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 (
Plant genome size ranges widely, providing many opportunities to examine how genome size variation affects plant form and function. We analyzed trends in chromosome number, genome size, and leaf traits for the woody angiosperm clade
Chromosome counts and genome size estimates were mapped onto a
We discovered nine independent polyploidization events, two reductions in base chromosome number, and substantial variation in genome size with a slight trend toward genome size reduction in polyploids. We did not find strong relationships between genome size and the functional and morphological traits that have been highlighted at broader phylogenetic scales.
Polyploidization events were sometimes associated with rapid radiations, demonstrating that polyploid lineages can be highly successful. Relationships between genome size and plant physiological function observed at broad phylogenetic scales may be largely irrelevant to the evolutionary dynamics of genome size at smaller scales. The view that plants readily tolerate changes in ploidy and genome size, and often do so, appears to apply to
- NSF-PAR ID:
- 10381600
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- American Journal of Botany
- Volume:
- 107
- Issue:
- 11
- ISSN:
- 0002-9122
- Page Range / eLocation ID:
- p. 1527-1541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Asclepias spp.) 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. -
Abstract Aim Canopy structural complexity, which describes the degree of heterogeneity in vegetation density, is strongly tied to a number of ecosystem functions, but the community and structural characteristics that give rise to variation in complexity at site to subcontinental scales are poorly defined. We investigated how woody plant taxonomic and phylogenetic diversity, maximum canopy height, and leaf area index (LAI) relate to canopy rugosity, a measure of canopy structural complexity that is correlated with primary production, light capture, and resource‐use efficiency.
Location Our analysis used 122 plots distributed across 10 ecologically and climatically variable forests spanning a > 1,500 km latitudinal gradient within the National Ecological Observatory Network (NEON) of the USA.
Time period 2016–2018.
Taxa studied Woody plants.
Methods We used univariate and multivariate modelling to examine relationships between canopy rugosity, and community and structural characteristics hypothesized to drive site and subcontinental variation in complexity.
Results Spatial variation in canopy rugosity within sites and across the subcontinent was strongly and positively related to maximum canopy height (
r 2 = .87 subcontinent‐wide), with the addition of species richness in a multivariate model resolving another 2% of the variation across the subcontinent. Individually, woody plant species richness and phylogenetic diversity (r 2 = .17 to .44, respectively) and LAI (r 2 = .16) were weakly to moderately correlated with canopy rugosity at the subcontinental scale, and inconsistently explained spatial variation in canopy rugosity within sites.Main conclusions We conclude that maximum canopy height is a substantially stronger predictor of complexity than diversity or LAI within and across forests of eastern North America, suggesting that canopy volume places a primary constraint on the development of structural complexity. Management and land‐use practices that encourage and sustain tall temperate forest canopies may support greater complexity and associated increases in ecosystem functioning.
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Premise of the Study Plant traits are often associated with the environments in which they occur, but these associations often differ across spatial and phylogenetic scales. Here we study the relationship between microenvironment, microgeographical location, and traits within populations using co‐occurring populations of two closely related evergreen shrubs in the genus
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