*library_books*

## Similar protocols

## Protocol publication

[…] We calculated amplification and genotyping rates on a per locus basis using data for multiplexes 1 and 2, because those were the only loci amplified for all scats. The remaining multiplexes were selectively applied to samples that were successfully amplified at the first two multiplexes; thus, their rates are likely positively biased.We accepted a genotype at an individual locus only if that genotype was observed in three independent PCRs. For putative homozygous genotypes, a single allele had to be observed in all PCRs in order to be accepted as homozygous. Once genotypes were identified at each locus, we generated a consensus multilocus genotype for every **scat**. Only scats that produced consensus genotypes at six different loci were included in further analyses, which minimized the probability (P < 10−6) of identifying siblings as the same individual.We used **GENALEX** (Peakall and Smouse ) to perform a matching analysis with these six locus genotypes to identify duplicate genotypes. To be grouped together as a single consensus genotype, scat genotypes had to match at a minimum of five loci. With these duplicate genotypes, we then generated composite genotypes representing unique animals in the population. We also used GENALEX to estimate deviation from Hardy–Weinberg equilibrium and measures of heterozygosity and allelic richness (the total number of alleles in the population) for each locus.We estimated pairwise relatedness (r) and inbreeding coefficients because we expected many of the individuals in this isolated, restricted population to be related. For relatedness we used two methods: the maximum‐likelihood method employed by ML‐Relate (Kalinowski et al. ) and the triadic likelihood estimator employed by COANCESTRY (Wang , ). We used the triadic likelihood method to estimate inbreeding coefficients (F) based on allele frequencies. The inbreeding coefficient, F, is the probability that an individual is homozygous (i.e., has two identical alleles) at any particular gene locus because its parents were related, that is, the alleles are identical by descent from a common ancestor. In these analyses, we utilized true allele frequencies with 100 simulated reference individuals and 100 bootstrapping replicates to estimate confidence intervals. We used GENALEX to estimate population level inbreeding (F
IS) to measure the extent of homozygous excess relative to allele frequencies, where F
IS is the proportion of the genetic variance in a subpopulation that is contained within an individual, and high F
IS values imply inbreeding. [...] We estimated the abundance of the present‐day bobcat population on Cumberland Island (23 years post‐reintroduction) using the spatially explicit capture–recapture population estimation program, secr (version 2.9.0, Efford et al. ) implemented in R (R Development Core Team ). We divided transects into 749 sections of 200 m each, and defined the coordinates of the midpoint of the transect section as the location of a proximity detector. The location of each scat was assigned to the nearest 200 m transect segment. Paths searched along the interdune meadow were not as well defined as along roads and differed upon each visit. Therefore, for interdune meadow transects, we plotted a single transect along the long axis of the habitat and assigned the location of each scat to the nearest transect (Fig. ). Although this introduced error in the location of scats, it was usually less than the transect segment length (200 m) because interdune meadow habitats were linear and generally <200 m wide.As a comparison to our mark–recapture population estimates, we estimated effective population size (N
e) to provide an indication of the effective number of bobcats that have contributed to the current gene pool. We used two methods implemented in program **NeEstimator** 2.01 (Do et al. ): one based on heterozygous excess (Pudovkin et al. ; Zhdanova & Pudovkin ) and a second based on molecular co‐ancestry (Nomura ). […]

## Pipeline specifications

Software tools | SCAT, GenAlEx, NeEstimator |
---|---|

Application | Population genetic analysis |

Organisms | Lynx rufus, Homo sapiens |