Trait-based ecology at large scales: Assessing functional trait correlations, phylogenetic constraints and spatial...

Area of Science:

• Ecology
• Biodiversity Research
• Environmental Change

Background:

• Functional traits offer insights into biodiversity responses to global environmental change.
• Progress is hindered by statistical trait correlations, phylogenetic constraints, and spatial effects.
• Existing methods struggle to integrate these factors effectively at large scales.

Purpose of the Study:

• To introduce a novel framework for quantifying trait correlations, phylogenetic constraints, and spatial variability.
• To develop a computational approach combining trait, occurrence, phylogenetic, and environmental data.
• To provide a flexible tool applicable across diverse taxonomic groups and habitats.

Main Methods:

• Combined openly available species' trait, occurrence, and phylogenetic data.
• Integrated gridded, high-resolution environmental layers with computational modelling.
• Applied the framework to freshwater macroinvertebrate data from 35 European countries.

Main Results:

• Identified a subset of traits (resistance, resilience, resource use) less affected by correlations and phylogenetic constraints.
• Observed that trait structure responded more consistently to environmental variation than taxonomic structure.
• Demonstrated that functional diversity indices are sensitive to the traits included in their calculation.

Conclusions:

• Emphasize the need for conceptual frameworks linking community responses to environmental change via life-history traits.
• Suggest that single traits or simple combinations are insufficient for predicting trait-environment relationships.
• Advocate for the use of integrated tools and databases to address complex ecological questions.