Extended Data Fig. 6: Distribution of and relationship between S_space and S_time among species sampled within narrow latitudinal bands.

These analyses included 157 species with 200 or more specimens collected within a latitudinal band of 1° (~111 km) in the continental United States (analogous to Fig. 2 of the main text). Light blue and red shaded regions in (a) respectively correspond to the kernel-density distributions of S_space and S_time among the 157 species included in the analysis. The solid black line in (b) indicates a 1:1 relationship corresponding to perfect agreement between the two types of sensitivity. The solid curved line indicates the line of best fit obtained from a Generalized Additive Model (GAM) of S_time vs. S_space, with the shaded area around it denoting the standard error of the predicted mean value. Each point in (b) represents a species whose x, y coordinates are given by the maximum a posteriori (MAP) estimates for S_space and S_time, respectively. Point shapes and colours in (b) indicate whether sensitivity patterns were consistent with plasticity or adaptation as the sole drivers of flowering time variation along the temperature gradient, with both plasticity and adaptation having significant effects in a co- or counter-gradient adaptation pattern, or not showing statistically significant adaptation nor plasticity. The straight, solid black line in (b) indicates a 1:1 relationship (that is, S_space = S_time), whereas the curved solid line shows the observed relationship estimated from a generalized additive model (GAM). The shaded region along the curved solid line in (b) corresponds to the standard error of the predicted value of S_time. The percent of species showing each pattern is shown in the legend in parenthesis. The 95% credible interval for the correlation between S_space and S_time is provided as a text inset in (b). Both temperature and photoperiod are known to be the predominant environmental cues controlling both vegetative and reproductive phenology among plants in temperature regions. Therefore, across latitudinal ranges such as those spanned by most species in our data (median latitudinal range = ca. 12.2°), it is possible that differences in S_time and S_space (for example, geographic temperature gradients) might reflect the confounding influence of latitudinal shifts in photoperiod on our estimates of sensitivity to TMEAN_Normal. To account for this possibility, we identified 157 species in our data that were well sampled (200 or more specimens) within narrow latitudinal bands (≤1°). Using this subset of species and including only specimens from such 1° bands, we ran the model presented in the main text, obtaining estimates of S_time and S_space and their difference for each species and an estimate of their correlation accounting for parameter uncertainty. The results did not qualitatively differ from those presented in the main text, with a high correlation between S_space and S_time and similar relative frequencies of each sensitivity pattern among species.