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Allometric relationships among the dimensions of leaves and their cells hold across diverse eudicotyledons, but have remained untested in the leaves of grasses. We hypothesised that geometric (proportional) allometries of cell sizes across tissues and of leaf dimensions would arise due to the coordination of cell development and that of cell functions such as water, nutrient and energy transport, and that cell sizes across tissues would be associated with light‐saturated photosynthetic rate. We tested predictions across 27 globally distributed C₃and C₄grass species grown in a common garden. We found positive relationships among average cell sizes within and across tissues, and of cell sizes with leaf dimensions. Grass leaf anatomical allometries were similar to those of eudicots, with exceptions consistent with the fewer cell layers and narrower form of grass leaves, and the specialised roles of epidermis and bundle sheath in storage and leaf movement. Across species, mean cell sizes in each tissue were associated with light‐saturated photosynthetic rate per leaf mass, supporting the functional coordination of cell sizes. These findings highlight the generality of evolutionary allometries within the grass lineage and their interlinkage with coordinated development and function.

The uptake and deposition of silicon (Si) as silica phytoliths is common among land plants and is associated with a variety of functions. Among these, herbivore defense has received significant attention, particularly with regard to grasses and grasslands. Grasses are well known for their high silica content, a trait which has important implications ranging from defense to global Si cycling. Here, we test the classic hypothesis that C₄grasses evolved stronger mechanical defenses than C₃grasses through increased phytolith deposition, in response to extensive ungulate herbivory (“C₄‐grazer hypothesis”). Despite mixed support, this hypothesis has received broad attention, even outside the realm of plant biology. Because C₃and C₄grasses typically dominate in different climates, with the latter more abundant in hot, dry regions, we also investigated the effects of water availability and temperature on Si deposition. We compiled a large dataset of grasses grown under controlled environmental conditions. Using phylogenetically informed generalized linear mixed models and character evolution models, we evaluated whether photosynthetic pathway or growth condition influenced Si concentration. We found that C₄grasses did not show consistently elevated Si concentrations compared with C₃grasses. High temperature treatments were associated with increased concentration, especially in taxa adapted to warm regions. Although the effect was less pronounced, reduced water treatment also promoted silica deposition, with slightly stronger response in dry habitat species. The evidence presented here rejects the “C₄‐grazer hypothesis.” Instead, we propose that the tendency for C₄grasses to outcompete C₃species under hot, dry conditions explains previous observations supporting this hypothesis. These findings also suggest a mechanism via which anthropogenic climate change may influence silica deposition in grasses and, by extension, alter the important ecological and geochemical processes it affects.

Process‐based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass‐dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C₃grasses and (sub)tropical C₄grasses. Incorporation of species‐level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance‐related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage‐based functional types (LFTs), situated between species‐level trait data and PFT‐level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models.