Data and code from: Individual bumble bee foraging repertoires: Implications for disease persistence
Data files
Sep 28, 2026 version files 1.48 MB
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Data_and_Code_final.zip
1.48 MB
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README.md
2.94 KB
Abstract
Data files and R scripts for the article "Individual bumble bee foraging repertoires: implications for disease persistence" by Weiss et al. (2026), to be published in Functional Ecology.
In this work, we analyzed pollen samples collected from individual Bombus impatiens workers to assess whether they exhibited individual specialization. We mounted automated monitoring systems to the colonies to improve recapture rates so that we could better characterize the pollen foraging repertoire of each individual. We also developed mathematical models that assessed the effects of individual specialization on pollinator diseases transmitted via shared floral resources.
This dataset contains data on pollen samples collected from individual bees, and bee entry/exit events detected by the automated monitoring system. It also includes R scripts used to analyze the data, as well as to generate numerical results from the mathematical models of disease transmission.
Dataset DOI: 10.5061/dryad.bcc2fqzvw
Related article "Individual bumble bee foraging repertoires: Implications for disease persistence" to be published in Functional Ecology.
Generalist pollinator species may include individual floral specialists, which can alter disease transmission pathways through shared flowers. This study examines individual specialization in the common eastern bumble bee (Bombus impatiens) and assesses its potential consequences for pathogen persistence via mathematical models.
This repository contains the data and scripts for three sets of analyses:
- Pollen Analysis: Empirical palynological data of pollen loads collected from individually tagged B. impatiens foragers over time, and scripts used to quantify individual floral diet breadth and temporal repertoire turnover.
- Theoretical Disease Modeling: Code for modeling transmission dynamics of pathogens spread at shared flowers, when individual bees exhibit small foraging repertoires.
- Tunnel / Automated Monitoring Analysis: Data of entry and exit events for tagged bees automatically recorded by Raspberry Pi devices placed at colony entrances, and scripts used to analyze whether the act of pollen collection influenced various aspects of their foraging behavior, e.g., duration of foraging bouts.
List of files
Data_and_Code_final.zip
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|- Pollen_Analysis/
| |- additional_PERMANOVA.R
| |- data_prep.R
| |- Histogram_Fig3a_S3.R
| |- Jaccard_and_stats_Fig6_S5.R
| |- Network_Fig4.R
| |- NMDS_and_stats_Fig4.R
| |- pollen_data_2022.csv
| |- pollen_data_2024.csv
| |- readme_pollen.md
| |- Simpson_Fig3b_5_S4.R
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|- Supp_Sec_S3_theory/
| |- double_major_funs.R
| |- original_funs.R
| |- R0_and_switching.R
| |- random_sampling_funs.R
| |- readme_theory.md
| |- test_R0_double_major.R
| |- test_R0_random_sampling.R
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|- Supp_Sec_S4_tunnel_analysis/
| |- readme_tunnel_analysis.md
| |- tunnel_analysis.R
| |- tunnel_analysis_events_Trial2.csv
| |- tunnel_analysis_sampling_Trial2.csv
The files have been organized into three subfolders, one for each of the analyses mentioned above. Each folder has its own readme file with more details.
- The first folder,
Pollen_Analysis, contains data on pollen samples, as well as R scripts used to analyze the data. - The second folder,
Supp_Sec_S3_theory, contains R scripts used to generate numerical results from the mathematical models of disease transmission. See Supplementary Section 3 in the online supplement of the article for details. - The third folder,
Supp_Sec_S4_tunnel_analysis, contains data on events detected by the automated monitoring system, as well as R scripts used to analyze the data. See Supplementary Section 4 in the online supplement of the article for details.