Effects of hunting on mating, relatedness, and genetic diversity in a puma population
Data files
Dec 06, 2023 version files 65.25 GB
Abstract
Hunting mortality can affect population abundance, demography, patterns of dispersal and philopatry, breeding, and genetic diversity. We investigated the effects of hunting on the reproduction and genetic diversity in a puma population in western Colorado, USA. We genotyped over 11,000 single nucleotide polymorphisms (SNPs), using double-digest, restriction site-associated DNA sequencing (ddRADseq) in 291 tissue samples collected as part of a study on the effects of hunting on puma population abundance and demography in Colorado from 2004−2014. The study was designed with a reference period (years 1−5), during which hunting was suspended, followed by a treatment period (years 6−10), in which hunting was reinstated. Our objectives were to examine the effects of hunting on: (1) paternity and male reproductive success; (2) the relatedness between pumas within the population, and (3) genetic diversity. We found that hunting reduced the average age of male breeders. The number of unique fathers siring litters increased each year without hunting and decreased each year during the hunting period. Mated pairs were generally unrelated during both time periods, and females were more closely related than males. Hunting was also associated with increased relatedness among males and decreased relatedness among females in the population. Finally, genetic diversity increased during the period without hunting and decreased each year when hunting was present. This study demonstrates the utility of merging demographic data with large-scale genomic datasets in order to better understand the consequences of management actions. Specifically, we believe that this study highlights the need for long-term experimental research in which hunting mortality is manipulated, including at least one non-harvested control population, as part of a broader adaptive, zone management scheme.
README: Effects of hunting on mating, relatedness, and genetic diversity in a puma population
https://doi.org/10.5061/dryad.bnzs7h4hm
Included is: the raw sequencing data, VCF files and Plink outputs for both the paternity analyses dataset and the overall dataset, and an excel spreadsheet with necessary sample information.
Description of the data and file structure
As described in the paper, this is ddRAD-seq data. There is raw sequencing data from four separate libraries. Samples are divided into 6 different folders to reduce file sizes. The first library was sequenced on a HiSeq4000 machine using 100 bp single-end sequencing. The remaining 3 libraries were sequenced on a HiSeq4000 machine using 150 bp paired-end sequencing. The raw sequence data has been demultiplexed and trimmed to the standard 95 bps.
Two separate datasets were used in the study and the VCF files for each dataset are included here. For the full dataset used in all analyses other than the paternity analyses, we removed loci that were sequenced in less than 75% of individuals (-- geno 0.25). Then we removed samples that had more than 50% missing data (-- mind 0.5). Finally, we filtered out all loci with a minor allele frequency less than 0.01 (-- maf 0.01). For the paternity analyses dataset, we removed loci that were sequenced in less than 90% of individuals (-- geno 0.1), samples that had more than 70% of missing data (-- mind 0.7), and loci with a minor allele frequency less than 0.3 (-- maf 0.3). Additionally, we removed loci that were not in Hardy-Weinberg proportions (--hwe 0.005 using the p midpoint adjustment). Finally, we used Plink to create a blacklist and subsequently remove loci that were found to be in statistical linkage disequilibrium (r > 0.2) using a proxy filter (--indep-pairwise 50 5 0.2).
The Excel spreadsheet has all relevant metadata on sequence ID, sample number, sex, birth year, and death year.
Sharing/Access information
Some samples, denoted as "*_CSU_lib_trim95" in the spreadsheet, were downloaded from: Trumbo, Daryl R et al. (2019). Urbanization impacts apex predator gene flow but not genetic diversity across an urban-rural divide [Dataset]. Dryad. https://doi.org/10.5061/dryad.12jm63xsr.
Code/Software
No special code was utilized.