Quercus_IUCN_samp_sims:储存代表IUCN Red List濒危橡树的代码，模拟和参数文件的存储库

# Quercus_IUCN_samp_sims Repository storing code, simulation, and parameter files that represent IUCN Red List endangered oaks for my honor's capstone project at Northern Illinois University. This project is being completed in collaboration with Emily Schumacher and Dr. Sean Hoban from the Morton Arboretum. #### Background The overall aim of this project is to contribute to practical seed sampling guidelines for creating and maintaining genetically diverse collections for botanic garden and arboreta. Informing these sampling guidelines is one way to ensure a genetically representative sample is obtained from wild populations. Prior work has found that it is important to consider species' traits like dispersal, mode of reproduction, population history, and more, when sampling from wild populations. **For this project, we focused on the genus Quercus, using IUCN Red List endangered oaks in the US as our species of interest.** Oaks are keystone species for many environments and have a high ecological importance. In addition, oaks cannot be seed banked using traditional methods, so they must be conserved through living collections. Since maintaining living collections requires extensive space and energy for gardens, creating efficient collections that represent the diversity of wild oak populations is extremely important. Thus, creating and maintaining genetically diverse collections in botanic gardens and arboreta is essential for the future survival and restoration of these rare, endangered species, and this can be achieved through proper sampling techniques. #### Summary We chose 16 species from the IUCN Red List of endangered species in the US. We create species-tailored parameter values to represent each species realistically in simulation, using the software Simcoal 2. We then created scripts with R that represent sampling from the simulated populations. Here, we test the entire range of sampling for each species--from one individual, to the entire population size. From this, we will be able to determine the minimum sample size required to capture 95% of the species’ genetic diversity (a common threshold for sufficient genetic diversity). With this data, we aim to recommend a minimum sample size to capture sufficient genetic diversity for each of these species, which would be directly useful to botanic gardens and arboreta. #### File types **Parameter files:** .par .txt Edited in text editor Notepad++ These are input to the software Simcoal/Simcoal2 to create genetic datasets The .par signifies parameter files. They contain information to create the genetic datasets via a coalescent simulation, including population sizes and migration rates. **Simulation output files:** .par .arp .gen .simparam Created through the software Simcoal2 after a parameter file is successfully imported into Simcoal2 and the simulation is run. The .arp files (genetic data) are the initial dataset in Arlequin format; the .gen files are the datasets after conversion to genepop format. The .simparam is just a mirror file of simulation parameters run. **Rscripts:** .R For this project, R scripts were used to import .arp files into R for conversion to .gen files through adegenet package, convert .gen files to genind objects through adegenet package, analyze data through functions associated with the adegenet package, run custom sampling scripts, and create figures for data visualization with package ggplot2 ### Directory contents Figures R_scripts Simulations