Occurrences of annual killifish (Rivulidae) in different bioregionalizations across the Neotropical domain
Data files
Jan 14, 2025 version files 218.30 KB
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Appendix_S2.zip
214.89 KB
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README.md
3.41 KB
Abstract
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 (> 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.
README: Occurrences of annual killifish (Cyprinodontiformes: Rivulidae) in different bioregionalizations across the Neotropical domain
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.
- 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 |
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 |
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
Methods
Occurrence data
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.
Bioregionalization frameworks
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).