DOI: 10.5061/dryad.zpc866tjz
title: Occurrences of annual killifish (Rivulidae) in different bioregionalizations across the Neotropical domain

description: Aim Bioregionalization frameworks represent unique assemblages of species
 resulting from geographic isolation and environmental heterogeneity.
 Understanding how different bioregionalizations capture community
 compositional variation is crucial, as underlying patterns and processes
 are scale-dependent. This study aims to (1) explore the underlying
 ecological processes through the decomposition of beta diversity (turnover
 and nestedness); (2) identify which bioregionalization framework offers
 the optimal spatial granularity for distinguishing between communities;
 and (3) evaluate the effective number of compositionally distinct areas.
 Location Neotropical domain Taxon Rivulidae - annual species Methods
 Presence-absence data of fish species were analyzed using pairwise
 β-diversity and hierarchical clustering methods (UPGMA) and compared with
 14 comprehensive bioregionalization frameworks, including terrestrial
 ecoregions (TEOW), freshwater ecoregions (FEOW), Neotropical provinces,
 and watersheds (HydroBasins). Results The study revealed that (1) turnover
 is the dominant component of β-diversity, surpassing nestedness across all
 bioregionalization frameworks; (2) turnover increases non-linearly as
 regionalization area decreases, with a threshold identified beyond which
 further area reduction does not significantly increase turnover; and (3)
 the optimal spatial granularity for bioregionalization is achieved at
 smaller watershed scales (146–414 km²), where turnover is maximized and
 the optimal number of bioregions (&gt; 180) is identified. Main
 Conclusions Turnover patterns are linked to factors such as high endemism,
 low dispersal capacity, and the significant isolation of temporary
 wetlands. The scale-dependence of β-diversity is influenced not only by
 the area of bioregionalizations but also by the underlying design of these
 units, such as those based on hydrogeomorphological features (HydroBasins)
 or taxon distribution patterns (FEOW, TEOW). Finer spatial scales are more
 effective for assessing biodiversity patterns for endemic taxa and in
 habitats with low connectivity. These findings can enhance the
 understanding of how bioregionalization frameworks reflect species
 compositional variation, with important implications for interpreting
 ecological patterns and developing scale-dependent conservation
 strategies.
description: <strong>Occurrence data</strong>
 Occurrence records of annual killifish (Rivulidae:
 Cyprinodontiformes) were exhaustively compiled between January 2021 and
 September 2023 from various sources, including articles, books, and public
 digital repositories that aggregate information from collections/museums,
 such as the Global Biodiversity Information Facility (GBIF, gbif.org),
 Brazilian Biodiversity Information System (SIBBR, sibbr.gov.br),
 SpeciesLink (splink.org.br), and Biodiversity Extinction Risk Assessment
 System (SALVE, salve.icmbio.gov.br). To include occurrences in our
 database, we applied the following filters: (i) only records identified at
 the species level (sp., cf. or aff. excluded) and (ii) geographic
 coordinates consistent with distribution information available in the
 literature. Species distributions were validated by plotting individual
 species maps and comparing them with those published in the primary
 taxonomic literature. For species with unavailable/unknown geographic
 coordinates, we estimated approximate locations based on georeferenced
 maps or descriptions of type localities. All occurrences used in this
 study were compiled during the respective rainy seasons in the areas where
 the species occur. Our final database includes 1,635 occurrence records,
 encompassing all 261 annual species (41 genera) currently recognized in
 the Neotropical. <strong>Bioregionalization
 frameworks</strong> Species occurrence data were
 overlaid with 14 different bioregionalization frameworks: terrestrial
 ecoregions (TEOW; Olson et al., 2001), freshwater ecoregions (FEOW, Abell
 et al., 2008), Neotropical provinces (Morrone et al., 2022), and eleven
 (11) different levels of hierarchically nested sub-basins (HydroBasins;
 Lehner & Grill, 2013). This results in presence or absence
 matrices of species for the 14 different bioregionalizations (Figure 1),
 with mean area and number of grains/levels ranging from 3,251,927 to 146
 km², and 6 to 767 levels, respectively (Table 1). These
 bioregionalizations were chosen for different reasons. Watersheds
 represent natural boundaries that can significantly affect the
 distribution and endemism of fish. Freshwater ecoregions were specifically
 delineated based on the distribution of fish and other aquatic organisms
 (Abell et al., 2008). Terrestrial ecoregions provide a complementary
 context for understanding the interaction between terrestrial and aquatic
 habitats, as annual fishes occupy temporary wetlands, which are
 essentially terrestrial environments during the dry period. Finally, the
 neotropical provinces offer a broad and integrative scale that encompasses
 large ecological provinces with distinct climatic and biogeographic
 characteristics (Morrone et al., 2022). The overlay of occurrence data and
 vector layers with the boundaries of the regionalizations was performed in
 QGIS software version 3.32.3 Lima (QGIS Development Team, 2024).
description: # Occurrences of annual killifish (Cyprinodontiformes: Rivulidae) in
 different bioregionalizations across the Neotropical domain
 [https://doi.org/10.5061/dryad.zpc866tjz](https://doi.org/10.5061/dryad.zpc866tjz) ## Description of the data and file structure ## Submitted Files * **Metadata.xlsx**: Contains occurrence data for annual killifish species across various bioregionalizations in the Neotropical domain. * **BL2-12.txt**: Includes species presence or absence data across different bioregionalization schemes. * **Appendix S2 - R scripts.R**: R script used for data processing and analysis. ## Data Descriptions ### **Metadata.xlsx** * **Order**: Taxonomic order of the species. * **Family**: Taxonomic family of the species. * **Genus**: Taxonomic genus of the species. * **Species (original name)**: Species name according to the consulted source. * **Species (updated name)**: Species name updated according to [Eschmeyer's Catalog of Fishes](https://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp). * **Threat**: Species threat status according to the IUCN Red List or the national assessment of the country of occurrence. * **Country**: Country where the occurrence record was documented. * **Latitude**: Latitude coordinate of the occurrence record (decimal degrees). * **Longitude**: Longitude coordinate of the occurrence record (decimal degrees). * **Source**: Type of consulted source for the occurrence record. * **Reference**: Full reference of the occurrence record. ### **BL2-12.txt** Contains presence (1) or absence (0) data for killifish species across various bioregionalization schemes, with species organized in columns and bioregionalizations in rows. The first column of the '.txt' files presents the names of the bioregionalizations or the codes according to the primary literature. The bioregionalization codes and references are as follows: | **Code** | **Name** | **Reference** | | :------- | :--------------------- | :------------------------------------------------------------------------------------------------------------------------ | | PRO | Provinces | Morrone, J.J. et al. (2022). *An Acad Bras Ciênc*, 94(1), E20211167. [DOI](https://doi.org/10.1590/0001-3765202220211167) | | TEOW | Terrestrial Ecoregions | Olson, D.M. et al. (2001). *BioScience*, 51(11), 933-938. | | FEOW | Freshwater Ecoregions | Abell, R. et al. (2008). *BioScience*, 58(5), 403-414. | | BL2–BL12 | Basin Levels 2–12 | Lehner, B., & Grill, G. (2013). *Hydrological Processes*, 27(15), 2171–2186. [DOI](https://doi.org/10.1002/hyp.9740) | ### **Appendix S2 - R scripts**.R R script for data cleaning, processing, and statistical analyses of species occurrences across bioregions. ## Data Usage All data are released under the CC0 license, allowing free reuse, distribution, and modification without restrictions. Users are encouraged to cite the associated references where applicable. ## Contact For questions or clarifications, please contact: **Gustavo Henrique Soares Guedes** Email: [gustavohsg@outlook.com](mailto:gustavohsg@outlook.com)