Data analysis and REML
We filtered period estimates from Biodare2 to exclude rhythms with RAE>0.65 and period >28h as we found that rhythms beneath these cut-offs gave the most reliable period estimates. We next used restricted maximum likelihood (REML) to fit a linear mixed model to the 191 accession dataset and thus obtain accession means for period and RAE which were adjusted for the effects of cabinet and experimental run (see details in Extended Methods). An additional step was required to calculate phase means for each accession as the raw phase data is circular and relative to dawn (0) with a full circle representing 24 hours. Phase data was analysed with a circular regression model using the Genstat RCIRCULAR procedure to obtain accession mean phases adjusted for cabinet and run effects (Fisher & Lee, 1992).
For temperature experiments, no period or RAE cut-offs were imposed as we predicted an increase in both these variables with lower temperatures (Dodd et al., 2014; Rees et al., 2019). We fitted linear models to the period and RAE data and identified the contribution of each component by analysis of variance (Supplementary Tables 12-14). The above data analysis was done using Genstat 18th edition (RRID:SCR_014595).
Map figures (Figure 2 and 4) were created using the ggmaps package in R using Google maps (2018) (Kahle & Wickham, 2013).