Sexual dimorphism in pollen foraging and sensory traits in Heliconius butterflies

# Sexual dimorphism in pollen foraging and sensory traits in Heliconius butterfliesData & Analysis Repository (Zenodo) This repository contains datasets and analysis scripts used in a study of sexual dimorphism in pollen foraging and sensory traits in Heliconius butterflies, including brain morphology, eye morphology, wing reflectance spectrometry, pollen metabarcoding, and microhabitat capture–recapture analyses. DOI: 10.5281/zenodo.17777739 ## Version history - v1.1 (2026-02-08): Added raw (untransformed) brain volume data, expanded variable-level documentation in the README, and removed absolute file paths from R scripts. ## Abstract This repository contains the data and analysis scripts supporting the study “Sexual dimorphism in pollen foraging and sensory traits in Heliconius butterflies.” The study integrates brain neuroanatomy, eye morphology, wing reflectance spectrometry, pollen DNA metabarcoding, and microhabitat recapture data to test sex-specific differences in sensory investment and foraging ecology in Heliconius himera. Statistical analyses were conducted in R using mixed-effects models, allometric scaling, and multivariate community analyses. The datasets provided here allow reproduction of the key analyses and figures reported in the manuscript. Sexual dimorphism in foraging behaviour is widespread in insects and may arise from differences in nutritional demands,sensory systems, or cognition. In Heliconius, pollen-feeding is an evolutionary innovation among butterflies that supports extended lifespans and sustained reproduction. However, how foraging behaviour varies between the sexes and how it relates to sexually dimorphic traits remains poorly understood. We investigated sex-specific foraging strategies in wild Heliconius himera, a highland specialist from southern Ecuador, using field surveys and DNA metabarcoding. Females carried more pollen than males, consistent with higher nutritional demands. Yet both sexes used similar plant richness and composition, indicating that differences reflect foraging effort rather than shifts in plant choice. Gut samples revealed greater pollen diversity and a more consistent community profile than proboscis samples, suggesting they better capture cumulative foraging history. To place these behavioural differences in a sensory context, we quantified sexually dimorphic sensory traits. Males had larger eyes and more ommatidia, whereas females had larger mushroom bodies, brain regions that support associative learning and memory. These patterns are consistent with sexual dimorphism reported across Heliconius and may contribute to the observed sex differences in pollen foraging. Our findings highlight how sex-specific foraging differences may arise from effort on shared floral resources and co-occur with divergent sensory and neural investment, offering insights into the ecological basis of intraspecific variation in pollen use. ## Contents This Zenodo record contains:- Data files: 9 (CSV/TXT) + 1 Excel workbook- R scripts: 6- README: this file File names listed below match those deposited on Zenodo. ## Data and file overview ### 1) Brain morphology and sexual dimorphism Data:- Cyr_him_combined_brain_volumes.csv Log10-transformed neuropil volumes and grouping variables for Heliconius (H. e. cyrbia and H. himera).- Cyr_him_combined_brain_volumes_raw.csv Raw (untransformed) neuropil volumes corresponding to the log-transformed file above.- himera_lrt_table.csv Likelihood-ratio test (LRT) results from mixed-effects models of neuropil volumes.- smatr_table_himera.csv Summary of SMATR outputs (slope, elevation, and major axis shift tests).- TableS1_Hhim-brain-dimorphism.xlsx Curated summary table used in the manuscript for brain dimorphism results. Scripts:- Brains_sex_him.r Main pipeline for modelling sexual dimorphism in brain structure (mixed models, LRT tables, figures).- smatr_eyes_himera.R SMATR major axis analyses of scaling relationships (eye/brain scaling as used in the study). ### 2) Reflectance spectrometry and age prediction Data:- reflectance_age.csv Raw reflectance spectra used for age prediction modelling (long format; wavelength-level reflectance).- Vilcabamba_samples_age.csv Individual-level table containing known ages (when available), predicted ages, and associated metadata. Scripts:- reflectance_age_modeling_full.R End-to-end reflectance-based age modelling script (model fitting, validation, diagnostics). ### 3) Pollen metabarcoding and foraging ecology Data:- asv_vilcabamba_table.merge.txt Merged ITS2 ASV table from proboscis and gut samples.- samples_metadata_vilcabamba.csv Metadata for sequenced samples and linked individual-level predicted age groupings. Scripts:- metabarcoding_tools_0-1a.R Helper functions for data cleaning, ASV processing, and taxonomic lookup.- R_ITS2_vilcabamba.R ITS2 metabarcoding pipeline including filtering, taxonomic assignment, and diversity analyses.- Pollen_loads.R Analyses of pollen load categories, taxonomic richness, Shannon diversity, and related models. ### 4) Microhabitat and capture–recapture data Data:- Vilcambamba_recapture_data.csv Capture–recapture dataset including pollen categories and environmental/logistical fields.- recaptures_logger_1h.csv High-frequency temperature and humidity logger data linked to capture/recapture events. ## Variable descriptions (data dictionaries) This section describes variables (columns), their data types, and units/formats where applicable. ### Cyr_him_combined_brain_volumes.csv Neuropil volume measurements and grouping variables for Heliconius (H. e. cyrbia and H. himera) used in brain dimorphism and scaling analyses. Important note: All neuropil volume variables in this file are log10-transformed and stored with the prefix `log_` (i.e., log10(volume in µm³)). Variables:- ID (factor): individual identifier (e.g., `1_wild`, `10_wild`)- Species (factor): species identity (e.g., `H. e. cyrbia`, `H. himera`)- Sex (factor): `female`, `male`- Location (factor): collection / rearing location (e.g., `Balsas`, `Cambridge`, etc.)- Type (factor): `reared`, `wild` Log10-transformed neuropil volumes (numeric; log10(µm³)):- log_ME: medulla- log_LAM: lamina- log_LOB: lobula- log_LOP: lobula plate- log_aME: accessory medulla- log_vLOB: ventral lobula- log_rCB: remainder of central brain- log_AL: antennal lobe- log_AOTU: anterior optic tubercle- log_POTU: posterior optic tubercle- log_MBCA: mushroom body calyx- log_MBPED: mushroom body peduncle / lobes (as defined in the study)- log_OL: optic lobe (aggregate)- log_CBR: central brain region (as defined in the study) Raw (untransformed) neuropil volumes are provided in Cyr_him_combined_brain_volumes_raw.csv. ### Cyr_him_combined_brain_volumes_raw.csv Raw (untransformed) neuropil volumes corresponding to the same individuals and structures as Cyr_him_combined_brain_volumes.csv. Volumes are expressed in cubic micrometers (µm³). Values were log10-transformed for analysis. Variables:- ID (factor): individual identifier- Species (factor): species identity- Sex (factor): `female`, `male`- Location (factor): collection / rearing location- Type (factor): `reared`, `wild` Raw neuropil volumes (numeric; µm³):- ME: medulla- LAM: lamina- LOB: lobula- LOP: lobula plate- aME: accessory medulla- vLOB: ventral lobula- rCB: remainder of central brain- AL: antennal lobe- AOTU: anterior optic tubercle- POTU: posterior optic tubercle- MBCA: mushroom body calyx- MBPED: mushroom body peduncle / lobes (as defined in the study)- OL: optic lobe (aggregate)- CBR: central brain region (as defined in the study) ### Hhimera_eyemorph.csv Eye and body size measurements for Heliconius himera. Identifiers and grouping:- ID (factor): individual identifier (e.g., `H543`)- collection (factor): collection code (e.g., `ERC_ECU`)- sex (factor): `female`, `male`- type (factor): taxon label (here `H_himera`)- brood (character): brood / stock identifier (may be NA)- wild_insectary (factor): `insectary`, `wild`- location (factor): sampling location (`IKIAM`, `Vilcabamba`), may be NA- latitude, longitude (numeric): coordinates in decimal degrees, may be NA- elevation (character): elevation label / notes, may be NA- observer (character): measurer identity Body size:- tibia_length (numeric): tibia length (units as measured in the study, typically mm)- abdomen_length (numeric): abdomen length (same unit convention)- total_body_length (numeric): total body length (same unit convention; may be NA)- inter_eye_width (numeric): inter-eye width (same unit convention; may be NA) Eye area and facet counts:- L_area, R_area (numeric): left and right eye area (units as measured; typically mm²)- L_whole_count, R_whole_count (numeric/integer): facet (ommatidia) counts per eye Image bookkeeping and notes:- wing_image (logical): whether a wing image exists/was used- box_and_location (character): storage / box reference- notes (character): notes on reanalysis / issues- clade (factor): genetic clade label (e.g., `EAST_1`), may be NA- gps_location (character): optional GPS location field, may be NA- gps_latitude, gps_longitude (numeric): optional GPS coordinates, may be NA- wing_id (character): wing image identifier (may be NA) ### himera_lrt_table.csv Likelihood-ratio test (LRT) results from mixed-effects models of neuropil volumes. Variables:- Neuropil (character): neuropil name (e.g., `AL`)- Predictor (character): model term tested (e.g., `Location`, `sex`, `rCB`, `SexLocation`)- LogLik_reduced (numeric): log-likelihood of reduced model- LogLik_full (numeric): log-likelihood of full model- CHISQ (numeric): likelihood-ratio chi-square statistic- p_value (numeric): p-value for the LRT- Adjusted_p_value (numeric): multiple-testing adjusted p-value- Significance (character): significance code used in the manuscript tables ### smatr_table_himera.csv Summary of SMATR outputs for sex differences in scaling rela