DOI: 10.5061/dryad.m4f17
title: Data from: Ecological resistance surfaces predict fine scale genetic differentiation in a terrestrial woodland salamander

description: Landscape genetics has seen tremendous advances since its introduction,
 but parameterization and optimization of resistance surfaces still poses
 significant challenges. Despite increased availability and resolution of
 spatial data, few studies have integrated empirical data to directly
 represent ecological processes as genetic resistance surfaces. In our
 study, we determine the landscape and ecological factors affecting gene
 flow in the western slimy salamander (Plethodon albagula). We used field
 data to derive resistance surfaces representing salamander abundance and
 rate of water loss through combinations of canopy cover, topographic
 wetness, topographic position, solar exposure, and distance from ravine.
 These ecologically-explicit composite surfaces directly represent an
 ecological process or physiological limitation of our organism. Using
 generalized linear mixed effects models, we optimized resistance using a
 non-linear optimization algorithm to minimize model AIC. We found clear
 support for the resistance surface representing the rate of water loss
 experienced by adult salamanders in the summer. Resistance was lowest at
 intermediate levels of water loss and higher when the rate of water loss
 was predicted to be low or high. This pattern may arise from the
 compensatory movement behavior of salamanders through suboptimal habitat,
 but also reflects the physiological limitations of salamanders and their
 sensitivity to extreme environmental conditions. Our study demonstrates
 that composite representations of ecologically-explicit processes can
 provide novel insight and can better explain genetic differentiation than
 ecologically-implicit landscape resistance surfaces. Additionally, our
 study underscores the fact that spatial estimates of habitat suitability
 or abundance may not serve as adequate proxies for describing gene flow,
 as predicted abundance was a poor predictor of genetic differentiation.
description: abundRaw '.asc'
 file of salamander abundance. Abundance values were calculated as
 described in Peterman WE, Semlitsch RD (2013) Fine-scale habitat
 associations of a terrestrial salamander: the role of environmental
 gradients and implications for population dynamics. PLoS ONE 8,
 e62184.ad_spring_rateRaw '.asc' file of water loss rates experienced by adult salamanders during the springad_summer_rateRaw '.asc' file of water loss rates experienced by adult salamanders during the summerjv_summer_rateRaw '.asc' file of water loss rates experienced by juvenile salamanders during the summerjv_spring_rateRaw '.asc' file of water loss rates experienced by juvenile salamanders during the springmaxtRaw '.asc' file of maximum surface soil temperature. Temperatures were predicted using hierarchical mixed effects models from data collected using iButton data loggersndviRaw '.asc' file of canopy cover (NDVI)prrRaw '.asc' file of Potential Relative Radiation (PRR). This is a measure of the average amount of solar exposure any point on the landscape gets, accounting for solar elevation, slope of the land surface, aspect of the land, and hillshade effectsrav_distRaw '.asc' file of distance to ravine. Ravines were designated based on flow accumulation analyses of a 3-m resolution DEM surfacetpiRaw '.asc' file of Topographic Position Index (TPI), calculated relative to the surrounding 90m using a 3-m resolution DEMtwiRaw '.asc' file of Topographic Wetness Index (TWI), calculated based on flow accumulation and solar exposure.PLAL_GenePopGenePOP format of microsatellite genotype data