Traditional functional groups capture limited variation in the trait space of macroalgae

Abstract

Macroalgal (seaweed) beds and forests fuel coastal ecosystems and are rapidly reorganising under global change, but quantifying their functional structure still relies on binning species into coarse groups on the assumption that they adequately capture relevant underlying traits. To interrogate this “group gambit”, we first measured 12 traits relating to competitive dominance and resource economics across 95 macroalgal species collected from UK rocky shores. We then assessed trait variation explained by traditional grouping approaches consisting of (i) two highly-cited schemes based on gross morphology and anatomy and (ii) two commonly-used categorisations of vertical space use. To identify the limitations of traditional grouping approaches and to reveal potential alternatives, we also assessed the ability of (iii) emergent groups created from post hoc clustering of our dataset to account for macroalgal trait variation. (i) Traditional groups explained about a third of multivariate trait expression with considerable group overlap. (ii) Classifications of vertical space use accounted for even less multivariate trait expression. Notwithstanding considerable overlap, the canopy vs. turf scheme explained significant differences in most individual traits, with turf species tending to display attributes of opportunistic forms. (iii) Emergent groups were substantially more parsimonious than all existing grouping approaches. Synthesis: Our analysis using a comprehensive dataset of directly measured functional traits failed to strongly support the group gambit in macroalgae. While existing grouping approaches may allow first order approximations, they risk considerable loss of information at the trait and, potentially, ecosystem levels. We call for further development of a trait-based approach to macroalgal functional ecology to capture unfolding community and ecosystem changes with greater accuracy and generality.