Code from: Fitness as the organismal performance measure guiding adaptive evolution

A long-standing problem in evolutionary theory is to clarify in what sense (if any) natural selection cumulatively improves the design of organisms. Various concepts, such as fitness and inclusive fitness, have been proposed to resolve this problem. In addition, there have been attempts to replace the original problem with more tractable questions such as whether a given gene or trait is favoured by selection. Here we ask what theoretical properties the concept of fitness should possess to encapsulate the improvement criterion required to talk meaningfully about adaptive evolution. We argue that natural selection tends to shape phenotypes based on the causal properties of individuals and that this tendency is, therefore, best captured by a fitness concept that focuses on these properties. We highlight a fitness concept that meets this role under broad conditions but requires adjustments in our conceptual understanding of adaptive evolution. These adjustments combine elements of Dawkinsi..., , , # Code from: Fitness as the organismal performance measure guiding adaptive evolution

[https://doi.org/10.5061/dryad.7sqv9s50r](https://doi.org/10.5061/dryad.7sqv9s50r)

This is the Matlab code used to run the simulations presented in Figure 1B.

## Description of the data and file structure

1\. Overview

The function 'nonregulatory.m' contains the main code for simulations. When contained in the same folder, this code can be called from the script 'run_nonregulatory.m' such that multiple simulation runs from different initial allelic values are executed and plotted.

2\. File list

File name: nonregulatory.m

Description: Main code for executing one simulation run

Title: Higher-level code for executing multiple simulation runs and plotting

File name: run_nonregulatory.m

Description: Script that calls function 'nonregulatory.m' in an automated fashion to compute multiple simulation runs from different initial settings. Then the mean allelic values of each simulation run are plotted...