Seaweed functional diversity revisited: confronting traditional groups with quantitative traits

1. 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. 2. To
interrogate this ‘group gambit’, we measured 12 traits relating to
competitive dominance and resource economics across 95 macroalgal species
collected from the UK and widespread on North-East Atlantic rocky shores.
We assessed the amount of trait variation explained by commonly-used
traditional groups – (i) two schemes based on gross morphology and anatomy
and (ii) two categorisations of vertical space use – and examined species
reclassification into post hoc, so-called emergent groups arising from the
functional trait dataset. We then offer an alternative, emergent grouping
scheme of macroalgal functional diversity. 3. (i) Morphology and
anatomy-based groups explained slightly more than a third of multivariate
trait expression with considerable group overlap (i.e. low precision) and
extensive mismatch with underlying trait expression (i.e. low accuracy).
(ii) Categorisations of vertical space use accounted for about a quarter
of multivariate trait expression with considerable group overlap.
Nonetheless, turf species tended to display attributes of opportunistic
forms. (iii) A nine-group emergent scheme provided a highly explanatory
and parsimonious alternative to traditional functional groupings. 4.
Synthesis: Our analysis using a comprehensive dataset of directly measured
functional traits revealed a general mismatch between traditional groups
and underlying traits, highlighting the deficiencies of the group gambit
in macroalgae. While existing grouping schemes may allow first order
approximations, they risk considerable loss of information at the trait
and, potentially, ecosystem levels. Instead, 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.