Data and source code from "Estimating inbreeding rates in natural populations: addressing the problem of incomplete pedigrees"

We used Monte Carlo simulations to compare properties of the two estimators and determine their utility for empirical analyses. Simulations were performed using idealized populations that were tracked over 15 generations. Separate simulations were performed using generation sizes of 100 individuals (50 male and 50 females) or 20 individuals (10 males and 10 females). In each generation, parents for new individuals were chosen using a simple set of rules. Individuals in the first generation were created de novo with no parental information, and second generation progeny were created as offspring of first generation parents. Starting with the third generation, a parent for an individual was selected with equal probability from either of the previous two generations, thereby allowing for inbreeding to arise from intergenerational pairings (parent-offspring, uncle-niece, and aunt-nephew). Use of this strategy eliminated the possibility for grandparent-grandchild pairs to form, however, our results were nonetheless generalizable and easily interpreted. Inbreeding rates were controlled by introducing a parameter that specified the width of a spatial window that determined the number of potential male and female parents for each new individual created in each generation. The widest window size was determined by generation size, and could maximally be set to one half of the generation size (equal to the number of males or females) to allow for random selection of any male or female parent from an appropriate generation. When window sizes were less than the maximum window size, higher inbreeding rates were produced as a consequence of restricting the number of potential parents. Thus, observed inbreeding rates recorded for simulations were emergent properties of the simulation as opposed to pre-specified parameters.