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  1. All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal,Annu. Rev. Plant Biol., 68, 513–534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth–defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipolliniet al.,Annual Plant Reviews(Wiley, 2014), pp. 263–307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth–defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunneret al.,Funct. Ecol.33, 7–12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

     
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  2. Summary

    Concurrent measurement of multiple foliar traits to assess the full range of trade‐offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment.

    We analyzed leaf trait measurements from 32 sites along the wide eco‐climatic gradient encompassed by the US National Ecological Observatory Network (NEON). We explored the relationships among 14 foliar traits of 1103 individuals across and within species, and with environmental factors.

    Across all species pooled, the relationships between leaf economic traits (leaf mass per area, nitrogen) and traits indicative of defense and stress tolerance (phenolics, nonstructural carbohydrates) were weak, but became strong within certain species. Elevation, mean annual temperature and precipitation weakly predicted trait variation across species, although some traits exhibited species‐specific significant relationships with environmental factors.

    Foliar functional traits vary idiosyncratically and species express diverse combinations of leaf traits to achieve fitness. Leaf spectroscopy offers an effective approach to quantify intra‐species trait variation and covariation, and potentially could be used to improve the characterization of vegetation in Earth system models.

     
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  3. Summary

    The ability to tolerate neighboring plants (i.e. degree of competitive response) is a key determinant of plant success in high‐competition environments. Plant genotypes adjust their functional trait expression under high levels of competition, which may help explain intra‐specific variation in competitive response. However, the relationships between traits and competitive response are not well understood, especially in trees. In this study, we investigated among‐genotype associations between tree trait plasticity and competitive response.

    We manipulated competition intensity in experimental stands of trembling aspen (Populus tremuloides) to address the covariance between competition‐induced changes in functional trait expression and aspects of competitive ability at the genotype level.

    Genotypic variation in the direction and magnitude of functional trait responses, especially those of crown foliar mass, phytochemistry, and leaf physiology, was associated with genotypic variation in competitive response. Traits exhibited distinct plastic responses to competition, with varying degrees of genotypic variation and covariance with other trait responses.

    The combination of genotypic diversity and covariance among functional traits led to tree responses to competition that were coordinated among traits yet variable among genotypes. Such relationships between tree traits and competitive success have the potential to shape stand‐level trait distributions over space and time.

     
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  4. Abstract

    Expression of herbivore defense traits can change dramatically during the course of plant development. Little is known, however, about the degree of genetic or sexual variation in these ontogenetic defense trajectories or whether the trajectories themselves are adaptive, especially in long‐lived species.

    We used a 13‐year dataset of chemical defense traits, growth and survivorship from a common garden of trembling aspen (Populus tremuloides) genotypes to document long‐term defense trajectories and their relationship to tree fitness during juvenile and early mature stages.

    Overall, concentrations of the two principal classes of aspen defense compounds (salicinoid phenolic glycosides [SPGs] and condensed tannins [CTs]) decreased to differing degrees in foliage of juvenile trees and then remained relatively constant in maturity. Initial values, juvenile rates of change and average mature values all exhibited significant genetic variation for both SPGs and CTs.

    Relationships between defense trajectory parameters and metrics of tree fitness (growth and survivorship) depended on compound type and tree sex. Females with higher‐allocation SPG trajectories (high initial juvenile concentrations, slow juvenile declines, high mature concentrations) grew more slowly relative to females with lower‐allocation trajectories. In males, higher‐allocation SPG trajectories had a lesser effect on growth but were associated with reduced mortality. Juvenile CT trajectories were not correlated with tree fitness, but average CT concentration in maturity was positively related to growth in females.

    These results suggest that ontogenetic defense trajectories are adaptive and subject to natural selection. Genotypic variation and ontogeny shape tree defensive chemistry, both independently and interactively. These patterns of defense expression have the potential to structure trophic interactions and the genetic composition of forests in both space and time.

    A freePlain Language Summarycan be found within the Supporting Information of this article.

     
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  5. Niu, Shuli (Ed.)
  6. Summary

    Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long‐standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking.

    We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 g m−2. Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad‐ and needleleaf species, and upper‐ and lower‐canopy (i.e. sun and shade) growth environments.

    Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R2 = 0.89; root mean square error (RMSE) = 15.45 g m−2).

    Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

     
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