Leaf:wood allometry and functional traits together explain substantial growth rate variation in rainforest trees

Abstract

Plant growth rates drive ecosystem productivity and are a central element of plant ecological strategies. For seedlings grown under controlled conditions, a large literature has firmly identified the functional traits that drive interspecific variation in growth rate. For adult plants, the corresponding knowledge is surprisingly poorly understood. Until recently it was widely assumed that the key trait drivers would be the same (e.g. specific leaf area, or SLA), but an increasing number of papers has demonstrated this not to be the case, or not generally so. New theory has provided a prospective basis for understanding these discrepancies. Here we quantified relationships between stem diameter growth rates and functional traits of adult woody plants for 41 species in an Australian tropical rainforest. From various cost-benefit considerations, core predictions included that: (i) photosynthetic rate would be positively related to growth rate; (ii) SLA would be unrelated to growth rate (unlike in seedlings where it is positively related to growth); (iii) wood density would be negatively related to growth rate; and (iv) leaf mass:sapwood mass ratio (LM:SM) in branches (analogous to a benefit:cost ratio) would be positively related to growth rate. All our predictions found support, particularly those for LM:SM and wood density; photosynthetic rate was more weakly related to stem diameter growth rates. Specific leaf area was convincingly correlated to growth rate, in fact negatively. Together, SLA, wood density and LM:SM accounted for 52 % of variation in growth rate among these 41 species, with each trait contributing roughly similar explanatory power. That low SLA species can achieve faster growth rates than high SLA species was an unexpected result but, as it turns out, not without precedent, and easily understood via cost-benefit theory that considers whole-plant allocation to different tissue types. Branch-scale leaf:sapwood ratio holds promise as an easily measurable variable that may help to understand growth rate variation. Using cost-benefit approaches teamed with combinations of leaf, wood and allometric variables may provide a path towards a more complete understanding of growth rates under field conditions.

Applying the economic concept of profitability to leaves

“…Higher benefits have been suggested for species with large leaves, for example species with larger leaves tend to deploy branches with a higher ratio of leaf area to stem dry mass 29 , which itself could be associated with a higher growth rate 24 , 30 and therefore profitability. However, there are also disadvantages for species with large leaves, for example, higher within-leaf support costs reflected in their higher leaf mass per area (LMA) 29 , 31 , 32 , and more structural and less metabolic tissue 32 , 33 , or an increased risk of overheating or frost damage 24 .…”

Convergent Variations in the Leaf Traits of Desert Plants

“…Desert plants show adaptive variations in such types of extreme arid environments [ 37 ]; as well as adaptations and evolution for the long term in desert plants make them able to develop some special structures and strategies for their survival [ 93 ]. For example, plant species with rich contents of leaf N and P generally grow faster [ 94 ], and hence changes in the concentrations of leaf traits can be related to the physiological demand of plant species [ 19 ]. However, soil moisture and temperature also can affect the uptake of N and its utilization by plants [ 95 ].…”

Can Trait-Based Schemes Be Used to Select Species in Urban Forestry?

“…Even traits that are well-recognised, such as Specific Leaf Area (SLA) present paradoxes in that they can be highly plastic but nevertheless repeatedly trade off against or correlate with other traits (such as Relative Growth Rate or Leaf Lifespan) (Sancho-Knapik et al, 2020) and explain fundamental dimensions of plant variation (Pierce et al, 2013). Further, traits appear to vary in the extent to which they are plastic or under genetic control (Saccone et al, 2017;Walker et al, 2017), whilst others have been shown to vary in significance over time (Gray et al, 2019) leading to changing relationships between traits as plants age (Gibert et al, 2016;Falster et al, 2018). These conceptual challenges are compounded by the characteristics of data that are used to develop theoretical advances: whilst major databases are being developed (Kattge et al, 2011(Kattge et al, , 2020Salguero-Gómez et al, 2015;Maitner et al, 2018) that can advance macro-ecological questions, data are patchy in terms of species covered and traits measured, making it difficult to find sufficient traits for a species in order to ordinate them within a scheme.…”