The relationship of leaf photosynthetic traits - V cmax and J max - to leaf nitrogen, leaf phosphorus, and specific leaf area: a meta-analysis and modeling study

Carboxylation capacity is the main limitation of carbon assimilation in High Arctic shrubs

Increases in shrub height, biomass and canopy cover are key whole-plant features of warming-induced vegetation change in tundra. We investigated leaf functional traits underlying photosynthetic capacity of Arctic shrub species, particularly its main limiting processes such as mesophyll conductance. In this nutrient-limited ecosystem, we expect leaf nitrogen concentration to be the main limiting factor for photosynthesis. We measured the net photosynthetic rate at saturated light (Asat) in three Salix species throughout a glacial valley in High-Arctic tundra and used a causal approach to test relationships between leaf stomatal and mesophyll conductances (gsc, gm), carboxylation capacity (Vcmax), nitrogen and phosphorus concentration (Narea, Parea) and leaf mass ratio (LMA). Arctic Salix species showed no difference in Asat compared to a global data set, while being characterized by higher Narea, Parea and LMA. Vcmax, gsc and gm independently increased Asat, with Vcmax as its main limitation. We highlighted a nitrogen-influenced pathway for increasing photosynthesis in the two prostrate mesic habitat species. In contrast, the erect wetland habitat Salix richardsonii mainly increased Asat with increasing gsc. Overall, our study revealed high photosynthetic capacities of Arctic Salix species but contrasting regulatory pathways that may influence shrub ability to respond to environmental changes in High Arctic tundra.

Complex imprint of air pollution in the basal area increments of three European tree species

The impact of atmospheric pollution on the growth of European forest tree species, particularly European beech, Silver fir and Norway spruce, is examined in five mesic forests in the Czech Republic. Analyzing of basal area increment (BAI) patterns using linear mixed effect models reveals a complex interplay between atmospheric nitrogen (N) and sulphur (S) deposition, climatic variables and changing CO2 concentrations. Beech BAI responds positively to N deposition (in tandem with air CO2 concentration), with soil phosphorus (P) availability emerging as a significant factor influencing overall growth rates. Fir BAI, on the other hand, was particularly negatively influenced by S deposition, although recent growth acceleration suggests growth resilience in post-pollution period. This fir growth surge likely coincides with stimulation of P acquisition following the decline of acidic pollution. The consequence is the current highest productivity among the studied tree species. The growth dynamics of both conifers were closely linked to the stoichiometric imbalance of phosphorus in needles, indicating the possible sensitivity of exogenous controls on nutrient uptake. Furthermore, spruce BAI was positively linked to calcium availability across sites. Despite enhanced water-use efficiency under elevated CO2, spruce growth is constrained by precipitation deficit and demonstrates weakening resilience to increasing growing season air temperatures. Overall, these findings underscore the intricate relationships between atmospheric pollution, nutrient availability, and climatic factors in shaping the growth dynamics of European forest ecosystems. Thus, incorporating biogeochemical context of nutrient availability is essential for realistic modelling of tree growth in a changing climate.

Acclimation of Photosynthesis to CO2 Increases Ecosystem Carbon Storage due to Leaf Nitrogen Savings

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 CO2 by downregulating RuBisCO and thus nitrogen in leaves, but this acclimation response is not currently included in land surface models. Acclimation of photosynthesis to CO2 can 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 CO2 conditions 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.

Empirical evidence and theoretical understanding of ecosystem carbon and nitrogen cycle interactions

Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO2 and N input, alongside theoretical and ecological principles for modelling. N fertilisation increases leaf N content but inconsistently enhances leaf-level photosynthetic capacity. Whole-plant responses include increased leaf area and biomass, with reduced root allocation and increased aboveground biomass. Elevated atmospheric CO2 also boosts leaf area and biomass but intensifies belowground allocation, depleting soil N and likely reducing N losses. Global leaf traits data confirm these findings, indicating that soil N availability influences leaf N content more than photosynthetic capacity. A demonstration model based on the functional balance hypothesis accurately predicts responses to N and CO2 fertilisation on tissue allocation, growth and biomass, offering a path to reduce uncertainty in global C cycle projections.

Stomata Are Driving the Direction of CO2-Induced Water-Use Efficiency Gain in Selected Tropical Trees in Fiji

Understanding plant physiological response to a rising atmospheric CO2 concentration (ca) is key in predicting Earth system plant-climate feedbacks; however, the effects of long-term rising ca on plant gas-exchange characteristics in the tropics are largely unknown. Studying this long-term trend using herbarium records is challenging due to specimen trait variation. We assessed the impact of a ca rise of ~95 ppm (1927-2015) on the intrinsic water-use efficiency (iWUE) and maximum stomatal conductance (gsmax) of five tropical tree species in Fiji using the isotopic composition and stomatal traits of herbarium leaves. Empirical results were compared with simulated values using models that uniquely incorporated the variation in the empirical gsmax responses and species-specific parameterisation. The magnitude of the empirical iWUE and gsmax response was species-specific, ranging from strong to negligible. Stomatal density was more influential than the pore size in determining the gsmax response to ca. While our simulation results indicated that photosynthesis is the main factor contributing to the iWUE gain, stomata were driving the iWUE trend across the tree species. Generally, a stronger increase in the iWUE was accompanied by a stronger decline in stomatal response. This study demonstrates that the incorporation of variation in the gsmax in simulations is necessary for assessing an individual species' iWUE response to changing ca.

Dynamics of growth, physiology, radiation interception, production, and quality of autumn black gram (Vigna mungo (L.) Hepper) as influenced by nutrient scheduling

To analyse the effect of nutrient management on the growth, physiology, energy utilization, production and quality of black gram, a field trial on black gram was conducted at eastern Indian Gangetic alluvium during the autumn of 2020 and 2021. Treatments were two soil applications of cobalt (Co) and foliar spray of potassium (K) and boron (B) in five combinations. All treatments were arranged in a split-plot design and repeated three times. Two soil applications of cobalt (Co) were assigned in the main plots and foliar spray of potassium (K) and boron (B) in five combinations were assigned in sub-plots. Applications of Co in soil and foliar K+B facilitated significantly higher (p≤0.05) values for aerial dry matter (ADM), leaf area index (LAI), nodules per plant, total chlorophyll, net photosynthetic rate and nitrate reductase content in both 2020 and 2021, with a greater realization of photosynthetically active radiation interception, and use efficiency (IPAR and PARUE respectively), seed yield, seed nutrients and protein contents. Differences in LAI exhibited positive and linear correlation with IPAR explaining more than 60% variations in different growth stages. The innovative combination of soil Co (beneficial nutrient) application at 4 kg ha-1 combined with foliar 1.25% K (macronutrient) + 0.2% B (micronutrient) spray is a potential agronomic management schedule for the farmers to sustain optimum production of autumn black gram through substantial upgradation of growth, physiology, energy utilization, production and quality in Indian subtropics.

A guide to photosynthetic gas exchange measurements: Fundamental principles, best practice and potential pitfalls

Gas exchange measurements enable mechanistic insights into the processes that underpin carbon and water fluxes in plant leaves which in turn inform understanding of related processes at a range of scales from individual cells to entire ecosytems. Given the importance of photosynthesis for the global climate discussion it is important to (a) foster a basic understanding of the fundamental principles underpinning the experimental methods used by the broad community, and (b) ensure best practice and correct data interpretation within the research community. In this review, we outline the biochemical and biophysical parameters of photosynthesis that can be investigated with gas exchange measurements and we provide step-by-step guidance on how to reliably measure them. We advise on best practices for using gas exchange equipment and highlight potential pitfalls in experimental design and data interpretation. The Supporting Information contains exemplary data sets, experimental protocols and data-modelling routines. This review is a community effort to equip both the experimental researcher and the data modeller with a solid understanding of the theoretical basis of gas-exchange measurements, the rationale behind different experimental protocols and the approaches to data interpretation.

Native arbuscular mycorrhizal fungi drive ecophysiology through phenotypic integration and functional plasticity under the Sonoran desert conditions

Knowledge is scarce to what extent environmental drivers and native symbiotic fungi in soil induce abrupt (short-term), systemic (multiple traits), or specific (a subset of traits) shifts in C3 plants' ecophysiological/mycorrhizal responses. We cultivated an emblematic native C3 species (Capsicum annuum var. glabriusculum, "Chiltepín") to look at how the extreme heat of the Sonoran desert, sunlight regimes (low = 2, intermediate = 15, high = 46 mol m2 d-1) and density of native arbuscular mycorrhizal fungi in soil (low AMF = 1% v/v, high AMF = 100% v/v), drive shifts on mycorrhizal responses through multiple functional traits (106 traits). The warming thresholds were relentlessly harsh even under intensive shade (e.g. superheat maximum thresholds reached ranged between 47-63°C), and several pivotal traits were synergistically driven by AMF (e.g. photosynthetic capacity, biomass gain/allometry, and mycorrhizal colonization traits); whereas concurrently, sunlight regimes promoted most (76%) alterations in functional acclimation traits in the short-term and opposite directions (e.g. survival, phenology, photosynthetic, carbon/nitrogen economy). Multidimensional reduction analysis suggests that the AMF promotes a synergistic impact on plants' phenotypic integration and functional plasticity in response to sunlight regimes; however, complex relationships among traits suggest that phenotypic variation determines the robustness degree of ecophysiological/mycorrhizal phenotypes between/within environments. Photosynthetic canopy surface expansion, Rubisco activity, photosynthetic nitrogen allocation, carbon gain, and differential colonization traits could be central to plants' overall ecophysiological/mycorrhizal fitness strengthening. In conclusion, we found evidence that a strong combined effect among environmental factors in which AMF are key effectors could drive important trade-offs on plants' ecophysiological/mycorrhizal fitness in the short term.

Seasonal dynamics and punctuated carbon sink reduction suggest photosynthetic capacity of boreal silver birch is reduced by the accumulation of hexose

The 'assimilates inhibition hypothesis' posits that accumulation of nonstructural carbohydrates (NSCs) in leaves reduces leaf net photosynthetic rate, thus internally regulating photosynthesis. Experimental work provides equivocal support mostly under controlled conditions without identifying a particular NSC as involved in the regulation. We combined 3-yr in situ leaf gas exchange observations (natural dynamics) in the upper crown of mature Betula pendula simultaneously with measurements of concentrations of sucrose, hexoses (glucose and fructose), and starch, and similar measurements during several one-day shoot girdling (perturbation dynamics). Leaf water potential and water and nitrogen content were measured to account for their possible contribution to photosynthesis regulation. Leaf photosynthetic capacity (A/Ci) was temporally negatively correlated with NSC accumulation under both natural and perturbation states. For developed leaves, leaf hexose concentration explained A/Ci variation better than environmental variables (temperature history and daylength); the opposite was observed for developing leaves. The weaker correlations between NSCs and A/Ci in developing leaves may reflect their strong internal sink strength for carbohydrates. By contrast, the strong decline in photosynthetic capacity with NSCs accumulation in mature leaves, observed most clearly with hexose, and even more tightly with its constituents, provides support for the role of assimilates in regulating photosynthesis under natural conditions.

Physiological, transcriptomic and metabolomic insights of three extremophyte woody species living in the multi-stress environment of the Atacama Desert

MAIN CONCLUSIONS

In contrast to Neltuma species, S. tamarugo exhibited higher stress tolerance, maintaining photosynthetic performance through enhanced gene expression and metabolites. Differentially accumulated metabolites include chlorophyll and carotenoids and accumulation of non-nitrogen osmoprotectants. Plant species have developed different adaptive strategies to live under extreme environmental conditions. Hypothetically, extremophyte species present a unique configuration of physiological functions that prioritize stress-tolerance mechanisms while carefully managing resource allocation for photosynthesis. This could be particularly challenging under a multi-stress environment, where the synthesis of multiple and sequential molecular mechanisms is induced. We explored this hypothesis in three phylogenetically related woody species co-occurring in the Atacama Desert, Strombocarpa tamarugo, Neltuma alba, and Neltuma chilensis, by analyzing their leaf dehydration and freezing tolerance and by characterizing their photosynthetic performance under natural growth conditions. Besides, the transcriptomic profiling, biochemical analyses of leaf pigments, and metabolite analysis by untargeted metabolomics were conducted to study gene expression and metabolomic landscape within this challenging multi-stress environment. S. tamarugo showed a higher photosynthetic capacity and leaf stress tolerance than the other species. In this species, a multifactorial response was observed, which involves high photochemical activity associated with a higher content of chlorophylls and β-carotene. The oxidative damage of the photosynthetic apparatus is probably attenuated by the synthesis of complex antioxidant molecules in the three species, but S. tamarugo showed the highest antioxidant capacity. Comparative transcriptomic and metabolomic analyses among the species showed the differential expression of genes involved in the biosynthetic pathways of key stress-related metabolites. Moreover, the synthesis of non-nitrogen osmoprotectant molecules, such as ciceritol and mannitol in S. tamarugo, would allow the nitrogen allocation to support its high photosynthetic capacity without compromising leaf dehydration tolerance and freezing stress avoidance.

Variations in water use efficiency and carbon and nitrogen concentrations in red heart Chinese fir

Temperature can significantly (P < 0.05) affect plant growth by modifying water use strategies, which are determined by intrinsic water use efficiency (WUEi). Red Heart Chinese Fir (Cunninghamia lanceolata) is one of the most important ecological and economic plantation species in China. However, the C. lanceolata water use strategy in response to increased temperatures and uneven temporal distribution of precipitation during the growing season is rarely reported. In a 7-year-old C. lanceolata plantation, differences in WUEi and C and N concentrations in different organs were analysed by anova, and the δ13C stable isotope, C, and N concentrations in stems determined at different tree heights. Stepwise regression and variance inflation factor were used to remove autocorrelated factors, and structural equation modelling was then used to explore relationships between WUEi and climate and biological factors. WUEi differed significantly between leaf and branch at different standardized precipitation evapotranspiration indices (SPEI). WUEi and N concentration decreased with age. The highest WUEi in branches and leaves were 92.7 and 88.4 μmol·mol-1 in 2020 (SPEI = 0.00), respectively. δ13C increased with relative tree height but N concentration and C/N ratio were not affected. Air temperatures has increased in between 2014 and 2020. WUEi and N concentration decreased with increasing branch and leaf age, but C concentration increased. SPEI significantly positively affected WUEi (P < 0.05), and WUEi was significantly negatively related to C concentration, which is consistent with the trade-off between C and water.

Carbon-phosphorus cycle models overestimate CO2 enrichment response in a mature Eucalyptus forest

The importance of phosphorus (P) in regulating ecosystem responses to climate change has fostered P-cycle implementation in land surface models, but their CO2 effects predictions have not been evaluated against measurements. Here, we perform a data-driven model evaluation where simulations of eight widely used P-enabled models were confronted with observations from a long-term free-air CO2 enrichment experiment in a mature, P-limited Eucalyptus forest. We show that most models predicted the correct sign and magnitude of the CO2 effect on ecosystem carbon (C) sequestration, but they generally overestimated the effects on plant C uptake and growth. We identify leaf-to-canopy scaling of photosynthesis, plant tissue stoichiometry, plant belowground C allocation, and the subsequent consequences for plant-microbial interaction as key areas in which models of ecosystem C-P interaction can be improved. Together, this data-model intercomparison reveals data-driven insights into the performance and functionality of P-enabled models and adds to the existing evidence that the global CO2-driven carbon sink is overestimated by models.

Impacts of elevated temperature and vapour pressure deficit on leaf gas exchange and plant growth across six tropical rainforest tree species

Elevated air temperature (Tair) and vapour pressure deficit (VPDair) significantly influence plant functioning, yet their relative impacts are difficult to disentangle. We examined the effects of elevated Tair (+6°C) and VPDair (+0.7 kPa) on the growth and physiology of six tropical tree species. Saplings were grown under well-watered conditions in climate-controlled glasshouses for 6 months under three treatments: (1) low Tair and low VPDair, (2) high Tair and low VPDair, and (3) high Tair and high VPDair. To assess acclimation, physiological parameters were measured at a set temperature. Warm-grown plants grown under elevated VPDair had significantly reduced stomatal conductance and increased instantaneous water use efficiency compared to plants grown under low VPDair. Photosynthetic biochemistry and thermal tolerance (Tcrit) were unaffected by VPDair, but elevated Tair caused Jmax25 to decrease and Tcrit to increase. Sapling biomass accumulation for all species responded positively to an increase in Tair, but elevated VPDair limited growth. This study shows that stomatal limitation caused by even moderate increases in VPDair can decrease productivity and growth rates in tropical species independently from Tair and has important implications for modelling the impacts of climate change on tropical forests.

The outstanding capacity of Prasiola antarctica to thrive in contrasting harsh environments relies on the constitutive protection of thylakoids and on morphological plasticity

The determination of physiological tolerance ranges of photosynthetic species and of the biochemical mechanisms underneath are fundamental to identify target processes and metabolites that will inspire enhanced plant management and production for the future. In this context, the terrestrial green algae within the genus Prasiola represent ideal models due to their success in harsh environments (polar tundras) and their extraordinary ecological plasticity. Here we focus on the outstanding Prasiola antarctica and compare two natural populations living in very contrasting microenvironments in Antarctica: the dry sandy substrate of a beach and the rocky bed of an ephemeral freshwater stream. Specifically, we assessed their photosynthetic performance at different temperatures, reporting for the first time gnsd values in algae and changes in thylakoid metabolites in response to extreme desiccation. Stream population showed lower α-tocopherol content and thicker cell walls and thus, lower gnsd and photosynthesis. Both populations had high temperatures for optimal photosynthesis (around +20°C) and strong constitutive tolerance to freezing and desiccation. This tolerance seems to be related to the high constitutive levels of xanthophylls and of the cylindrical lipids di- and tri-galactosyldiacylglycerol in thylakoids, very likely related to the effective protection and stability of membranes. Overall, P. antarctica shows a complex battery of constitutive and plastic protective mechanisms that enable it to thrive under harsh conditions and to acclimate to very contrasting microenvironments, respectively. Some of these anatomical and biochemical adaptations may partially limit photosynthesis, but this has a great potential to rise in a context of increasing temperature.

Differential photosynthetic plasticity of Amazonian tree species in response to light environments

To investigate how and to what extent there are differences in the photosynthetic plasticity of trees in response to different light environments, six species from three successional groups (late successional, mid-successional, and pioneers) were exposed to three different light environments [deep shade - DS (5% full sunlight - FS), moderate shade - MS (35% FS) and full sunlight - FS]. Maximum net photosynthesis (Amax), leaf N partitioning, stomatal, mesophile, and biochemical limitations (SL, ML, and BL, respectively), carboxylation velocity (Vcmax), and electron transport (Jmax) rates, and the state of photosynthetic induction (IS) were evaluated. Higher values of Amax, Vcmax, and Jmax in FS were observed for pioneer species, which invested the largest amount of leaf N in Rubisco. The lower IS for pioneer species reveals its reduced ability to take advantage of sunflecks. In general, the main photosynthetic limitations are diffusive, with SL and ML having equal importance under FS, and ML decreasing along with irradiance. The leaf traits, which are more determinant of the photosynthetic process, respond independently in relation to the successional group, especially with low light availability. An effective partitioning of leaf N between photosynthetic and structural components played a crucial role in the acclimation process and determined the increase or decrease of photosynthesis in response to the light conditions.

Simulation of Automatically Annotated Visible and Multi-/Hyperspectral Images Using the Helios 3D Plant and Radiative Transfer Modeling Framework

Deep learning and multimodal remote and proximal sensing are widely used for analyzing plant and crop traits, but many of these deep learning models are supervised and necessitate reference datasets with image annotations. Acquiring these datasets often demands experiments that are both labor-intensive and time-consuming. Furthermore, extracting traits from remote sensing data beyond simple geometric features remains a challenge. To address these challenges, we proposed a radiative transfer modeling framework based on the Helios 3-dimensional (3D) plant modeling software designed for plant remote and proximal sensing image simulation. The framework has the capability to simulate RGB, multi-/hyperspectral, thermal, and depth cameras, and produce associated plant images with fully resolved reference labels such as plant physical traits, leaf chemical concentrations, and leaf physiological traits. Helios offers a simulated environment that enables generation of 3D geometric models of plants and soil with random variation, and specification or simulation of their properties and function. This approach differs from traditional computer graphics rendering by explicitly modeling radiation transfer physics, which provides a critical link to underlying plant biophysical processes. Results indicate that the framework is capable of generating high-quality, labeled synthetic plant images under given lighting scenarios, which can lessen or remove the need for manually collected and annotated data. Two example applications are presented that demonstrate the feasibility of using the model to enable unsupervised learning by training deep learning models exclusively with simulated images and performing prediction tasks using real images.

Water deficit differentially modulates leaf photosynthesis and transpiration of fungus-tolerant Muscadinia x Vitis hybrids

Screening for drought performance among novel fungi-tolerant grapevine genotypes is a key point to consider in semiarid regions where water scarcity is a common problem during fruit ripening period. It is therefore important to evaluate the genotypes' responses at the level of carbon metabolism and water demand, under water deficit conditions. This study aimed to characterize leaf and plant water use efficiency (respectively named WUEi and WUEpl) of novel INRAE fungi-tolerant genotypes (including LowSugarBerry (LSB) genotypes), under mild and high-water deficit (WD) and to decipher the photosynthetic parameters leading to higher WUEi. For this purpose, experiments were conducted on potted plants during one season using a phenotyping platform. Two stabilized soil moisture capacity (SMC) conditions, corresponding to mild (SMC 0.6) and high (SMC 0.3) WD, were imposed from the onset of berry ripening until the physiological ripeness stage, which was defined as the point at which fruits reach their maximum solutes and water content. At the whole plant level, all genotypes increased WUEpl under high WD. The highest WUEpl was reached for 3176N, which displayed both a high rate of non-structural carbon accumulation in fruits due to high fruit-to-leaf ratio and low plant transpiration because of low total leaf area. However, when normalizing the fruit-to-leaf ratio among the genotypes, G14 reached the highest normalized WUEpl_n under high WD. At the leaf level, WUEi also increased under high WD, with the highest value attained for G14 and 3176N and the lowest value for Syrah. The higher WUEi values for all genotypes compared to Syrah were associated to higher levels of photosynthesis and changes in light-harvesting efficiency parameters (ΦCO2, qP and qN), while no clear trend was apparent when considering the photosynthetic biochemical parameters (Vcmax, Jmax). Finally, a positive correlation between leaf and plant WUE was observed regardless of genotypes. This study allowed us to classify grapevine genotypes based on their grapes primary metabolite accumulation and water consumption during the critical sugar-loading period. Additionally, the study highlighted the potential drought adaptation mechanism of the LSB genotypes.

The importance of species-specific and temperature-sensitive parameterisation of A/Ci models: A case study using cotton (Gossypium hirsutum L.) and the automated 'OptiFitACi' R-package

Leaf gas exchange measurements are an important tool for inferring a plant's photosynthetic biochemistry. In most cases, the responses of photosynthetic CO2 assimilation to variable intercellular CO2 concentrations (A/Ci response curves) are used to model the maximum (potential) rate of carboxylation by ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco, Vcmax) and the rate of photosynthetic electron transport at a given incident photosynthetically active radiation flux density (PAR; JPAR). The standard Farquhar-von Caemmerer-Berry model is often used with default parameters of Rubisco kinetic values and mesophyll conductance to CO2 (gm) derived from tobacco that may be inapplicable across species. To study the significance of using such parameters for other species, here we measured the temperature responses of key in vitro Rubisco catalytic properties and gm in cotton (Gossypium hirsutum cv. Sicot 71) and derived Vcmax and J2000 (JPAR at 2000 µmol m-2 s-1 PAR) from cotton A/Ci curves incrementally measured at 15°C-40°C using cotton and other species-specific sets of input parameters with our new automated fitting R package 'OptiFitACi'. Notably, parameterisation by a set of tobacco parameters produced unrealistic J2000:Vcmax ratio of <1 at 25°C, two- to three-fold higher estimates of Vcmax above 15°C, up to 2.3-fold higher estimates of J2000 and more variable estimates of Vcmax and J2000, for our cotton data compared to model parameterisation with cotton-derived values. We determined that errors arise when using a gm,25 of 2.3 mol m-2 s-1 MPa-1 or less and Rubisco CO2-affinities in 21% O2 (KC 21%O2) at 25°C outside the range of 46-63 Pa to model A/Ci responses in cotton. We show how the A/Ci modelling capabilities of 'OptiFitACi' serves as a robust, user-friendly, and flexible extension of 'plantecophys' by providing simplified temperature-sensitivity and species-specificity parameterisation capabilities to reduce variability when modelling Vcmax and J2000.

Quantifying water-use efficiency in plant canopies with varying leaf angle and density distribution

BACKGROUND AND AIMS

Variation in architectural traits related to the spatial and angular distribution of leaf area can have considerable impacts on canopy-scale fluxes contributing to water-use efficiency (WUE). These architectural traits are frequent targets for crop improvement and for improving the understanding and predictions of net ecosystem carbon and water fluxes.

METHODS

A three-dimensional, leaf-resolving model along with a range of virtually generated hypothetical canopies were used to quantify interactions between canopy structure and WUE by examining its response to variation of leaf inclination independent of leaf azimuth, canopy heterogeneity, vegetation density and physiological parameters.

KEY RESULTS

Overall, increasing leaf area index (LAI), increasing the daily-averaged fraction of leaf area projected in the sun direction (Gavg) via the leaf inclination or azimuth distribution and increasing homogeneity had a similar effect on canopy-scale daily fluxes contributing to WUE. Increasing any of these parameters tended to increase daily light interception, increase daily net photosynthesis at low LAI and decrease it at high LAI, increase daily transpiration and decrease WUE. Isolated spherical crowns could decrease photosynthesis by ~60 % but increase daily WUE ≤130 % relative to a homogeneous canopy with equivalent leaf area density. There was no observed optimum in daily canopy WUE as LAI, leaf angle distribution or heterogeneity was varied. However, when the canopy was dense, a more vertical leaf angle distribution could increase both photosynthesis and WUE simultaneously.

CONCLUSIONS

Variation in leaf angle and density distributions can have a substantial impact on canopy-level carbon and water fluxes, with potential trade-offs between the two. These traits might therefore be viable target traits for increasing or maintaining crop productivity while using less water, and for improvement of simplified models. Increasing canopy density or decreasing canopy heterogeneity increases the impact of leaf angle on WUE and its dependent processes.

A novel hybrid modelling framework for GPP estimation: Integrating a multispectral surface reflectance based Vcmax25 simulator into the process-based model

Terrestrial gross primary productivity (GPP) is the key element in the carbon cycle process. Accurate GPP estimation hinges on the maximum carboxylation rate (Vcmax,025). The high uncertainty in deriving ecosystem-level Vcmax,025 has long hampered efforts toward the performance of the GPP model. Recently studies suggest the strong relationship between spectral reflectance and Vcmax,025. We proposed the multispectral surface reflectance-driven Vcmax,025 simulator using the fully connected deep neural network and built the hybrid modelling framework for GPP estimation by integrating the data-driven Vcmax,025 simulator in the process-based model. The performance of hybrid GPP model was evaluated at 95 flux sites. The result shows that the multispectral surface reflectance-driven Vcmax,025 simulator acquires the satisfactory estimation, with correlation coefficient (R), root mean square error (RMSE) and median absolute percentage error (MdAPE) ranging from 0.34 to 0.80, 14 to 43 μmol m-2 s-1 and 21 % to 66 % across different land cover types, respectively. The hybrid framework generates good GPP estimates with R, RMSE and MdAPE varying from 0.76 to 0.89, 1.79 to 6.16 μmol m-2 s-1 and 27 % to 90 %, respectively. Compared with EVI-driven method, the multispectral surface reflectance significantly improves the Vcmax,025 and GPP estimates, with MdAPE declining by 0.6 %-18 % and 1 % to 21 %, respectively. The Shapley value analysis reveals that red (620-670 nm), near-infrared (841-876 nm) and shortwave infrared (1628-1652 nm and 2105-2155 nm) are the key bands for Vcmax,025 estimation. This study highlights the potential of multispectral surface reflectance for quantifying ecosystem-level Vcmax,025. The new hybrid framework fully extracts the information of all available spectral bands using deep learning to reduce parameter uncertainty while maintains the description of photosynthetic process to ensure its physical reasonability. It can serve as a powerful tool for accurate global GPP estimation.

Plant responses to elevated CO2 under competing hypotheses of nitrogen and phosphorus limitations

The future ecosystem carbon cycle has important implications for biosphere-climate feedback. The magnitude of future plant growth and carbon accumulation depends on plant strategies for nutrient uptake under the stresses of nitrogen (N) versus phosphorus (P) limitations. Two archetypal theories have been widely acknowledged in the literature to represent N and P limitations on ecosystem processes: Liebig's Law of the Minimum (LLM) and the Multiple Element Limitation (MEL) approach. LLM states that the more limiting nutrient controls plant growth, and commonly leads to predictions of dramatically dampened ecosystem carbon accumulation over the 21st century. Conversely, the MEL approach recognizes that plants possess multiple pathways to coordinate N and P availability and invest resources to alleviate N or P limitation. We implemented these two contrasting approaches in the E3SM model, and compiled 98 in situ forest N or P fertilization experiments to evaluate how terrestrial ecosystems will respond to N and P limitations. We find that MEL better captured the observed plant responses to nutrient perturbations globally, compared with LLM. Furthermore, LLM and MEL diverged dramatically in responses to elevated CO2 concentrations, leading to a two-fold difference in CO2 fertilization effects on Net Primary Productivity by the end of the 21st century. The larger CO2 fertilization effects indicated by MEL mainly resulted from plant mediation on N and P resource supplies through N2 fixation and phosphatase activities. This analysis provides quantitative evidence of how different N and P limitation strategies can diversely affect future carbon and nutrient dynamics.

Vertical variation in leaf functional traits of Parashorea chinensis with different canopy layers

Introduction

Canopy species need to shift their ecological adaptation to improve light and water resources utilization, and the study of intraspecific variations in plant leaf functional traits based at individual scale is of great significance for evaluating plant adaptability to climate change.

Methods

In this study, we evaluate how leaf functional traits of giant trees relate to spatial niche specialization along a vertical gradient. We sampled the tropical flagship species of Parashorea chinensis around 60 meters tall and divided their crowns into three vertical layers. Fourteen key leaf functional traits including leaf morphology, photosynthetic, hydraulic and chemical physiology were measured at each canopy layer to investigate the intraspecific variation of leaf traits and the interrelationships between different functional traits. Additionally, due to the potential impact of different measurement methods (in-situ and ex-situ branch) on photosynthetic physiological parameters, we also compared the effects of these two gas exchange measurements.

Results and discussion

In-situ measurements revealed that most leaf functional traits of individual-to-individual P. chinensis varied significantly at different canopy heights. Leaf hydraulic traits such as midday leaf water potential (MWP) and leaf osmotic potential (OP) were insignificantly correlated with leaf photosynthetic physiological traits such as maximal net assimilation rate per mass (A mass). In addition, great discrepancies were found between in-situ and ex-situ measurements of photosynthetic parameters. The ex-situ measurements caused a decrease by 53.63%, 27.86%, and 38.05% in A mass, and a decrease of 50.00%, 19.21%, and 27.90% in light saturation point compared to the in-situ measurements. These findings provided insights into our understanding of the response mechanisms of P. chinensis to micro-habitat in Xishuangbanna tropical seasonal rainforests and the fine scale adaption of different resultant of decoupled traits, which have implications for understanding ecological adaption strategies of P. chinensis under environmental changes.

Variable influence of photosynthetic thermal acclimation on future carbon uptake in Australian wooded ecosystems under climate change

Climate change will impact gross primary productivity (GPP), net primary productivity (NPP), and carbon storage in wooded ecosystems. The extent of change will be influenced by thermal acclimation of photosynthesis-the ability of plants to adjust net photosynthetic rates in response to growth temperatures-yet regional differences in acclimation effects among wooded ecosystems is currently unknown. We examined the effects of changing climate on 17 Australian wooded ecosystems with and without the effects of thermal acclimation of C3 photosynthesis. Ecosystems were drawn from five ecoregions (tropical savanna, tropical forest, Mediterranean woodlands, temperate woodlands, and temperate forests) that span Australia's climatic range. We used the CABLE-POP land surface model adapted with thermal acclimation functions and forced with HadGEM2-ES climate projections from RCP8.5. For each site and ecoregion we examined (a) effects of climate change on GPP, NPP, and live tree carbon storage; and (b) impacts of thermal acclimation of photosynthesis on simulated changes. Between the end of the historical (1976-2005) and projected (2070-2099) periods simulated annual carbon uptake increased in the majority of ecosystems by 26.1%-63.3% for GPP and 15%-61.5% for NPP. Thermal acclimation of photosynthesis further increased GPP and NPP in tropical savannas by 27.2% and 22.4% and by 11% and 10.1% in tropical forests with positive effects concentrated in the wet season (tropical savannas) and the warmer months (tropical forests). We predicted minimal effects of thermal acclimation of photosynthesis on GPP, NPP, and carbon storage in Mediterranean woodlands, temperate woodlands, and temperate forests. Overall, positive effects were strongly enhanced by increasing CO2 concentrations under RCP8.5. We conclude that the direct effects of climate change will enhance carbon uptake and storage in Australian wooded ecosystems (likely due to CO2 enrichment) and that benefits of thermal acclimation of photosynthesis will be restricted to tropical ecoregions.

Determinants of photochemical characteristics of the photosynthetic electron transport chain of maize

Introduction

The photosynthetic electron transport chain (ETC) is the bridge that links energy harvesting during the photophysical reactions at one end and energy consumption during the biochemical reactions at the other. Its functioning is thus fundamental for the proper balance between energy supply and demand in photosynthesis. Currently, there is a lack of understanding regarding how the structural properties of the ETC are affected by nutrient availability and plant developmental stages, which is a major roadblock to comprehensive modeling of photosynthesis.

Methods

Redox parameters reflect the structural controls of ETC on the photochemical reactions and electron transport. We conducted joint measurements of chlorophyll fluorescence (ChlF) and gas exchange under systematically varying environmental conditions and growth stages of maize and sampled foliar nutrient contents. We utilized the recently developed steady-state photochemical model to infer redox parameters of electron transport from these measurements.

Results and discussion

We found that the inferred values of these photochemical redox parameters varied with leaf macronutrient content. These variations may be caused either directly by these nutrients being components of protein complexes on the ETC or indirectly by their impacts on the structural integrity of the thylakoid and feedback from the biochemical reactions. Also, the redox parameters varied with plant morphology and developmental stage, reflecting seasonal changes in the structural properties of the ETC. Our findings will facilitate the parameterization and simulation of complete models of photosynthesis.

Higher global gross primary productivity under future climate with more advanced representations of photosynthesis

Gross primary productivity (GPP) is the key determinant of land carbon uptake, but its representation in terrestrial biosphere models (TBMs) does not reflect our latest physiological understanding. We implemented three empirically well supported but often omitted mechanisms into the TBM CABLE-POP: photosynthetic temperature acclimation, explicit mesophyll conductance, and photosynthetic optimization through redistribution of leaf nitrogen. We used the RCP8.5 climate scenario to conduct factorial model simulations characterizing the individual and combined effects of the three mechanisms on projections of GPP. Simulated global GPP increased more strongly (up to 20% by 2070-2099) in more comprehensive representations of photosynthesis compared to the model lacking the three mechanisms. The experiments revealed non-additive interactions among the mechanisms as combined effects were stronger than the sum of the individual effects. The modeled responses are explained by changes in the photosynthetic sensitivity to temperature and CO2 caused by the added mechanisms. Our results suggest that current TBMs underestimate GPP responses to future CO2 and climate conditions.

Improving the predictions of leaf photosynthesis during and after short-term heat stress with current rice models

In response to increasing global warming, extreme heat stress significantly alters photosynthetic production. While numerous studies have investigated the temperature effects on photosynthesis, factors like vapour pressure deficit (VPD), leaf nitrogen, and feedback of sink limitation during and after extreme heat stress remain underexplored. This study assessed photosynthesis calculations in seven rice growth models using observed maximum photosynthetic rate (Pmax ) during and after short-term extreme heat stress in multi-year environment-controlled experiments. Biochemical models (FvCB-type) outperformed light response curve-based models (LRC-type) when incorporating observed leaf nitrogen, photosynthetically active radiation, temperatures, and intercellular CO2 concentration (Ci ) as inputs. Prediction uncertainty during heat stress treatment primarily resulted from variation in temperatures and Ci . Improving FVPD (the slope for the linear effect of VPD on Ci /Ca ) to be temperature-dependent, rather than constant as in original models, significantly improved Ci prediction accuracy under heat stress. Leaf nitrogen response functions led to model variation in leaf photosynthesis predictions after heat stress, which was mitigated by calibrated nitrogen response functions based on active photosynthetic nitrogen. Additionally, accounting for observed differences in carbohydrate accumulation between panicles and stems during grain filling improved the feedback of sink limitation, reducing Ci overestimation under heat stress treatments.

Soil nitrogen fertilization reduces relative leaf nitrogen allocation to photosynthesis

The connection between soil nitrogen availability, leaf nitrogen, and photosynthetic capacity is not perfectly understood. Because these three components tend to be positively related over large spatial scales, some posit that soil nitrogen positively drives leaf nitrogen, which positively drives photosynthetic capacity. Alternatively, others posit that photosynthetic capacity is primarily driven by above-ground conditions. Here, we examined the physiological responses of a non-nitrogen-fixing plant (Gossypium hirsutum) and a nitrogen-fixing plant (Glycine max) in a fully factorial combination of light by soil nitrogen availability to help reconcile these competing hypotheses. Soil nitrogen stimulated leaf nitrogen in both species, but the relative proportion of leaf nitrogen used for photosynthetic processes was reduced under elevated soil nitrogen in all light availability treatments due to greater increases in leaf nitrogen content than chlorophyll and leaf biochemical process rates. Leaf nitrogen content and biochemical process rates in G. hirsutum were more responsive to changes in soil nitrogen than those in G. max, probably due to strong G. max investments in root nodulation under low soil nitrogen. Nonetheless, whole-plant growth was significantly enhanced by increased soil nitrogen in both species. Light availability consistently increased relative leaf nitrogen allocation to leaf photosynthesis and whole-plant growth, a pattern that was similar between species. These results suggest that the leaf nitrogen-photosynthesis relationship varies under different soil nitrogen levels and that these species preferentially allocated more nitrogen to plant growth and non-photosynthetic leaf processes, rather than photosynthesis, as soil nitrogen increased.

Comparative physiology of canopy tree leaves in evergreen and deciduous forests in lowland Thailand

The typical seasonally dry forests in Southeast Asia are the mixed deciduous forest (MDF), dry dipterocarp (deciduous) forest (DDF), and dry evergreen forest (DEF). We obtained 21 physiological traits in the top/sunlit leaves of 107, 65 and 51 tree species in MDF, DEF and DDF, respectively. Approximately 70%, 95% and 95% of canopy tree species which consist of MDF, DEF and DDF are sampled, respectively. Light-saturated photosynthetic rates (Asat) exhibit a positive correlation with foliar nitrogen (N) and phosphorus (P) on leaf mass and area bases across tree species. Decreased leaf mass-based P reduces the positive slope of the mass-based N and Asat relationship across species and habitats. The differences in nutrient and water use and leaf habits are well matched to the variation in soil properties among the forest types, highlighting the reliability of this comprehensive database for revealing the mechanism of niche segregation based on edaphic factors.

Observed forest trait velocities have not kept pace with hydraulic stress from climate change

The extent to which future climate change will increase forest stress and the amount to which species and forest ecosystems can acclimate or adapt to increased stress is a major unknown. We used high-resolution maps of hydraulic traits representing the diversity in tree drought tolerance across the United States, a hydraulically enabled tree model, and forest inventory observations of demographic shifts to quantify the ability for within-species acclimation and between-species range shifts to mediate climate stress. We found that forests are likely to experience increases in both acute and chronic hydraulic stress with climate change. Based on current species distributions, regional hydraulic trait diversity was sufficient to buffer against increased stress in 88% of forested areas. However, observed trait velocities in 81% of forested areas are not keeping up with the rate required to ameliorate projected future stress without leaf area acclimation.

Connecting the dots: Path model to identify key phenotypic traits for screening plants with tolerance to nitrogen deficiency

Varieties that tolerate low nitrogen (N) application rates can reduce fertilizer costs, minimize nitrate leaching and runoff losses, and lower overall CO2 emissions associated with fertilizer manufacturing. The goal of our research is to show the usefulness of path models to identify key phenotypic traits for screening plants with a tolerance to low N application rates. We grew tolerant and sensitive cultivars of poinsettia (Euphorbia pulcherrima) using a water-soluble fertilizer (15-5-15 Cal Mag) in both optimal (electrical conductivity of 2.5 dS·m-1) and N-deficient (electrical conductivity of 0.75 dS·m-1) treatments and measured 24 different traits at the cellular, leaf, and whole-plant scales in both cultivars and treatments. The experiment was laid out as a split-plot design with N treatments as main plots and cultivars as sub-plots, with five replications. Path analysis was conducted to develop sequential relationships among these traits. Statistical comparisons between tolerant and sensitive cultivars in the N-deficient treatment indicated an increase in shoot biomass (19.9 vs 14.4 g), leaf area (2775 vs 1824 cm2), leaf dry weight (14.7 vs 10.0 g), lateral root dry weight (3.7 vs 2.4 g), light-saturated photosynthesis (14.5 vs 10.1 μmol∙m-2∙s-1), maximum electron transport rate (119 vs 89 μmol∙m-2∙s-1), chlorophyll content (28.1 vs 12.9 g∙100g-1), leaf N content (27.5 vs 19.9 mg∙g-1), and fine root N content (26.1 vs 20.9 mg∙g-1), and a decrease in anthocyanin content (0.07 vs 0.16 ΔOD∙g-1). The path model indicated that an increase in the lateral root growth and fine root N content can lead to an increase in the leaf N content, in the N-deficient treatment. There were three separate paths that connected higher leaf N content to increased shoot biomass. These paths were mediated by the levels of anthocyanin, chlorophylls, and light-saturated photosynthesis rate (or rubisco capacity). The light-saturated photosynthesis model suggested that the increased uptake of N by fine roots in the tolerant cultivar was likely supported by the photosynthates translocated from the shoot to the root. Leaf N content was associated with multiple plant responses in the N-deficient treatment, and can be a useful screening trait for developing new cultivars, especially in marker-assisted molecular breeding.

Roles of lower-side leaf trichomes in diffusion resistance and gas-exchange characteristics across environmental gradients in Metrosideros polymorpha

Leaf trichomes on the lower leaf surface are common in many plant species, especially those grown under dry and/or low-temperature conditions; however, their adaptive significance remains unclear. Lower-side leaf trichomes can directly decrease gas fluxes through increased gas-diffusion resistance but can indirectly increase gas fluxes through increased leaf temperature owing to increased heat-diffusion resistance. We examined whether the combined direct and indirect effects of trichome resistance increase photosynthetic rates and water-use efficiency (WUE) using Metrosideros polymorpha Gaud., which varies widely in the masses of lower-side non-glandular leaf trichomes across various environments on the Hawaiian Islands. We employed both field surveys, including ecophysiological measurements at five elevation sites, and simulation analyses to predict the gas-exchange rates of leaves with various trichome-layer thicknesses across a wide range of environmental conditions. Field surveys showed that the trichome-layer thickness was the largest at the coldest and driest site and the thinnest at the wettest site. Field surveys, experimental manipulations and simulation analyses demonstrated that leaf trichomes significantly increased leaf temperature owing to the increased heat resistance. Simulation analyses showed that the effect of leaf trichomes on heat resistance was much larger than that on gas-flux resistance. Leaf trichomes can increase daily photosynthesis only in cold dry areas by increasing the leaf temperature. However, the increased leaf temperature with leaf trichomes resulted in a consistent decrease in the daily WUE at all elevation sites. The magnitudes of trichome effects on gas-exchange rates were associated with the temperature difference across the elevational gradient, the strong light intensity in Hawaii, the leaf-size variation and the conservative stomatal behavior of M. polymorpha as well as the trichome-layer thickness. In summary, the lower-side leaf trichomes in M. polymorpha can be beneficial for carbon assimilation in low-temperature environments but not for water conservation in most environments in terms of diffusion resistance.

Leaf photosynthetic pigment as a predictor of leaf maximum carboxylation rate in a farmland ecosystem

The leaf maximum rate of carboxylation (V_cmax) is a key parameter of plant photosynthetic capacity. The accurate estimation of V_cmax is crucial for correctly predicting the carbon flux in the terrestrial carbon cycle. V_cmax is correlated with plant traits including leaf nitrogen (N_area) and leaf photosynthetic pigments. Proxies for leaf chlorophyll (Chl_area) and carotenoid contents (Car_area) need to be explored in different ecosystems. In this study, we evaluated the relationship between leaf maximum rate of carboxylation (scaled to 25°C; V_cmax25) and both leaf N_area and photosynthetic pigments (Chl_area and Car_area) in winter wheat in a farmland ecosystem. Our results showed that V_cmax25 followed the same trends as leaf Chl_area. However, leaf N_area showed smaller dynamic changes before the flowering stage, and there were smaller seasonal variations in leaf Car_area. The correlation between leaf V_cmax25 and leaf Chl_area was the strongest, followed by leaf Car_area and leaf N_area (R² = 0.69, R² = 0.47 and R² = 0.36, respectively). The random forest regression analysis also showed that leaf Chl_area and leaf Car_area were more important than leaf N_area for V_cmax25. The correlation between leaf V_cmax25 and N_area can be weaker since nitrogen allocation is dynamic. The estimation accuracy of the V_cmax25 model based on N_area, Chl_area, and Car_area (R² = 0.75) was only 0.05 higher than that of the V_cmax25 model based on Chl_area and Car_area (R² = 0.70). However, the estimation accuracy of the V_cmax25 model based on Chl_area and Car_area (R² = 0.70) was 0.34 higher than that of the V_cmax25 model based on N_area (R² = 0.36). These results highlight that leaf photosynthetic pigments can be a predictor for estimating V_cmax25, expanding a new way to estimate spatially continuous V_cmax25 on a regional scale, and to improve model simulation accuracy.

Seasonal dynamics of photosynthetic nitrogen content and partitioning in deciduous forests

Nitrogen allocated to the photosynthetic apparatus and its partitioning into different photosynthetic components is crucial for understanding plant carbon gain and plant productivity. It is known that photosynthetic nitrogen content and partitioning are controlled by both environmental and vegetation factors and have versatile and dynamic responses. However, such responses are greatly simplified in most current gas exchange models, in which only a prescribed relationship is commonly applied to describe the effect of nitrogen on photosynthesis and with limited model performance. While within-canopy variation at a specific time in leaf photosynthetic nitrogen content and partitioning has been studied previously, far less attention has been paid to the seasonal dynamics of photosynthetic nitrogen content and partitioning, which is especially critical to deciduous forests. In this study, we integrated long-term field observations in deciduous forests in Japan to determine seasonal patterns of photosynthetic nitrogen content and partitioning (rubisco, electron transport, and light capture) and to examine how photosynthetic nitrogen content and partitioning varied seasonally in deciduous forest canopies growing at different altitudes. The results demonstrated that there were remarkable seasonal variations in both photosynthetic nitrogen content and partitioning in deciduous forests along the altitudinal gradient. Moreover, photosynthetic nitrogen use efficiency was well explained by nitrogen partitioning rather than total leaf nitrogen. These results suggest that seasonal patterns of nitrogen partitioning should be integrated into ecosystem models to accurately project emergent properties of ecosystem productivity on local, regional, and global scales.

The effect of the vertical gradients of photosynthetic parameters on the CO2 assimilation and transpiration of a Panamanian tropical forest

Terrestrial biosphere models (TBMs) include the representation of vertical gradients in leaf traits associated with modeling photosynthesis, respiration, and stomatal conductance. However, model assumptions associated with these gradients have not been tested in complex tropical forest canopies. We compared TBM representation of the vertical gradients of key leaf traits with measurements made in a tropical forest in Panama and then quantified the impact of the observed gradients on simulated canopy-scale CO₂ and water fluxes. Comparison between observed and TBM trait gradients showed divergence that impacted canopy-scale simulations of water vapor and CO₂ exchange. Notably, the ratio between the dark respiration rate and the maximum carboxylation rate was lower near the ground than at the top-of-canopy, leaf-level water-use efficiency was markedly higher at the top-of-canopy, and the decrease in maximum carboxylation rate from the top-of-canopy to the ground was less than TBM assumptions. The representation of the gradients of leaf traits in TBMs is typically derived from measurements made within-individual plants, or, for some traits, assumed constant due to a lack of experimental data. Our work shows that these assumptions are not representative of the trait gradients observed in species-rich, complex tropical forests.

A Mechanistic Model for Estimating Rice Photosynthetic Capacity and Stomatal Conductance from Sun-Induced Chlorophyll Fluorescence

Enhancing the photosynthetic rate is one of the effective ways to increase rice yield, given that photosynthesis is the basis of crop productivity. At the leaf level, crops' photosynthetic rate is mainly determined by photosynthetic functional traits including the maximum carboxylation rate (V_cmax) and stomatal conductance (gs). Accurate quantification of these functional traits is important to simulate and predict the growth status of rice. In recent studies, the emerging sun-induced chlorophyll fluorescence (SIF) provides us an unprecedented opportunity to estimate crops' photosynthetic traits, owing to its direct and mechanistic links to photosynthesis. Therefore, in this study, we proposed a practical semimechanistic model to estimate the seasonal V_cmax and gs time-series based on SIF. We firstly generated the coupling relationship between the open ratio of photosystem II (qL) and photosynthetically active radiation (PAR), then estimate the electron transport rate (ETR) based on the proposed mechanistic relationship between SIF and ETR. Finally, V_cmax and gs were estimated by linking to ETR based on the principle of evolutionary optimality and the photosynthetic pathway. Validation with field observations showed that our proposed model can estimate V_cmax and gs with high accuracy (R² > 0.8). Compared to simple linear regression model, the proposed model could increase the accuracy of V_cmax estimates by >40%. Therefore, the proposed method effectively enhanced the estimation accuracy of crops' functional traits, which sheds new light on developing high-throughput monitoring techniques to estimate plant functional traits, and also can improve our understating of crops' physiological response to climate change.

Shrub Invasion Overrides the Effect of Imposed Drought on the Photosynthetic Capacity and Physiological Responses of Mediterranean Cork Oak Trees

Mediterranean ecosystems face threats from both climate change and shrub invasion. As shrub cover increases, competition for water intensifies, exacerbating the negative effects of drought on ecosystem functioning. However, research into the combined effects of drought and shrub invasion on tree carbon assimilation has been limited. We used a Mediterranean cork oak (Quercus suber) woodland to investigate the effects of drought and shrub invasion by gum rockrose (Cistus ladanifer) on cork oak carbon assimilation and photosynthetic capacity. We established a factorial experiment of imposed drought (ambient and rain exclusion) and shrub invasion (invaded and non-invaded) and measured leaf water potential, stomatal conductance and photosynthesis as well as photosynthetic capacity in cork oak and gum rockrose over one year. We observed distinct detrimental effects of gum rockrose shrub invasion on the physiological responses of cork oak trees throughout the study period. Despite the imposed drought, the impact of shrub invasion was more pronounced, resulting in significant photosynthetic capacity reduction of 57% during summer. Stomatal and non-stomatal limitations were observed under moderate drought in both species. Our findings provide significant knowledge on the impact of gum rockrose invasion on the functioning of cork oak and can be used to improve the representation of photosynthesis in terrestrial biosphere models.

Ericoid mycorrhizal fungi mediate the response of ombrotrophic peatlands to fertilization: a modeling study

Ericaceous shrubs adapt to the nutrient-poor conditions in ombrotrophic peatlands by forming symbiotic associations with ericoid mycorrhizal (ERM) fungi. Increased nutrient availability may diminish the role of ERM pathways in shrub nutrient uptake, consequently altering the biogeochemical cycling within bogs. To explore the significance of ERM fungi in ombrotrophic peatlands, we developed the model MWMmic (a peat cohort-based biogeochemical model) into MWMmic-NP by explicitly incorporating plant-soil nitrogen (N) and phosphorus (P) cycling and ERM fungi processes. The new model was applied to simulate the biogeochemical cycles in the Mer Bleue (MB) bog in Ontario, Canada, and their responses to fertilization. MWMmic_NP reproduced the carbon(C)-N-P cycles and vegetation dynamics observed in the MB bog, and their responses to fertilization. Our simulations showed that fertilization increased shrub biomass by reducing the C allocation to ERM fungi, subsequently suppressing the growth of underlying Sphagnum mosses, and decreasing the peatland C sequestration. Our species removal simulation further demonstrated that ERM fungi were key to maintaining the shrub-moss coexistence and C sink function of bogs. Our results suggest that ERM fungi play a significant role in the biogeochemical cycles in ombrotrophic peatlands and should be considered in future modeling efforts.

Optimal coordination and reorganization of photosynthetic properties in C4 grasses

Each of >20 independent evolutions of C₄ photosynthesis in grasses required reorganization of the Calvin-Benson-cycle (CB-cycle) within the leaf, along with coordination of C₄ -cycle enzymes with the CB-cycle to maximize CO₂ assimilation. Considering the vast amount of time over which C₄ evolved, we hypothesized (i) trait divergences exist within and across lineages with both C₄ and closely related C₃ grasses, (ii) trends in traits after C₄ evolution yield the optimization of C₄ through time, and (iii) the presence/absence of trends in coordination between the CB-cycle and C₄ -cycle provides information on the strength of selection. To address these hypotheses, we used a combination of optimality modelling, physiological measurements and phylogenetic-comparative-analysis. Photosynthesis was optimized after the evolution of C₄ causing diversification in maximal assimilation, electron transport, Rubisco carboxylation, phosphoenolpyruvate carboxylase and chlorophyll within C₄ lineages. Both theory and measurements indicated a higher light-reaction to CB-cycle ratio (J_atpmax /V_cmax ) in C₄ than C₃ . There were no evolutionary trends with photosynthetic coordination between the CB-cycle, light reactions and the C₄ -cycle, suggesting strong initial selection for coordination. The coordination of CB-C₄ -cycles (V_pmax /V_cmax ) was optimal for CO₂ of 200 ppm, not to current conditions. Our model indicated that a higher than optimal V_pmax /V_cmax affects assimilation minimally, thus lessening recent selection to decrease V_pmax /V_cmax .

Determining reclaimed water quality thresholds and farming practices to improve food crop yield: A meta-analysis combined with random forest model

Irrigated agricultural systems with reclaimed water (RW) play a crucial role in alleviating global water scarcity and increased food demand. However, appropriate reclaimed water quality thresholds and farming practices to improve food crop yield is virtually unclear. Therefore, for the first time, this study made a large compilation of previous studies using meta-analysis combined with a random forest (RF) model and analyzed the impact of RW versus freshwater (FW) on the yield of food crops (cereals, vegetables, and fruits). It was found that magnesium ion (Mg²⁺), calcium ion (Ca²⁺), electrical conductivity (EC), total nitrogen (TN), and potential of hydrogen (pH) were the most important factors for RW quality indicators. Based on the results, water managers should establish more conservative RW quality thresholds to promote food crop production, especially for salts and pollutants in RW. Compared to international water quality standards, it could be slightly relaxed the restrictions of TN in RW. The optimal farming practices obtained that irrigation amount of the mixed RW and FW (RW + FW) was from 1000 m³ ha^-1 to 5000 m³ ha^-1, and the cultivation period was no more than three years. Flood irrigation (FI) and drip irrigation (DI) for cereals were also recommended. Finally, a comparison of the determined results from this method with other scenarios published, finding a good agreement.

Application of the rapid leaf A-Ci response (RACiR) technique: examples from evergreen broadleaved species

Using steady-state photosynthesis-intercellular CO₂ concentration (A-C_i) response curves to obtain the maximum rates of ribulose-1,5-bisphosphate carboxylase oxygenase carboxylation (V_cmax) and electron transport (J_max) is time-consuming and labour-intensive. Instead, the rapid A-C_i response (RACiR) technique provides a potential, high-efficiency method. However, efficient parameter settings of RACiR technique for evergreen broadleaved species remain unclear. Here, we used Li-COR LI-6800 to obtain the optimum parameter settings of RACiR curves for evergreen broadleaved trees and shrubs. We set 11 groups of CO₂ gradients ([CO₂]), i.e. R1 (400-1500 ppm), R2 (400-200-800 ppm), R3 (420-20-620 ppm), R4 (420-20-820 ppm), R5 (420-20-1020 ppm), R6 (420-20-1220 ppm), R7 (420-20-1520 ppm), R8 (420-20-1820 ppm), R9 (450-50-650 ppm), R10 (650-50 ppm) and R11 (650-50-650 ppm), and then compared the differences between steady-state A-C_i and RACiR curves. We found that V_cmax and J_max calculated by steady-state A-C_i and RACiR curves overall showed no significant differences across 11 [CO₂] gradients (P > 0.05). For the studied evergreens, the efficiency and accuracy of R2, R3, R4, R9 and R10 were higher than the others. Hence, we recommend that the [CO₂] gradients of R2, R3, R4, R9 and R10 could be applied preferentially for measurements when using the RACiR technique to obtain V_cmax and J_max of evergreen broadleaved species.

A small dynamic leaf-level model predicting photosynthesis in greenhouse tomatoes

The conversion of supplemental greenhouse light energy into biomass is not always optimal. Recent trends in global energy prices and discussions on climate change highlight the need to reduce our energy footprint associated with the use of supplemental light in greenhouse crop production. This can be achieved by implementing "smart" lighting regimens which in turn rely on a good understanding of how fluctuating light influences photosynthetic physiology. Here, a simple fit-for-purpose dynamic model is presented. It accurately predicts net leaf photosynthesis under natural fluctuating light. It comprises two ordinary differential equations predicting: 1) the total stomatal conductance to CO2 diffusion and 2) the CO2 concentration inside a leaf. It contains elements of the Farquhar-von Caemmerer-Berry model and the successful incorporation of this model suggests that for tomato (Solanum lycopersicum L.), it is sufficient to assume that Rubisco remains activated despite rapid fluctuations in irradiance. Furthermore, predictions of the net photosynthetic rate under both 400ppm and enriched 800ppm ambient CO2 concentrations indicate a strong correlation between the dynamic rate of photosynthesis and the rate of electron transport. Finally, we are able to indicate whether dynamic photosynthesis is Rubisco or electron transport rate limited.

Contributions of leaf distribution and leaf functions to photosynthesis and water-use efficiency from leaf to canopy in apple: A comparison of interstocks and cultivars

Grafting has been widely used in horticulture to induce dwarfing and avoid stress-derived limitations on plant growth and yield by affecting plant architecture and leaf functions. However, the respective effects on plant photosynthesis and water use efficiency (WUE) of leaf distribution and functions that depend on both rootstock and scion have not been fully elucidated. This study aimed to (i) clarify the scion × interstock impacts on the variability of leaf photosynthetic traits and WUE, and (ii) decipher the respective effects of leaf distribution and functions on canopy photosynthesis and WUE (WUEc). Leaf gas exchange over light gradients and responses to light, CO₂, temperature, and vapor pressure deficit were measured in two apple cultivars, 'Liquan Fuji' ('Fuji') and 'Regal Gala' ('Gala'), grafted onto rootstocks combined with interstocks: a vigorous (VV, 'Qinguan'), or a dwarf one (VD, M26). The 3D architecture-based RATP model was parameterized to estimate the canopy photosynthesis rate (A_c ), transpiration rate (E _c), and WUEc. Then, virtual scenarios were used to compare the relative contributions of cultivar and interstock to canopy A _c, E _c, and WUE _c. These scenarios changed the leaf distribution and functions of either cultivar or interstock. At the leaf scale, VD trees had significantly higher leaf nitrogen per area but a lower maximum carboxylation rate and dark respiration in both cultivars. In parallel with higher leaf stomatal conductance (g_s ) and transpiration in VD 'Fuji' and similar g_s in VD 'Gala', VD trees showed significantly lower leaf photosynthesis rate and WUE than VV trees. However, lower leaf photosynthetic capacities in VD trees were compensated at the canopy scale, with A _c and WUE _c for 'Fuji' significantly improved in VD trees under both sunny and cloudy conditions, and for 'Gala' significantly improved in VD trees under cloudy conditions compared with VV trees. Switching scenarios highlighted that 'Gala' leaf functions and distribution and VD leaf distributions enhanced A _c and WUE _c simultaneously, irrespective of weather conditions. Up-scaling leaf gas exchange to the canopy scale by utilizing 3D architecture-based modeling and reliable measurements of tree architecture and leaf functional traits provides insights to explore the influence of genetic materials and tree management practices.

Photosynthetic decline in aging perennial grass is not fully explained by leaf nitrogen

Aging in perennial plants is traditionally observed in terms of changes in end-of-season biomass; however, the driving phenological and physiological changes are poorly understood. We found that 3-year-old (mature) stands of the perennial grass Miscanthus×giganteus had 19-30% lower Anet than 1-year-old M.×giganteus (juvenile) stands; 10-34% lower maximum carboxylation rates of Rubisco and 34% lower light-saturated Anet (Asat). These changes could be related to nitrogen (N) limitations, as mature plants were larger and had 14-34% lower leaf N on an area basis (Na) than juveniles. However, N fertilization restored Na to juvenile levels but compensated only 50% of the observed decline in leaf photosynthesis with age. Comparison of leaf photosynthesis per unit of leaf N (PNUE) showed that mature stands had at least 26% lower PNUE than juvenile stands across all N fertilization rates, suggesting that other factors, besides N, may be limiting photosynthesis in mature stands. We hypothesize that sink limitations in mature stands could be causing feedback inhibition of photosynthesis which is associated with the age-related decline in photosynthesis.

Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub

Leaf trait variation enables plants to utilize large gradients of light availability that exist across canopies of high leaf area index (LAI), allowing for greater net carbon gain while reducing light availability for understory competitors. While these canopy dynamics are well understood in forest ecosystems, studies of canopy structure of woody shrubs in grasslands are lacking. To evaluate the investment strategy used by these shrubs, we investigated the vertical distribution of leaf traits and physiology across canopies of Cornus drummondii, the predominant woody encroaching shrub in the Kansas tallgrass prairie. We also examined the impact of disturbance by browsing and grazing on these factors. Our results reveal that leaf mass per area (LMA) and leaf nitrogen per area (Na) varied approximately threefold across canopies of C. drummondii, resulting in major differences in the physiological functioning of leaves. High LMA leaves had high photosynthetic capacity, while low LMA leaves had a novel strategy for maintaining light compensation points below ambient light levels. The vertical allocation of leaf traits in C. drummondii canopies was also modified in response to browsing, which increased light availability at deeper canopy depths. As a result, LMA and Na increased at lower canopy depths, leading to a greater photosynthetic capacity deeper in browsed canopies compared to control canopies. This response, along with increased light availability, facilitated greater photosynthesis and resource-use efficiency deeper in browsed canopies compared to control canopies. Our results illustrate how C. drummondii facilitates high LAI canopies and a compensatory growth response to browsing-both of which are key factors contributing to the success of C. drummondii and other species responsible for grassland woody encroachment.

Leaf pigments and photosystems stoichiometry underpin photosynthetic efficiency of related C3 , C-C4 and C4 grasses under shade

The quantum yield of photosynthesis (QY, CO₂ fixed per light absorbed) depends on the efficiency of light absorption, the coupling between light absorption and electron transport, and the coupling between electron transport and carbon metabolism. QY is generally lower in C₃ relative to C₄ plants at warm temperatures and differs among the C₄ subtypes. We investigated the acclimation to shade of light absorption and electron transport in six representative grasses with C₃ , C₃ -C₄ and C₄ photosynthesis. Plants were grown under full (control) or 25% (shade) sunlight. We measured the in vivo activity and stoichiometry of PSI and PSII, leaf spectral properties and pigment contents, and photosynthetic enzyme activities. Under control growth-light conditions, C₄ species had higher CO₂ assimilation rates, which declined to a greater extent relative to the C₃ species. Whole leaf PSII/PSI ratios were highest in the C₃ species, while QY and cyclic electron flow (CEF) were highest in the C₄ , NADP-ME species. Shade significantly reduced leaf PSII/PSI, linear electron flow (LEF) and CEF of most species. Overall, shade reduced leaf absorptance, especially in the green region, as well as carotenoid and chlorophyll contents in C₄ more than non-C₄ species. The NAD-ME species underwent the greatest reduction in leaf absorptance and pigments under shade. In conclusion, shade compromised QY the least in the C₃ and the most in the C₄ -NAD-ME species. Different sensitivity to shade was associated with the ability to maintain leaf absorptance and pigments. This is important for maximising light absorption and minimising photoprotection under low light.

Leaf nitrogen from the perspective of optimal plant function

Leaf dry mass per unit area (LMA), carboxylation capacity (V cmax) and leaf nitrogen per unit area (Narea) and mass (Nmass) are key traits for plant functional ecology and ecosystem modelling. There is however no consensus about how these traits are regulated, or how they should be modelled. Here we confirm that observed leaf nitrogen across species and sites can be estimated well from observed LMA and V cmax at 25°C (V cmax25). We then test the hypothesis that global variations of both quantities depend on climate variables in specific ways that are predicted by leaf-level optimality theory, thus allowing both Narea to be predicted as functions of the growth environment.A new global compilation of field measurements was used to quantify the empirical relationships of leaf N to V cmax25 and LMA. Relationships of observed V cmax25 and LMA to climate variables were estimated, and compared to independent theoretical predictions of these relationships. Soil effects were assessed by analysing biases in the theoretical predictions.LMA was the most important predictor of Narea (increasing) and Nmass (decreasing). About 60% of global variation across species and sites in observed Narea, and 31% in Nmass, could be explained by observed LMA and V cmax25. These traits, in turn, were quantitatively related to climate variables, with significant partial relationships similar or indistinguishable from those predicted by optimality theory. Predicted trait values explained 21% of global variation in observed site-mean V cmax25, 43% in LMA and 31% in Narea. Predicted V cmax25 was biased low on clay-rich soils but predicted LMA was biased high, with compensating effects on Narea. Narea was overpredicted on organic soils. Synthesis. Global patterns of variation in observed site-mean Narea can be explained by climate-induced variations in optimal V cmax25 and LMA. Leaf nitrogen should accordingly be modelled as a consequence (not a cause) of V cmax25 and LMA, both being optimized to the environment. Nitrogen limitation of plant growth would then be modelled principally via whole-plant carbon allocation, rather than via leaf-level traits. Further research is required to better understand and model the terrestrial nitrogen and carbon cycles and their coupling.

Leaf Photosynthetic and Functional Traits of Grassland Dominant Species in Response to Nutrient Addition on the Chinese Loess Plateau

Leaf photosynthetic and functional traits of dominant species are important for understanding grassland community dynamics under imbalanced nitrogen (N) and phosphorus (P) inputs. Here, the effects of N (N0, N50, and N100, corresponding to 0, 50, and 100 kg ha^-1 yr^-1, respectively) or/and P additions (P0, P40, and P80, corresponding to 0, 40, and 80 kg ha^-1 yr^-1) on photosynthetic characteristics and leaf economic traits of three dominant species (two grasses: Bothriochloa ischaemum and Stipa bungeana; a leguminous subshrub: Lespedeza davurica) were investigated in a semiarid grassland community on the Loess Plateau of China. Results showed that, after a three-year N addition, all three species had higher specific leaf area (SLA), leaf chlorophyll content (SPAD value), maximum net photosynthetic rate (P_Nmax), and leaf instantaneous water use efficiency (WUE), while also having a lower leaf dry matter content (LDMC). The two grasses, B. ischaemum and S. bungeana, showed greater increases in P_Nmax and SLA than the subshrub L. davurica. P addition alone had no noticeable effect on the P_Nmax of the two grasses while it significantly increased the P_Nmax of L. davurica. There was an evident synergetic effect of the addition of N and P combined on photosynthetic traits and most leaf economic traits in the three species. All species had relatively high P_Nmax and SLA under the addition of N50 combined with P40. Overall, this study suggests that N and P addition shifted leaf economic traits towards a greater light harvesting ability and, thus, elevated photosynthesis in the three dominant species of a semiarid grassland community, and this was achieved by species-specific responses in leaf functional traits. These results may provide insights into grassland restoration and the assessment of community development in the context of atmospheric N deposition and intensive agricultural fertilization.

Low phosphorus induces differential metabolic responses in eucalyptus species improving nutrient use efficiency

Phosphorus (P) is a vital nutrient for plant growth. P availability is generally low in soils, and plant responses to low P availability need to be better understood. In a previous study, we studied the growth and physiological responses of 24 species to low P availability in the soil and verified of eucalypts, five (Eucalyptus acmenoides, E. grandis, E. globulus, E. tereticornis, and Corymbia maculata) contrasted regarding their efficiency and responsiveness to soil P availability. Here, we obtained the metabolomic and lipidomic profile of leaves, stems, and roots from these species growing under low (4.5 mg dm^-3) and sufficient (10.8 mg dm^-3) P in the soil. Disregarding the level of P in the soils, P allocation was always higher in the stems. However, when grown in the P-sufficient soil, the stems steadily were the largest compartment of the total plant P. Under low P, the relative contents of primary metabolites, such as amino acids, TCA cycle intermediates, organic acids and carbohydrates, changed differently depending on the species. Additionally, phosphorylated metabolites showed enhanced turnover or reductions. While photosynthetic efficiencies were not related to higher biomass production, A/Ci curves showed that reduced P availability increased the eucalypt species' Vcmax, Jmax and photosynthetic P-use efficiency. Plants of E. acmenoides increased galactolipids and sulfolipids in leaves more than other eucalypt species, suggesting that lipid remodelling can be a strategy to cope with the P shortage in this species. Our findings offer insights to understand genotypic efficiency among eucalypt species to accommodate primary metabolism under low soil P availability and eventually be used as biochemical markers for breeding programs.

Leaf relative uptake of carbonyl sulfide to CO2 seen through the lens of stomatal conductance-photosynthesis coupling

Carbonyl sulfide (COS) has emerged as a multi-scale tracer for terrestrial photosynthesis. To infer ecosystem-scale photosynthesis from COS fluxes often requires knowledge of leaf relative uptake (LRU), the concentration-normalized ratio between leaf COS uptake and photosynthesis. However, current mechanistic understanding of LRU variability remains inadequate for deriving robust COS-based estimates of photosynthesis. We derive a set of closed-form equations to describe LRU responses to light, humidity and CO₂ based on the Ball-Berry stomatal conductance model and the biochemical model of photosynthesis. This framework reproduces observed LRU responses: decreasing LRU with increasing light or decreasing humidity; it also predicts that LRU increases with ambient CO₂ . By fitting the LRU equations to flux measurements on a C₃ reed (Typha latifolia), we obtain physiological parameters that control LRU variability, including an estimate of the Ball-Berry slope of 7.1 without using transpiration measurements. Sensitivity tests reveal that LRU is more sensitive to photosynthetic capacity than to the Ball-Berry slope, indicating stomatal response to photosynthesis. This study presents a simple framework for interpreting observed LRU variability and upscaling LRU. The stoma-regulated LRU response to CO₂ suggests that COS may offer a unique window into long-term stomatal acclimation to elevated CO₂ .