skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: A direct comparison of ecological theories for predicting the relationship between plant traits and growth
Abstract Despite long‐standing theory for classifying plant ecological strategies, limited data directly link organismal traits to whole‐plant growth rates (GRs). We compared trait‐growth relationships based on three prominent theories: growth analysis, Grime's competitive–stress tolerant–ruderal (CSR) triangle, and the leaf economics spectrum (LES). Under these schemes, growth is hypothesized to be predicted by traits related to relative biomass investment, leaf structure, or gas exchange, respectively. We also considered traits not included in these theories but that might provide potential alternative best predictors of growth. In phylogenetic analyses of 30 diverse milkweeds (Asclepiasspp.) and 21 morphological and physiological traits, GR (total biomass produced per day) varied 50‐fold and was best predicted by biomass allocation to leaves (as predicted by growth analysis) and the CSR traits of leaf size and leaf dry matter content. Total leaf area (LA) and plant height were also excellent predictors of whole‐plant GRs. Despite two LES traits correlating with growth (mass‐based leaf nitrogen and area‐based leaf phosphorus contents), these were in the opposite direction of that predicted by LES, such that higher N and P contents corresponded to slower growth. The remaining LES traits (e.g., leaf gas exchange) were not predictive of plant GRs. Overall, differences in GR were driven more by whole‐plant characteristics such as biomass fractions and total LA than individual leaf‐level traits such as photosynthetic rate or specific leaf area. Our results are most consistent with classical growth analysis—combining leaf traits with whole‐plant allocation to best predict growth. However, given that destructive biomass measures are often not feasible, applying easy‐to‐measure leaf traits associated with the CSR classification appear more predictive of whole‐plant growth than LES traits. Testing the generality of this result across additional taxa would further improve our ability to predict whole‐plant growth from functional traits across scales.  more » « less
Award ID(s):
2209762
PAR ID:
10493737
Author(s) / Creator(s):
; ;
Publisher / Repository:
Ecology
Date Published:
Journal Name:
Ecology
Volume:
104
Issue:
4
ISSN:
0012-9658
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, Physiologia Plantarum)
    Abstract The leaf economics spectrum (LES) characterizes a tradeoff between building a leaf for durability versus for energy capture and gas exchange, with allocation to leaf dry mass per projected surface area (LMA) being a key trait underlying this tradeoff. However, regardless of the biomass supporting the leaf, high rates of gas exchange are typically accomplished by small, densely packed stomata on the leaf surface, which is enabled by smaller genome sizes. Here, we investigate how variation in genome size‐cell size allometry interacts with variation in biomass allocation (i.e. LMA) to influence the maximum surface conductance to CO2and the rate of resource turnover as measured by leaf water residence time. We sampled both evergreen and deciduousRhododendron(Ericaceae) taxa from wild populations and botanical gardens, including naturally occurring putative hybrids and artificially generated hybrids. We measured genome size, anatomical traits related to cell sizes, and morphological traits related to water content and dry mass allocation. Consistent with the LES, higher LMA was associated with slower water residence times, and LMA was strongly associated with leaf thickness. Although anatomical and morphological traits varied orthogonally to each other, cell size had a pervasive impact on leaf functional anatomy: for a given leaf thickness, reducing cell size elevated the leaf surface conductance and shortened the mean water residence time. These analyses clarify how anatomical traits related to genome size‐cell size allometry can influence leaf function independently of morphological traits related to leaf longevity and durability. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, New Phytologist)
    Summary Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO2and N input, alongside theoretical and ecological principles for modelling. N fertilisation increases leaf N content but inconsistently enhances leaf‐level photosynthetic capacity. Whole‐plant responses include increased leaf area and biomass, with reduced root allocation and increased aboveground biomass. Elevated atmospheric CO2also boosts leaf area and biomass but intensifies belowground allocation, depleting soil N and likely reducing N losses. Global leaf traits data confirm these findings, indicating that soil N availability influences leaf N content more than photosynthetic capacity. A demonstration model based on the functional balance hypothesis accurately predicts responses to N and CO2fertilisation on tissue allocation, growth and biomass, offering a path to reduce uncertainty in global C cycle projections. 
    more » « less
  3. ; ; ; (, AoB PLANTS)
    Kalcsits, Lee (Ed.)
    Abstract Many plant species form symbiotic associations with nitrogen-fixing bacteria. Through this symbiosis, plants allocate photosynthate belowground to the bacteria in exchange for nitrogen fixed from the atmosphere. This symbiosis forms an important link between carbon and nitrogen cycles in many ecosystems. However, the economics of this relationship under soil nitrogen availability gradients is not well understood, as plant investment toward symbiotic nitrogen fixation tends to decrease with increasing soil nitrogen availability. Here, we used a manipulation experiment to examine how costs of nitrogen acquisition vary under a factorial combination of soil nitrogen availability and inoculation with Bradyrhizobium japonicum in Glycine max L. (Merr.). We found that inoculation decreased belowground biomass carbon costs to acquire nitrogen and increased total leaf area and total biomass, but these patterns were only observed under low fertilization and were the result of increased plant nitrogen uptake and no change in belowground carbon allocation. These results suggest that symbioses with nitrogen-fixing bacteria reduce carbon costs of nitrogen acquisition by increasing plant nitrogen uptake, but only when soil nitrogen is low, allowing individuals to increase nitrogen allocation to structures that support aboveground growth. This pattern may help explain the prevalence of plants capable of forming these associations in less fertile soils and provides useful insight into understanding the role of nutrient acquisition strategy on plant nitrogen uptake across nitrogen availability gradients. 
    more » « less
  4. ; ; ; ; ; ; ; ; ; ; et al (, New Phytologist)
    Summary Nonstructural carbohydrate (NSC) concentrations might reflect the strategies described in the leaf economic spectrum (LES) due to their dependence on photosynthesis and respiration.We examined if NSC concentrations correlate with leaf structure, chemistry, and physiology traits for 114 species from 19 sites and 5 biomes around the globe.Total leaf NSC concentrations varied greatly from 16 to 199 mg g−1dry mass and were mostly independent of leaf gas exchange and the LES traits. By contrast, leaf NSC residence time was shorter in species with higher rates of photosynthesis, following the fast‐slow strategies in the LES. An average leaf held an amount of NSCs that could sustain one night of leaf respiration and could be replenished in just a few hours of photosynthesis under saturating light, indicating that most daily carbon gain is exported.Our results suggest that NSC export is clearly linked to the economics of return on resource investment. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, Journal of Ecology)
    Abstract Ensuring the sustainability of forest ecosystems requires understanding the mechanisms underlying tree growth and predicting their relative influence across taxa and environments.Functional ecology posits that variation in tree growth is related to individual differences in functional traits, which serve as proxies for resource acquisition and investment strategies. However, studies of trait–growth relationships have produced inconsistent results, likely due to unaccounted factors like interspecific interactions, ontogeny, differing leaf habit strategies, and variation in resource acquisition and allocation.We investigated the utility of key functional traits as predictors of tree height growth rates in common garden experiments in the absence of interspecific interactions. We posit that trait–growth relationships vary with age and between two groups relating to leaf habit: deciduous and evergreen species.Using data from 38 tree species planted in monoculture plots across seven sites of the International Diversity Experiment Network with Trees (IDENT) in North America and Europe, we compiled height growth rates over 9 years post‐germination. We modelled growth using a Bayesian hierarchical generalized linear model incorporating four above‐ground functional traits related to resource acquisition and investment: specific leaf area (SLA), wood density (WD), leaf dry matter content (LDMC) and seed mass (SM). Improvements in predictive power due to the variation of trait effects with age and leaf habit were evaluated via alternative hypothesis‐driven models, using the Expected Log Pointwise Predictive Density (ELPD) as a performance measure.Trait effects on growth varied with age and leaf habit, shifting between positive and negative effects, reflecting changes in resource acquisition and investment strategies. The relationships between traits and growth were strongest during the first three growing seasons for deciduous species and during the seventh to the ninth for evergreen species. Accounting for age and leaf habit substantially improved predictive power.Synthesis.Traits are not consistently associated with tree growth rates but instead reflect dynamic resource acquisition and investment strategies over time and between deciduous and evergreen species. Despite this variability, our findings confirm the utility of functional traits to predict tree growth rates, especially when trait effects are considered to vary with age and leaf habit. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Text Encoded Conversion
  • XML
  • Save / Share this Record
  • Send to Email