Applying continuous functional traits to large brown macroalgae: variation across tidal emersion and wave exposure gradients

Abstract

A functional trait-based approach seeks a general understanding of organism -environment interactions, but, among primary producers, its empirical basis rests on vascular plants. We hypothesised that with increasing intertidal elevation, traits of large brown macroalgae would reflect a resource-acquisition vs. conservation (stress tolerance) trade-off at species and community levels. Across the elevation gradient at four UK sites of varying wave exposure, we: i) screened species' relevant morphological traits, using principal component analysis to reduce dimensionality; and ii) up-scaled species' traits using community weighted trait means (CWMs). The first principal component (PC1) strongly related to specific thallus area and thallus dry matter content, representing an acquisition -conservation trade-off. Although species generally shifted to the conservative end of this axis as elevation increased, mid-shore Ascophyllum nodosum sat at the extreme conservative end. PC2 associated with holdfast ratio, thickness and length, with A. nodusum scoring higher than other mid-shore species. CWMs of PC1 decreased with elevation at two sites indicating a shift from 'fast' to 'slow' ecosystem functioning, but this relationship was disrupted by A. nodusum at the sheltered site, and by the up-shore extent of Laminaria digitata at the most exposed site. The anomalous traits of A. nodusum reflect its unique competitive strategy (slow, persistent growth) in the relatively stressful mid-shore. Seaweed functional traits show promise in linking species' identities to their strategies and ecosystem contributions. However, because resource conservation traits can be related to competitive as well as stress tolerance strategies, predicting seaweed trait responses to environmental stress gradients is challenging.

Seaweed functional diversity revisited: Confronting traditional groups with quantitative traits

“…As an alternative to direct use of trait values, we also provide a nine‐group emergent scheme, potentially simplifying field and analytical methods, while still allowing meaningful measurements of functional diversity (Chapin et al., 1996; Chen et al., 2017; Díaz & Cabido, 2001). Although intraspecific variation was relatively small in our dataset—and in a previous study where large brown seaweeds were sampled across sites of contrasting wave exposure (Cappelatti et al., 2019)—care should be taken when applying the trait data at sites with unusual conditions (e.g. very sheltered sea loughs) or in regions distant from the UK (e.g.…”

“…Traits a–g relate to photosynthesis and/or structural integrity, and hence, position on the economics spectrum: (a) Thallus Dry Matter Content (TDMC) is the ratio between dry and wet mass and represents the proportion of structural compounds and water‐filled—and therefore mainly photosynthetically active—tissues (Elger & Willby, 2003; Littler & Littler, 1981; Schonbeck & Norton, 1979). (b) Thickness also increases with the amount of structural tissue, providing resistance to physical stress and herbivore grazing (Cappelatti, Mauffrey, & Griffin, 2019; Littler & Littler, 1980; Littler, Taylor, & Littler, 1983); (c) Carbon (C) content and its ratio with (d) Nitrogen (N) content, (e) C:N, more directly quantify recalcitrant structural compounds relative to N‐rich photosynthetically active tissues (Cornelissen et al., 2003; Weykam et al, 1996). Analogously to Specific Leaf Area (Wilson, Thompson, & Hodgson, 1999), (f) specific thallus area (STA), obtained by dividing surface area by dry mass, captures light‐ and nutrient‐ absorbing surfaces and increases with the extent of low density, water‐filled, photosynthetically active tissues relative to recalcitrant, structural compounds (Littler & Littler, 1980).…”

When form does not predict function: Empirical evidence violates functional form hypotheses for marine macroalgae

“…This framework was originally developed for terrestrial vegetation (Chapin, 1993; Eviner & Chapin, 2003; Grime, 1974; McGill et al., 2006; Voille et al., 2007; Wright et al., 2004) to understand mechanisms of community assembly and ecosystem functioning, but has been increasingly applied to other taxa such as marine phytoplankton (Edwards et al., 2013; Litchman & Klausmeier, 2008) and terrestrial fauna (García‐Llamas et al., 2019). There have been some promising recent efforts in this direction for marine macroalgae (Cappelatti et al., 2019; Jänes et al., 2017; Mauffrey et al., 2020; Stelling‐Wood et al., 2020), with functional traits successfully predicting in macroalgal productivity (Jänes et al., 2017) and associated community structure (Stelling‐Wood et al., 2020), as well as providing stronger links with macroalgal strategies and functions (Cappelatti et al., 2019; Mauffrey et al., 2020). However, more work is needed to understand which traits are most informative for macroalgal eco‐physiology and function.…”

Macroalgal germplasm banking for conservation, food security, and industry

“…A major obstacle to the creation of an extensive and viable macroalgal germplasm bank rests on the documentation and understanding of the genetic variation in coastal macroalgal communities and how genotype influences each organisms' phenotype and its functional importance within the ecosystem. Maintaining biodiversity within a marine macroalgal ecosystem necessitates observing key interactions within a community to identify those species that provide invaluable ecological services [81] and maintaining that biodiversity and functional variation in macroalgal germplasm banks [82]. Loss of seaweed genetic diversity through poor commercial breeding programs has led to yield declines globally [62,63,83,84]; therefore, maintaining wild or "heirloom" strains is critical for continued yield success of cultured seaweed and for maintaining diversity and ecosystem function globally.…”