Aim
To investigate how trait correlations between life stages associated with complex life cycles (aquatic nymph and terrestrial adult) shape the functional diversity and trait–environment relationships of European dragonflies (Odonata: Anisoptera).
Location
European mainland.
Time Period
Pre-1990 and post-1990.
Major Taxa Studied
Dragonflies (Odonata: Anisoptera).
Methods
Based on functional traits linked to dispersal and microhabitat preference, we use trait hypervolumes and structural equation modelling to estimate spatial and temporal trait correlations between terrestrial (adult) and aquatic (nymphal) life stages, and potential complex trait–environment relationships across life stages.
Results
Adult and nymphal functional diversity were positively correlated and trait variation between life stages did show reciprocal causality. Cross-lagged correlations showed that historical nymphal traits most strongly impacted present nymphal and adult diversity, suggesting that functional diversity patterns are influenced by carryover effects and differential selection pressures on nymphs relative to adults. Between the two life stages, we find both parallel and contrasting patterns between direct and indirect trait–environment relationships. The effect of mean annual temperature on adult trait diversity is largely driven by its positive correlation with nymphal traits. Positive nymphal trait correlations with habitat availability and topography are reducing the direct negative effects these variables have on adult trait diversity.
Main Conclusions
We show that constraints inherent to complex life cycles significantly influence functional diversity patterns in European dragonflies, creating indirect trait–environment relationships across life stages. Spatial patterns in functional diversity were determined by both life stages, not just adults or nymphs, via a combination of independent and interactive trait–environment relationships.
These findings challenge conventional functional biogeography models focused solely on direct environmental filtering. Consequently, integrating reciprocal trait relationships enhances causal claims when predicting functional biodiversity responses to environmental changes.
