Data for: Outcomes of multifarious selection on the evolution of visual signals

Multifarious sources of selection shape visual signals and can produce phenotypic divergence. Theory predicts variance in warning signals should be minimal due to purifying selection, yet polymorphism is abundant. While in some instances divergent signals can evolve into discrete morphs, continuously variable phenotypes are also encountered in natural populations. Notwithstanding, we currently have an incomplete understanding of how combinations of selection shape fitness landscapes, particularly those which produce polymorphism. We modeled how combinations of natural and sexual selection act on aposematic traits within a single population to gain insights into what combinations of selection favor the evolution and maintenance of phenotypic variation. With a rich foundation of studies on selection and phenotypic divergence, we reference the poison frog genus Oophaga to model signal evolution. Multifarious selection on aposematic traits created the topology of our model’s fitness landsca..., All the data are computational and generated with the code provided., The programs required to open the data files, generate the scenarios and reproduce the computations are Python 3.0 (open-source; https://www.python.org/downloads/) and Matlab (proprietary; MATLAB and Statistics Toolbox Release 2019b, 9.7.0.1190202 (R2019b). Natick, Massachusetts, The MathWorks Inc.). The Matlab files can be opened directly using Python as shown the Python code (Pop_Evo_multifarious_evolution_free_energy_Fokker_Planck_equation.py). An open-source alternative to run the Matlab routines and generate/modify the scenarios (cf. README.md) is Octave (https://octave.org/)., # Data for: Outcomes of multifarious selection on the evolution of visual signals

Yeager, Justin and Penacchio, Olivier, Proceedings of the Royal Society B, March 2023

This repository contains all the experimental data to reproduce the simulations, results and analysis of the paper \"Outcomes of multifarious selection on the evolution of visual signals\", [https://royalsocietypublishing.org/doi/abs/10.1098/rspb.2023.0327](https://royalsocietypublishing.org/doi/abs/10.1098/rspb.2023.0327).

## Description of the Data and file structure

### Summary:

* File count: 9
* Total file size: 4.08 MB
* Range of individual file sizes: 35 kB - 801 kB
* File formats: .mat

### File naming:

* The Matlab files (*.mat) that give the fitness landscape (total\_free\_energy\_landscape\_for\_Fokker\_Plank\_equation\_*) are named after the different scenarios contemplated in the manuscript, namely scenarios A, B1, B2, and C, and include information on the size of the phenotypic space (Siz50); each files p...

多种选择压塑造视觉信号并可引发表型分化。理论预测，由于纯化选择的作用，警戒信号的变异度应处于较低水平，但自然界中多态现象却十分普遍。尽管在某些情况下，分化的信号可演化出离散的形态型，但自然种群中也存在连续变异的表型。尽管如此，目前我们对于多种选择压共同如何塑造适应度景观（fitness landscape），尤其是那些驱动多态演化的适应度景观，仍缺乏完整的认知。
本研究构建模型，探究单一种群内自然选择与性选择的共同作用如何影响警戒色（aposematic）性状，以期明确哪些选择组合会促进表型变异的演化与维持。依托选择作用与表型分化领域的丰富研究基础，我们以箭毒蛙属（Oophaga）为研究对象来构建信号演化模型。对警戒色性状的多种选择压共同作用，构建了本研究模型的适应度景观拓扑结构。
所有数据均为计算生成，可通过提供的代码复现。
用于打开数据文件、生成模拟场景以及复现计算流程的程序包括Python 3.0（开源软件，获取地址：https://www.python.org/downloads/）与Matlab（专有软件，MATLAB及统计工具箱2019b版，版本号9.7.0.1190202 (R2019b)，马萨诸塞州内蒂克市，MathWorks公司）。
Matlab格式文件可直接通过Python读取，具体操作可参考配套Python代码（Pop_Evo_multifarious_evolution_free_energy_Fokker_Planck_equation.py）。
用于运行Matlab程序、生成或修改模拟场景（详见README.md文件）的开源替代工具为Octave（获取地址：https://octave.org/）。
# 关联数据集：多种选择压对视觉信号演化的影响结果
作者：Yeager, Justin 与 Penacchio, Olivier，发表期刊：《英国皇家学会会报B辑：生物科学》，2023年3月
本数据集仓库包含复现论文"Outcomes of multifarious selection on the evolution of visual signals"所需的全部实验数据、模拟结果与分析代码，论文链接：https://royalsocietypublishing.org/doi/abs/10.1098/rspb.2023.0327。
## 数据与文件结构说明
### 数据概况：
* 文件总数：9个
* 总文件大小：4.08 MB
* 单文件大小区间：35 kB 至 801 kB
* 文件格式：.mat
### 文件命名规则：
* 用于存储适应度景观的Matlab格式文件（命名格式为total_free_energy_landscape_for_Fokker-Planck_equation_*）以论文中提及的不同模拟场景命名，即场景A、B1、B2与C，文件中包含表型空间大小（Siz50）等信息；各文件的命名相关内容详见原文（原文此处未完整显示）。