Habitat variability in an underwater forest: Using a trait‐based approach to predict associated communities

Abstract

Abstract By providing food, living space and reducing biotic and abiotic stress, habitat‐formers support diverse communities. The characteristics that mediate their value to associated organisms, however, are not always clear. Traditional assessments of habitat‐former and associated community relationships use broad‐scale classifications to group habitat‐formers according to identity or gross morphology. Trait‐based approaches instead measure traits at the level of the individual and in doing so allow for predictions that are not constrained to taxonomic groups. By measuring at the level of the individual, trait‐based approaches have the potential to capture not only interspecific variability, but also the intraspecific variation that is often ignored by traditional approaches. Trait‐based approaches may therefore provide a novel way to link the characteristics of habitat‐formers to ecosystem functioning. Here we quantified inter‐ and intraspecific variation in six macroalgal species and tested the relative importance of morphological traits and species identity in predicting the abundance of associated fauna. All species of macroalgae displayed substantial intraspecific morphological variation. Morphological traits were more important than species identity in predicting epifaunal abundances. Total surface area was the most important trait when predicting total abundance per thallus, whilst mean frond length was the most important predictor for abundance per gram algal biomass. This suggests that traits that describe the quantity of available habitat were the most important predictors of community abundance, but the shape or architecture of the habitat also contributes to structuring these communities. Our results indicate that trait‐based approaches may be more useful than traditional species‐based approaches when predicting the abundances of fauna associated with habitat‐forming species. A free Plain Language Summary can be found within the Supporting Information of this article.