Functional groups are widely used to reduce complexity and generalize across ecological communities. These models assume that shared traits among species correspond to some ecological role, process or function, and that these traits can be leveraged to generate meaningful and distinct functional groups so that intergroup trait variation exceeds intragroup variation. We sought to validate the assumptions of the widely used functional group model (FGM) for marine macroalgae, which groups species based on morphological complexity, by testing the predictions of the FGM for several traits assumed to correspond with morphological complexity. The FGM predicts increased resistance to disturbance and herbivory as morphological complexity (tensile strength and thallus toughness, respectively) increases. The FGM also predicts a trade‐off between complexity and growth rate. To test predictions, we measured (a) thallus toughness (force to penetrate), (b) tensile strength (force to break) and (c) relative growth for both tropical and temperate macroalgae from different functional groups. Thallus toughness followed model predictions at the functional group level, though there was significant variability among species. However, the model did not predict tensile strength at any level for either tropical or temperate macroalgae. Furthermore, relative growth did not follow predictions; rather it was highly variable among species and functional groups. Synthesis. The assumptions of the FGM that differences in morphological complexity can be used to generate distinct functional groups and that intergroup trait variation outweighs intragroup variation were violated, providing strong evidence that individual species responses need to be considered. Furthermore, violations of assumptions indicate that functional groups should not be used to predict community responses to ecological drivers and/or species contributions to ecosystem function. Our study challenges the usefulness of functional form groups for marine macroalgae and emphasizes the need for a different conceptual framework.

While trait‐based approaches have been effectively leveraged by plant ecologists to advance our understanding of community responses to major global challenges, such as climate change and invasive species, the study of marine macroalgae is still mired in a functional group (FG) framework developed in the 1980s. In this paper, we used predominantly categorical data for 18 macroalgal traits that were accessible in public databases and/or the literature to explore their usefulness in a trait‐based framework for marine macroalgae. Species were clustered into emergent, data‐driven groups using a Gower dissimilarity matrix, then a k‐medoid clustering approach called partitioning around the medoids. We identified 14 emergent groups (EGs) that captured a spectrum of strategies used by different macroalgal species. However, significant ‘gaps’ in trait space may identify evolutionary constraints to algal adaptive strategies. Multivariate analysis showed how the 18 traits created trait space and drove the clustering. A spectrum of strategies and the influence of multiple traits imply that algal strategies are likely governed by complex multivariate, not bivariate, trade‐offs. Finally, we found that our EGs appeared to reflect multivariate trade‐offs and diverse ecological strategies more than the traditional FG model for macroalgae. We tested the usefulness of our EGs by comparing real‐world spatial distributions of species across habitats with known strong environmental filters to their area occupied in trait space. We found significant separation in trait space and divergent occupancy patterns across global distributions, attachment substrates and elevational zones. These results support the use of categorical data accessible in the literature as a useful step towards developing trait‐based ecology for marine macroalgae. Synthesis. Our findings indicate that readily accessible categorical traits produce emergent FGs that reflect environmental filtering and therefore demonstrate the power of trait‐based approaches over the current FG framework. Furthermore, we posit that categorical traits are a valuable and potentially complementary addition to a newly developing database of continuous traits because they encompass a broader, more globally accessible set of traits.

Rhodolith distribution, morphology, and cryptofauna have been minimally studied on fringing reefs. We present the first study to examine both rhodolith distribution and associated cryptofauna in a tropical fringing reef, located along the microtidal, wave-dominated north shore of Moorea, French Polynesia. We find higher abundances of larger, rounder, and more branching rhodoliths in locations where longer waves impact the fringing reef. Among 1879 animals extracted and identified from 145 rhodoliths, ophiuroids, polychaetes, decapod crustaceans, and gastropods are most abundant, with a wide range of additional taxa contributing to diversity. Large and branching rhodoliths contain the greatest number and diversity of cryptofaunal organisms and are the preferred habitat of rigid-bodied, non-burrowing forms. Overall, exposure to waves entering the lagoon through passes appears to be a critical determinant of rhodolith abundance, morphotype, and in turn cryptofaunal composition in fringing reef habitats.

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Trait‐based ecology (TBE) has proven useful in the terrestrial realm and beyond for collapsing ecological complexity into traits that can be compared and generalized across species and scales. However, TBE for marine macroalgae is still in its infancy, motivating research to build the foundation of macroalgal TBE by leveraging lessons learned from other systems. Our objectives were to evaluate the utility of mean trait values (MTVs) across species, to explore the potential for intraspecific trait variability, and to identify macroalgal ecological strategies by clustering species with similar traits and testing for bivariate relationships between traits. To accomplish this, we measured thallus toughness, a trait associated with resistance to herbivory, and tensile strength, a trait associated with resistance to physical disturbance, in eight tropical macroalgal species across up to seven sites where they were found around Moorea, French Polynesia. We found interspecific trait variation generally exceeded intraspecific variation across species. Furthermore, MTV within species varied across sites, suggesting future research should focus on whether these traits are influenced by site‐specific differences in biotic and abiotic drivers. Species grouped into three clusters representing different ecological strategies: species that were defended against herbivores but not strong, species that were strong but not defended and species that were neither. Intraspecific standardized major axis regressions revealed five species exhibited significant or marginally significant positive relationships between these two traits, suggesting trait syndromes within species. Only one species exhibited a significant intraspecific trade‐off, as indicated by a negative regression slope. Synthesis. Our results point to three key takeaways that should provide a foundation to rapidly advance development of TBE for macroalgae in the future. First, our evidence supports the use of MTVs for macroalgae. Second, we identified significant spatial variability in macroalgal traits that may indicate an ability to respond to shifting environmental drivers. Third, measuring even a few traits can be a powerful tool to identify different ecological strategies to resist disturbances such as herbivory and removal by wave action. We hope these novel findings motivate future research into a wider suite of macroalgal traits, functions and strategies to further develop trait‐based approaches for marine macroalgae.