Data description:

Molecular dataset: final.gl.drop
A total of 207 lizards were captured during sampling trips across south west queensland and once individuals were genotyped for their chromosomal sex this amounted to: ZZf (n = 18), ZWf (n = 98), ZZm (n = 91). Reduced representation sequencing (Kilian et al., 2012) was used to genotype individuals in order to determine the levels of population genetic structure (as an indicator of gene flow) across the study area. Genomic DNA from tail tissue and blood samples was extracted using two DNA extraction methods appropriate for each sample type: (a) Qiagen's Gentra® Puregene® DNA purification kit for tail tips, or (b) Whatman Elute quick extraction protocol for blood on WhatmanTM FTATM Elute Cards. Specifically, DNA was extracted and sequenced and informative SNP markers identified using the commercial provider Diversity Arrays Technology (DArT Pty Ltd, Canberra, ACT, Australia, www.diveristyarrays.com). Briefly, SNP genotyping was performed using a combination of complexity reduction using restriction enzymes, implicit fragment-size selection and next-generational sequencing (Kilian et al., 2012). The restriction enzyme combination of PstI (recognition sequence 5’-CTGCA|G-3’) and SphI (5’-GCATG|C-3’) was used for complexity reduction by double digestion. Sequencies were processed using proprietary DArT analytical pipelines (Kilian et al., 2012) to yield SNPs that were polymorphic within the set of samples. Calling quality was assured by high average read depth per locus (medium coverage, average ca 10x). In addition, approximately one-third of samples were processed twice from DNA to allelic calls as technical replicates. Scoring consistency (repeatability) was used as the main selection criteria for high-quality and low error-rate markers. Sequences were then filtered using the R package dartR (v.1.1.11; Gruber et al., 2018). Loci were removed with a call rate of less than 95%, repeatability less than 99%, and if they were monomorphic across all individuals. Secondary SNPs, that is, SNPs residing on a single sequence tag, were filtered, retaining only one at random. All sex-linked loci were filtered.

Genomic data:

The script for analysis can be found under the folder name "R". Here you will find all models and their checks that were used to make figures and used in rmd file. Models from this file were saved and then used in Results_figures.Rmd.

Movement Data:

Average movement rate dataset : Movement.Rates.Winter_divided.csv
Reproduction movement rate dataset: reproductive.status.csv
MCP/KDE dataset: MCP.KDE.Morp.Summ.csv
Movement rate (m/d) was calculated as the straight-line distance between consecutive GPS locations divided by the number of days elapsed between relocations. The effect of season, sex class, and their interaction on movement rate was compared using the lmer function in the lme4 package (Bates et al., 2015) with individual lizard as a repeated (random) effect. To determine if reproductive status influenced female movement, within-individual variability of movement between gravid and non-gravid periods was compared by recording distance moved per day for gravid females (2 weeks pre/post lay date) with the distances moved while non-gravid (2-6 weeks post lay date). We then tested for the effect of reproductive status on distance moved per day (response variable) , with reproductive status (gravid or not gravid) as a fixed effect, and female ID as a repeated effect. We estimated space use only for animals that had a minimum of 15 GPS locations, and estimates were log10-transformed for both 100% MCP and 95% KDE to fit normality assumptions. The effect of season, sex class, body size (SVL/ cm) and their interaction on space use estimates was compared using the lmer function in the lme4 package with individual lizard as a repeated (random) effect. When results were significant, we followed with pairwise comparisons from emmeans package in R (Lenth et al., 2018). Interactions (sex class×season) or covariates (SVL/cm) for movement and space use estimates that were not significant were removed from further analysis.

Survivorship Data:

Season_updated.FPT
In cases where a tracked lizard was found dead, the date of death was determined using the last movement recorded by the accelerometer housed on the GPS units. Accelerometers recorded average changes in acceleration over a minimum of 120 s intervals. Maximum likelihood survival probabilities were estimated using known fate models in the program MARK (White & Garrott, 1999) and were compared using the Akaike Information Criteria (AICc). Models within < 2.0 were considered to have support. Time intervals were set seasonally (spring, summer, autumn, winter) and sex class was defined as the genotype and phenotype combination (ZZf, ZZm, ZWf). We started with a fully saturated model in which survival probability was dependent on sex class, body size (SVL/cm), mass (g), season (spring, summer, autumn, winter), and their interaction, then we fitted a series of reduced-parameters models.