DOI: 10.5061/dryad.gxd2547sf
title: VCF files and regression analyses for: Assessing fine-scale pondscape connectivity with amphibian eyes: an integrative approach using genomic and capture-mark-recapture data

description: In the face of habitat loss, preserving functional connectivity is
 essential to maintain genetic diversity and the demographic dynamics
 required for the viability of biotic communities. This requires knowledge
 of the dispersal behavior of target species, which can be modeled as
 kernels, or probability density functions of dispersal distances at
 increasing geographic distances. We present an integrative approach to
 investigate the relationships between genetic connectivity and demographic
 parameters in organisms with low vagility focusing on five syntopic
 pond-breeding amphibians. We genotyped 1,056 individuals of two anuran and
 three urodele species (1,732–3,913 SNPs per species) from populations
 located in a landscape comprising 64 ponds to characterize fine-scale
 genetic structure in a comparative framework and combined this genetic
 data with information obtained in a previous two-year
 capture-mark-recapture (CMR) study. Specifically, we contrasted graphs
 reconstructed from genomic data with connectivity graphs based on
 dispersal kernels and demographic information obtained from CMR data from
 previous studies and assessed the effects of population size, population
 density, geographical distances, inverse movement probabilities and the
 presence of habitat patches potentially functioning as stepping stones on
 genetic differentiation. Our results suggest a significant influence of
 local population sizes on patterns of genetic connectivity at small
 spatial scales. In addition, movement records and cluster-derived kernels
 provide robust inferences on most likely dispersal paths that are
 consistent with genomic inferences on genetic connectivity. The
 integration of genetic and CMR data holds great potential for
 understanding genetic connectivity at spatial scales relevant to
 individual organisms, with applications for the implementation of
 management actions at the landscape level.
description: The vcf files available in this dataset were obtained from tissue
 samples from five syntopic pond-breeding amphibian species:
 <em>Epidalea calamita</em>, <em>Triturus
 pygmaeus</em>, <em>Pelophylax perezi</em>,
 <em>Lissotriton boscai </em>and <em>Pleurodeles
 waltl</em>. All species were sampled in the same study area, a
 dehesa pondscape located in the municipality of Alpedrete, Madrid, Spain.
 Tissue samples consisted in finger clips plus fin clips for
 <em>Lissotriton boscai</em>. Tissue was digested with
 proteinase K and DNA was extracted with the Promega Wizard Kit. Libraries
 were prepared using 3RAD and size selection was performed with Pippin Prep
 prior to sequencing. Sequenced reads were treated with Stacks to obtain
 the vcf files. Geographic-, demographic- and movement-related information
 were obtained in a previous study performed in the same spatial and
 temporal frame. Genetic distances, available as genetic matrices were
 obtained with EDENetworks, using filtered .vcf files from ponds with at
 least 4 individuals.
description: # VCF files and regression analyses for "Assessing fine-scale
 pondscape connectivity with amphibian eyes: an integrative approach using
 genomic and capture-mark-recapture data"
 [https://doi.org/10.5061/dryad.gxd2547sf](https://doi.org/10.5061/dryad.gxd2547sf) ## Description of the data and file structure This dataset contains both "raw" unfiltered vcfs files obtained using the Stacks pipeline and R scripts for regression analyses using maximum-likelihood population effects models. In these models, genetic distance is used as response variable and several demographic, geographic and movement related variables as explanatory variables. Data for explanatory variables were obtained in a previous work. The study area is divided in half by a road; analyses were performed with and without cross-road connections between ponds. Scripts that exclude cross-road connections are identified by the suffix "*\_no\_crossroad*". Scripts and all necessary data are compressed in a .rar file for each species so that no treatment of the files or working directory setting is needed. Just open the R script from its own folder and run it. Five .rar files are provided, one for each species. Inside each .rar file you may find, depending on the species: \- a \.csv file with the suffix "*\*distances*", which contains a vector of the movement distances, in meters, of all displacements recorded for each species. This information is used to generate dispersal kernels. \- a "*extrainfo.txt*" file which contains information on the pond in which each individual was sampled ("POND" column) and the area of the study site where that pond is found ("SIDE" column). The column for individual IDs is titled "node\_label". \- a \.csv file with the prefix "*nodes\**", which contains information of each of the ponds (Pond IDs are listed in the "POOL" column), specifically, the area of the study site in which each is found ("SIDE" column), their geographic location (longitude and latitude in the "X" and "Y" columns respectively), water surface area in square meters ("area" column) and the estimated population of the species of interest (in the column named as the abbreviation of the species (see abbreviations below). For example, for the forlder that contains the Pelophylax perezi script and data, the column that contains population size is called "PP"). \- Two R scripts containing the analyses\, one of them not accounting for crossroad connections\, marked with a "*\_no\_crossroad*" prefix. \- a "*squarematrix.txt*" file, containing genetic distances between populaltions. \- a "*squarematrix.ind.txt*" file, containing the names of the pond IDs for the "*squarematrix.txt*" file. Some abbreviations used: EC or IEC: *Epidalea calamita* PP or IPP: *Pelpophylax perezi* PW or IPW: *Pleurodeles waltl* TP or ITP: *Triturus pygmaeus* LB or ILB: *Lissotriton boscai* Abbreviations used in the ## Sharing/Access information Demographic, geographic and movement data was obtained in a previous work: https://link.springer.com/article/10.1007/s10980-022-01520-x