The evaluation of the habitat suitability models revealed ‘fair’ predictions for six species, ‘good’ for height and ‘excellent’ for two of the 16 species modelled in Guisane, and ‘good’ for four and ‘excellent’ for one of the five species in Anzeindaz (see the electronic supplementary material, table S1).
The three measured traits presented strong intraspecific variability. For example, Hmax was particularly variable, with species' coefficients of variation (CVs) between 0.19 and 0.49, while LDMC (CV in 0.08–0.25) and LNC (CV in 0.09–0.29) tended to be less variable (see the electronic supplementary material, table S2).
Overall, the link between predicted habitat suitability and functional traits was species- and trait-specific (). In general, the link between habitat suitability and Hmax was positive (e.g. Leucanthemum vulgare, ). For some species, there were no relationships between predicted habitat suitability and any trait (e.g. Festuca paniculata, Rhododendron ferrugineum). Interestingly, Vaccinium myrtillus had a positive relationship between habitat suitability and Hmax in the French site but a negative one in the Swiss site. The sign of the relationship between habitat suitability and LNC or LDMC was species-specific (). For instance, variation of LNC of Dactylis glomerata was negatively correlated to variation in habitat suitability in both Swiss and French sites, while it was strongly positively correlated for Polygonum viviparum (). The same pattern emerges for LDMC with a strong negative correlation between habitat suitability and LDMC for Carex sempervirens in the French site () and a strong positive one for V. myrtillus in the Swiss site ().
Variation in species' functional traits against variation in species’ habitat suitability. (a) Maximum height of C. sempervirens, (b) leaf nitrogen content of P. viviparum and (c) leaf dry matter content of L. vulgare.
The strength of the covariation between predicted habitat suitability and trait expression was not related to the accuracy (AUC) of the habitat suitability model (p > 0.05).