The leaf economics spectrum (LES) describes multivariate correlations that constrain leaf traits of plant species primarily to a single axis of variation if data are normalized by leaf mass. We show that these traits are approximately distributed proportional to leaf area instead of mass, as expected for a light- and carbon dioxide-collecting organ. Much of the structure in the mass-normalized LES results from normalizing area-proportional traits by mass. Mass normalization induces strong correlations among area-proportional traits because of large variation among species in leaf mass per area (LMA). The high LMA variance likely reflects its functional relationship with leaf life span. A LES that is independent of mass- or area-normalization and LMA reveals physiological relationships that are inconsistent with those in global vegetation models designed to address climate change.

SignificanceLeaf traits, such as photosynthetic capacity, nitrogen concentration, and leaf mass per area, strongly affect plant growth and nutrient cycles. Understanding relationships among leaf traits is, therefore, a fundamental challenge in plant biology, crop science, and ecology. Different groups of leaves exhibit distinct relationships among pairs of traits. For example, photosynthetic capacity per unit leaf area increases strongly with leaf mass per area from sun to shade within species, but these same traits are only weakly related across global species. Our analysis suggests that divergent trait relationships can be understood by partitioning leaf mass into photosynthetic and structural support components. Our paper clarifies the causes of relationships among traits and why those relationships differ among different groups of plants.

Summary1. Plant functional traits are important determinants of survival and fitness, and wood density (WD) is a key trait linked to mechanical stability, growth rates and drought-and shade-tolerance strategies. Thus, rigorous WD estimates are necessary to identify factors affecting tree performance. 2. We obtained 1766 records of WD from the literature for 141 tree species in the United States. We implemented a hierarchical Bayesian (HB) meta-analysis that incorporated sample size, variance, covariate (e.g. moisture content and latewood proportion) and methodological information to obtain standardized estimates of WD for 305 U.S. tree species. The HB framework allowed 'borrowing of strength' between species such that WD estimates for data-poor species were informed by data-rich species via taxonomic or phylogenetic relationships. 3. After accounting for important covariates and sampling effects, evaluation of the residual variation revealed the potential importance of environmental factors and evolutionary history. Differential variation in WD between species within genera and between genera within orders suggested that WD is relatively conserved in some genera and orders, but not in others. WD also varied between studies (or sites) indicating the potential influence of edaphic, topographic, or population factors on intraspecific variation in WD. 4. Synthesis. Our hierarchical Bayesian approach overcomes many of the limitations of traditional meta-analyses, and the incorporation of phylogenetic or taxonomic information facilitates estimates of trait values for data-poor species. We provide relatively well-constrained WD estimates for 305 tree species, which may be useful for tree growth and forest models, and the uncertainties associated with the estimates may inform future sampling campaigns.

The ability to down-regulate leaf maximum net photosynthetic capacity (Amax) and dark respiration rate (Rdark) in response to shading is thought to be an important adaptation of trees to the wide range of light environments that they are exposed to across space and time. A simple, general rule that accurately described this down-regulation would improve carbon cycle models and enhance our understanding of how forest successional diversity is maintained. In this paper, we investigated the light response of Amax and Rdark for saplings of six temperate forest tree species in New Jersey, USA, and formulated a simple model of down-regulation that could be incorporated into carbon cycle models. We found that full-sun values of Amax and Rdark differed significantly among species, but the rate of down-regulation (proportional decrease in Amax or Rdark relative to the full-sun value) in response to shade was not significantly species- or taxon-specific. Shade leaves of sun-grown plants appear to follow the same pattern of down-regulation in response to shade as leaves of shade-grown plants. Given the light level above a leaf and one species-specific number (either the full-sun Amax or full-sun Rdark), we provide a formula that can accurately predict the leaf's Amax and Rdark. We further show that most of the down regulation of per unit area Rdark and Amax is caused by reductions in leaf mass per unit area (LMA): as light decreases, leaves get thinner, while per unit mass Amax and Rdark remain approximately constant.