Data from: Intraspecific competition can promote population-level specialization
Data files
Jan 16, 2026 version files 166.56 MB
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NichePosition.zip
84.05 MB
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NicheWidth.zip
82.43 MB
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PositionResult.csv
47.68 KB
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README.md
3.19 KB
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WidthResult.csv
32.94 KB
Abstract
This dataset is contains code and data used in a study that analyzed how population-level specialization of a consumer species may change in response to increased intraspecific competition by way of a larger population size. The study was a parameter sweep of an evolutionary game theoretic consumer-resource model to see now optimal niche breadth and selection on niche position would change in response to an increased population.
Included in this dataset is the code used to generate the raw data on optimal niche breadth and selection on niche position, the raw data itself, the code used to analyze the raw data, the analyzed data, and the code used to generate figures.
Contained in this dataset is code used to generate and analyze data as well as generate some of the figures for this paper. Also contained are the results of that analysis.
Description of the data and file structure
NichePosition.zip -- A ZIP file that contains a series of CSV files. Each CSV file contains the values of selection on niche position given a fixed population size and variable resource diversity and benefit to specialization. Within each cell of a given CSV is the selection on niche position at a given resource diversity (rows) and benefit to specialization (columns).
NicheWidth.zip -- A ZIP file that contains a series of CSV files. Each CSV file contains the values of optimal niche width given a fixed population size and variable resource diversity and benefit to specialization. Within each cell of a given CSV is the optimal niche width value at a given resource diversity (rows) and benefit to specialization (columns).
PositionResult.csv -- A CSV file describing the relationship between selection on niche position and population size. Each cell represents the relationship at a given resource diversity (rows) and benefit to specialization (columns). Below are the meanings of the labels in each cell
"CD" -- Always increasing generalization
"TS" -- Always increasing specialization
"ICD" -- Increased generalization followed by increased specialization
"CA" -- Increased specialization followed by increased generalization
"CD_CA" -- Increased generalization followed by increased specialization followed by increased generalization
"CA_CD" -- Increased specialization followed by increased generalization followed by increased specialization
"O" -- Other relationship
"NA" -- Indeterminate
WidthResult.csv -- A CSV file describing the relationship between optimal niche width and population size. Each cell represents the relationship at a given resource diversity (rows) and benefit to specialization (columns). Meanings of the labels in each cell are exactly the same as "PositionResult.csv"
Code/Software
All software is hosted on Zenodo via the Related works link
- CD dBetadv2 Integrals.R -- Functions used to solve the optimal niche width value
- CD ddBetadv22 Integrals.R -- Functions used to solve the selection on niche position value
- OptimSpec.R -- Code to generate the data for optimal niche width given a certain population size, resource diversity, and benefit to specialization.
- Disrupt.R -- Code to generate the data for the selection on niche position given a certain population size, resource diversity, and benefit to specialization.
- Correction.R -- Code used for data correction from results generated from OptimSpec.R
- Read.R -- Function to read in data generated from OptimSpec.R, Disrupt.R, and Correction.R
- Analysis.R -- Code used to do a first pass analysis of the response of niche width/position to population.
- Figure X.R -- The code to make "Figure X.png"
- Sensitivity_Analysis_Position.R -- Code for sensitivity analysis on niche position
- Sensitivity_Analysis_Width.R -- Code for sensitivity analysis on niche width
- Halloway, Abdel; Brown, Joel (2026). Data from: Intraspecific competition can promote population-level specialization. Zenodo. https://doi.org/10.5281/zenodo.8115132
- Halloway, Abdel; Brown, Joel (2026). Data from: Intraspecific competition can promote population-level specialization. Zenodo. https://doi.org/10.5281/zenodo.8115133
