Data from: Spatial replication is important for developing landscape genetic inferences for a wetland salamander
Data files
Jul 25, 2025 version files 583.21 MB
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coordinates.zip
4.63 KB
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fst.zip
7.60 KB
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README.md
2.62 KB
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SampleMetadata.csv
4.94 KB
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tif_files.zip
349.43 MB
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vcf_files.zip
233.76 MB
Abstract
Habitat fragmentation is one of the most pressing threats to wildlife populations. Maintenance of sustained dispersal and gene flow between populations is essential and often the end goal of conservation action. Use of resistance surfaces has emerged as an important strategy for developing conservation management strategies to mitigate the effects of habitat fragmentation (e.g., corridor design). However, recent studies have noted inconsistencies across study sites in the factors most strongly associated with genetic connectivity. Thus, replication of genetically based resistance surface optimization across landscapes may be necessary for making robust and generalizable conclusions about the influence of environmental variables on gene flow and for generating comprehensive predictions that can then be used by conservation practitioners in their focal landscape. In this study, we conducted replicated landscape genetic analyses across five sampling areas in Tennessee and Kentucky for a threatened wetland-obligate salamander, the four-toed salamander (Hemidactylium scutatum). We used genomic data to quantify fine-scale population structure in each of our study landscapes. We then tested multiple hypotheses of how different landscape features (e.g., canopy cover) influenced connectivity and gene flow. We found some concordance in the landscape features that were inferred to influence gene flow, but also some differences, potentially owing to the difference in variability of predictors at each site. Our work identifies landscape variables that may be important for H. scutatum conservation, and our replicated design allows us to identify important relationships that would have been missed if only using only one study site were used.
https://doi.org/10.5061/dryad.9kd51c5v6
Description of the data and file structure
To assess the influence of different landscape features on four-toed salamander gene flow, we generated genome-wide SNP data and used the R package radish. We assessed five different predictors at four different spatial resolutions using empirically generated FST matrices in a replicated landscape design, which included five study areas (Catoosa WMA [CWMA], the Great Smoky Mountains National Park [GSMNP], the Oak Ridge Reservation [ORR], Prentice Cooper State Forest [PCSF], and the Red River Gorge [RRG]).
Files and variables
SampleMetadata.csv:
Data associated with each four-toed salamander sample used in landscape genetic analyses
-Variables
- ID: identification code for the sample
- SiteCode: identification code from the sampling site
- Landscape: study landscape that the sample came from
coordinates.zip:
A folder containing files (.csv) with obscured (centered on 0,0) coordinates for each sampling site/wetland-(Catoosa WMA [CWMA], the Great Smoky Mountains National Park [GSMNP], the Oak Ridge Reservation [ORR], Prentice Cooper State Forest [PCSF], and the Red River Gorge [RRG]).
-Variables
- Code: identification code from the sampling site
- Latitude: obscured latitude of the sampling site
- Longitude: obscured longitude of the sampling site
tif_files.zip
A folder containing a raster (.tif) for every predictor at each landscape at each spatial resolution (total 100). For example, ORRCAN30 would represent canopy cover on the ORR at 30m resolution.
vcf_files.zip
A folder containing VCF files for each landscape ((Catoosa WMA [CWMA], the Great Smoky Mountains National Park [GSMNP], the Oak Ridge Reservation [ORR], Prentice Cooper State Forest [PCSF], and the Red River Gorge [RRG])) in the study. VCF files named "landscape_full.vcf" are input directly from ipyrad assembly. VCF files named "landscapeoneperlocus.vcf" have been filtered to only include one SNP per locus.
fst.zip
A folder containing Weir and Cockerham FST matrices for each study landscape (sites > 2 samples)-(Catoosa WMA [CWMA], the Great Smoky Mountains National Park [GSMNP], the Oak Ridge Reservation [ORR], Prentice Cooper State Forest [PCSF], and the Red River Gorge [RRG]).
Code/software
Code_for_analyses: We include a detailed pdf file that includes generalized code for ipyrad assembly, STRUCTURE, and R analyses.