DOI: 10.5061/dryad.qnk98sfs7
title: Ecological and evolutionary drivers of stingless bee honey variation at the global scale

description: Stingless bee honey (SBH) is a prime natural product consumed and used for
 diverse medicinal and traditional purposes by local communities across the
 (sub-)tropics. The drivers of its compositional variation within and among
 species remain poorly understood, although this could inform broader and
 less explored eco-evolutionary theories. In our study, we aimed to
 disentangle the roles of different drivers of SBH compositional variation
 at both continental and global scales. Using a comparative approach
 involving parallel analyses of honeys produced by Apis mellifera as
 reference points, we specifically aimed to characterize the relative
 importance of SBH variation in relation to stingless bee species and
 evolutionary history, environmental conditions and biogeography. We
 collected and analysed 100 honey samples from A. mellifera around the
 world and 150 samples from twenty-three genera of stingless bees equally
 distributed in the Afrotropics (n = 50), the Neotropics (n = 50) and the
 Indo-Malayan region/Oceania (n = 50). We performed honey profiling using
 H1-NMR spectroscopy to quantify 36 compounds grouped into five categories
 : sugars, organic acids, amino acids, fermentation markers and
 anti-microbial compounds. Our results showed a clear differentiation
 between the chemical composition and functional diversity of A. mellifera
 and stingless bee honeys, mainly due to the production of a range of
 bioproducts during sugar fermentation. The study of compositional
 variation of stingless bee honey showed that the role of ecological and
 evolutionary drivers and their joint effects varied within each tropical
 region, preventing the identification of a clear continental, phylogenetic
 or ecological pattern. Additionally, a significant part of the variation
 remained unexplained, presumably reflecting the various natural factors
 and human colony management that can affect honey properties. We provide
 the first global and comprehensive characterisation of stingless bee honey
 composition, a prerequisite for defining and accepting SBH in the
 different Codex Alimentarius. The chemical complexity of this product
 highlighted in this study requires either broad international standards or
 precise local quality labels. We also highlight the need for more
 interdisciplinary ethnographic studies on non-food uses of honeys, and to
 encourage trans-sectoral research adopting a holistic approach to
 investigate stingless bee honey characteristics.
description: Honey profiling by 1H‑NMR spectroscopy To characterize the
 compounds and properties of our honey samples, we used H1 Nuclear Magnetic
 Resonance spectroscopy (hereafter H1-NMR spectroscopy), a state-of-the-art
 analytical technique increasingly used alongside chemometrics statistical
 approaches for the qualitative and quantitative control of honeys, as well
 as to assess the botanical origin of honeys and to quantify their major
 constituting compounds (Schievano et al., 2012; Ohmenhaeuser et al.,
 2013). H1-NMR spectroscopy was carried out on all 240 samples described
 above at the laboratories of Quality Services International GmbH (QSI,
 Bremen, Germany) following the method described in Noiset et al, 2022. We
 quantified 36 compounds grouped in five categories : sugars (n=10),
 organic acids (n=3), amino acids (n=8), fermentation markers (i.e., all
 the compounds involved in sugar transformation trough alcoholic, acetic
 and lactic fermentation; n=10) and anti-microbial compounds (n=5)
 (Supplementary Table 3). Another set of physicochemical data of honey
 samples of Apis mellifera (n = 10) from Mexico analysed according to the
 protocol described previously at the QSI laboratories were pooled with our
 dataset of 90 Apis spp. samples; this provided a better balance between
 the number of honey bee and stingless bee samples analysed in this study.
 Statistical analyses All the statistical analyses presented here were
 performed in RStudio for R. We combined multivariate and model-based
 approach using R packages that are listed in the Scripts directory and
 produce plots that can be found in the Figure directory.
description: # Ecological and evolutionary drivers of stingless bee honey variation at
 the global scale ## Dataset overview This README outlines the data files,
 scripts, and figures used in the analysis, allowing for replication of
 results and further exploration. In this study, we aimed to disentangle
 the roles of evolutionary and environmental drivers of SBH compositional
 variation using a sampling design that combines honey profiling by H1-NMR
 spectroscopy with the collection of honeys from honey bees and stingless
 bees. The main dataset includes the compositional profiles of 240 honeys
 quantified by Quality Services International GmbH (QSI, Bremen, Germany)
 following the method described in Noiset et al. (2022; see below).
 **Corresponding author information** ``` Name: Pierre Noiset ORCID:
 https://orcid.org/0000-0003-0141-6051 Affiliation: Agroecology Lab,
 Université Libre de Bruxelles, Belgium email: pierre.noiset@ulb.be ```
 **Related publication** ``` Noiset, P., Cabirol, N., Rojas-Oropeza, M.,
 Warrit, N., Nkoba, K., & Vereecken, N. J. 2022. Honey compositional
 convergence and the parallel domestication of social bees. Scientific
 Reports, 12(1), 18280. https://doi.org/10.1038/s41598-022-23310-w ```
 **Funding information** ``` TThis work was supported by the Fonds National
 de la Recherche Scientifique (F.R.S-FNRS, T.0255.20), the Fonds David and
 Alice Van Buuren & Fondation Jaumotte-Demoulin. ``` ### DESCRIPTION OF
 DIRECTORIES AND FILES The repository is organized into the following
 subdirectories: /data: Contains the primary data used in the analysis,
 including metadata and compound identifiers. /scripts: Contains R scripts
 necessary for reproducing the analysis. /figures: Contains all main text
 and supplementary figures referenced in the manuscript.
 ***Sub-directories*** ### 1.Data Data sub-directory include 3 files and 2
 compressed directory : * Data_Global_EcoEvo_Honey.csv (Main dataset) *
 Chemodiv_package_Compounds.csv * SBphylo.con * Map.zip *
 Environmental_variables.zip **Data_Global_EcoEvo_Honey.csv** This excel
 file is the main dataset produced in our study. It contains the metadata
 of each honey samples associated with the quantification data for 36
 compounds by H1-NMR spectroscopy. The compounds were grouped in five
 categories : sugars (n=10), organic acids (n=3), amino acids (n=8),
 fermentation markers (i.e., all the compounds involved in sugar
 transformation trough alcoholic, acetic and lactic fermentation; n=10) and
 anti-microbial compounds (n=5). The following columns are included: *
 Index : Index number attributed to each sample, used in random forest
 analysis * LABEL : Unique label associated with NMR spectra  *
 Continent/Country/Region/site: Geographic location of the sample. *
 Lat/long : Geographic coordinates of the samples * Genus : Accepted Genus
 name of the bee associated with the sample * Species : AcceptedSpecies
 name of the bee associated with the sample * Compound names : | **Sugars
 (g/100g)** | **Organic acids (mg/kg)** | **Amino acids (mg/kg)** |
 **Fermentation markers (mg/kg)** | **Anti-microbial compounds (mg/kg)** |
 | | | | :------------------ | :------------------------ |
 :---------------------- | :------------------------------- |
 :----------------------------------- | -------------- | ------------- |
 ------------------- | | Fructose | Melezitose | Citric acid | Alanine |
 Valine | 2,3-butanediol | Lactic acid | Dihydroxyacetone | | Glucose |
 Maltotriose | Malic Acid | Aspartic acid | Tyrosine | 5-HMF | Formic acid
 | Methylglyoxal | | Sucrose | Gentiobiose | Quinic acid | Glutamine |
 Phenylalanine | Acetic acid | Fumaric acid | 3-phenyllactic acid | |
 Turanose | Raffinose |   | Leucine |   | Acetoin | Pyruvic acid |
 Kynurenic acid | | Maltose | Mannose |   | Proline |   | Ethanol |
 Succinic acid | Shikimic acid | **Chemodiv_package_Compounds.csv** This
 dataset contains SMILES and InChIKey PubChem identifiers for each
 quantified compound. SMILES and  are chemical identifiers that are easily
 obtained for each compound by searching for compounds in PubChem. They
 were used in the `chemodiv` R package (version (0.3.0); Petrén et al.,
 2023). for analysing phytochemical data. This package includes a number of
 functions that makes it straightforward to quantify and visualize
 phytochemical diversity and dissimilarity for any type of phytochemical
 samples. The following columns are included :  * Compound name * SMILE
 identifier * InChiKey identifier **SBphylo.con** This .con file was edited
 based on the stingless bee phylogeny at the genus level established by
 Rasmussen et Cameron (2010). The file includes the phylogenetic tree with
 information on the topology, branch lengths (if present), probability of
 the partition indicated by the branch & mean of the posterior
 probability density. We removed the genera for which we did not collect
 honey samples. **Map.zip** This compressed directory contains all the
 files needed to produce Figure 1. It includes : * NE2_HR_LC_SR_W_DR.tif :
 Global natural earth map at 10m resolution. (source
 : [http://www.naturalearthdata.com/)](http://www.naturalearthdata.com/) *
 TM_WORLD_BORDERS_SIMPL-0.3.prj/.shp/.dbf/.shx : 4 files used to plot
 country borders on the global map * worldmap_Apis.csv : It contains the
 number of *Apis mellifera* honey samples per country. * Regions_apis.csv
 : It contains geographic coordinates of *Apis mellifera* honey samples for
 specific region (e.g. La Réunion in France) Location of stingless bee
 honey samples are included in Data_Global_EcoEvo_Honey.csv.
 **Environmental_variables.zip**  This compressed directory contains Raster
 files of environmental predictors with a CC0 license waiver used in this
 study. Environmental dissimilarities between locations were computed based
 on 8 variables impacting nectar production (soil moisture, precipitation*,
 solar radiation*) and composition (Tree cover, moisture, temperature*,
 forest density, plant biodiversity). It includes the following files : *we
 used the monthly values for these predictors. *
 crop_current_30arcsec_topoWet.tif : SAGA-GIS topographic wetness index
 from ENVIREM, see Title & Bemmels (2018). *
 crop_current_30arcsec_climaticMoistureIndex.tif : relative wetness and
 aridity metric from ENVIREM * crop_fden9.tif : Global-Scale Patterns of
 Forest density from Riitters et al. (2000). * crop_plantbiodiv.tif :
 Global native species richnes from Ellis et al. (2012). Global raster
 datasets of historical monthly temperature (°C), precipitation (mm), and
 solar radiation (kJ m-2 day-1) for 1960-2018 were sourced from Worldclim
 (Fick & Hijmans, 2017), available
 at [https://www.worldclim.org/data/worldclim21.html](https://www.worldclim.org/data/worldclim21.html). Additionally, global-scale forest cover rasters were obtained from Crowther et al. (2015) and can be accessed at [https://elischolar.library.yale.edu/yale_fes_data/1/](https://elischolar.library.yale.edu/yale_fes_data/1/). ### 1.2 Scripts This folder contains the 3 script necessary to the analysis described in the manuscript * Global_EcoEvo_honey.R * mytoolbox.R * scores.rda.R **Global_EcoEvo_honey.R** This is the main script used to produce the results and plot of this study. It is divided in 9 section : 1. List of packages and custom function 2. Data import 3. Script to produce the map (Fig.1) 4. Comparison of Apis and SB honeys using multivariate analysis (Fig.2) 5. Chemical diversity analysis (Supplementary Fig. 2) 6. Random forest analysis to compare Apis and SB honeys 7. Comparison of SB honeys among Tropical regions (Supplementary Fig. 3) 8. Random forest analysis to compare SB honeys among Tropical regions (Table 1 & Figure 3) 9. Ecology and evolution of stingless bee honey (Fig. 4 & 5). **mytoolbox.R** This script includes a set of custom function used in Global_EcoEvo_honey.R, particularly NbClust2.R & mypalette.R **scores.rda.R** This is a function downloaded from the set of function provided in Borcard & Legendre (2018), see doi:10.1007/978-3-319-71404-2 ### 1.3 Figures This folder contain the main figures and supplementary table and figures referenced in the manuscript *Figures:* * **Figure 1**: Geographical distribution of honey samples from honey bees(n=100) and stingless bees (n=150) across the Afrotropics, Neotropics, and Indo-Malayan regions. * **Figure 2**: NMDS plot showing differentiation of stingless bee honey (SBH) into two distinct clusters by bee tribe. * **Figure 3**: Random forest analysis plot highlighting key variables influencing honey composition, color-coded by significance. * **Figure 4**: Stacked bar plot showing the contribution of different drivers to SBH compositional variation at global and regional scales. * **Figure 5**: Mantel correlograms depicting correlations between honey composition and phylogenetic/environmental dissimilarities. *Supporting Information*: All supporting information are available in Supporting_information.docx, which includes :  * **Supplementary Tables 1 & 2**: Distribution of honey samples from stingless bees and honey bees across different countries. * **Supplementary Figure 1**: Phylogeny of honey sample genera. * **Supplementary Table 3**: Compounds identified and quantified in honey samples. * **Supplementary Figure 2**: Comparison of chemodiversity indices between Apis mellifera and stingless bee honeys. * **Supplementary Figure 3**: Hierarchical clustering of honey samples based on geographic origin. * **Supplementary Table 4**: db-RDA analysis results linking honey composition to bee genus and environmental factors.