.

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. 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. 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. 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.

Achanarras Quarry, Caithness, Scotland displays a diverse fossil fish fauna which is presumed to have inhabited shallow lacustrine environments present in the Orcadian Basin during the Early to Middle Devonian. While Achanarras Quarry itself exposes deep lacustrine facies, the ecology of their depositional environment remains unknown in stark contrast to the detailed environmental reconstructions available for the lake margin. I report putative arthropod trace fossils from Achanarras Quarry which are tentatively interpreted as having been formed in a deep lake environment. Transport of doomed pioneers from the thriving shallow-water ecosystems by turbidite flows is discussed as possible scenario for their formation. The infrequent and ephemeral intrusions of animals into the deep waters of Lake Orcadie fits the broader narrative of the colonisation of deep lake ecosystems after the Devonian. These interpretations of deep-lacustrine trace fossils from Achanarras, along with their place within the narrative of lake ecosystem evolution, are made cautiously, however, given the paucity of the specimens and the uncertainty surrounding their sedimentary setting.

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