Genome size and species distribution: HMSC model
The HMSC model showed a good fit to the data, with a mean Tjur
R2 of 61% for explanatory power and 14% for
predictive power. We observed both positive and negative associations
with species occurrences for each variable (Fig. 4a). In our HMSC model,
parameter ρ, the strength of the phylogenetic signal, was 0.1 in median,
with the 95% confidence interval between 0.0 and 0.3 (overlap with
zero), suggesting that species niches (i.e. their responses to the
environmental covariates) showed no phylogenetic correlations. We then
calculated the community weighted mean (CWM) genome size against
environmental covariates by using predicted occurrences from the HMSC
model (Fig. 4b). This is because using CWMs based on raw occurrence data
in regressions can be subject to type I error (Miller et al.2019). The model approach to analyse trait–environment associations
with community data maximizes power and information contained in the
data (Brown et al. 2014; Miller et al. 2019). CWM of
genome size was greater in communities from those sites with higher
resource availability, supporting our hypothesis that alleviating
resource (water and nutrient) limitation would favour large-GS species.
Altitude was a poor predictor for CWM of genome size while MAT was
negatively correlated with CWM of genome size. Previous studies also
found that low temperature favours large-GS plants because the large-GS
species gain an advantage in frost resistance (Grime & Mowforth 1982;
MacGillivray & Grime 1995).