A holistic tree seedling model for the investigation of functional trait diversity

In vitro regeneration, photomorphogenesis and light signaling gene expression in Hydrangea quercifolia cv. 'Harmony' under different LED environments

MAIN CONCLUSION

Plant growth regulators, sucrose concentration, and light quality significantly impact in vitro regeneration of 'Harmony'. Blue light promotes photomorphogenesis by enhancing light energy utilization, adjusting transcription of light signal genes, and altering hormone levels. Hydrangea quercifolia cv. 'Harmony', celebrated for lush green foliage and clusters of white flowers, has been extensively researched for its regenerative properties. Regeneration in stem segments, leaves, and petioles is facilitated by exogenous auxin and cytokinins (CTKs), with the concentration of sucrose (SC) being a key determinant for shoot regeneration from leaves. The study also highlights the significant impact of light conditions on photomorphogenesis. With an increase in the proportion of red (R) light, there is an inhibitory effect, leading to a reduction in leaf area, a decrease in the quantum yield of PSII (ΦPSII), and an increase in non-photochemical quenching (ΦNPQ) and non-regulated energy dissipation in PSII (ΦNO). Conversely, blue (B) light enhances growth, characterized by an increase in leaf area, elevated ΦPSII, and stable ΦNPQ and ΦNO levels. Additionally, B light induces the upregulation of HqCRYs, HqHY5-like, HqXTH27-like, and HqPHYs genes, along with an increase in endogenous CTKs levels, which positively influence photomorphogenesis independent of HqHY5-like regulation. This light condition also suppresses the synthesis of endogenous gibberellins (GA) and brassinosteroids (BR), further facilitating photomorphogenesis. In essence, B light is fundamental in expediting photomorphogenesis in 'Harmony', demonstrating the vital role in plant growth and development.

Local hydrological gradients structure high intraspecific variability in plant hydraulic traits in two dominant central Amazonian tree species

Addressing the intraspecific variability of functional traits helps understand how climate change might influence the distribution of organismal traits across environments, but this is notably understudied in the Amazon, especially for plant hydraulic traits commonly used to project drought responses. We quantified the intraspecific trait variability of leaf mass per area, wood density, and xylem embolism resistance for two dominant central Amazonian tree species, along gradients of water and light availability, while accounting for tree age and height. Intraspecific variability in hydraulic traits was high, with within-species variability comparable to the whole-community variation. Hydraulic trait variation was modulated mostly by the hydrological environment, with higher embolism resistance of trees growing on deep-water-table plateaus compared with shallow-water-table valleys. Intraspecific variability of leaf mass per area and wood density was mostly modulated by intrinsic factors and light. The different environmental and intrinsic drivers of variation among and within individuals lead to an uncoupled coordination among carbon acquisition/conservation and water-use traits. Our findings suggest multivariate ecological strategies driving tropical tree distributions even within species, and reflect differential within-population sensitivities along environmental gradients. Therefore, intraspecific trait variability must be considered for accurate predictions of the responses of tropical forests to climate change.

Relating leaf traits to seedling performance in a tropical forest: building a hierarchical functional framework

Trait-based approaches have been extensively used in community ecology to provide a mechanistic understanding of the drivers of community assembly. However, a foundational assumption of the trait framework, traits relate to performance, has been mainly examined through univariate relationships that simplify the complex phenotypic integration of organisms. We evaluate a conceptual framework in which traits are organized hierarchically combining trait information at the individual- and species-level from biomass allocation and organ-level traits. We focus on photosynthetic traits and predict that the positive effects of increasing plant leaf mass on growth depend on species-level leaf traits. We modeled growth data on more than 1,500 seedlings from 97 seedling species from a tropical forest in China. We found that seedling growth increases with allocation to leaves (high leaf area ratio and leaf mass fraction) and this effect is accentuated for species with high specific leaf area and leaf area. Also, we found that light has a significant effect on growth, and this effect is additive with leaf allocation traits. Our work offers an approach to gain further understanding of the effects of traits on the whole plant-level growth via a hierarchical framework including organ-level and biomass allocation traits at species and individual levels.

Trait Multi-Functionality in Plant Stress Response

Plants often experience multiple stresses in a given day or season, and it is self-evident that given functional traits can provide tolerances of multiple stresses. Yet, the multiple functions of individual traits are rarely explicitly considered in ecology and evolution due to a lack of a quantitative framework. We present a theory for considering the combined importance of the several functions that a single trait can contribute to alleviating multiple stresses. We derive five inter-related general predictions: (1) that trait multifunctionality is overall highly beneficial to fitness; (2) that species possessing multifunctional traits should increase in abundance and in niche breadth; (3) that traits are typically optimized for multiple functions and thus can be far from optimal for individual functions; (4) that the relative importance of each function of a multifunctional trait depends on the environment; and (5) that traits will be often "co-opted" for additional functions during evolution and community assembly. We demonstrate how the theory can be applied quantitatively by examining the multiple functions of leaf trichomes (hairs) using heuristic model simulations, substantiating the general principles. We identify avenues for further development and applications of the theory of trait multifunctionality in ecology and evolution.

Why Functional Traits Do Not Predict Tree Demographic Rates

Foundational to trait-based community ecology is the expectation that functional traits determine demographic outcomes. However, trait-demographic rate relationships are frequently weak, particularly in tree communities. The foundation of trait-based tree community ecology may, therefore, appear to be unstable. Here we argue that there are three core reasons why trait-demographic relationships are generally weak in tree communities. Specifically, important contextual information is frequently ignored, there is too much focus on species relative to individuals, and there are dimensions of tree function that are critical for determining tree demographic rates that are not captured by easily measured functional traits. Rather than being evidence that trait-based community ecology is fundamentally flawed, these issues elucidate a pathway towards a more robust research program.

Early subtropical forest growth is driven by community mean trait values and functional diversity rather than the abiotic environment

While functional diversity (FD) has been shown to be positively related to a number of ecosystem functions including biomass production, it may have a much less pronounced effect than that of environmental factors or species-specific properties. Leaf and wood traits can be considered particularly relevant to tree growth, as they reflect a trade-off between resources invested into growth and persistence. Our study focussed on the degree to which early forest growth was driven by FD, the environment (11 variables characterizing abiotic habitat conditions), and community-weighted mean (CWM) values of species traits in the context of a large-scale tree diversity experiment (BEF-China). Growth rates of trees with respect to crown diameter were aggregated across 231 plots (hosting between one and 23 tree species) and related to environmental variables, FD, and CWM, the latter two of which were based on 41 plant functional traits. The effects of each of the three predictor groups were analyzed separately by mixed model optimization and jointly by variance partitioning. Numerous single traits predicted plot-level tree growth, both in the models based on CWMs and FD, but none of the environmental variables was able to predict tree growth. In the best models, environment and FD explained only 4 and 31% of variation in crown growth rates, respectively, while CWM trait values explained 42%. In total, the best models accounted for 51% of crown growth. The marginal role of the selected environmental variables was unexpected, given the high topographic heterogeneity and large size of the experiment, as was the significant impact of FD, demonstrating that positive diversity effects already occur during the early stages in tree plantations.

Disentangling coordination among functional traits using an individual-centred model: impact on plant performance at intra- and inter-specific levels

Background

Plant functional traits co-vary along strategy spectra, thereby defining trade-offs for resource acquisition and utilization amongst other processes. A main objective of plant ecology is to quantify the correlations among traits and ask why some of them are sufficiently closely coordinated to form a single axis of functional specialization. However, due to trait co-variations in nature, it is difficult to propose a mechanistic and causal explanation for the origin of trade-offs among traits observed at both intra- and inter-specific level.

Methodology/Principal Findings

Using the Gemini individual-centered model which coordinates physiological and morphological processes, we investigated with 12 grass species the consequences of deliberately decoupling variation of leaf traits (specific leaf area, leaf lifespan) and plant stature (height and tiller number) on plant growth and phenotypic variability. For all species under both high and low N supplies, simulated trait values maximizing plant growth in monocultures matched observed trait values. Moreover, at the intraspecific level, plastic trait responses to N addition predicted by the model were in close agreement with observed trait responses. In a 4D trait space, our modeling approach highlighted that the unique trait combination maximizing plant growth under a given environmental condition was determined by a coordination of leaf, root and whole plant processes that tended to co-limit the acquisition and use of carbon and of nitrogen.

Conclusion/Significance

Our study provides a mechanistic explanation for the origin of trade-offs between plant functional traits and further predicts plasticity in plant traits in response to environmental changes. In a multidimensional trait space, regions occupied by current plant species can therefore be viewed as adaptive corridors where trait combinations minimize allometric and physiological constraints from the organ to the whole plant levels. The regions outside this corridor are empty because of inferior plant performance.

Next-generation dynamic global vegetation models: learning from community ecology

Dynamic global vegetation models (DGVMs) are powerful tools to project past, current and future vegetation patterns and associated biogeochemical cycles. However, most models are limited by how they define vegetation and by their simplistic representation of competition. We discuss how concepts from community assembly theory and coexistence theory can help to improve vegetation models. We further present a trait- and individual-based vegetation model (aDGVM2) that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow and compete. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to a site's biotic and abiotic conditions. The aDGVM2 simulates how environmental conditions influence the trait spectra of plant communities; that fire selects for traits that enhance fire protection and reduces trait diversity; and the emergence of life-history strategies that are suggestive of colonization-competition trade-offs. The aDGVM2 deals with functional diversity and competition fundamentally differently from current DGVMs. This approach may yield novel insights as to how vegetation may respond to climate change and we believe it could foster collaborations between functional plant biologists and vegetation modellers.

Leaf-trait variation explained by the hypothesis that plants maximize their canopy carbon export over the lifespan of leaves

Measured values of four key leaf traits (leaf area per unit mass, nitrogen concentration, photosynthetic capacity, leaf lifespan) co-vary consistently within and among diverse biomes, suggesting convergent evolution across species. The same leaf traits co-vary consistently with the environmental conditions (light intensity, carbon-dioxide concentration, nitrogen supply) prevailing during leaf development. No existing theory satisfactorily explains all of these trends. Here, using a simple model of the carbon-nitrogen economy of trees, we show that global leaf-trait relationships and leaf responses to environmental conditions can be explained by the optimization hypothesis (MAXX) that plants maximize the total amount of carbon exported from their canopies over the lifespan of leaves. Incorporating MAXX into larger-scale vegetation models may improve their consistency with global leaf-trait relationships, and enhance their ability to predict how global terrestrial productivity and carbon sequestration respond to environmental change.

Towards a worldwide wood economics spectrum

Wood performs several essential functions in plants, including mechanically supporting aboveground tissue, storing water and other resources, and transporting sap. Woody tissues are likely to face physiological, structural and defensive trade-offs. How a plant optimizes among these competing functions can have major ecological implications, which have been under-appreciated by ecologists compared to the focus they have given to leaf function. To draw together our current understanding of wood function, we identify and collate data on the major wood functional traits, including the largest wood density database to date (8412 taxa), mechanical strength measures and anatomical features, as well as clade-specific features such as secondary chemistry. We then show how wood traits are related to one another, highlighting functional trade-offs, and to ecological and demographic plant features (growth form, growth rate, latitude, ecological setting). We suggest that, similar to the manifold that tree species leaf traits cluster around the 'leaf economics spectrum', a similar 'wood economics spectrum' may be defined. We then discuss the biogeography, evolution and biogeochemistry of the spectrum, and conclude by pointing out the major gaps in our current knowledge of wood functional traits.

Modelling interactions in fungi

Indeterminate organisms have received comparatively little attention in theoretical ecology and still there is much to be understood about the origins and consequences of community structure. The fungi comprise an entire kingdom of life and epitomize the indeterminate growth form. While interactions play a significant role in shaping the community structure of indeterminate organisms, to date most of our knowledge relating to fungi comes from observing interaction outcomes between two species in two-dimensional arena experiments. Interactions in the natural environment are more complex and further insight will benefit from a closer integration of theory and experiment. This requires a modelling framework capable of linking genotype and environment to community structure and function. Towards this, we present a theoretical model that replicates observed interaction outcomes between fungal colonies. The hypotheses underlying the model propose that interaction outcome is an emergent consequence of simple and highly localized processes governing rates of uptake and remobilization of resources, the metabolic cost of production of antagonistic compounds and non-localized transport of internal resources. The model may be used to study systems of many interacting colonies and so provides a platform upon which the links between individual-scale behaviour and community-scale function in complex environments can be built.

The causes of variation in tree seedling traits: the roles of environmental selection versus chance

A key aspect of biodiversity is the great quantitative variation in functional traits observed among species. One perspective asserts that trait values should converge on a single optimum value in a particular selective environment, and consequently trait variation would reflect differences in selective environment, and evolutionary outcomes would be predictable. An alternative perspective asserts that there are likely multiple alternative optima within a particular selective environment, and consequently different lineages would evolve toward different optima due to chance. Because there is evidence for both of these perspectives, there is a long-standing controversy over the relative importance of convergence due to environmental selection versus divergence due to chance in shaping trait variation. Here, I use a model of tree seedling growth and survival to distinguish trait variation associated with multiple alternative optima from variation associated with environmental differences. I show that variation in whole plant traits is best explained by environmental differences, whereas in organ level traits variation is more affected by alternative optima. Consequently, I predict that in nature variation in organ level traits is most closely related to phylogeny, whereas variation in whole plant traits is most closely related to ecology.