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

Martin A Wilkes,Wilco C E P Verberk,Nikolai Friberg,Philippe Usseglio‐Polatera,Judy England,Jon Webb,J Iwan Jones,François Edwards,Lee E Brown,N Leroy Poff,Daniel Hering,John F Murphy

doi:10.1111/gcb.15344

Abstract

The growing use of functional traits in ecological research has brought new insights into biodiversity responses to global environmental change. However, further progress depends on overcoming three major challenges involving (a) statistical correlations between traits, (b) phylogenetic constraints on the combination of traits possessed by any single species, and (c) spatial effects on trait structure and trait-environment relationships. Here, we introduce a new framework for quantifying trait correlations, phylogenetic constraints and spatial variability at large scales by combining openly available species' trait, occurrence and phylogenetic data with gridded, high-resolution environmental layers and computational modelling. Our approach is suitable for use among a wide range of taxonomic groups inhabiting terrestrial, marine and freshwater habitats. We demonstrate its application using freshwater macroinvertebrate data from 35 countries in Europe. We identified a subset of available macroinvertebrate traits, corresponding to a life-history model with axes of resistance, resilience and resource use, as relatively unaffected by correlations and phylogenetic constraints. Trait structure responded more consistently to environmental variation than taxonomic structure, regardless of location. A re-analysis of existing data on macroinvertebrate communities of European alpine streams supported this conclusion, and demonstrated that occurrence-based functional diversity indices are highly sensitive to the traits included in their calculation. Overall, our findings suggest that the search for quantitative trait-environment relationships using single traits or simple combinations of multiple traits is unlikely to be productive. Instead, there is a need to embrace the value of conceptual frameworks linking community responses to environmental change via traits which correspond to the axes of life-history models. Through a novel integration of tools and databases, our flexible framework can address this need.

Highlights

Trait-based ecology uses the phenotypic characteristics of organisms to study biodiversity responses to environmental change
Our re-analysis of these data suggests that trait-based ecologists should think carefully about which traits to include in large-scale analyses, especially when occurrence-based functional diversity (FD) indices are of interest
We have shown how three major challenges in largescale trait-based ecology can be better understood using openly available ecological, phylogenetic and environmental data

Summary

| INTRODUCTION

Trait-based ecology uses the phenotypic characteristics of organisms to study biodiversity responses to environmental change. To make further progress, there are at least three major challenges that need to be overcome when working at the largest scales These challenges involve (a) statistical correlations between trait, (b) phylogenetic constraints on the combination of traits possessed by any single species, and (c) spatial effects on trait structure (occurrence probability- or abundance-weighted means of traits in a community) and trait–environment relationships (statistical links between trait structure and environmental variables). By combining openly available environmental data and species' occurrence, trait and phylogenetic records with computational modelling, we establish a new, generalized analytical framework for quantifying trait correlations, phylogenetic constraints and spatial variability at large scales. We discuss present capabilities and recommend future directions in trait-based ecology

| MATERIALS AND METHODS

| RESULTS AND DISCUSSION

| CONCLUSIONS