Global biogeography of living brachiopods: Bioregionalization patterns and possible controls

Abstract

The global distribution patterns of 14918 geo-referenced occurrences from 394 living brachiopod species were mapped in 5° grid cells, which enabled the visualization and delineation of distinct bioregions and biodiversity hotspots. Further investigation using cluster and network analyses allowed us to propose the first systematically and quantitatively recognized global bioregionalization framework for living brachiopods, consisting of five bioregions and thirteen bioprovinces. No single environmental or ecological variable is accountable for the newly proposed global bioregionalization patterns of living brachiopods. Instead, the combined effects of large-scale ocean gyres, climatic zonation as well as some geohistorical factors (e.g., formation of land bridges and geological recent closure of ancient seaways) are considered as the main drivers at the global scale. At the regional scale, however, the faunal composition, diversity and biogeographical differentiation appear to be mainly controlled by seawater temperature variation, regional ocean currents and coastal upwelling systems.

Variation of shell ornamentation with latitude and water depth—A case study using living brachiopods

“…For this study, an extended database with shell ornamentation‐enriched information was built based on an earlier version of the global database built for living brachiopods (Ye et al, 2021). In brief, in addition to the well‐defined basic information of living brachiopods (such as taxonomy, geo‐coordinated, and water depth distribution), various attributes of shell ornamentation of corresponding species have been added to the new database, sourced primarily from the published literature by referring to a range of information including text descriptions and illustrations (figures/plates of photographed brachiopod images).…”

“…The identity and taxonomy of the species included were initially based on the classification on BrachNet (http://paleopolis.rediris.es/BrachNet/) and further verified by one of the authors (M.A.B.). The data acquisition procedures and the exclusion of doubtful records were described in more detail by Ye et al (2021). Finally, a total of 14,312 geo‐referenced occurrences, including 342 species of living brachiopods with adequate ornamentation information (i.e., at least with ornamentation either described in the text or illustrated in the figures) in our final dataset, were accepted and used for further analysis.…”

“…Global map showing the variation of shell ornamentation index (expressed by OI) from different bioprovinces (Ye et al, 2021). Different colors from the pie chart indicate the proportion of OI (dark gray: with ornamentation, light gray: smooth).…”

A natural history of networks: Modeling higher-order interactions in geohistorical data

“…Research employing network-based approaches to describe biogeography in the fossil record is overwhelmingly focused on describing one-step dynamics (Markov time = 1) in relatively small bipartite networks derived from the relatively limited fossil data (e.g., Penn-Clarke and Harper, 2020; Ye et al, 2021), to reveal continental to global scale marine bioregions. Although first-order network representations of fossil occurrences have been shown to capture a biogeographic signal at some geological stages in the Phanerozoic (Rojas et al 2017; Kocsis et al 2018), these studies are unable to identify transition zones, provide a single-scale description of the bioregions and obscure larger-scale patterns.…”

“…Although network science provides methods for statistical analysis and machine learning of relational data (Brandes et al 2013; Lambiotte et al 2019), paleobiologists often describe network analysis as a tool for visualization and qualitative assessment (Huang et al 2016; Penn-Clarke and Harper 2020; Ye et al 2021). While network visualization techniques are powerful tools for exploratory data analysis (Perri and Scholtes 2020), this misrepresentation reflects a need to adapt research practices in quantitative paleobiology based on theoretical and methodological advances of network science.…”