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  1. D'Amato, A.W. (Ed.)
    The functional trait values that constitute a whole‐plant phenotype interact with the environment to determine demographic rates. Current approaches often fail to explicitly consider trait × trait and trait × environment interactions, which may lead to missed information that is valuable for understanding and predicting the drivers of demographic rates and functional diversity. Here, we consider these interactions by modeling growth performance landscapes that span multidimensional trait spaces along environmental gradients. We utilize individual‐level leaf, stem, and root trait data combined with growth data from tree seedlings along soil nutrient and light gradients in a hyper‐diverse tropical rainforest. We find that multiple trait combinations in phenotypic space (i.e., alternative designs) lead to multiple growth performance peaks that shift along light and soil axes such that no single or set of interacting traits consistently results in peak growth performance. Evidence from these growth performance peaks also generally indicates frequent independence of above‐ and belowground resource acquisition strategies. These results help explain how functional diversity is maintained in ecological communities and question the practice of utilizing a single trait or environmental variable, in isolation, to predict the growth performance of individual trees. 
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  2. null (Ed.)
    Abstract Background and Aims The composition and dynamics of plant communities arise from individual-level demographic outcomes, which are driven by interactions between phenotypes and the environment. Functional traits that can be measured across plants are frequently used to model plant growth and survival. Perhaps surprisingly, species average trait values are often used in these studies and, in some cases, these trait values come from other regions or averages calculated from global databases. This data aggregation potentially results in a large loss of valuable information that probably results in models of plant performance that are weak or even misleading. Methods We present individual-level trait and fine-scale growth data from >500 co-occurring individual trees from 20 species in a Chinese tropical rain forest. We construct Bayesian models of growth informed by theory and construct hierarchical Bayesian models that utilize both individual- and species-level trait data, and compare these models with models only using individual-level data. Key Results We show that trait–growth relationships measured at the individual level vary across species, are often weak using commonly measured traits and do not align with the results of analyses conducted at the species level. However, when we construct individual-level models of growth using leaf area ratio approximations and integrated phenotypes, we generated strong predictive models of tree growth. Conclusions Here, we have shown that individual-level models of tree growth that are built using integrative traits always outperform individual-level models of tree growth that use commonly measured traits. Furthermore, individual-level models, generally, do not support the findings of trait–growth relationships quantified at the species level. This indicates that aggregating trait and growth data to the species level results in poorer and probably misleading models of how traits are related to tree performance. 
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  3. The relationship between plant functional traits and demographic performance forms the foundation of trait-based ecology. It also serves as the natural linkage between trait-based ecology and much of evolutionary biology. Despite these important aspects, plant trait–demographic performance relationships reported in the literature are typically weak or nonexistent, and a synthetic picture of how traits are related to ecological and evolutionary patterns remains underdeveloped. Here, we begin by presenting an overview of the shortcomings in functional trait–demographic performance research and why weak results are more common than trait-based ecologists like to admit. We then discuss why there should be a natural synthesis between trait-based ecology and evolutionary ecology and potential reasons for why this synthesis has yet to emerge. Finally, we present a series of conceptual and empirical foci that should be incorporated into future trait–demographic performance research that will hopefully solidify the foundation of trait-based ecology and catalyze a synthesis with evolutionary ecology. These include (1) focusing on individuals as the fundamental unit of study instead of relying on population or species mean values for traits and demographic rates; (2) placing more emphasis on phenotypic integration, alternative designs, and performance landscapes; (3) coming to terms with the importance of regional- and local-scale context on plant performance; (4) an appreciation of the varied drivers of life-stage transitions and what aspects of function should be linked to those transitions; and (5) determining how the drivers of plant mortality act independently and in concert and what aspects of plant function best predict these outcomes. Our goal is to help highlight the shortcomings of trait–demographic performance research as it stands and areas where this research could course correct, ultimately, with the hope of promoting a trait-based research program that speaks to both ecologists and evolutionary biologists. 
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