Statistical analyses
Differences in fragment survivorship between source-recipient treatments were analysed with a chi-squared test at the end of the heat stress period (T2) and end of the recovery period (T4). Differences in 1) Shoot mortality per fragment, 2) herbivory impact, 3) C:N of leaves, 4) growth, 5) new leaf production and 6) total leaf length were each compared between treatments (n = 6) within discrete time periods using Analysis of variance (ANOVA). Normality was tested using Shapiro-Wilks test and Q-Q plots, and homogeneity of variance was tested with Levene’s test and residuals plot. No transformations were applied. Tukey-HSD analysis was used to examine differences between groups for significant main effects. To assess the relationship between thermal performance, source location and 1) maximum absolute realised temperature and 2) maximum thermal stress anomalies, linear mixed effects models were used using the lme4 package in R (Bates et al. 2015). Source location and temperature metric were treated as fixed effects and recipient location’ and ‘time point’ were treated as random effects, to account for differences in performance across locations and seasonality. Separate models were conducted for each temperature metric (i.e. max temperature or heat stress anomaly) and performance metric (i.e. growth, new leaf production and total leaf length) combination. We started with a full model based on a priori hypotheses about the inclusion of terms and higher order interactions. We identified the minimum adequate model by a stepwise removal of non-significant terms using likelihood ratio tests of the model with the effect in question against the model without the effect in question. Visual inspection of residual plots did not reveal any obvious deviations from homoscedasticity or normality and therefore no transformations were conducted. P-values were obtained by likelihood ratio tests of the full model with the effect in question against the model without the effect in question. All analyses were conducted in R (version 4.0.3, 10/10/2020).