Social network differences and phenotypic divergence between stickleback ecotypes
Data files
Nov 10, 2022 version files 29.47 KB
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all_edges.csv
7.24 KB
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edges_common.csv
2.81 KB
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edges_mixed.csv
2.69 KB
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edges_white.csv
2.83 KB
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ind_shoaling_data.csv
5.22 KB
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nodes_common.csv
1.63 KB
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nodes_mixed.csv
1.66 KB
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nodes_white.csv
1.38 KB
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README.md
4 KB
Jun 29, 2024 version files 29.57 KB
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all_edges.csv
7.24 KB
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edges_common.csv
2.81 KB
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edges_mixed.csv
2.69 KB
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edges_white.csv
2.83 KB
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ind_shoaling_data.csv
5.22 KB
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nodes_common.csv
1.63 KB
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nodes_mixed.csv
1.66 KB
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nodes_white.csv
1.38 KB
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README.md
4.10 KB
Abstract
Elucidating the mechanisms underlying differentiation between populations is essential to our understanding of ecological and evolutionary processes. While social network analysis has yielded numerous insights in behavioral ecology in recent years, it has rarely been applied to questions about population differentiation. Here, we use social network analysis to assess the potential role of social behavior in the recent divergence between two three-spined stickleback ecotypes, “whites” and “commons”. These ecotypes differ significantly in their social behavior and mating systems as adults, but it is unknown when or how differences in social behavior develop. We found that as juveniles, the white ecotype was bolder and more active than the common ecotype. Furthermore, while there was no evidence for assortative shoaling preferences, the two ecotypes differed in social network structure. Specifically, groups of the white ecotype had a lower clustering coefficient than groups of the common ecotype, suggesting that groups of the white ecotype were characterized by the formation of smaller subgroups, or ‘cliques’. Interestingly, ecotypic differences in clustering coefficient were not apparent in mixed groups composed of whites and commons. The formation of cliques could contribute to population divergence by restricting the social environment that individuals experience, potentially influencing future mating opportunities and preferences. These findings highlight the insights that social network analysis can offer into our understanding of population divergence and reproductive isolation.
README: Data for article - Social network differences underlie phenotypic divergence between stickleback ecotypes
Authors: Kevin M. Neumann, Alison M. Bell
Date created: 11/09/22
Article is currently in review in Behavioral Ecology.
Data is from a study conducted in October - November 2020 at the University of Illinois, Urbana-Champaign. This is a laboratory study exploring the social behavior of three-spined stickleback fish. Fish from two ecoytypes - white and common - were tested for inividual boldness and activity. They were then assigned to one of three group types - common groups that were ony common ecotype fish, white groups that were only white ecotype fish, and mixed groups made up of 50% white ecotype and 50% common ecotype.
Upon publication, methodological details will be available in the manuscript. Until then, contact Kevin M. Neumann for details via email - kevinn4@illinois.edu
Description of the Data and file structure
File count: 8
Total file size: 26 KB
File formats: .csv
Files:
nodes_white.csv
nodes_common.csv
nodes_mixed.csv
edges_white.csv
edges_common.csv
edges_mixed.csv
all_edges.csv
ind_shoaling_data.csv
The 8 .csv files are all to be analyzed in R - RStudio 2022.07.0 recommended. The nodes and edges files are for constructing social networks of the fish; nodes represent individual fish and edges represent interactions between pairs of fish. The individual shoaling data file contain further individual level information on fish. Details on each file are listed below.
Details on .csv files
- 1. 1. nodes_white.csv, nodes_common.csv, nodes_mixed.csv
Each row is an individual fish from either the white, common, or mixed group types.
Columns:
name = unique individual ID for each fish
id = identifier of fish within each group as displayed in the idtracker software; idtracker automatically assigns an individual a value from 0-(size of group) during tracking
color = color for plotting networks; color corresponds to fish type (white or common)
size = length of fish, in mm
boldness = latency to emerge from a shelter, in seconds
shoaling_group = group that fish was in; all fish sharing shoaling group were tested at the same time for social behavior
holding_tank = tank that fish were held in prior to experiment
fish_type = ecotype - C = common, W = white
- 1. 1. edges_white.csv, edges_common.csv, edges_mixed.csv, all_edges.csv
Each row is a pair of fish within either the white, common or mixed group types, or for all_edges, all three group types in the same file. All possible pairs of fish are listed.
Columns:
source = individual ID of one interacting fish (IDs correspond to "name" in the nodes files)
target = individual ID of the other interacting fish
weight = frequency of interaction between the two fish, in seconds
interaction = type of interaction occurring - sameCC = two common fish in common groups; sameWW = two white fish in white groups; sameCM = two common fish in mixed groups; sameWM = two white fish in mixed groups; diff = white and common fish in mixed groups
- ind_shoaling_data.csv
Each row is an individual fish and columns provide information on each individual.
Columns:
fish_ID = unique identifier (this is the same as "name" in the nodes files)
length_mm = fish length, in mm
latency_sec = latency to emerge from a shelter, in seconds
fish_type = ecotype - C = common, W = white
group_type = group type - C = common, M = mixed, W = white
group = specific shoaling group, all fish within a group were tested together
family = family of origin, fish with same family number are siblings
holding_tank = tank that fish were held in prior to experiment
distance_swam_m = how far fish swam during social behavior assays, in meters
total_interaction_time = sum of time fish spent interacting with each other conspecific in behavior assays, in seconds
Sharing/access Information
Data is also available on figshare:
https://figshare.com/articles/dataset/Analysis_code_and_data/18737369
Methods
Dataset is social behavior data on stickleback using automated video tracking technolgy (idTracker - https://www.idtracker.es/).
Usage notes
All data was analyzed in R.