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Abstract Grasslands cover approximately a third of the Earth’s land surface and account for about a third of terrestrial carbon storage. Yet, we lack strong predictive models of grassland plant biomass, the primary source of carbon in grasslands. This lack of predictive ability may arise from the assumption of linear relationships between plant biomass and the environment and an underestimation of interactions of environmental variables. Using data from 116 grasslands on six continents, we show unimodal relationships between plant biomass and ecosystem characteristics, such as mean annual precipitation and soil nitrogen. Further, we found that soil nitrogen and plant diversity interacted in their relationships with plant biomass, such that plant diversity and biomass were positively related at low levels of nitrogen and negatively at elevated levels of nitrogen. Our results show that it is critical to account for the interactive and unimodal relationships between plant biomass and several environmental variables to accurately include plant biomass in global vegetation and carbon models. 

Abstract Background and AimsDynamic global vegetation models (DGVMs) are essential for quantifying the role of terrestrial ecosystems in the Earth’s climate system, but struggle with uncertainty and complexity. Eco-evolutionary optimality (EEO) theory provides a promising approach to improve DGVMs based on the premise that leaf carbon gain is optimized with resource costs. However, the timescales at which plant traits can adjust to environmental changes have not yet been systematically incorporated in EEO-based models. Our aims were to identify temporal constraints on key leaf photosynthetic and leaf functional traits, and develop a conceptual framework for incorporation of temporal leaf trait dynamics in EEO-based models. MethodsWe reviewed the scientific literature on temporal responses of leaf traits associated with stomata and hydraulics, photosynthetic biochemistry, and morphology and lifespan. Subsequent response times were categorized from fast to slow considering physiological, phenotypic (acclimation) and evolutionary (adaptation) mechanisms. We constructed a conceptual framework including several key leaf traits identified from the literature review. We considered temporal separation of dynamics in the leaf interior to atmospheric CO2 concentration (ci:ca) from the optimal ci:ca ratio [χ(optimal)] and dynamics in stomatal conductance within the constraint of the anatomical maximum stomatal conductance (gsmax). A proof-of-concept was provided by modelling temporally separated responses in these trait combinations to CO2 and humidity. Key ResultsWe identified 17 leaf traits crucial for EEO-based modelling and determined their response mechanisms and timescales. Physiological and phenotypic response mechanisms were considered most relevant for modelling EEO-based trait dynamics, while evolutionary constraints limit response ranges. Our conceptual framework demonstrated an approach to separate near-instantaneous physiological responses in ci:ca from week-scale phenotypic responses in χ(optimal), and to separate minute-scale physiological responses in stomatal conductance from annual-scale phenotypic responses in gsmax. ConclusionsWe highlight an opportunity to constrain leaf trait dynamics in EEO-based models based on physiological, phenotypic and evolutionary response mechanisms. 

Summary Natural selection favors growth by selecting a combination of plant traits that maximize photosynthetic CO₂assimilation at the lowest combined carbon costs of resource acquisition and use. We quantified how soil nutrient availability, plant nutrient acquisition strategies, and aridity modulate the variability in plant costs of nutrient acquisition relative to water acquisition (β).We used an eco‐evolutionary optimality framework and a global carbon isotope dataset to quantify β.Under low soil nitrogen‐to‐carbon (N : C) ratios, a mining strategy (symbioses with ectomycorrhizal and ericoid mycorrhizal fungi) reduced β by mining organic nitrogen, compared with a scavenging strategy (symbioses with arbuscular mycorrhizal fungi). Conversely, under high N : C ratios, scavenging strategies reduced β by effectively scavenging soluble nitrogen, compared with mining strategies. N₂‐fixing plants did not exhibit reduced β under low N : C ratios compared with non‐N₂‐fixing plants. Moisture increased β only in plants using a scavenging strategy, reflecting direct impacts of aridity on the carbon costs of maintaining transpiration in these plants. Nitrogen and phosphorus colimitation further modulated β.Our findings provide a framework for simulating the variability of plant economics due to plant nutrient acquisition strategies in earth system models. 

Summary It has been 60 years since the discovery of C₄photosynthesis, an event that rewrote our understanding of plant adaptation, ecosystem responses to global change, and global food security. Despite six decades of research, one aspect of C₄photosynthesis that remains poorly understood is how the pathway fits into the broader context of adaptive trait spectra, which form our modern view of functional trait ecology. The C₄CO₂‐concentrating mechanism supports a general C₄plant phenotype capable of fast growth and high resource‐use efficiencies. The fast‐efficient C₄phenotype has the potential to operate at high productivity rates, while allowing for less biomass allocation to root production and nutrient acquisition, thereby providing opportunities for the evolution of novel trait covariances and the exploitation of new ecological niches. We propose the placement of the C₄fast‐efficient phenotype near the acquisitive pole of the world‐wide leaf economic spectrum, but with a pathway‐specific span of trait space, wherein selection shapes both acquisitive and conservative adaptive strategies. A trait‐based perspective of C₄photosynthesis will open new paths to crop improvement, global biogeochemical modeling, the management of invasive species, and the restoration of disturbed ecosystems, particularly in grasslands. 

Abstract Plants respond to increasing atmospheric CO2 concentrations by reducing leaf nitrogen content and photosynthetic capacity—patterns that correspond with increased net photosynthesis and growth. Despite the longstanding notion that nitrogen availability regulates these responses, eco-evolutionary optimality theory posits that leaf-level responses to elevated CO2 are driven by leaf nitrogen demand for building and maintaining photosynthetic enzymes and are independent of nitrogen availability. In this study, we examined leaf and whole-plant responses of Glycine max L. (Merr) subjected to full-factorial combinations of two CO2, two inoculation, and nine nitrogen fertilization treatments. Nitrogen fertilization and inoculation did not alter leaf photosynthetic responses to elevated CO2. Instead, elevated CO2 decreased the maximum rate of ribulose-1,5-bisophosphate oxygenase/carboxylase (Rubisco) carboxylation more strongly than it decreased the maximum rate of electron transport for ribulose-1,5-bisphosphate (RuBP) regeneration, increasing net photosynthesis by allowing rate-limiting steps to approach optimal coordination. Increasing fertilization enhanced positive whole-plant responses to elevated CO2 due to increased below-ground carbon allocation and nitrogen uptake. Inoculation with nitrogen-fixing bacteria did not influence plant responses to elevated CO2. These results reconcile the role of nitrogen availability in plant responses to elevated CO2, showing that leaf photosynthetic responses are regulated by leaf nitrogen demand while whole-plant responses are constrained by nitrogen availability. 

Abstract Forbs (“wildflowers”) are important contributors to grassland biodiversity but are vulnerable to environmental changes. In a factorial experiment at 94 sites on 6 continents, we test the global generality of several broad predictions: (1) Forb cover and richness decline under nutrient enrichment, particularly nitrogen enrichment. (2) Forb cover and richness increase under herbivory by large mammals. (3) Forb richness and cover are less affected by nutrient enrichment and herbivory in more arid climates, because water limitation reduces the impacts of competition with grasses. (4) Forb families will respond differently to nutrient enrichment and mammalian herbivory due to differences in nutrient requirements. We find strong evidence for the first, partial support for the second, no support for the third, and support for the fourth prediction. Our results underscore that anthropogenic nitrogen addition is a major threat to grassland forbs, but grazing under high herbivore intensity can offset these nutrient effects. 

Summary Affecting biodiversity, plants with larger genome sizes (GS) may be restricted in nutrient‐poor conditions. This pattern has been attributed to their greater cellular nitrogen (N) and phosphorus (P) investments and hypothesized nutrient–investment tradeoffs between cell synthesis and physiological attributes associated with growth. However, the influence of GS on cell size and functioning may also contribute to GS‐dependent growth responses to nutrients.To test whether and how GS is associated with cellular nutrient, stomata, and/or physiological attributes, we examined > 500 forbs and grasses from seven grassland sites conducting a long‐term N and P fertilization experiment.Larger GS plants had increased cellular nutrient contents and larger, but fewer stomata than smaller GS plants. Larger GS grasses (but not forbs) also had lower photosynthetic rates and water‐use efficiencies. However, nutrients had no direct effect on GS‐dependent physiological attributes and GS‐dependent physiological changes likely arise from how GS influences cells. At the driest sites, large GS grasses displayed high water‐use efficiency mostly because transpiration was reduced relative to photosynthesis in these conditions.We suggest that climatic conditions and GS‐associated cell traits that modify physiological responses, rather than resource–investment tradeoffs, largely explain GS‐dependent growth responses to nutrients (especially for grasses). 

Abstract Many plant species form symbiotic associations with nitrogen-fixing bacteria. Through this symbiosis, plants allocate photosynthate belowground to the bacteria in exchange for nitrogen fixed from the atmosphere. This symbiosis forms an important link between carbon and nitrogen cycles in many ecosystems. However, the economics of this relationship under soil nitrogen availability gradients is not well understood, as plant investment toward symbiotic nitrogen fixation tends to decrease with increasing soil nitrogen availability. Here, we used a manipulation experiment to examine how costs of nitrogen acquisition vary under a factorial combination of soil nitrogen availability and inoculation with Bradyrhizobium japonicum in Glycine max L. (Merr.). We found that inoculation decreased belowground biomass carbon costs to acquire nitrogen and increased total leaf area and total biomass, but these patterns were only observed under low fertilization and were the result of increased plant nitrogen uptake and no change in belowground carbon allocation. These results suggest that symbioses with nitrogen-fixing bacteria reduce carbon costs of nitrogen acquisition by increasing plant nitrogen uptake, but only when soil nitrogen is low, allowing individuals to increase nitrogen allocation to structures that support aboveground growth. This pattern may help explain the prevalence of plants capable of forming these associations in less fertile soils and provides useful insight into understanding the role of nutrient acquisition strategy on plant nitrogen uptake across nitrogen availability gradients. 

ABSTRACT Photosynthesis is the largest flux of carbon between the atmosphere and Earth's surface and is driven by enzymes that require nitrogen, namely, ribulose‐1,5‐bisphosphate (RuBisCO). Thus, photosynthesis is a key link between the terrestrial carbon and nitrogen cycle, and the representation of this link is critical for coupled carbon‐nitrogen land surface models. Models and observations suggest that soil nitrogen availability can limit plant productivity increases under elevated CO₂. Plants acclimate to elevated CO₂by downregulating RuBisCO and thus nitrogen in leaves, but this acclimation response is not currently included in land surface models. Acclimation of photosynthesis to CO₂can be simulated by the photosynthetic optimality theory in a way that matches observations. Here, we incorporated this theory into the land surface component of the Energy Exascale Earth System Model (ELM). We simulated land surface carbon and nitrogen processes under future elevated CO₂conditions to 2100 using the RCP8.5 high emission scenario. Our simulations showed that when photosynthetic acclimation is considered, photosynthesis increases under future conditions, but maximum RuBisCO carboxylation and thus photosynthetic nitrogen demand decline. We analyzed two simulations that differed as to whether the saved nitrogen could be used in other parts of the plant. The allocation of saved leaf nitrogen to other parts of the plant led to (1) a direct alleviation of plant nitrogen limitation through reduced leaf nitrogen requirements and (2) an indirect reduction in plant nitrogen limitation through an enhancement of root growth that led to increased plant nitrogen uptake. As a result, reallocation of saved leaf nitrogen increased ecosystem carbon stocks by 50.3% in 2100 as compared to a simulation without reallocation of saved leaf nitrogen. These results suggest that land surface models may overestimate future ecosystem nitrogen limitation if they do not incorporate leaf nitrogen savings resulting from photosynthetic acclimation to elevated CO₂. 

ABSTRACT Accurately representing the relationships between nitrogen supply and photosynthesis is crucial for reliably predicting carbon–nitrogen cycle coupling in Earth System Models (ESMs). Most ESMs assume positive correlations amongst soil nitrogen supply, leaf nitrogen content, and photosynthetic capacity. However, leaf photosynthetic nitrogen demand may influence the leaf nitrogen response to soil nitrogen supply; thus, responses to nitrogen supply are expected to be the largest in environments where demand is the greatest. Using a nutrient addition experiment replicated across 26 sites spanning four continents, we demonstrated that climate variables were stronger predictors of leaf nitrogen content than soil nutrient supply. Leaf nitrogen increased more strongly with soil nitrogen supply in regions with the highest theoretical leaf nitrogen demand, increasing more in colder and drier environments than warmer and wetter environments. Thus, leaf nitrogen responses to nitrogen supply are primarily influenced by climatic gradients in photosynthetic nitrogen demand, an insight that could improve ESM predictions.