DOI: 10.5061/dryad.0k6djh9x8
title: Precipitation and vegetation shape patterns of genomic and craniometric variation in the Central African rodent Praomys misonnei

description: Predicting species capacity to respond to climate change is an essential
 first step in developing effective conservation strategies. However,
 conservation prioritization schemes rarely take evolutionary potential
 into account. Ecotones provide important opportunities for diversifying
 selection and may thus constitute important reservoirs of standing
 variation, increasing the capacity for future adaptation. Here we map
 patterns of environmentally-associated genomic and craniometric variation
 in the central African rodent Praomys misonnei to identify areas with the
 greatest turnover in genomic composition. We also project patterns of
 environmentally-associated genomic variation under future climate change
 scenarios to determine where populations may be under the greatest
 pressure to adapt. While precipitation gradients influence both genomic
 and craniometric variation, craniometric variation is also affected by
 changes in vegetation structure. Areas of elevated
 environmentally-associated genomic and craniometric variation overlap with
 zones of rapid ecological transition underlining their importance as
 reservoirs of evolutionary potential. We find that populations in the
 Sanaga river basin, central Cameroon and coastal Gabon are likely to be
 under the greatest pressure from climate change. Lastly, we make specific
 conservation recommendations on how to protect zones of high evolutionary
 potential and identify areas where populations will be the most
 susceptible to climate change.
description: Genomic DNA was extracted from 132 individuals, sampled from 10
 populations across Gabon and Cameroon. The genomic data was generated
 using Restriction
 Site-Associated DNA sequencing
 (rad-seq). Processing of RAD-seq
 data was carried out using the Stacks v 1.48 pipeline
 (Catchen et al. 2013).
 SNPs were called running STACKS with the following parameters: m=3, M=3,
 n=4. Rare
 SNPs with a minor allele frequency (MAF) of 0.05 or below were filtered
 and discarded. The remaining SNPs were further filtered to include only a
 single, randomly selected SNP for each RAD
 locus.
 Morphometric data
 was generated from 169 individuals sampled from 10 populations across
 Gabon and Cameroon. The skull was extracted from sampled individuals and
 preserved in 70% ethanol. Each skull was
 photographed and digitized using Image J (Klingenberg). Homologous
 landmarks were chosen to cover all functional areas of the skull,
 including 20 landmarks on the dorsal surface and 16 landmarks on the
 ventral surface. The effects of size, position and orientation were
 removed, and covariance matrices describing shape variation were generated
 from the resulting Procrustes shape coordinates. Principal Components
 Analysis (PCA) was used to summarise inter-individual shape variation and
 the first three principal components describing dorsal and ventral shape
 variation were
 retained.
description: The genomic data is stored in a VCF file
 ("m3M3n4_allpops_FinalSNPset.vcf"). The GPS coordinates for
 sampling localities are stored in a separate text file
 ("GPS_coords.txt"). The morphometric data
 includes raw landmark data ("Dorsal_Raw_skull_data.csv" and
 "Ventral_Raw_skull_data.csv") as well as the first three
 principal components describing each of dorsal
 ("Dorsal_PCscores.csv") and ventral
 ("Ventral_PCscores.csv") skull shape.