Data from: Altruism or selfishness: Floral behavior based on genetic relatedness with neighboring plants
Data files
Mar 21, 2025 version files 66.46 MB
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Dataset.zip
66.45 MB
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README.md
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Abstract
Kin recognition in plants may lead to plastic changes in their behavior, such as altering their floral display size. In this study, we conducted evolutionary simulations of the two floral tactics utilized by plants depending on the genetic relatedness of their neighboring plants. We found that the evolutionary consequences of floral display size in plants can be classified into four types, which were determined by pollinator foraging behavior and plant ecological traits. The plants that grew with kin behaved altruistically by increasing their floral display size, while those that coexisted with strangers behaved selfishly by reducing their floral display size. Moreover, our findings suggest that kin recognition also increases intraspecific variation in floral display size and seed production and decreases the genetic diversity of plant populations.
This dataset contains the C-language simulation code and Mathematica scripts used to generate and visualize the results presented in the forthcoming paper:
Tomizuka, H., Yamawo, A., & Tachiki, Y. (2025). Altruism or Selfishness: Floral behavior based on genetic relatedness with neighboring plants. Journal of Evolutionary Biology. (https://doi.org/10.1093/jeb/voaf015)
The dataset includes simulation codes for evolutionary models examining how kin recognition influences floral display size and the resulting population-level consequences. The Mathematica scripts are used to process and visualize simulation results. Description of the Data and File Structure The dataset consists of simulation code, raw and processed data from simulations, Mathematica visualization scripts, and resulting figures.
The directory structure is as follows: makefile
Dataset/
├── Floral_Display_Evolution_Kin_Recognition_Fig2/ #This code manipulates two key parameters: the kin recognition threshold (R) in plants and the pollinators’ preference for plants with larger flowers (α). For each condition, we recorded the evolutionary outcomes of floral display size.
│ ├── Simulation_Code/ # Computer code used to conduct simulation.
│ ├── Data/
│ │ ├── Raw.csv # Raw data was obtained from the C-language simulation.
│ │ ├── Processed.csv # Processed data.
│ ├── Figure_Code/
│ │ ├──Figure_Code.nb # Mathematica code used to produce figures.
│├── Results/
│ │ ├──Floral_Display_Evolution.tiff # Image file of output figures.
│
├── Floral_Display_Size_Individual_Fitness_Fig3/ This code simulates how fitness changes when plants have kin recognition ability, compared to when they do not.
│ ├── Simulation_Code/ # Computer code used to conduct simulation.
│ ├── Data/
│ │ ├── Raw_a.csv # Raw data was obtained from the C-language simulation for Individual_Fitness_a.tiff.
│ │ ├── Raw_b.csv # Raw data was obtained from the C-language simulation for Individual_Fitness_b.tiff.
│ ├── Figure_Code/
│ │ ├── Figure_Code.nb # Mathematica code used to produce figures.
│ ├── Results/
│ │ ├── Individual_Fitness_a.tiff # Image file of output figures.
│ │ ├── Individual_Fitness_b.tiff
│
├── Pollinator_Foraging_and_Floral_Display_Evolution_Fig4/ ##This code manipulate two key parameters: the pollinators’ preference for patchs with larger flowers (n). For each condition, we recorded the evolutionary outcomes of floral display size.
│ ├── Simulation_Code/ # Computer code used to conduct simulation.
│ ├── Data/
│ │ ├── Raw.csv # Raw data was obtained from the C-language simulation.
│ │ ├── Processed.csv # Processed data.
│ ├── Figure_Code/
│ │ ├── Figure_Code.nb # Mathematica code used to produce figures.
│ ├── Results/
│ │ ├── Floral_display_size_for_kin.tiff # Image file of output figures.
│ │ ├── Floral_display_size_for_stranger.tiff
│
├── Kin_Recognition_Population_Effects_Fig5/ #This code simulates the population-scale effects of kin recognition in plants, including changes in genetic diversity, seed production, and floral investment.
│ ├── Simulation_Code/ # Computer code used to conduct simulation.
│ ├── Data/
│ │ ├── Raw_ab-1.csv # Raw data without kin recognition.
│ │ ├── Raw_ab-2.csv # Raw data with kin recognition, threshold (R) is 0.105.
│ │ ├── Raw_ab-3.csv # Raw data with kin recognition, threshold (R) is 0.145.
│ │ ├── Processed_ab.csv # Processed data for Display_sizes.tiff and Seed_distribution.tiff.
│ │ ├── Raw_cdef.csv # Raw data for figure 5cdef.
│ │ ├── Processed_cdef.csv # Processed data for Coancestry.tiff, Floral_investment.tiff, Pollination_rate.tiff, Seed_production.tiff.
│ ├── Figure_Code/
│ │ ├── Figure_Code_mathematica.nb # Mathematica code used to produce figures.
│ │ ├── Figure_Code_R.nb # R code used to produce figures.
│ ├── Results/
│ │ ├── Coancestry.tiff # Image file of output figures.
│ │ ├── Display_sizes.tiff
│ │ ├── Floral_investment.tiff
│ │ ├── Pollination_rate.tiff
│ │ ├── Seed_distribution.tiff
│ │ ├── Seed_production.tiff
│
├── Appendix/
│ ├── Analytical_Derivation_Floral_Display_Evolution_App1/
│ │ ├── Figure_Code/
│ │ │ ├── Figure_Code.nb # Mathematica code used to produce figures.
│ │ ├── Results/
│ │ │ ├── figureS1a.tiff # Image file of output figures.
│ │ │ ├── figureS1b.tiff
│ │ │ ├── figureS1c.tiff
│ │ │ ├── figureS1d.tiff
│ │ │ ├── figureS1e.tiff
│ │ │ ├── figureS1f.tiff
│ ├── Detailed_Floral_Display_Evolution_App2/
│ │ ├── Simulation_Code/ # Computer code used to conduct simulation.
│ │ ├── Data/
│ │ │ ├── Raw.csv # Raw data was obtained from the C-language simulation.
│ │ │ ├── Processed.csv # Processed data.
│ │ ├── Figure_Code/
│ │ │ ├── Figure_Code.nb # Mathematica code used to produce figures.
│ │ ├── Results/
│ │ │ ├── figureS2a.tiff # Image file of output figures.
│ │ │ ├── figureS2b.tiff
The random number generator “MT.h” is based on the Mersenne Twister code by Makoto Matsumoto and Takuji Nishimura. Due to its license conditions, the file is not included in this Dryad dataset. You can download “MT.h” from the associated Zenodo repository. Please place the file in the “include” directory to reproduce the simulation results.
Each folder contains:
・Simulation_Code/: C-language source code for evolutionary simulations. The main script for each experiment is provided here.
・Data/: Raw and processed data generated from simulations.
Raw.csv: Direct output from the simulation model.
Processed.csv: Data post-processed for visualization and analysis
・Figure_Code/: Mathematica (.nb) scripts for generating figures. A corresponding PDF file is also included for reference.
・Results/: Final visual outputs in TIFF format.
The dataset includes different simulation scenarios:
Floral_Display_Evolution_Kin_Recognition_Fig2: Evolution of floral display size under different kin recognition conditions.
Floral_Display_Size_Individual_Fitness_Fig3: Changes in plant fitness based on floral display size.
Pollinator_Foraging_and_Floral_Display_Evolution_Fig4: Effects of pollinator foraging behavior (parameter n).
Kin_Recognition_Population_Effects_Fig5: Population-level consequences of kin recognition (e.g., genetic diversity).
Description of Variables
The meanings of each column name are shown below.
| Variables | |
|---|---|
| intrapatch competition | An index representing the strength of pollinators’ preference for individuals with larger flowers. |
| interpatch competition | An index representing the strength of pollinators’ preference for patches with larger flowers. |
| Threshold | A plant individual considers a patch as a kin patch if its genetic relatedness with surrounding individuals exceeds this threshold; otherwise, it is regarded as a non-kin patch. Based on this, the plant individual adjusts its behavior. |
| population size of pollinator | The total number of pollinators available to the plant population examined in this study. All plant individuals compete for this limited pollinator resource. |
| Seed dispersal rate | The probability that a plant’s seeds disperse to another patch. |
| fkin* | The evolutionary final value of the floral display size expressed toward kin. Evolutionary outcome. |
| fstr* | The evolutionary final value of the floral display size expressed toward stranger. Evolutionary outcome. |
| defference of floral fitness | The effect of a plant acquiring kin recognition ability on changes in its own fitness. |
| defference of neighboring fitness | The effect of a plant acquiring kin recognition ability on changes in its neighboring plants fitness. |
| Average seed production | The average seed production of the entire plant population. |
| Average floral display size | The average floral display size of the entire plant population. |
| Average pollination rate | The average pollination rate of the entire plant population. |
| Average coancestry | The average coancestry coefficient of the entire plant population. |
All variables are dimensionless and do not have specific units. The dataset consists of normalized values derived from evolutionary simulations. Users can interpret these values as relative measures rather than absolute quantities.
Sharing/Access Information
Data was derived from the following sources: The dataset is generated entirely through computational simulations and does not contain empirical data.
Code/Software
Computational Environment
Operating System: Windows 11 Pro
Processor: 12th Gen Intel Core i9-12900H (2.90 GHz)
RAM: 64 GB
Software Used
C Compiler: GCC (TDM-GCC version 10.3.0)
Data Visualization: R (version 4.3.1)
Data Visualization: Wolfram Mathematica (version 13.1.0.0)
Simulation Code (C-Language)
The main simulation script is default_simulation.c, which models plant evolutionary dynamics under varying levels of kin recognition and pollinator foraging behavior. The script allows users to modify key parameters such as:
R (Threshold for Kin Recognition): Determines the relatedness threshold at which a plant recognizes neighbors as kin.
α (Intrapatch Competition Intensity): Represents how much pollinators prefer individuals with larger flowers within the same patch.
n (Interpatch Competition Intensity): Represents how much pollinators prefer patches with larger flowers.
pd (Seed Dispersal Rate): The probability that a plant’s seeds disperse to another patch.
The code includes:
・Random number generation using the Mersenne Twister method (implemented in include/).
Mathematica Scripts (.nb)
Each .nb script imports processed simulation data from CSV files and generates figures corresponding to those in the paper.
The output consists of line graphs, scatter plots, and bar charts visualizing: Evolutionary changes in floral display size (Fig. 2; Fig. 4).
Effects of kin recognition on fitness outcomes (Fig. 3).
Population-level consequences such as genetic diversity shifts (Fig. 5).
Evolutionary individual based (i.e., stochastic) simulation of floral display size.