Evolutionary history and root trait coordination predict nutrient strategy in tropical legume trees.

Plants express diverse nutrient use and acquisition traits, but it is unclear how trait combinations at the species level are constrained by phylogeny, trait coordination, or trade-offs in resource investment. One trait - nitrogen (N) fixation - is assumed to correlate with other traits and used to define plant functional groups, despite potential confounding effects of phylogeny. We quantified growth, carbon metabolism, fixation rate, root phosphatase activity (RPA), mycorrhizal colonization, and leaf and root morphology/chemistry across 22 species of fixing and nonfixing tropical Fabaceae trees under common conditions. Belowground trait variation was high even among closely related species, and most traits displayed a phylogenetic signal, including N-fixation rate and nodule biomass. Across species, we observed strong positive correlations between physiological traits such as RPA and root respiration. RPA increased ~ fourfold per unit increase in fixation, supporting the debated hypothesis that N-fixers 'trade' N for phosphatases to enhance phosphorus acquisition. Specific root length and root N differed between functional groups, though for other traits, apparent differences became nonsignificant after accounting for phylogenetic nonindependence. We conclude that evolutionary history, trait coordination, and fixation ability contribute to nutrient trait expression at the species level, and recommend explicitly considering phylogeny in analyses of functional groupings.

Is variation in inter-annual precipitation a mechanism for maintaining plant metabolic diversity?

In order for diverse species to coexist in ecological communities, they must vary in ways that reduce competition. Often, this is done by some form of spatial niche separation where small differences in environment allow for coexistence among species. However, temporal separation of resources could also be a factor in driving community diversity. Here, we ask whether inter-annual variation in growing season precipitation could provide sufficient variation in water availability to allow plant species with different intrinsic metabolism to co-occur. We hypothesized that species would differentially respond to soil water availability, and that species with a metabolic strategy to conserve water at the expense of carbon gain would grow better in dry conditions relative to species with a metabolic strategy to gain carbon at the expense of foliar water loss. We measured above-ground biomass and leaf-level metabolism using carbon and oxygen stable isotope ratios for seven Asteraceae species across five experimental water treatments. Species differentially responded to variation in growing season water availability and, importantly, how they responded could be explained by differences in metabolism. Water-conservative species grew best in the dry treatments and had lower growth in wet treatments. Carbon-acquisitive species displayed the opposite pattern, with maximal growth in wet treatments and steep declines in dry treatments. Metabolic differences among co-occurring species may help explain temporal variation in growth, and could provide an underlying physiological mechanism for long-term dynamics that promote biodiversity.

Leaf stable isotopes suggest shared ancestry is an important driver of functional diversity.

Plant physiological strategies of carbon (C) and nitrogen (N) uptake and metabolism are often regarded as outcomes of environmental selection. This is likely true, but the role of evolutionary history may also be important in shaping patterns of functional diversity. Here, we used leaf C and N stable isotope ratios (δ13C, δ15N) as integrators of physiological processes to assess the relative roles of phylogenetic history and environment in a diverse group of Ericaceae species native to North America. We found strong phylogenetic signal in both leaf δ13C and δ15N, suggesting that close relatives have similar physiological strategies. The signal of phylogeny was generally stronger than that of the local environment. However, within some specialized environments (e.g., wetlands, sandy soils), we found environmental effects and/or niche conservatism. Phylogenetic signal in δ13C appears to be most closely related to the constraints on metabolic demand and supply of C, and δ15N appears to be most strongly related to mycorrhizal associations within the family.

A direct comparison of ecological theories for predicting the relationship between plant traits and growth.

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 (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.