DOI: 10.5061/dryad.wm37pvmtx
title: Data from: Deforestation limits evolutionary rescue under climate change in Amazonian lizards

description: Aim: The impact of climate change on biodiversity is often analyzed under
 a stable evolutionary perspective focused on whether species can currently
 tolerate warmer climates. However, species may adapt to changes, and
 particularly under conditions of limited fragmentation, adaptive genetic
 variation can spread across populations tracking changing climates, a
 process termed evolutionary rescue.  Here, our aim is to
 integrate genomic data, niche modeling, and landscape ecology to predict
 range shifts and the potential for evolutionary rescue. Location: the
 megadiverse Amazonian rainforest Methods: We use genome-environment
 association analyses to search for candidate loci under environmental
 selection, while accounting for neutral genetic variation in a widespread
 Amazonian whiptail lizard (Teiidae: Kentropyx calcarata). We then model
 the distribution of individuals with genotypes adapted to different
 climate conditions. Finally, we predict range shifts in distinct future
 climate change scenarios by integrating this information with dispersal
 constraints based on predicted scenarios of forest cover across Amazonia.
 Results: We find that the potential for evolutionary rescue and,
 therefore, a smaller degree of range loss buffering extinction risk in the
 future is considerably high, provided that current forest cover is
 retained and climate change is not extreme. However, under extreme
 environmental change scenarios, range loss will be high in central and
 southern Amazonia, irrespective of the degree of deforestation. Main
 Conclusions: Our results suggest that protecting the Amazonian rainforest
 against further deforestation and mitigating climate change to moderate
 scenarios until 2070 could foster evolutionary rescue. These actions could
 prevent substantial biodiversity loss in Amazonia, emphasizing the
 importance of understanding species adaptability in maintaining
 biodiversity.
description: We sampled individuals of <em>K. calcarata</em> in
 Amazonia, the Atlantic Forest, and the Cerrado savannas (information on
 specimens, museums, and localities are available in Supporting
 Information, Table S1). We extracted genomic DNA from
 each sample (liver and muscles) using the
 Macherey-Nagel<sup>®</sup> Mini Kit with a high salinity
 protocol with proteinase K. We then visualized fragment sizes in agarose
 gels and measured DNA concentration and quality with Qubit™ 3.0
 Fluorometer and Nanodrop, selecting only samples with a low degree of DNA
 fragmentation and normalizing the concentration to 20 ± 2 ng DNA for each
 50 μl solution (TE buffer). RAD-sequence library preparation (as detailed
 in Etter et al., 2011) was then performed by Floragenex, Inc. (Eugene, OR,
 USA). Individual samples were digested with the SbfI enzyme, linked with
 barcoded RAD ligators, multiplexed, sonicated, and then size-selected to a
 range within 300-500 bp. After PCR amplification, DNA sequencing was
 performed on a 2x100bp Illumina HiSeq platform. This procedure resulted in
 ~8,400,000 reads per individual with a length of 100 base pairs. We
 deposited the demultiplexed raw-sequencing data in the Sequence Read
 Archive (details to be provided upon acceptance).  We
 demultiplexed and assigned the reads for each sample and performed a
 <em>de novo</em> assembly and SNP calling using iPyrad 0.9.55
 (Eaton & Overcast, 2020), checking the quality of demultiplexed
 samples using MultiQC (Ewels et al., 2016). For the iPyrad pipeline, we
 allowed one mismatch from individual barcodes, clustering the reads of
 each sample (minimum size of 35 base pairs) and across the samples
 (<em>de novo</em> assembly), sequence coverage of 6x, and
 minimum Phred score of 33. We selected a minimum clustering threshold of
 0.90 after testing values from 0.85 to 0.95 for missingness and number of
 recovered SNPs (McCartney-Melstad et al., 2019). We allowed a maximum of
 two alleles and a maximum proportion of 0.5 for heterozygous sites per
 locus, including only loci present in 75% of the individuals.
description: # Deforestation limits evolutionary rescue under climate change in
 Amazonian lizards
 [https://doi.org/10.5061/dryad.wm37pvmtx](https://doi.org/10.5061/dryad.wm37pvmtx) SNPs recovered from iPyrad library prepation.This repository hosts the filtered SNP dataset (using VCPtools) and specimen metadata used to explore evolutionary rescue in *Kentropyx calcarata* populations across Amazonia. These files are ready for the first steps of the genomic analyses in R (e.g. population genetics, genome environment association analyses). #### Data files | Filename | Size | Description | | -------------------------------------- | ------ | ------------------------------------------------------------------------------------------ | | `ken_calcarata090_1SNP-locus.012` | 4.4 MB | Genotype matrix (one SNP per locus) in IPYRED “.012” format | | `ken_calcarata090_1SNP-locus.012.pos` | 420 KB | Marker positions: chromosome/scaffold and base‐pair coordinates | | `ken_calcarata090_1SNP-locus.012.indv` | 503 B | Sample list: one row per individual, in the same order as the `.012` matrix | | `coordinates.csv` | 9 KB | Specimen metadata: individual IDs and their collection‐site latitude/longitude coordinates | #### File details 1. **Genotypes** (`.012`) * Filtered with VCFtools * Retained only one biallelic SNP per RAD locus * Rows = samples; columns = SNPs 2. **Positions** (`.012.pos`) * Two columns: `chromosome` and `base_position` * Matches SNP columns in `.012` 3. **Individuals** (`.012.indv`) * Single‐column list of sample IDs * Matches rows in `.012` 4. **Coordinates** (`coordinates.csv`) * Columns: * `sample_id` * `latitude` * `longitude` * Use for geographic analyses or spatial plotting