Data from: Sexual conflict and sexually transmitted infections (STIs): coevolution of sexually antagonistic host traits with an STI

In many taxa, there is a conflict between the sexes over mating rate. The outcome of sexually antagonistic coevolution depends on the costs of mating and natural selection against sexually antagonistic traits. A sexually transmitted infection (STI) changes the relative strength of these costs. We study the three-way evolutionary interaction among male persistence, female resistance, and STI virulence for two types of STIs: a viability-reducing STI and a reproduction-reducing STI. A viability-reducing STI escalates conflict between the sexes. This leads to increased STI virulence (i.e., full coevolution) if the costs of sexually antagonistic traits occur through viability but not through reproduction. In contrast, a reproduction-reducing STI de-escalates the sexual conflict, but STI virulence does not coevolve in response. We also investigated the establishment probability of STIs under different combinations of evolvability. Successful invasion by a viability-reducing STI becomes less likely if hosts (but not parasites) are evolvable, especially if only the female trait can evolve. A reproduction-reducing STI can almost always invade because it does not kill its host. We discuss how the evolution of host and parasite traits in a system with sexual conflict differs from a system with female mate choice.Analytical ModelMathematica notebook outlining the analytical model described in the appendix and the functions used to determine numerical solutions appearing in Figures A3 and A4.sexualConflictSTIs_WardlawAgrawal_AmNat.nbPython scripts that runs all parameter combinations.Python script that takes a text file of all parameter combinations to be run and runs them in the command line automatically.lazyLoopTheBest.pyBash script that runs the simulations.This bash script takes the name of the text file containing parameters to be run, as well as the name of the database and .csv file where output data will be stored. It runs all parameter combinations through lazyLoopTheBest.py and then uses SQL to make a .csv file for import into R for plotting.runStuffWithCommandLinePrompts.bashText file with parameters to be runThis text file specifies all parameter combinations to be run, as well as the number of replicates of each parameter combination, and the number of processors to use.runAll.txtPython script that exports output data to a databasePython script called by IBM.py that adds output data to a database. While IBM.py is run separately for each parameter combination, the database contains the output of all parameter combinations contained in the runAll.txt file.sexualConflictDatabaseHandler.pyIndividual Based Simulation ModelSource code for the simulation model.IBM_WardlawAgrawal_AmNat.pyREADMEDescription of how to use the program package