Exploring intraspecific and interspecific variation of coral reef algae using a novel trait-based framework

The development of trait-based approaches has accelerated our understanding of how communities assemble, respond to environmental change, and may best be managed in the Anthropocene. Understanding the magnitude and pattern of interspecific variability forms a critical underpinning of trait-based approaches while exploring intraspecific variability can identify the potential of species to adapt to changing environmental drivers. Our work is motivated by the critical need for a novel conceptual framework for understanding the functional ecology of macroalgae, as the current paradigm is still mired in functional group models developed in the 1980s.

Our objective was to quantify interspecific and intraspecific functional trait variability in three common and morphologically diverse species of tropical marine macroalgae by exploring traits relating to the ecological functions of resource acquisition, resistance to herbivory, and resistance to physical disturbance and the tradeoffs between them.

We quantified intraspecific and interspecific variability of 11 functional traits for three common and morphologically diverse species of tropical macroalgae from five fringing reefs of Mo’orea, French Polynesia that were likely to capture a wide range of environmental variability. Differences in traits among species and sites were determined with PERMANOVA, visualized with NMDS, and tradeoffs between pairs of traits explored with correlation. Finally, spatial patterns among select traits across all species were quantified.

Species clustered together in distinctly different trait spaces driven by tradeoffs among suites of functional traits. Two of three species had considerable intraspecific variability, though this variability occurred at different scales, while one clustered tightly. Exploration of individual traits across species and sites revealed tradeoffs between two strategies for resource acquisition, growing tall and strong vs investing in large surface area.

Synthesis: We captured novel patterns of interspecific and intraspecific variability for tropical marine macroalgae. We found fundamental differences in traits between species that may represent ecological strategies while considerable intraspecific variability demonstrates a wide range in abilities to respond to environmental drivers. Overall, our work provides novel insights into intra and interspecific trait variation that form an essential underpinning for using a trait-based framework in a taxon that is increasingly dominant on tropical reefs.

Methods
We chose three macroalgal species from Class Phaeophyceae, Padina boryana, Sargassum pacificum, and Turbinaria ornata (hereafter referred to by genus name) due to their abundance on fringing reefs of Mo’orea. We chose five fringing reefs along the north shore of Mo’orea, French Polynesia that differ in their structure and orientation to wind and current. Three reefs (Public Beach Ta’ahiamanu East and West and the Gump Station) are patch reefs within bays that are more sheltered from wave action. Two other reefs (Hilton Resort (patch reef) and Maharepa (continuous reef)) are along the more exposed north shore. Surface flows in the lagoon are driven by waves generated by the prevailing northeasterly trade winds and the diurnal sea breeze.  

All macroalgal individuals were collected between 20 January and 5 February at each of the five fringing reef sites at depths ranging from approximately 0.25 to 3m. Twenty samples of each species were collected from each site (N=300). To capture the full range of inter and intraspecific variability in traits, individual macroalgal thalli were randomly collected across all habitats in this depth range, including hard bottom, coral rubble, and the shallow tops of dead coral heads on the reef slope, crest, flat, and backreef. When possible, we ensured a minimum distance of 10-15m between collected individuals. We only collected individuals that appeared healthy and intact. Collections were stored in flow-through water tables and traits were measured within 12 hours. 

TH was measured with a ruler from the bottom of the holdfast to the top of the longest branch. WW was measured on a scale after spinning thalli for 60 seconds in a salad spinner to remove a consistent amount of surface water. V was measured as the displacement of water in a graduated cylinder. SA of Padina and Sargassum was calculated on Adobe Photoshop from photographs of individuals or subsamples laid flat on a white background with a ruler; subsamples were scaled to whole individuals. Turbinaria SA was approximated by splitting the thallus into simple geometric shapes, taking measurements with a ruler, calculating appropriate surface areas of each shape, and adding them together. For DW, thalli were rinsed of salts and dried in a drying oven at < 60oC until constant weight. BN was counted on whole or subsamples of individuals, subsamples were scaled to whole individuals. For Sargassum and Turbinaria BWW, five randomly selected blades were weighted, averaged, and multiplied by blade number for the final value. For Padina, BWW was the W after the holdfast was removed. BT was measured as resistance to piercing by a penetrometer. For Padina, measurements were taken 1cm from the apical ridge. For Turbinaria and Sargassum, five blades were randomly chosen and pierced and these values were averaged. TS was measured by attaching the thallus to a spring scale and pulling on the thallus until it broke.

Statistical Analysis 

We conducted a PERMANOVA (dissimilarity method: Bray, 999 permutations) to detect differences in trait distributions due to species, location, and interaction. NMDS visualised the distribution of individuals in trait space and a loading plot illustrated how the functional traits drove this distribution. Ellipses enclose groups of individuals separated by site and species using the 50% confidence interval of the SD. We used Pearson’s correlation to explore bivariate tradeoffs.  

We conducted post hoc univariate analysis on five selected traits: TH, SA, SA:DW, BT and TS. We were unable to normalise our data through transformation. Thus, we used GLMs with a gamma distribution to test for differences among traits with species and site as fixed effects.