Data and code from: Environmental drivers of wild bee reproductive performance across a South American dryland ecoregion
Data files
Apr 01, 2025 version files 139.89 KB
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Aranda-Rickert_data_Rcode_ProceedingsB.zip
138.34 KB
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README.md
1.55 KB
Abstract
The reproductive performance of wild bees is a key determinant of their population persistence. However, few studies have directly examined the environmental drivers of demographic processes using a geographically broad approach. In this study, we explored how biotic and abiotic factors influence the reproduction of solitary, cavity-nesting bees across the Monte Desert ecoregion in Argentina. Using artificial wood nests and a standardized sampling spanning 2,000 km and 20° of latitude, we related key reproductive metrics—nest establishment, offspring production, and offspring survival—to latitude, climate, and biotic factors (flower abundance, vegetation cover, and brood parasitism). Climate was the most consistent and strongest predictor of bee reproductive performance: warm, humid conditions during the nesting period were associated with reduced nest establishment and offspring survival. Brood parasitism also emerged as a strong driver, significantly reducing offspring survival. Across the Monte Desert's latitudinal gradient, nest establishment peaked at mid-latitudes, while offspring production and survival increased toward higher latitudes. These findings highlight the sensitivity of wild bee reproduction to climatic conditions, particularly during the critical nesting period. Our study advances our understanding of the potential impacts of climate change on wild bees in the Neotropics, where extensive areas are experiencing dramatic land-use changes.
https://doi.org/10.5061/dryad.0gb5mkmcc
Description of the data and file structure
Data and code for Aranda-Rickert et al. 2025: “Environmental Drivers of Wild Bee Reproductive Performance Across a South American Dryland Ecoregion”
Files and variables
File: Aranda-Rickert_data_Rcode_ProceedingsB.zip
Description:
The excel file ‘Aranda-Rickert_bee_data_column_headers’ contains 2 spreadsheets (‘raw_data’ / ‘column_headers’). Spreadsheet ‘raw_data’ contains the dataset with the response variables and the environmental predictors used in this study. Spreadsheet ‘column_headers’ explains each variable.
The csv file ‘Aranda-Rickert_bee_data’ contains the dataset with the response variables and the environmental predictors to run the R scripts.
The R file ‘Aranda-Rickert_R_code’ contains the R scripts with the analyses to reproduce the results in this study.
Missing values are indicated as N/A.
Code/software
R version and list of R packages used for the analyses and plots:
We conducted all analyses with R statistical software, version 4.3.3
We used the gamm4 function from the gamm4 R package version 0.2-6 (Wood & Scheipl, 2020) to perform the GAMMs.
We ussed the glmer function from the lme4 R package version 1.1-34 (Bates et al., 2015) to perform the GLMMs.
We drew plots with ggplot2 R package version 0.9.3.1 (Wickham, 2016)