Harriet B. Drage

Integrating taxonomic data across heterogeneous biological databases remains a major challenge in biodiversity research due to non-standardized nomenclature, incomplete synonym annotation, and inconsistencies in taxonomic hierarchies. These issues limit interoperability between key resources such as the Global Biodiversity Information Facility (GBIF), the National Center for Biotechnology Information (NCBI), and citizen science platforms such as iNaturalist. Here, we present TaxonMatch, a scalable and reproducible framework for taxonomic reconciliation and cross-database integration. The workflow combines string-based candidate generation using TF–IDF vectorization, supervised machine learning for match classification, and lineage-aware synonym resolution to align taxonomic entities across multiple sources. By integrating both declared and implicit equivalences, TaxonMatch resolves typographical variation, synonymy, and structural inconsistencies in taxonomic data. The framework produces a unified taxonomic structure in which equivalent entities are reconciled while preserving source-specific identifiers, provenance information, and hierarchical relationships. We evaluate its robustness across multiple classifiers and demonstrate its effectiveness in resolving ambiguous taxonomic cases that are not handled by traditional matching approaches. We illustrate the applicability of TaxonMatch through three use cases: the construction of a unified arthropod taxonomy integrating GBIF, NCBI, and iNaturalist data; the identification of closest extant relatives of fossil taxa with molecular information; and the integration of genomic resources with conservation data from the IUCN Red List. These applications highlight the ability of the workflow to support the integration of ecological, genomic, and paleontological datasets. TaxonMatch provides a flexible and generalizable solution for taxonomic data integration, enabling the construction of coherent and interoperable biodiversity datasets for downstream analyses in ecology, evolution, and conservation biology.

Arthropods must periodically moult their exoskeleton to permit growth, a conserved developmental process whose morphological and behavioural execution varies widely among lineages. Horseshoe crabs (Limulidae) are members of Xiphosura, a chelicerate lineage with a fossil record extending as far back as the Ordovician and provide a valuable comparative framework for studying the evolution of moulting strategies in Arthropoda. Despite their importance, detailed morphological characterization of moulting in horseshoe crabs remains scarce, limiting developmental studies and broader comparative analyses. Here, we provide a detailed morphological characterization of the moulting process in the Atlantic horseshoe crab Limulus polyphemus . Morphological changes in specific anatomical structures, including the anterior margin of the prosoma, lateral spines and dorsal spinous process of the opisthosoma, were observed during the moulting process. By tracking these morphological markers, such as retraction of the epidermis from the cuticle and degree of corrugation of the epidermis, we were able to identify individuals in the early and late pre-moult stage, predict the onset of ecdysis, and distinguish post-moult and intermoult stages. We compare ecdysis patterns in L. polyphemus with other arthropod taxa, both extant and fossil. We find that, despite differences in behavioural execution, ecdysis in L. polyphemus shares features with other chelicerates, and that both phylogenetic signal and convergent patterns are evident across Arthropoda. This study offers a robust, non-invasive method for determining moult stages in juvenile horseshoe crabs and provides insights into the diversity and constraints of ecdysis in Arthropoda.

In 2025, with the contract with SpringerOpen running out at the end of the year, the Kommission for the SJP and the Swiss Geological Society decided to start collaborating from 2026 onwards with a publisher, where processes are more streamlined to the needs of the SJP. This will allow us to satisfy our quality standards and improve the overall quality of the journal in the future. Negotiations with Pensoft Publishers started in July 2025 and contracts were signed in September 2025. Together with the SJP, the Swiss Journal of Geosciences, also affiliated with the Swiss Geological Society, migrated from SpringerOpen to Pensoft Publishers.

In 2025, with the contract with SpringerOpen running out at the end of the year, the Kommission for the SJP and the Swiss Geological Society decided to start collaborating from 2026 onwards with a publisher, where processes are more streamlined to the needs of the SJP. This will allow us to satisfy our quality standards and improve the overall quality of the journal in the future. Negotiations with Pensoft Publishers started in July 2025 and contracts were signed in September 2025. Together with the SJP, the Swiss Journal of Geosciences, also affiliated with the Swiss Geological Society, migrated from SpringerOpen to Pensoft Publishers.

Large datasets of fossil occurrences, often downloaded from online community‐maintained databases, are a vital resource for understanding broad‐scale evolutionary patterns, such as how biodiversity has changed through time and space. Such datasets, however, are not infallible and must be ‘cleaned’ of inaccurate, incomplete, or duplicate data prior to analysis. Researchers must decide upon the extent, feasibility, and value of data cleaning steps to perform, but while guides are available for working with neontological occurrences, there is currently no clear procedure for palaeobiological data despite its unique attributes. Here, we outline ten rules that aim to aid the process of cleaning fossil occurrence data for downstream analysis. These rules cover the major steps involved in processing data prior to analysis, including project setup, data exploration and cleaning, and finalizing and reporting work. We provide accompanying examples and a vignette covering the entire data cleaning process to demonstrate the application of each rule. We believe that these rules will serve as a useful guideline to support data cleaning and foster new standards for the palaeobiological community.

1 Trilobite cephala show high disparity owing to their supporting of key functional ecological structures, such as sensory and feeding structures, and those enabling important behaviours like enrollment and exoskeleton moulting. Previous studies analysed associations between cephalic morphometry, trends through time and with diversity, and these behaviours. However, no studies have yet quantitatively compared the importance of these different varied factors on cephalic morphometry. Here, we explore the association between trilobite cephalic morphometry and taxonomic variables, moulting behaviour, and facial suture type in Principal Components Analysis morphospace, and assess whether these variables can predict cephalic morphometry using Linear Discriminant Analyses. We employed Linear Mixed-Effects Models (LMMs) to quantify the hierarchical importance of these variables for determining cephalic disparity. The dataset used comprises cephalon outlines for 762 species of trilobites from across the globe and through the entire Palaeozoic. We found that variation in cephalic morphometry is not clearly associated with moulting behaviour, nor is moulting behaviour linked to facial suture type. Trilobite moulting behaviour is evidently too phenotypically plastic, and/or preservationally impacted, to produce clear signals across broad datasets. Results demonstrate the utility of LMMs for palaeontological datasets; we found that family-level assignment overall well explains cephalic morphometry, more so than order-level assignment which shows significant overlap in morphospace. Geological Period, facial suture type, and moulting behaviour had little impact on cephalic morphometry. We thereby demonstrate that trilobite cephalic outline morphometry is generally in accordance with trilobite family-level systematics and highlight the use of LMMs for interrogating broad-scale fossil morphological data.

Large datasets of fossil occurrences, often downloaded from online community-maintained databases, are a vital resource for understanding broad-scale evolutionary patterns, such as how biodiversity has changed through time and space. Such datasets, however, are not infallible and must be ‘cleaned’ of inaccurate, incomplete, or duplicate data prior to analysis. Researchers must decide upon the extent, feasibility, and value of data cleaning steps to perform, but while guides are available for working with neontological occurrences, there is currently no clear procedure for palaeobiological data despite its unique attributes. Here, we outline ten rules that aim to aid the process of cleaning fossil occurrence data for downstream analysis. These rules cover the major steps involved in processing data prior to analysis, including project setup, data exploration and cleaning, and finalising and reporting work. We provide accompanying examples and a vignette covering the entire data cleaning process to demonstrate the application of each rule. We believe that these rules will serve as a useful guideline to support data cleaning and foster new standards for the palaeobiological community.

Open Palaeontology is a new diamond open access (DOA) journal for publishing academic research on all aspects of palaeontology. Open Palaeontology, or OPal, is founded on the principles of academic rigour, accessibility, transparency, and innovation. As a diamond open access (DOA) online-only journal, Open Palaeontology is free for authors to publish in and free for readers to access. Open Palaeontology facilitates a step-wise and flexible approach to scholarly publishing that is intended to increase transparency throughout the academic research process with our Hypotheticals, Research Protocols, and Research Articles formats. We also encourage the submission of multimedia articles where research is presented in audio and/or visual formats. Our commitment to transparency includes an open peer review process, with signed reviewer reports published alongside accepted articles. We hope that Open Palaeontology will encourage different thinking about academic publishing, and we intend to continue to incorporate new ideas into our publication model. Open Palaeontology is open for submissions and we look forward to receiving your work for consideration for publication.

Trilobite cephalic shape disparity varied through geological time and was integral to their ecological niche diversity, and so is widely used for taxonomic assignments. To fully appreciate trilobite cephalic evolution, we must understand how this disparity varies and the factors responsible. We explore trilobite cephalic disparity using a dataset of 983 cephalon outlines of c. 520 species, analysing the associations between cephalic morphometry and taxonomic assignment and geological Period. Elliptical Fourier transformation visualised as a Principal Components Analysis suggests significant differences in morphospace occupation and in disparity measures between the groups. Cephalic shape disparity peaks in the Ordovician and Devonian. The Cambrian–Ordovician expansion of morphospace occupation reflects radiations to new niches, with all trilobite orders established by the late Ordovician. In comparison, the Silurian–Devonian expansion seems solely a result of within-niche diversification. Linear Discriminant Analyses cross-validation, average cephalon shapes, and centroid distances demonstrate that, except for Harpida and the Cambrian and Ordovician Periods, order and geological Period cannot be robustly predicted for an unknown trilobite. Further, k-means clustering analyses suggest the total dataset naturally subdivides into only seven groups that do not correspond with taxonomy, though k-means clusters do decrease in number through the Palaeozoic, aligning with findings of decreasing disparity.