palaeoverse: A community‐driven R package to support palaeobiological analysis

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

Mind the uncertainty: Global plate model choice impacts deep‐time palaeobiological studies

Abstract Global plate models (GPMs) aim to reconstruct the tectonic evolution of the Earth by modelling the motion of the plates and continents through time. These models enable palaeobiologists to study the past distribution of extinct organisms. However, different GPMs exist that vary in their partitioning of the Earth's surface and the modelling of continental motions. Consequently, the preferred use of one GPM will influence palaeogeographic reconstruction of fossil occurrences and any inferred palaeobiological and palaeoclimatic conclusion. Here, using five open‐access GPMs, we reconstruct the palaeogeographic distribution of cell centroids from a global hexagonal grid and quantify palaeogeographic uncertainty across the entire Phanerozoic (540–0 Ma). We measure uncertainty between reconstructed coordinates using two metrics: (1) palaeolatitudinal standard deviation and (2) mean pairwise geodesic distance. Subsequently, we evaluate the impact of GPM choice on palaeoclimatic reconstructions when using fossil occurrence data. To do so, we use two climatically sensitive entities (coral reefs and crocodylomorphs) to infer the palaeolatitudinal extent of subtropical climatic conditions for the last 240 million years. Our results indicate that differences between GPMs increase with the age of reconstruction. Specifically, cell centroids rotated to older intervals show larger differences in palaeolatitude and geographic spread than those rotated to younger intervals. However, high palaeogeographic uncertainty is also observed in younger intervals within tectonically complex regions (i.e. in the vicinity of terrane and plate boundaries). We also show that when using fossil data to infer the distribution of subtropical climatic conditions across the last 240 Ma, estimates vary by 6–7° latitude on average, and up to 24° latitude in extreme cases. Our findings confirm that GPM choice is an important consideration when studying past biogeographic patterns and palaeoclimatic trends. We recommend using GPMs that report true palaeolatitudes (i.e. use a palaeomagnetic reference frame) and incorporating palaeogeographic uncertainty into palaeobiological analyses

palaeoverse: A community‐driven R package to support palaeobiological analysis

Abstract 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