William Gearty

As practitioners of a historical science, paleontologists and geoscientists are well versed in the idea that the ability to understand and to anticipate the future relies upon our collective knowledge of the past. Despite this understanding, the fundamental role that the history of paleontology and the geosciences plays in shaping the structure and culture of our disciplines is seldom recognized and therefore not acted upon sufficiently. Here, we present a brief review of the history of paleontology and geology in Western countries, with a particular focus on North America since the 1800s. Western paleontology and geology are intertwined with systematic practices of exclusion, oppression, and erasure that arose from their direct participation in the extraction of geological and biological resources at the expense of Black, Indigenous, and People of Color (BIPOC). Our collective failure to acknowledge this history hinders our ability to address these issues meaningfully and systemically in present-day educational, academic, and professional settings. By discussing these issues and suggesting some ways forward, we intend to promote a deeper reflection upon our collective history and a broader conversation surrounding racism, colonialism, and exclusion within our scientific communities. Ultimately, it is necessary to listen to members of the communities most impacted by these issues to create actionable steps forward while holding ourselves accountable for the past.

Diet and body mass are inextricably linked in vertebrates: while herbivores and carnivores have converged on much larger sizes, invertivores and omnivores are, on average, much smaller, leading to a roughly U-shaped relationship between body size and trophic guild. Although this U-shaped trophic-size structure is well documented in extant terrestrial mammals, whether this pattern manifests across diverse vertebrate clades and biomes is unknown. Moreover, emergence of the U-shape over geological time and future persistence are unknown. Here we compiled a comprehensive dataset of diet and body size spanning several vertebrate classes and show that the U-shaped pattern is taxonomically and biogeographically universal in modern vertebrate groups, except for marine mammals and seabirds. We further found that, for terrestrial mammals, this U-shape emerged by the Palaeocene and has thus persisted for at least 66 million years. Yet disruption of this fundamental trophic-size structure in mammals appears likely in the next century, based on projected extinctions. Actions to prevent declines in the largest animals will sustain the functioning of Earth’s wild ecosystems and biomass energy distributions that have persisted through deep time.

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.

Effective data visualisation is vital for data exploration, analysis and communication in research. In ecology and evolutionary biology, data are often associated with various taxonomic entities. Graphics of organisms associated with these taxa are valuable for framing results within a broader biological context. However, acquiring and using such resources can be challenging due to availability and licensing constraints. The PhyloPic database solves many of these issues by making organism silhouettes freely available. Tools that integrate this database with existing research workflows are needed to remove hurdles associated with data visualisation in the biological sciences. Here, we introduce rphylopic, an R package for fetching, transforming and visualising silhouettes of organisms from the PhyloPic database. In addition to making over 8000 organism silhouettes available within the R programming language, rphylopic empowers users to modify the appearance of these silhouettes for ultimate customisability when coding production–quality visualisations in both base R and ggplot2 workflows. In this work, we provide details about how the package can be installed, its implementation and potential use cases. For the latter, we showcase three examples across the ecology and evolutionary biology spectrum. Our hope is that rphylopic will make it easier for biologists to develop more accessible and engaging data visualisations by making external resources readily accessible, customisable and usable within R. In turn, by integrating into existing workflows, rphylopic helps to ensure that science is reproducible and accessible.