Almost 15 years ago Wright et al. (Nature 428:821–827; 2004 – doi: 10.1038/nature02403) described the worldwide leaf economics spectrum “a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties.” Since then, an enormous number of articles have been published that examine or refer to it – more than 4000 according to Google Scholar. In the past few years, many authors have pointed out that it may not be as universal as originally presumed. For example, in Mitchell et al. (The American Naturalist 185:525-537; 2015 – http://www.jstor.org/stable/10.1086/680051) we found a negative relationship between an important component of the leaf economics spectrum (leaf mass per area) and mean annual temperature in Pelargonium from the Cape Floristic Region of southwestern South Africa, while the global pattern is for a positive relationship.1
Now Tim Moore and several of my colleagues follow up with a more detailed analysis of trait-environment relationships in Pelargonium. They demonstrate several ways in which the global pattern breaks down in South African samples of this genus. Here’s the abstract and a link to the paper.
- Functional traits in closely related lineages are expected to vary similarly along common environmental gradients as a result of shared evolutionary and biogeographic history, or legacy effects, and as a result of biophysical tradeoffs in construction. We test these predictions in Pelargonium, a relatively recent evolutionary radiation.
- Bayesian phylogenetic mixed effects models assessed, at the subclade level, associations between plant height, leaf area, leaf nitrogen content and leaf mass per area (LMA), and five environmental variables capturing temperature and rainfall gradients across the Greater Cape Floristic Region of South Africa. Trait–trait integration was assessed via pairwise correlations within subclades.
- Of 20 trait–environment associations, 17 differed among subclades. Signs of regression coefficients diverged for height, leaf area and leaf nitrogen content, but not for LMA. Subclades also differed in trait–trait relationships and these differences were modulated by rainfall seasonality. Leave‐one‐out cross‐validation revealed that whether trait variation was better predicted by environmental predictors or trait–trait integration depended on the clade and trait in question.
- Legacy signals in trait–environment and trait–trait relationships were apparently lost during the earliest diversification of Pelargonium, but then retained during subsequent subclade evolution. Overall, we demonstrate that global‐scale patterns are poor predictors of patterns of trait variation at finer geographic and taxonomic scales.
- If you read The American Naturalist paper, you’ll see that we wrote in the Discussion that “We could not detect a relationship between LMA and MAT in Protea….” I wouldn’t write it that way now. Look at Table 2. You’ll see that the posterior mean for the relationship is 0.135 with a 95% credible interval of (-0.078,0.340). I would now write that “We detected a weakly supported positive relationship between LMA and MAT….” Why the difference? I’ve taken to heart Andrew Gelman’s observation that “The difference between significant’ and ‘not significant’ is not itself statistically significant” (blog post; article in The American Statistician). I am training myself to pay less attention to which coefficients in a regression and which aren’t and more to reporting the best guess we have about each relationship (the posterior means) and the amount of confidence we have about them (the credible intervals). I recently learned about hypothesis() in brms, which will provide an estimate of the posterior probability that the you’ve got the sign of the relationship right. I need to investigate that. I suspect that’s what I’ll be using in the future. ↩