Data and code from: Acoustic and visual traits predict species nuclearity in Neotropical mixed-species bird flocks
Data files
Jul 22, 2026 version files 330.29 KB
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Eyesize_subset.xlsx
136.95 KB
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Full_dataset.xlsx
178.32 KB
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README.md
4.34 KB
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Script_flocks_bipartite.R
10.68 KB
Abstract
Mixed-species bird flocks constitute a striking example of heterospecific sociality, offering participants potential benefits such as enhanced foraging efficiency and reduced predation risk. Yet, not all species join these flocks with the same frequency. Moreover, beyond simply participating, species may play distinct roles within flock networks. While some bird species may exhibit high nuclearity and occupy a central position in flock formation, cohesion, and dynamics (i.e., social hubs), others are merely peripheral followers. Understanding how phenotypic and ecological traits relate to both flocking propensity and network position can provide key insights into the drivers of interspecific social behavior in birds. Using a comprehensive dataset of over 3,000 flocks, we applied network theory to explore the relationship between species-level network metrics (connectivity, strength, and closeness), flocking propensity, and key phenotypic traits (relative eye size, beak shape, maximum song frequency, and plumage coloration) in Neotropical birds. Bayesian phylogenetic models revealed that flocking propensity was positively associated with maximum song frequency and carotenoid-based coloration, and negatively associated with relative eye size. In addition, the extent of white in plumage significantly predicted species centrality. This is the first study to evaluate whether acoustic and visual traits predict both flocking propensity and a species’ structural role within flock networks. These findings, along with the moderate phylogenetic signal detected in network metrics, suggest that the evolution of heterospecific sociality may involve distinct morphological and sensory adaptations.
Dataset DOI: 10.5061/dryad.vx0k6dk4z
Description of the data and file structure
Datasets employed to conduct the analyses.
The first dataset (Full_dataset.xls) includes average trait values and network metrics for 559 bird species.
The second dataset (Eyesize_subset.xls) includes avergae trait values and network metrics for 282 bird species.
Files and variables
File: Script_flocks_bipartite.R
Description: R code employed to obtain the network metrics, z-scores (null models) and conduct PGLS and Bayesian models
File: Eyesize_subset.xlsx
Description: Average trait values and network metrics for 282 species.
Variables:
- species: species name
- Family: family
- ResEyeAD: Residual axial eye length
- AxialEyeLength: Axial eye length
- LogAEL: Log-transformed axial eye length
- BeakLength: Beak length
- MaxHeadWidth: Maximum head width
- LogMaxHeadW: Log-transformed maximum head width
- BodyLength: HBL-Body length
- LogBodyLength: Log-transformed body length
- Mass: Body mass
- LogMass: Log-transformed body mass
- FP_obs: Flocking propensity
- logFP_obs: Log-transformed flocking propensity
- flock_size_mean: average flock size
- FreqMax: Maximum frequency (song)
- ResFreqMax: Residual (size-corrected) Maximum frequency
- Beak.Length_Culmen_COR: Size-corrected beak (tip-to-culmen) length
- Beak.Length_Nares_COR: Size-corrected beak (tip-to-nares) length
- Beak.Width_COR: Size-corrected beak width
- Beak.Depth_COR: Size-corrected beak depth
- BeakPCA: PC1 summarizing Beak shape
- z-score_strength: z-score (null model approach) for strength
- z-score_closeness: z-score (null model approach) for closeness
- z-score_degree: z-score (null model approach) for degree connectivity
- mean_degree: Normalized degree
- mean_ND: Degree (connectivity)
- mean_strength: Strength
- mean_specifity: Specifity
- mean_between: Betweeness
- mean_between_w: Weighted Betweeness
- mean_closeness: Closeness centrality
- mean_closeness_w: Weighted closeness centrality
- mean_d: Level of Specialization (d')
- MELANINM: Amount of melanin coloration
- CAROTENOIDM: Amount of carotenoid coloration
- GREENM: Amount of green coloration
- STRUCTURM: Amount of structural coloration
- WHITEM: Amount of white
Cells with NAs denote missing data
File: Full_dataset.xlsx
Description: Average trait values and network metrics for 559 species.
Variables:
- species: species name
- Family: family
- flock_size_mean: average flock size
- Mass: Body mass
- LogMass: Log-transformed body mass
- FreqMax: Maximum frequency (song)
- LogFreqMax: Log-transformed Maximum frequency (song)
- ResFreqMax: Residual (size-corrected) Maximum frequency
- BeakPCA: PC1 summarizing Beak shape
- FP_obs: Flocking propensity
- logFP_obs: Log-transformed flocking propensity
- z-score_strength: z-score (null model approach) for strength
- z-score_closeness: z-score (null model approach) for closeness
- z-score_degree: z-score (null model approach) for degree connectivity
- mean_strength: Strength
- mean_closeness: Closeness centrality
- mean_closeness_w: Weighted closeness centrality
- mean_ND: Normalized degree
- mean_degree: Degree (connectivity)
- mean_nestedrank: Nestedrank
- mean_specifity: Specifity
- mean_betweeness: Betweeness
- mean_betweeness_w: Weighted Betweeness
- mean_d: Level of Specialization (d')
- MELANINM: Amount of melanin coloration
- CAROTENOIDM: Amount of carotenoid coloration
- GREENM: Amount of green coloration
- STRUCTURM: Amount of structural coloration
- WHITEM: Amount of white
Units:
- Mass (g)
- FreqMax (kHz)
- AxialEyeLength (mm)
- BeakLength (mm)
- MaxHeadWidth (mm)
- BodyLength (mm)
- MELANIM (sum of body proportions)
- CAROTENOIDM (sum of body proportions)
- GREENM (sum of body proportions)
- STRUCTURM (sum of body proportions)
- WHITEM (sum of body proportions)
Code/software
R script to obtain species-level network metric (bipartite) and conduct Bayesian (brms) and PGLS models.
Libraries:
- library(bipartite)
- library(dplyr)
- library(parallel)
- library(purrr)
- library(brms)
- library(phytools)
- library(tidyverse)
- library(dbplyr)
- library(posterior)
- library(ggplot2)