DOI: 10.5061/dryad.1vhhmgr33
title: Data from: Heterogeneous palaeo-ecogeography of brachiopods during the Late Ordovician mass extinction in South China

description: Following the first phase of the Late Ordovician Mass Extinction (LOME),
 the globally distributed Hirnantia brachiopod fauna exhibited homogeneity
 both latitudinally and longitudinally. The uniform global
 paleobiogeography of the Hirnantia Fauna, solely based on occurrence data,
 might obscure its heterogeneous nature during glaciation. In this study,
 leveraging diversity and abundance data from well-sampled collections in
 South China, along with NMDS using the Raup-Crick measure, Network
 Analysis (NA), and abundance models, we unveil the paleo-ecogeography of
 the Hirnantia Fauna for the first time. The distribution of the Hirnantia
 Fauna in South China is categorized into three areas: the deep water area,
 the shallower water area, and the very shallow water area based on NMDS
 and NA. Drastically different benthic assemblages among these areas reveal
 diverse environmental settings, with a rough westward shallower trend and
 a deeper trend extending both northward and southeastward. Analysis of
 species-abundance models for eight well-sampled collections demonstrates
 different best-fitted models, suggesting competitive ecology operates in
 varied contexts despite common BA 3 environmental settings and close
 geographic proximity. While a substantial global sea level falling and
 climate cooling around the Katian-Hirnantian boundary plays important
 roles in the LOME, the paleo-ecogeography of the Hirnantia Fauna in South
 China is predominantly influenced by the expansion of the Cathaysian
 oldland and the Qianzhong uplift. The interval between the two LOME
 phases, marked by kinetic conditions, witnessed heterogeneous thriving of
 the Hirnantia Fauna.
description: There are two datasets: one based on occurrence information and
 the other on abundance data.For the occurrence dataset of Hirnantian
 brachiopod fauna from South China, we aggregated adjacent localities into
 a unified palaeogeographical analysis unit to balance the distribution of
 the occurrence data. Consequently, our analysis involved a total of 22
 distinct units.The abundance data is derived from 9070 specimens collected
 from 8 representative sections of the Hirnantia Fauna.
 We conducted the palaeobiogeographic study using NMDS with PAST
 (version 4.01) and network analysis with Gephi (version 0.10) for the 22
 occurrence data units. Additionally, we used rarefaction analysis with
 PAST (version 4.01) to test the sampling sufficiency of the 8
 representative sections. We also built species-abundance models using R
 programming with the Vegan package to test the abundance models for these
 sections.
description: # Data from: Heterogeneous palaeo-ecogeography of brachiopods during the
 Late Ordovician mass extinction in South China
 [https://doi.org/10.5061/dryad.1vhhmgr33](https://doi.org/10.5061/dryad.1vhhmgr33) There are two datasets files: “Occurrences_data_for_NMDS_and_NA.csv” based on occurrence information and “Abundance_data_for_models.csv” on abundance data. For the occurrence dataset of Hirnantian brachiopod fauna from South China, we aggregated adjacent localities into a unified palaeogeographical analysis unit to balance the distribution of the occurrence data. Consequently, our analysis involved a total of 22 distinct units. The abundance data is derived from 9070 specimens collected from 8 representative sections of the Hirnantia Fauna. ## Description of the data and file structure `Occurrences_data_for_NMDS_and_NA.csv` includes occurrence information in binary data, with palaeogeographic units as rows and brachiopod genera as columns. This dataset involves 41 genera and 22 units. Please note that this is 0-1 data, and when using it, especially for calculating similarity matrices, it is important to choose algorithms appropriate for binary data. `Abundance_data_for_models.csv` contains specimen count information of brachiopod species from 8 selected representative sections, involving a total of 9070 specimens. Relevant abundance model analyses should be performed based on an assessment of sampling sufficiency. It is recommended to use Chao-1 diversity estimation. ## Sharing/Access information n/a ## Code/Software We also built species-abundance models using R programming with the Vegan package to test the abundance models for these sections. The R script uploaded is designed to analyze species abundance data by fitting species abundance models to different collections of data and then plotting the results.