Where water meets rock: Ecological niches and diversity hotspots of hygropetric beetles in the Neotropics
Data files
Dec 17, 2025 version files 2.27 MB
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raw_records_compiled.xlsx
57.59 KB
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README.md
4.85 KB
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script.R
18.47 KB
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Supplementary_material_S1.pdf
2.18 MB
Abstract
Freshwater biodiversity is structured by climate and topography controls on moisture at fine scales. Hygropetric habitats (thin water films over rock) remain underrepresented in macroecology. We tested whether major Neotropical areas occupy distinct environmental space, whether hygropetric beetle genera show low niche overlap, and quantified richness in mountainous and topographically steep regions. We assembled 144 species in 15 genera across seven families from taxonomic literature, GBIF, and targeted field sampling at 97 waterfalls and streams in the Brazilian Shield, including 66 new occurrences. Species distribution models, using five algorithms and predictors that included bioclimatic variables, elevation, compound topographic index, and profile curvature, were cross-validated. Multivariate analyses compared environmental space among provinces, and niche overlap metrics assessed intergeneric segregation. Major Neotropical areas occupied significantly different environmental space, and genera formed ecologically distinct groups with low niche overlap, indicating environmental partitioning and some convergence onto similar moisture and energy regimes across disjunct regions. Mountainous areas were richness hotspots, with the Brazilian Shield representing 40% of species richness, the Guiana Shield 33%, the Andes 19%, and the Northern Neotropics 8%. Integrating macroecology, niche modelling, and new field data yields a scalable approach to forecasting hygropetric biodiversity. It closes key knowledge gaps for Neotropical beetles and improves planning for freshwater biodiversity conservation.
Dataset DOI: 10.5061/dryad.dv41ns2bw
Description of the data and file structure
This dataset accompanies the study Where water meets rock: Ecological niches and diversity hotspots of hygropetric beetles in the Neotropics and documents the environmental predictors used, model evaluation thresholds, and compiled occurrence records for hygropetric beetle taxa across the Neotropics. Data were assembled from public environmental layers and curated species‑occurrence records (GBIF and taxonomic literature) to support species distribution modelling (SDM) and downstream diversity analyses. The occurrence table includes vetted geographic coordinates and a per‑record “Filter” flag indicating whether each record was retained ("Used") or excluded after quality control. Environmental variables include bioclimatic, elevation, and terrain‑derived layers.
Files and variables
File: Supplementary_material_S1.pdf
Description: master document listing environmental variables and their sources; model threshold metrics and values by taxon; and the compiled occurrence records table with provenance and curation flags.
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Table S2 – Sources and coordinates for raw occurrence records (post‑vetting status indicated in Filter column): raw_records_compiled.xls.x
Note on derived occurrence files:
All tab-delimited.txtfiles containing occurrence records used in the analyses are exports derived from the master spreadsheetraw_records_compiled.xlsx(Table S2 in Supplementary_material_S1.pdf). In particular, the following files are filtered or restructured versions of this main table:dados_full2.1.txt– occurrence table used for calculating species richness by genus and region (Section 2 of the analysis script);hygropetric_occurrences_genus.txt– occurrence table aggregated by genus, used for macro-area richness analyses (Section 3 of the analysis script);dados_full2.txt– occurrence table combined with PCA scores for niche overlap and environmental differentiation analyses (Sections 4–7 of the analysis script).
Occurrence records (Table S2)
Columns and meanings:
Genus– Genus namespecies– Species epithetfamily– Family assignment (e.g., Hydrophilidae, Dytiscidae, Hydraenidae, Torridincolidae)source1– High‑level source (e.g.,Gbif)source– Specific provenance (e.g., “article taxonomy”, “New record”, author/year)Filter– Curation status after vetting (Used= retained;Exclued= excluded as listed in S1)longitude,latitude– Geographic coordinates (decimal degrees)localization– Broad region tag (e.g., Andes, Guiana Shield, Brazilian Shield, North Neotropic)
Coordinate system: Datum WGS84.
Environmental predictors (rasters)
Climate variables (WorldClim v2.1):
BIO1– Annual Mean Temperature (0.1 °C)BIO2– Mean Diurnal Range (mean of monthly (max temp − min temp)) (0.1 °C)BIO3– Isothermality (BIO2/BIO7 × 100) (unitless; % scale)BIO4– Temperature Seasonality (standard deviation × 100) (unitless; % scale)BIO5– Max Temperature of Warmest Month (0.1 °C)BIO6– Min Temperature of Coldest Month (0.1 °C)BIO7– Temperature Annual Range (BIO5 − BIO6) (0.1 °C)BIO8– Mean Temperature of Wettest Quarter (0.1 °C)BIO9– Mean Temperature of Driest Quarter (0.1 °C)BIO10– Mean Temperature of Warmest Quarter (0.1 °C)BIO11– Mean Temperature of Coldest Quarter (0.1 °C)BIO12– Annual Precipitation (mm)BIO13– Precipitation of Wettest Month (mm)BIO14– Precipitation of Driest Month (mm)BIO15– Precipitation Seasonality (coefficient of variation) (%)BIO16– Precipitation of Wettest Quarter (mm)BIO17– Precipitation of Driest Quarter (mm)BIO18– Precipitation of Warmest Quarter (mm)BIO19– Precipitation of Coldest Quarter (mm)
Physiographic variables:
Elevation– digital elevation model (WorldClim v2.1) (m a.s.l.)CTI– Compound Topographic Index (terrain wetness index) (radians per metre; rad/m)Pcurv– Profile curvature (terrain curvature along slope) (radians per metre; rad/m)
Access information
We confirm that the dataset, in the form submitted to Dryad, is compatible with Dryad’s requirements. The package consists of (i) occurrence records generated by our team (new records) and (ii) harmonized occurrence metadata compiled from openly accessible sources. No copyrighted material or third-party content under restrictive licenses is redistributed in this submission.