Modelling C₃ photosynthesis from the chloroplast to the ecosystem

Leaf stomatal configuration and photosynthetic traits jointly affect leaf water use efficiency in forests along climate gradients

Water use efficiency (WUE) represents the trade-off between carbon assimilation and water loss in plants. It remains unclear how leaf stomatal and photosynthetic traits regulate the spatial variation of leaf WUE in different natural forest ecosystems. We investigated 43 broad-leaf tree species spanning from cold-temperate to tropical forests in China. We quantified leaf WUE using leaf δ13C and measured stomatal traits, photosynthetic traits as well as maximum stomatal conductance (G w max $$ {G}_{{\mathrm{w}}_{\mathrm{max}}} $$ ) and maximum carboxylation capacity (V c max $$ {V}_{{\mathrm{c}}_{\mathrm{max}}} $$ ). We found that leaves in cold-temperate forests displayed 'fast' carbon economics, characterized by higher leaf nitrogen, Chl, specific leaf area, andV c max $$ {V}_{{\mathrm{c}}_{\mathrm{max}}} $$ , as an adaptation to the shorter growing season. However, these leaves exhibited 'slow' hydraulic traits, with larger but fewer stomata and similarG w max $$ {G}_{{\mathrm{w}}_{\mathrm{max}}} $$ , resulting in higher leaf WUE. By contrast, leaves in tropical forests had smaller and denser stomata, enabling swift response to heterogeneous light conditions. However, this stomatal configuration increased potential water loss, and coupled with their low photosynthetic capacity, led to lower WUE. Our findings contribute to understanding how plant photosynthetic and stomatal traits regulate carbon-water trade-offs across climatic gradients, advancing our ability to predict the impacts of climate changes on forest carbon and water cycles.

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.

Nitrogen modulates the ozone response of Mediterranean wheat: Considerations for ozone risk assessment

The experiment was conducted in an Open Top Chamber facility located in the Mediterranean basin to investigate how nitrogen (N) fertilization affects the response of wheat to ozone (O3) exposure. The study considered the response of Artur Nick, a modern wheat cultivar commonly used in the area, to three O3 exposure levels (ambient and elevated ambient, +20 and +40 nL L-1 O3), and two N fertilization doses (100 and 200 kg ha-1). Measurements included leaf gas exchange, leaf chlorophyll content, leaf and grain N content, plant growth and yield parameters. Ozone × N interactive effects were studied and quantified based on accumulated O3 concentrations above a 40 nL L-1 threshold (AOT40) and phytotoxic O3 dose (POD) indices, which are used in O3-risk assessments, from which critical levels (CL) for a 5 % effect were derived. Results revealed that O3 impacts on growth and yield parameters were stronger under the highest N fertilization dose. In consequence, O3 Critical Levels (CL) were as much as 3-4 times lower for grain yield in the high-N compared to the low-N treatment. Interestingly, O3 limited the fertilizer stimulus, strongly reducing the N use efficiency for grain yield and the agronomic efficiency of N for protein yield. Another important aspect was that 71 % of the POD was accumulated before anthesis, stressing the potential importance of O3 exposure during the vegetative phase of wheat under Mediterranean conditions, which is usually considered less important than post-anthesis exposure. In conclusion, this study suggests the need to consider crop N management in the derivation of O3 CLs, due to its effect on dose-response relationships used for CL derivation, including the potential O3 effects in N use efficiency. Therefore, N modulation could be considered in the O3-risk assessment methodology to be applied in risk exercises when negotiating air pollution abatement policies.

From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement

To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.

Addressing the long-standing limitations of double exponential and non-rectangular hyperbolic models in quantifying light-response of electron transport rates in different photosynthetic organisms under various conditions

The models used to describe the light response of electron transport rate in photosynthesis play a crucial role in determining two key parameters i.e., the maximum electron transport rate (J max) and the saturation light intensity (I sat). However, not all models accurately fit J-I curves, and determine the values of J max and I sat. Here, three models, namely the double exponential (DE) model, the non-rectangular hyperbolic (NRH) model, and a mechanistic model developed by one of the coauthors (Z-P Ye) and his coworkers (referred to as the mechanistic model), were compared in terms of their ability to fit J-I curves and estimate J max and I sat. Here, we apply these three models to a series of previously collected Chl a fluorescence data from seven photosynthetic organisms, grown under different conditions. Our results show that the mechanistic model performed well in describing the J-I curves, regardless of whether photoinhibition/dynamic down-regulation of photosystem II (PSII) occurs. Moreover, both J max and I sat estimated by this model are in very good agreement with the measured data. On the contrary, although the DE model simulates quite well the J-I curve for the species studied, it significantly overestimates both the J max of Amaranthus hypochondriacus and the I sat of Microcystis aeruginosa grown under NH4 +-N supply. More importantly, the light intensity required to achieve the potential maximum of J (J s) estimated by this model exceeds the unexpected high value of 105 μmol photons m-2 s-1 for Triticum aestivum and A. hypochondriacus. The NRH model fails to characterize the J-I curves with dynamic down-regulation/photoinhibition for Abies alba, Oryza sativa and M. aeruginosa. In addition, this model also significantly overestimates the values of J max for T. aestivum at 21% O2 and A. hypochondriacus grown under normal condition, and significantly underestimates the values of J max for M. aeruginosa grown under NO3 -N supply. Our study provides evidence that the 'mechanistic model' is much more suitable than both the DE and NRH models in fitting the J-I curves and in estimating the photosynthetic parameters. This is a powerful tool for studying light harvesting properties and the dynamic down-regulation of PSII/photoinhibition.

SlSERK3B Promotes Tomato Seedling Growth and Development by Regulating Photosynthetic Capacity

Brassinosteroids (BRs) are a group of polyhydroxylated steroids for plant growth and development, regulating numerous physiological and biochemical processes and participating in multi-pathway signaling in plants. 24-Epibrassinolide (EBR) is the most commonly used BR for the investigation of the effects of exogenous steroidal phytohormones on plant physiology. Although SlSERK3B is considered a gene involved in the brassinosteroid (BR) signaling pathway, its specific role in plant growth and development has not been reported in detail. In this study, tomato (Solanum lycopersicum L.) seedlings treated with 0.05 μmol L-1 EBR showed a significant increase in plant height, stem diameter, and fresh weight, demonstrating that BR promotes the growth of tomato seedlings. EBR treatment increased the expression of the BR receptor gene SlBRI1, the co-receptor gene SlSERK3A and its homologs SlSERK3B, and SlBZR1. The SlSERK3B gene was silenced by TRV-mediated virus-induced gene silencing (VIGS) technology. The results showed that both brassinolide (BL) content and BR synthesis genes were significantly up-regulated in TRV-SlSERK3B-infected seedlings compared to the control seedlings. In contrast, plant height, stem diameter, fresh weight, leaf area and total root length were significantly reduced in silenced plants. These results suggest that silencing SlSERK3B may affect BR synthesis and signaling, thereby affecting the growth of tomato seedlings. Furthermore, the photosynthetic capacity of TRV-SlSERK3B-infected tomato seedlings was reduced, accompanied by decreased photosynthetic pigment content chlorophyll fluorescence, and photosynthesis parameters. The expression levels of chlorophyll-degrading genes were significantly up-regulated, and carotenoid-synthesising genes were significantly down-regulated in TRV-SlSERK3B-infected seedlings. In conclusion, silencing of SlSERK3B inhibited BR signaling and reduced photosynthesis in tomato seedlings, and this correlation suggests that SlSERK3B may be related to BR signaling and photosynthesis enhancement.

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 photosynthetic efficiency toward food security: Strategies, advances, and perspectives

Photosynthesis in crops and natural vegetation allows light energy to be converted into chemical energy and thus forms the foundation for almost all terrestrial trophic networks on Earth. The efficiency of photosynthetic energy conversion plays a crucial role in determining the portion of incident solar radiation that can be used to generate plant biomass throughout a growth season. Consequently, alongside the factors such as resource availability, crop management, crop selection, maintenance costs, and intrinsic yield potential, photosynthetic energy use efficiency significantly influences crop yield. Photosynthetic efficiency is relevant to sustainability and food security because it affects water use efficiency, nutrient use efficiency, and land use efficiency. This review focuses specifically on the potential for improvements in photosynthetic efficiency to drive a sustainable increase in crop yields. We discuss bypassing photorespiration, enhancing light use efficiency, harnessing natural variation in photosynthetic parameters for breeding purposes, and adopting new-to-nature approaches that show promise for achieving unprecedented gains in photosynthetic efficiency.

Seasonal trends in leaf-level photosynthetic capacity and water use efficiency in a North American Eastern deciduous forest and their impact on canopy-scale gas exchange

Vegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems. We investigated seasonal patterns in leaf-level physiological, hydraulic, and anatomical properties, including the seasonal progress of the stomatal slope parameter (g1 ; inversely proportional to WUE) and the maximum carboxylation rate (Vcmax ). Vcmax and g1 were seasonally variable; however, their patterns were not temporally synchronized. g1 generally showed an increasing trend until late in the season, while Vcmax peaked during the midsummer months. Seasonal progression of Vcmax was primarily driven by changes in leaf structural, and anatomical characteristics, while seasonal changes in g1 were most strongly related to changes in Vcmax and leaf hydraulics. Using a seasonally variable Vcmax and g1 to parameterize a canopy-scale gas exchange model increased seasonally aggregated A and E by 3% and 16%, respectively.

Does plant ecosystem thermoregulation occur? An extratropical assessment at different spatial and temporal scales

To what degree plant ecosystems thermoregulate their canopy temperature (T_c ) is critical to assess ecosystems' metabolisms and resilience with climate change, but remains controversial, with opinions from no to moderate thermoregulation capability. With global datasets of T_c , air temperature (T_a ), and other environmental and biotic variables from FLUXNET and satellites, we tested the 'limited homeothermy' hypothesis (indicated by T_c & T_a regression slope < 1 or T_c  < T_a around midday) across global extratropics, including temporal and spatial dimensions. Across daily to weekly and monthly timescales, over 80% of sites/ecosystems have slopes ≥1 or T_c  > T_a around midday, rejecting the above hypothesis. For those sites unsupporting the hypothesis, their T_c -T_a difference (ΔT) exhibits considerable seasonality that shows negative, partial correlations with leaf area index, implying a certain degree of thermoregulation capability. Spatially, site-mean ΔT exhibits larger variations than the slope indicator, suggesting ΔT is a more sensitive indicator for detecting thermoregulatory differences across biomes. Furthermore, this large spatial-wide ΔT variation (0-6°C) is primarily explained by environmental variables (38%) and secondarily by biotic factors (15%). These results demonstrate diverse thermoregulation patterns across global extratropics, with most ecosystems negating the 'limited homeothermy' hypothesis, but their thermoregulation still occurs, implying that slope < 1 or T_c  < T_a are not necessary conditions for plant thermoregulation.

Genotypic variation rather than ploidy level determines functional trait expression in a foundation tree species in the presence and absence of environmental stress

BACKGROUND AND AIMS

At the population level, genetic diversity is a key determinant of a tree species' capacity to cope with stress. However, little is known about the relative importance of the different components of genetic diversity for tree stress responses. We compared how two sources of genetic diversity, genotype and cytotype (i.e. differences in ploidy levels), influence growth, phytochemical and physiological traits of Populus tremuloides in the presence and absence of environmental stress.

METHODS

In a series of field studies, we first assessed variation in traits across diploid and triploid aspen genotypes from Utah and Wisconsin under non-stressed conditions. In two follow-up experiments, we exposed diploid and triploid aspen genotypes from Wisconsin to individual and interactive drought stress and defoliation treatments and quantified trait variations under stress.

KEY RESULTS

We found that (1) tree growth and associated traits did not differ significantly between ploidy levels under non-stressed conditions. Instead, variation in tree growth and most other traits was driven by genotypic and population differences. (2) Genotypic differences were critical for explaining variation of most functional traits and their responses to stress. (3) Ploidy level played a subtle role in shaping traits and trait stress responses, as its influence was typically obscured by genotypic differences. (4) As an exception to the third conclusion, we showed that triploid trees expressed 17 % higher foliar defence (tremulacin) levels, 11 % higher photosynthesis levels and 23 % higher rubisco activity under well-watered conditions. Moreover, triploid trees displayed greater drought resilience than diploids as they produced 35 % more new tissue than diploids when recovering from drought stress.

CONCLUSION

Although ploidy level can strongly influence the ecology of tree species, those effects may be relatively small in contrast to the effects of genotypic variation in highly diverse species.

isocalcR: An R package to streamline and standardize stable isotope calculations in ecological research

The use of stable isotopes to characterize ecosystem dynamics and infer leaf gas exchange processes has become increasingly prevalent over the last few decades within the ecological community. While advancements in theory and our understanding of the physiological processes controlling isotopic signatures in plants has been well-documented, no standardized tool currently exists to facilitate the computation of common isotope-derived plant physiological indices. Here, we present isocalcR, an R package intended to facilitate the use of stable isotope data from plant tissues by providing an integrated collection of functions and recommended reference data. The isocalcR R package contains a suite of functions that compute leaf carbon isotope discrimination (∆¹³ C), leaf intercellular [CO₂ ], the ratio of leaf intercellular to atmospheric [CO₂ ], the difference between atmospheric and leaf intercellular [CO₂ ], and intrinsic water use efficiency from carbon isotope signatures in leaf or wood tissue with minimal inputs from the user. isocalcR also implements and provides recommended input atmospheric [CO₂ ] (ppm) and atmospheric δ¹³ CO₂ (‰) data for the period 0-2021 C.E. A major goal of isocalcR is to provide a standardized, open-source tool to streamline the calculation of reproducible physiological indices from stable isotope signatures in plant tissues, incorporating the most up-to-date theory, while simultaneously eliminating potential errors associated with complex calculations. isocalcR can be used for any location globally as long as the user provides information regarding temperature and elevation to the main workhorse functions.

Overexpression of cytoplasmic C4 Flaveria bidentis carbonic anhydrase in C3 Arabidopsis thaliana increases amino acids, photosynthetic potential, and biomass

An important method to improve photosynthesis in C₃ crops, such as rice and wheat, is to transfer efficient C₄ characters to them. Here, cytosolic carbonic anhydrase (CA: βCA3) of the C₄ Flaveria bidentis (Fb) was overexpressed under the control of ³⁵ S promoter in Arabidopsis thaliana, a C₃ plant, to enhance its photosynthetic efficiency. Overexpression of CA resulted in a better supply of the substrate HCO3- for the endogenous phosphoenolpyruvate carboxylase in the cytosol of the overexpressers, and increased its activity for generating malate that feeds into the tricarboxylic acid cycle. This provided additional carbon skeleton for increased synthesis of amino acids aspartate, asparagine, glutamate, and glutamine. Increased amino acids contributed to higher protein content in the transgenics. Furthermore, expression of FbβCA3 in Arabidopsis led to a better growth due to expression of several genes leading to higher chlorophyll content, electron transport, and photosynthetic carbon assimilation in the transformants. Enhanced CO₂ assimilation resulted in increased sugar and starch content, and plant dry weight. In addition, transgenic plants had lower stomatal conductance, reduced transpiration rate, and higher water-use efficiency. These results, taken together, show that expression of C₄ CA in the cytosol of a C₃ plant can indeed improve its photosynthetic capacity with enhanced water-use efficiency.

Late-day measurement of excised branches results in uncertainty in the estimation of two stomatal parameters derived from response curves in Populus deltoides Bartr. × Populus nigra L

Many terrestrial biosphere models depend on an understanding of the relationship between stomatal conductance and photosynthesis. However, unlike the measurement of photosynthetic parameters, such as the maximum carboxylation capacity, where standard methods (e.g., CO2 response or ACi curves) are widely accepted, a consensus method for empirically measuring parameters representing stomatal response has not yet emerged. Most models of stomatal response to environment represent stomatal conductance as being bounded by a lower intercept parameter (g0), and linearly scaled based on a multivariate term described by the stomatal slope parameter (g1). Here we employ the widely used Unified Stomatal Optimization model, to test whether g1 and g0 parameters are impacted by the choice of measurement method, either on an intact branch or a cut branch segment stored in water. We measured paired stomatal response curves on intact and excised branches of a hybrid poplar clone (Populus deltoides Bartr. × Populus nigra L. OP367), measured twice over a diurnal period. We found that predawn branch excision did not significantly affect measured g0 and g1 when measured within 4 h of excision. Measurement in the afternoon resulted in significantly higher values of g1 and lower values of g0, with values changing by 55% and 56%, respectively. Excision combined with afternoon measurement resulted in a marked effect on parameter estimates, with g1 increasing 89% from morning to afternoon and a 25% lower g1 for cut branches than those measured in situ. We also show that in hybrid poplar the differences in parameter estimates obtained from plants measured under different conditions can directly impact models of canopy function, reducing modeled transpiration by 18% over a simulated 12.5-h period. Although these results are only for a single isohydric woody species, our findings suggest that stomatal optimality parameters may not remain constant throughout the day.

High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (Glycine max) nested association mapping population

Photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500-2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.

Climate change impacts plant carbon balance, increasing mean future carbon use efficiency but decreasing total forest extent at dry range edges

Carbon use efficiency (CUE) represents how efficient a plant is at translating carbon gains through gross primary productivity (GPP) into net primary productivity (NPP) after respiratory costs (R_a ). CUE varies across space with climate and species composition, but how CUE will respond to climate change is largely unknown due to uncertainty in R_a at novel high temperatures. We use a plant physiological model validated against global CUE observations and LIDAR vegetation canopy height data and find that model-predicted decreases in CUE are diagnostic of transitions from forests to shrubland at dry range edges. Under future climate scenarios, we show mean growing season CUE increases in core forested areas, but forest extent decreases at dry range edges, with substantial uncertainty in absolute CUE due to uncertainty in R_a . Our results highlight that future forest resilience is nuanced and controlled by multiple competing mechanisms.

Changes in carbon and nitrogen metabolism during seawater-induced mortality of Picea sitchensis trees

Increasing seawater exposure is causing mortality of coastal forests, yet the physiological response associated with seawater-induced tree mortality, particularly in non-halophytes, is poorly understood. We investigated the shifts in carbon and nitrogen (N) metabolism of mature Sitka-spruce trees that were dying after an ecosystem-scale manipulation of tidal seawater exposure. Soil porewater salinity and foliar ion concentrations increased after seawater exposure and were strongly correlated with the percentage of live foliated crown (PLFC; e.g., crown 'greenness', a measure of progression to death). Co-occurring with decreasing PLFC was decreasing photosynthetic capacity, N-investment into photosynthesis, N-resorption efficiency and non-structural carbohydrate (soluble sugars and starch) concentrations, with the starch reserves depleted to near zero when PLFC dropped below 5%. Combined with declining PLFC, these changes subsequently decreased total carbon gain and thus exacerbated the carbon starvation process. This study suggests that an impairment in carbon and N metabolism during the mortality process after seawater exposure is associated with the process of carbon starvation, and provides critical knowledge necessary to predict sea-level rise impacts on coastal forests.

The limiting factors and regulatory processes that control the environmental responses of C3, C3-C4 intermediate, and C4 photosynthesis

Here, we describe a model of C3, C3-C4 intermediate, and C4 photosynthesis that is designed to facilitate quantitative analysis of physiological measurements. The model relates the factors limiting electron transport and carbon metabolism, the regulatory processes that coordinate these metabolic domains, and the responses to light, carbon dioxide, and temperature. It has three unique features. First, mechanistic expressions describe how the cytochrome b6f complex controls electron transport in mesophyll and bundle sheath chloroplasts. Second, the coupling between the mesophyll and bundle sheath expressions represents how feedback regulation of Cyt b6f coordinates electron transport and carbon metabolism. Third, the temperature sensitivity of Cyt b6f is differentiated from that of the coupling between NADPH, Fd, and ATP production. Using this model, we present simulations demonstrating that the light dependence of the carbon dioxide compensation point in C3-C4 leaves can be explained by co-occurrence of light saturation in the mesophyll and light limitation in the bundle sheath. We also present inversions demonstrating that population-level variation in the carbon dioxide compensation point in a Type I C3-C4 plant, Flaveria chloraefolia, can be explained by variable allocation of photosynthetic capacity to the bundle sheath. These results suggest that Type I C3-C4 intermediate plants adjust pigment and protein distributions to optimize the glycine shuttle under different light and temperature regimes, and that the malate and aspartate shuttles may have originally functioned to smooth out the energy supply and demand associated with the glycine shuttle. This model has a wide range of potential applications to physiological, ecological, and evolutionary questions.

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO₂ absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO₂ absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO₂ exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO₂ fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration (R_dark25), the maximum rate of carboxylation by the enzyme Rubisco (V_cmax25), the maximum rate of electron transport (J_max25), and the triose phosphate utilization rate (T_p25), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V_cmax25, J_max25, T_p25 and R_dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m^-2 s^-1, and R² of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (V_c,max ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-V_c,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V_c,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V_c,max and the four morphological and biochemical traits (R²  ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V_c,max relationships across three forest biomes into a single robust model for V_c,max (R²  = 0.77), and also accurately estimated the four traits (R²  = 0.75-0.94). These findings challenge the traditional use of the empirical trait-V_c,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising V_c,max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology.

Rubisco substitutions predicted to enhance crop performance through carbon uptake modelling

Improving the performance of the CO2-fixing enzyme Rubisco is among the targets for increasing crop yields. Here, Earth system model (ESM) representations of canopy C3 and C4 photosynthesis were combined with species-specific Rubisco parameters to quantify the consequences of bioengineering foreign Rubiscos into C3 and C4 crops under field conditions. The 'two big leaf' (sunlit/shaded) model for canopy photosynthesis was used together with species-specific Rubisco kinetic parameters including maximum rate (Kcat), Michaelis-Menten constant for CO2 at ambient atmospheric O2 (Kc21%O2), specificity for CO2 to O2 (Sc/o), and associated heat activation (Ha) values. Canopy-scale consequences of replacing native Rubiscos in wheat, maize, and sugar beet with foreign enzymes from 27 species were modelled using data from Ameriflux and Fluxnet databases. Variation among the included Rubisco kinetics differentially affected modelled carbon uptake rates, and Rubiscos from several species of C4 grasses showed the greatest potential of >50% carbon uptake improvement in wheat, and >25% improvement in sugar beet and maize. This study also reaffirms the need for data on fully characterized Rubiscos from more species, and for better parameterization of 'Vcmax' and temperature response of 'Jmax' in ESMs.

Evolution of a biochemical model of steady-state photosynthesis

On the occasion of the 40th anniversary of the publication of the landmark model by Farquhar, von Caemmerer & Berry on steady-state C₃ photosynthesis (known as the "FvCB model"), we review three major further developments of the model. These include: (1) limitation by triose phosphate utilization, (2) alternative electron transport pathways, and (3) photorespiration-associated nitrogen and C₁ metabolisms. We discussed the relation of the third extension with the two other extensions, and some equivalent extensions to model C₄ photosynthesis. In addition, the FvCB model has been coupled with CO₂ -diffusion models. We review how these extensions and integration have broadened the use of the FvCB model in understanding photosynthesis, especially with regard to bioenergetic stoichiometries associated with photosynthetic quantum yields. Based on the new insights, we present caveats in applying the FvCB model. Further research needs are highlighted.

Seasonal trends in photosynthesis and leaf traits in scarlet oak

Understanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.e., at the time of peak photoperiod. Contrary to expectations, our results reveal a late-season peak in both photosynthetic capacity and rate before the expected sharp decrease at the start of senescence. This late-season maximum occurred after the higher summer temperatures and vapor pressure deficit and was correlated with the recovery of leaf water content and increased stomatal conductance. We modeled photosynthesis at the top of the canopy and found that the simulated results closely tracked the maximum carboxylation capacity of Rubisco. For both photosynthetic capacity and modeled top-of-canopy photosynthesis, the maximum value was therefore not observed at the summer solstice. Rather, in each case, the measurements at and around the solstice were close to the overall seasonal mean, with values later in the season leading to deviations from the mean by up to 41 and 52%, respectively. Overall, we found that the expected Gaussian pattern of photosynthesis was not observed. We conclude that an understanding of species- and environment-specific changes in photosynthesis across the season is essential for correct estimation of seasonal photosynthetic capacity.

Source:sink imbalance detected with leaf- and canopy-level spectroscopy in a field-grown crop

The finely tuned balance between sources and sinks determines plant resource partitioning and regulates growth and development. Understanding and measuring metabolic indicators of source or sink limitation forms a vital part of global efforts to increase crop yield for future food security. We measured metabolic profiles of Cucurbita pepo (zucchini) grown in the field under carbon sink limitation and control conditions. We demonstrate that these profiles can be measured non-destructively using hyperspectral reflectance at both leaf and canopy scales. Total non-structural carbohydrates (TNC) increased 82% in sink-limited plants; leaf mass per unit area (LMA) increased 38% and free amino acids increased 22%. Partial least-squares regression (PLSR) models link these measured functional traits with reflectance data, enabling high-throughput estimation of traits comprising the sink limitation response. Leaf- and canopy-scale models for TNC had R² values of 0.93 and 0.64 and %RMSE of 13 and 38%, respectively. For LMA, R² values were 0.91 and 0.60 and %RMSE 7 and 14%; for free amino acids, R² was 0.53 and 0.21 with %RMSE 20 and 26%. Remote sensing can enable accurate, rapid detection of sink limitation in the field at the leaf and canopy scale, greatly expanding our ability to understand and measure metabolic responses to stress.

Longer photoperiods negate the CO2 stimulation of photosynthesis in Betula papyrifera Marsh: Implications to climate change-induced migration

In response to global warming, trees are expected to shift their distribution ranges to higher latitudes. The range shift will expose them to novel environmental conditions, such as new photoperiod regimes. These factors can interact with rising atmospheric CO₂ ([CO₂ ]) to affect trees' physiology and growth. This study simulated future environmental conditions to investigate photosynthetic responses to changes in photoperiod regimes (seed origin [48°N], 52, 55, and 58°N) and [CO₂ ] (ambient 400 vs. elevated 1000 μmol mol^-1 ) in white birch (Betula papyrifera Marsh.) seedlings. Our results show that elevated [CO₂ ] stimulated leaf photosynthesis (P_n ) at the two lower latitudes (48 and 52°N). However, this stimulation by elevated [CO₂ ] was lost in the two higher latitudes (55 and 58°N). Elevated [CO₂ ] led to the downregulation of maximum Rubisco activity (V_cmax ) for the two higher latitudes, and maximum electron transport rate (J_max ) and triose phosphate utilization (TPU) at 58°N, while it enhanced J_max and TPU for the two lower latitudes. Increased instantaneous water-use efficiency (IWUE) for the two lower latitudes was primarily attributed to the CO₂ stimulation of P_n while the higher IWUE under the photoperiod regimes of 55 and 58°N latitudes was explained by reduced water loss. Photoperiod effects varied with [CO₂ ]: P_n increased at the photoperiod regimes of 55 and 58°N in ambient [CO₂ ] while it tended to decline under these photoperiods in elevated [CO₂ ]. Our study suggests that the photosynthesis of white birch will likely respond negatively to northward migration or seed transfer in response to climate change.

A cyanobacterial photorespiratory bypass model to enhance photosynthesis by rerouting photorespiratory pathway in C3 plants

Plants employ photosynthesis to produce sugars for supporting their growth. During photosynthesis, an enzyme Ribulose 1,5 bisphosphate carboxylase/oxygenase (Rubisco) combines its substrate Ribulose 1,5 bisphosphate (RuBP) with CO2 to produce phosphoglycerate (PGA). Alongside, Rubisco also takes up O2 and produce 2-phosphoglycolate (2-PG), a toxic compound broken down into PGA through photorespiration. Photorespiration is not only a resource-demanding process but also results in CO2 loss which affects photosynthetic efficiency in C3 plants. Here, we propose to circumvent photorespiration by adopting the cyanobacterial glycolate decarboxylation pathway into C3 plants. For that, we have integrated the cyanobacterial glycolate decarboxylation pathway into a kinetic model of C3 photosynthetic pathway to evaluate its impact on photosynthesis and photorespiration. Our results show that the cyanobacterial glycolate decarboxylation bypass model exhibits a 10% increase in net photosynthetic rate (A) in comparison with C3 model. Moreover, an increased supply of intercellular CO2 (Ci) from the bypass resulted in a 54.8% increase in PGA while reducing photorespiratory intermediates including glycolate (- 49%) and serine (- 32%). The bypass model, at default conditions, also elucidated a decline in phosphate-based metabolites including RuBP (- 61.3%). The C3 model at elevated level of inorganic phosphate (Pi), exhibited a significant change in RuBP (+ 355%) and PGA (- 98%) which is attributable to the low availability of Ci. Whereas, at elevated Pi, the bypass model exhibited an increase of 73.1% and 33.9% in PGA and RuBP, respectively. Therefore, we deduce a synergistic effect of elevation in CO2 and Pi pool on photosynthesis. We also evaluated the integrative action of CO2, Pi, and Rubisco carboxylation activity (Vcmax) on A and observed that their simultaneous increase raised A by 26%, in the bypass model. Taken together, the study potentiates engineering of cyanobacterial decarboxylation pathway in C3 plants to bypass photorespiration thereby increasing the overall efficiency of photosynthesis.

Modeling Light Response of Electron Transport Rate and Its Allocation for Ribulose Biphosphate Carboxylation and Oxygenation

Accurately describing the light response curve of electron transport rate (J-I curve) and allocation of electron flow for ribulose biphosphate (RuBP) carboxylation (J _C-I curve) and that for oxygenation (J _O-I curve) is fundamental for modeling of light relations of electron flow at the whole-plant and ecosystem scales. The non-rectangular hyperbolic model (hereafter, NH model) has been widely used to characterize light response of net photosynthesis rate (A _n; A _n-I curve) and J-I curve. However, NH model has been reported to overestimate the maximum A _n (A _nmax) and the maximum J (J _max), largely due to its asymptotic function. Meanwhile, few efforts have been delivered for describing J _C-I and J _O-I curves. The long-standing challenge on describing A _n-I and J-I curves have been resolved by a recently developed A _n-I and J-I models (hereafter, Ye model), which adopt a nonasymptotic function. To test whether Ye model can resolve the challenge of NH model in reproducing J-I, J _C-I and J _O-I curves over light-limited, light-saturated, and photoinhibitory I levels, we compared the performances of Ye model and NH model against measurements on two C₃ crops (Triticum aestivum L. and Glycine max L.) grown in field. The results showed that NH model significantly overestimated the A _nmax and J _max for both species, which can be accurately obtained by Ye model. Furthermore, NH model significantly overestimated the maximum electron flow for carboxylation (J _C-max) but not the maximum electron flow for oxygenation (J _O-max) for both species, disclosing the reason underlying the long-standing problem of NH model-overestimation of J _max and A _nmax.

Rubisco carboxylase/oxygenase: From the enzyme to the globe: A gas exchange perspective

Rubisco is the primary carboxylase of the photosynthetic process, the most abundant enzyme in the biosphere, and also one of the best-characterized enzymes. Rubisco also functions as an oxygenase, a discovery made 50 years ago by Bill Ogren. Carboxylation of ribulose bisphosphate (RuBP) is the first step of the photosynthetic carbon reduction cycle and leads to the assimilation of CO₂, whereas the oxygenase activity necessitates the recycling of phosphoglycolate through the photorespiratory carbon oxidation cycle with concomitant loss of CO₂. Since the discovery of Rubisco's dual function, the biochemical properties of Rubisco have underpinned the mechanistic mathematical models of photosynthetic CO₂ fixation which link Rubisco kinetic properties to gas exchange of leaves. This has allowed assessments of global CO₂ exchange and predictions of how Rubisco has and will shape the environmental responses of crop and global photosynthesis in future climates. Rubisco's biochemical properties, including its slow catalytic turnover and poor affinity for CO₂, constrain crop growth and therefore improving its activity and regulation and minimising photorespiration are key targets for crop improvement.

Dynamic light caused less photosynthetic suppression, rather than more, under nitrogen deficit conditions than under sufficient nitrogen supply conditions in soybean

BACKGROUND

Plants are always exposed to dynamic light. The photosynthetic light use efficiency of leaves is lower in dynamic light than in uniform irradiance. Research on the influence of environmental factors on dynamic photosynthesis is very limited. Nitrogen is critical for plants, especially for photosynthesis. Low nitrogen (LN) decreases ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) and thus limits photosynthesis. The decrease in Rubisco also delays photosynthetic induction in LN leaves; therefore, we hypothesized that the difference of photosynthetic CO2 fixation between uniform and dynamic light will be greater in LN leaves compared to leaves with sufficient nitrogen supply.

RESULTS

To test this hypothesis, soybean plants were grown under low or high nitrogen (HN), and the photosynthetic gas exchange, enzyme activity and protein amount in leaves were measured under uniform and dynamic light. Unexpectedly, dynamic light caused less photosynthetic suppression, rather than more, in LN leaves than in HN leaves. The underlying mechanism was also clarified. Short low-light (LL) intervals did not affect Rubisco activity but clearly deactivated fructose-1,6-bisphosphatase (FBPase) and sedoheptulose-1,7-bisphosphatase (SBPase), indicating that photosynthetic induction after a LL interval depends on the reactivation of FBPase and SBPase rather than Rubisco. In LN leaves, the amount of Rubisco decreased more than FBPase and SBPase, so FBPase and SBPase were present in relative excess. A lower fraction of FBPase and SBPase needs to be activated in LN leaves for photosynthesis recovery during the high-light phase of dynamic light. Therefore, photosynthetic recovery is faster in LN leaves than in HN leaves, which relieves the photosynthetic suppression caused by dynamic light in LN leaves.

CONCLUSIONS

Contrary to our expectations, dynamic light caused less photosynthetic suppression, rather than more, in LN leaves than in HN leaves of soybean. This is the first report of a stress condition alleviating the photosynthetic suppression caused by dynamic light.

The response of stomatal conductance to seasonal drought in tropical forests

Stomata regulate CO₂ uptake for photosynthesis and water loss through transpiration. The approaches used to represent stomatal conductance (g_s ) in models vary. In particular, current understanding of drivers of the variation in a key parameter in those models, the slope parameter (i.e. a measure of intrinsic plant water-use-efficiency), is still limited, particularly in the tropics. Here we collected diurnal measurements of leaf gas exchange and leaf water potential (Ψ_leaf ), and a suite of plant traits from the upper canopy of 15 tropical trees in two contrasting Panamanian forests throughout the dry season of the 2016 El Niño. The plant traits included wood density, leaf-mass-per-area (LMA), leaf carboxylation capacity (V_c,max ), leaf water content, the degree of isohydry, and predawn Ψ_leaf . We first investigated how the choice of four commonly used leaf-level g_s models with and without the inclusion of Ψ_leaf as an additional predictor variable influence the ability to predict g_s , and then explored the abiotic (i.e. month, site-month interaction) and biotic (i.e. tree-species-specific characteristics) drivers of slope parameter variation. Our results show that the inclusion of Ψ_leaf did not improve model performance and that the models that represent the response of g_s to vapor pressure deficit performed better than corresponding models that respond to relative humidity. Within each g_s model, we found large variation in the slope parameter, and this variation was attributable to the biotic driver, rather than abiotic drivers. We further investigated potential relationships between the slope parameter and the six available plant traits mentioned above, and found that only one trait, LMA, had a significant correlation with the slope parameter (R²  = 0.66, n = 15), highlighting a potential path towards improved model parameterization. This study advances understanding of g_s dynamics over seasonal drought, and identifies a practical, trait-based approach to improve modeling of carbon and water exchange in tropical forests.

How do vascular plants perform photosynthesis in extreme environments? An integrative ecophysiological and biochemical story

In this work, we review the physiological and molecular mechanisms that allow vascular plants to perform photosynthesis in extreme environments, such as deserts, polar and alpine ecosystems. Specifically, we discuss the morpho/anatomical, photochemical and metabolic adaptive processes that enable a positive carbon balance in photosynthetic tissues under extreme temperatures and/or severe water-limiting conditions in C₃ species. Nevertheless, only a few studies have described the in situ functioning of photoprotection in plants from extreme environments, given the intrinsic difficulties of fieldwork in remote places. However, they cover a substantial geographical and functional range, which allowed us to describe some general trends. In general, photoprotection relies on the same mechanisms as those operating in the remaining plant species, ranging from enhanced morphological photoprotection to increased scavenging of oxidative products such as reactive oxygen species. Much less information is available about the main physiological and biochemical drivers of photosynthesis: stomatal conductance (g_s ), mesophyll conductance (g_m ) and carbon fixation, mostly driven by RuBisCO carboxylation. Extreme environments shape adaptations in structures, such as cell wall and membrane composition, the concentration and activation state of Calvin-Benson cycle enzymes, and RuBisCO evolution, optimizing kinetic traits to ensure functionality. Altogether, these species display a combination of rearrangements, from the whole-plant level to the molecular scale, to sustain a positive carbon balance in some of the most hostile environments on Earth.

No evidence for triose phosphate limitation of light-saturated leaf photosynthesis under current atmospheric CO2 concentration

The triose phosphate utilization (TPU) rate has been identified as one of the processes that can limit terrestrial plant photosynthesis. However, we lack a robust quantitative assessment of TPU limitation of photosynthesis at the global scale. As a result, TPU, and its potential limitation of photosynthesis, is poorly represented in terrestrial biosphere models (TBMs). In this study, we utilized a global data set of photosynthetic CO₂ response curves representing 141 species from tropical rainforests to Arctic tundra. We quantified TPU by fitting the standard biochemical model of C₃ photosynthesis to measured photosynthetic CO₂ response curves and characterized its instantaneous temperature response. Our results demonstrate that TPU does not limit leaf photosynthesis at the current ambient atmospheric CO₂ concentration. Furthermore, our results showed that the light-saturated photosynthetic rates of plants growing in cold environments are not more often limited by TPU than those of plants growing in warmer environments. In addition, our study showed that the instantaneous temperature response of TPU is distinct from temperature response of the maximum rate of Rubisco carboxylation. The new formulations of the temperature response of TPU derived in this study may prove useful in quantifying the biochemical limits to terrestrial plant photosynthesis and improve the representation of plant photosynthesis in TBMs.

Is triose phosphate utilization involved in the feedback inhibition of photosynthesis in rice under conditions of sink limitation?

This study aimed to understand the physiological basis of rice photosynthetic response to C source-sink imbalances, focusing on the dynamics of the photosynthetic parameter triose phosphate utilization (TPU). Here, rice (Oriza sativa L.) indica cultivar IR64 were grown in controlled environment chambers under current ambient CO2 concentration until heading, and thereafter two CO2 treatments (400 and 800 μmol mol-1) were compared in the presence and absence of a panicle-pruning treatment modifying the C sink. At 2 weeks after heading, photosynthetic parameters derived from CO2 response curves, and non-structural carbohydrate content of flag leaf and internodes were measured three to four times of day. Spikelet number per panicle and flag leaf area on the main culm were recorded. Net C assimilation and TPU decreased progressively after midday in panicle-pruned plants, especially under 800 μmol mol-1 CO2. This TPU reduction was explained by sucrose accumulation in the flag leaf resulting from the sink limitation. Taking together, our findings suggest that TPU is involved in the regulation of photosynthesis in rice under elevated CO2 conditions, and that sink limitation effects should be considered in crop models.

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (V_c,max ) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting V_c,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of V_c,max was tested. V_c,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict V_c,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts V_c,max of mature leaves in Panamanian tropical forests (R²  = 0.90). However, this single-age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for V_c,max and leaf age enabled construction of the V_c,max -age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in V_c,max , assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize V_c,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.

High-throughput field phenotyping using hyperspectral reflectance and partial least squares regression (PLSR) reveals genetic modifications to photosynthetic capacity

Spectroscopy is becoming an increasingly powerful tool to alleviate the challenges of traditional measurements of key plant traits at the leaf, canopy, and ecosystem scales. Spectroscopic methods often rely on statistical approaches to reduce data redundancy and enhance useful prediction of physiological traits. Given the mechanistic uncertainty of spectroscopic techniques, genetic modification of plant biochemical pathways may affect reflectance spectra causing predictive models to lose power. The objectives of this research were to assess over two separate years, whether a predictive model can represent natural and imposed variation in leaf photosynthetic potential for different crop cultivars and genetically modified plants, to assess the interannual capabilities of a partial least square regression (PLSR) model, and to determine whether leaf N is a dominant driver of photosynthesis in PLSR models. In 2016, a PLSR analysis of reflectance spectra coupled with gas exchange data was used to build predictive models for photosynthetic parameters including maximum carboxylation rate of Rubisco (V _c,max ), maximum electron transport rate (J _max ) and percentage leaf nitrogen ([N]). The model was developed for wild type and genetically modified plants that represent a wide range of photosynthetic capacities. Results show that hyperspectral reflectance accurately predicted V _c,max, J _max and [N] for all plants measured in 2016. Applying these PLSR models to plants grown in 2017 resulted in a strong predictive ability relative to gas exchange measurements for V _c,max, but not for J _max, and not for genotypes unique to 2017. Building a new model including data collected in 2017 resulted in more robust predictions, with R² increases of 17% for V _c,max . and 13% J _max . Plants generally have a positive correlation between leaf nitrogen and photosynthesis, however, tobacco with reduced Rubisco (SSuD) had significantly higher [N] despite much lower V _c,max. The PLSR model was able to accurately predict both lower V _c,max and higher leaf [N] for this genotype suggesting that the spectral based estimates of V _c,max and leaf nitrogen [N] are independent. These results suggest that the PLSR model can be applied across years, but only to genotypes used to build the model and that the actual mechanism measured with the PLSR technique is not directly related to leaf [N]. The success of the leaf-scale analysis suggests that similar approaches may be successful at the canopy and ecosystem scales but to use these methods across years and between genotypes at any scale, application of accurately populated physical based models based on radiative transfer principles may be required.

The "one-point method" for estimating maximum carboxylation capacity of photosynthesis: A cautionary tale

The maximum carboxylation capacity of Rubisco, V_c,max , is an important photosynthetic parameter that is key to accurate estimation of carbon assimilation. The gold-standard technique for determining V_c,max is to derive V_c,max from the initial slope of an A-C_i curve (the response of photosynthesis, A, to intercellular CO₂ concentration, C_i ). Accurate estimates of V_c,max derived from an alternative and rapid "one-point" measurement of photosynthesis could greatly accelerate data collection and model parameterization. We evaluated the practical application of the one-point method in six species measured under standard conditions (saturating irradiance and 400 μmol CO₂ mol^-1 ) and under conditions that would increase the likelihood for successful estimation of V_c,max : (a) ensuring Rubisco-limited A by measuring at 300 μmol CO₂ mol^-1 and (b) allowing time for acclimation to saturating irradiance prior to measurement. The one-point method significantly underestimated V_c,max in four of the six species, providing estimates 21%-32% below fitted values. We identified ribulose-1,5-bisphosphate-limited A, light acclimation, and the use of an assumed respiration rate as factors that limited the effective use of the one-point method to accurately estimate V_c,max . We conclude that the one-point method requires a species-specific understanding of its application, is often unsuccessful, and must be used with caution.

Interactions between Climate and Nutrient Cycles on Forest Response to Global Change: The Role of Mixed Forests

Forest ecosystems are undergoing unprecedented changes in environmental conditions due to global change impacts. Modification of global biogeochemical cycles of carbon and nitrogen, and the subsequent climate change are affecting forest functions at different scales, from physiology and growth of individual trees to cycling of nutrients. This review summarizes the present knowledge regarding the impact of global change on forest functioning not only with respect to climate change, which is the focus of most studies, but also the influence of altered nitrogen cycle and the interactions among them. The carbon dioxide (CO2) fertilization effect on tree growth is expected to be constrained by nutrient imbalances resulting from high N deposition rates and the counteractive effect of increasing water deficit, which interact in a complex way. At the community level, responses to global change are modified by species interactions that may lead to competition for resources and/or relaxation due to facilitation and resource partitioning processes. Thus, some species mixtures can be more resistant to drought than their respective pure forests, albeit it depends on environmental conditions and species’ functional traits. Climate change and nitrogen deposition have additional impacts on litterfall dynamics, and subsequent decomposition and nutrient mineralization processes. Elemental ratios (i.e., stoichiometry) are associated with important ecosystem traits, including trees’ adaptability to stress or decomposition rates. As stoichiometry of different ecosystem components are also influenced by global change, nutrient cycling in forests will be altered too. Therefore, a re-assessment of traditional forest management is needed in order to cope with global change. Proposed silvicultural systems emphasize the key role of diversity to assure multiple ecosystem services, and special attention has been paid to mixed-species forests. Finally, a summary of the patterns and underlying mechanisms governing the relationships between diversity and different ecosystems functions, such as productivity and stability, is provided.

The influence of canopy radiation parameter uncertainty on model projections of terrestrial carbon and energy cycling

Reducing uncertainties in Earth System Model predictions requires carefully evaluating core model processes. Here we examined how canopy radiative transfer model (RTM) parameter uncertainties, in combination with canopy structure, affect terrestrial carbon and energy projections in a demographic land-surface model, the Ecosystem Demography model (ED2). Our analyses focused on temperate deciduous forests and tested canopies of varying structural complexity. The results showed a strong sensitivity of tree productivity, albedo, and energy balance projections to RTM parameters. Impacts of radiative parameter uncertainty on stand-level canopy net primary productivity ranged from ~2 to > 20% and was most sensitive to canopy clumping and leaf reflectance/transmittance in the visible spectrum (~400–750 nm). ED2 canopy albedo varied by ~1 to ~10% and was most sensitive to near-infrared reflectance (~800–1200 nm). Bowen ratio, in turn, was most sensitive to wood optical properties parameterization; this was much larger than expected based on literature, suggesting model instabilities. In vertically and spatially complex canopies the model response to RTM parameterization may show an apparent reduced sensitivity when compared to simpler canopies, masking much larger changes occurring within the canopy. Our findings highlight both the importance of constraining canopy RTM parameters in models and valuating how the canopy structure responds to those parameter values. Finally, we advocate for more model evaluation, similar to this study, to highlight possible issues with model behavior or process representations, particularly models with demographic representations, and identify potential ways to inform and constrain model predictions.

Critical review: incorporating the arrangement of mitochondria and chloroplasts into models of photosynthesis and carbon isotope discrimination

The arrangement of mitochondria and chloroplasts, together with the relative resistances of cell wall and chloroplast, determine the path of diffusion out of the leaf for (photo)respired CO₂. Traditional photosynthesis models have assumed a tight arrangement of chloroplasts packed together against the cell wall with mitochondria located behind the chloroplasts, deep inside the cytosol. Accordingly, all (photo)respired CO₂ must cross the chloroplast before diffusing out of the leaf. Different arrangements have recently been considered, where all or part of the (photo)respired CO₂ diffuses through the cytosol without ever entering the chloroplast. Assumptions about the path for the (photo)respiratory flux are particularly relevant for the calculation of mesophyll conductance (g_m). If (photo)respired CO₂ can diffuse elsewhere besides the chloroplast, apparent g_m is no longer a mere physical resistance but a flux-weighted variable sensitive to the ratio of (photo)respiration to net CO₂ assimilation. We discuss existing photosynthesis models in conjunction with their treatment of the (photo)respiratory flux and present new equations applicable to the generalized case where (photo)respired CO₂ can diffuse both into the chloroplast and through the cytosol. Additionally, we present a new generalized Δ¹³C model that incorporates this dual diffusion pathway. We assess how assumptions about the fate of (photo)respired CO₂ affect the interpretation of photosynthetic data and the challenges it poses for the application of different models.

Seasonal responses of photosynthetic parameters in maize and sunflower and their relationship with leaf functional traits

Estimates of seasonal variation in photosynthetic capacity (P_c ) are critical for modeling the time course of carbon fluxes. Given the time-intensive nature of calculating P_c parameters via gas exchange, it is appealing to calculate parameter variation via changes in chlorophyll (Chl) and nitrogen (N) content by assuming that P_c scales with these variables. Although seasonal changes in P_c and the relationships between N and P_c have been evaluated in forest canopies, there is limited data on seasonal parameter values in crops, nor is it clear if seasonal changes in P_c can be estimated from leaf traits under the high N fertility of managed systems. We characterized the seasonal variability of the maximum rates of carboxylation (V_cmax ) and electron transport (J_max ) under well-fertilized conditions for maize (Zea mays L.) and sunflower (Helianthus annuus L.) and coupled these data with measurements of Chl, N, and leaf mass per unit area (LMA). The seasonal Chl-N relationship was significant in maize, but not in sunflower. Area-based N-V_cmax relationships were not significant for either crop. Mass-based N-V_cmax relationships were weak in sunflower, but highly significant in maize. Our results suggest that P_c can be seasonally adjusted in maize with reliable estimates of changes in LMA.

Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought

Global climate change is expected to increase drought duration and intensity in certain regions while increasing rainfall in others. The quantitative consequences of increased drought for ecosystems are not easy to predict. Process-based models must be informed by experiments to determine the resilience of plants and ecosystems from different climates. Here, we demonstrate what and how experimentally derived quantitative information can improve the representation of stomatal and non-stomatal photosynthetic responses to drought in large-scale vegetation models. In particular, we review literature on the answers to four key questions: (1) Which photosynthetic processes are affected under short-term drought? (2) How do the stomatal and non-stomatal responses to short-term drought vary among species originating from different hydro-climates? (3) Do plants acclimate to prolonged water stress, and do mesic and xeric species differ in their degree of acclimation? (4) Does inclusion of experimentally based plant functional type specific stomatal and non-stomatal response functions to drought help Land Surface Models to reproduce key features of ecosystem responses to drought? We highlighted the need for evaluating model representations of the fundamental eco-physiological processes under drought. Taking differential drought sensitivity of different vegetation into account is necessary for Land Surface Models to accurately model drought responses, or the drought impacts on vegetation in drier environments may be over-estimated.

Modelling carbon sources and sinks in terrestrial vegetation

Contents Summary 652 I. Introduction 652 II. Discrepancy in predicting the effects of rising [CO₂ ] on the terrestrial C sink 655 III. Carbon and nutrient storage in plants and its modelling 656 IV. Modelling the source and the sink: a plant perspective 657 V. Plant-scale water and Carbon flux models 660 VI. Challenges for the future 662 Acknowledgements 663 Authors contributions 663 References 663 SUMMARY: The increase in atmospheric CO₂ in the future is one of the most certain projections in environmental sciences. Understanding whether vegetation carbon assimilation, growth, and changes in vegetation carbon stocks are affected by higher atmospheric CO₂ and translating this understanding in mechanistic vegetation models is of utmost importance. This is highlighted by inconsistencies between global-scale studies that attribute terrestrial carbon sinks to CO₂ stimulation of gross and net primary production on the one hand, and forest inventories, tree-scale studies, and plant physiological evidence showing a much less pronounced CO₂ fertilization effect on the other hand. Here, we review how plant carbon sources and sinks are currently described in terrestrial biosphere models. We highlight an uneven representation of complexity between the modelling of photosynthesis and other processes, such as plant respiration, direct carbon sinks, and carbon allocation, largely driven by available observations. Despite a general lack of data on carbon sink dynamics to drive model improvements, ways forward toward a mechanistic representation of plant carbon sinks are discussed, leveraging on results obtained from plant-scale models and on observations geared toward model developments.

Photorespiration differs among Arabidopsis thaliana ecotypes and is correlated with photosynthesis

A greater understanding of natural variation in photosynthesis will inform strategies for crop improvement by revealing overlooked opportunities. We use Arabidopsis thaliana ecotypes as a model system to assess (i) how photosynthesis and photorespiration covary and (ii) how mesophyll conductance influences water use efficiency (WUE). Phenotypic variation in photorespiratory CO2 efflux was correlated with assimilation rates and two metrics of photosynthetic capacity (i.e. VCmax and Jmax); however, genetic correlations were not detected between photosynthesis and photorespiration. We found standing genetic variation-as broad-sense heritability-for most photosynthetic traits, including photorespiration. Genetic correlation between photosynthetic electron transport and carboxylation capacities indicates that these traits are genetically constrained. Winter ecotypes had greater mesophyll conductance, maximum carboxylation capacity, maximum electron transport capacity, and leaf structural robustness when compared with spring ecotypes. Stomatal conductance varied little in winter ecotypes, leading to a positive correlation between integrated WUE and mesophyll conductance. Thus, variation in mesophyll conductance can modulate WUE among A. thaliana ecotypes without a significant loss in assimilation. Genetic correlations between traits supplying energy and carbon to the Calvin-Benson cycle are consistent with biochemical models, suggesting that selection on either of these traits would improve all of them. Similarly, the lack of a genetic correlation between photosynthesis and photorespiration suggests that the positive scaling of these two traits can be broken.

Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic

Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C (V_c,max.25 and J_max.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We measured photosynthetic CO₂ response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of V_c,max and J_max were 17% lower than commonly used values. When scaled to 25°C, V_c,max.25 and J_max.25 were two- to five-fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf-level modeling demonstrated that current parameterization of TBMs resulted in a two-fold underestimation of the capacity for leaf-level CO₂ assimilation in Arctic vegetation. This study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

Short-term thermal photosynthetic responses of C4 grasses are independent of the biochemical subtype

C4 photosynthesis evolved independently many times, resulting in multiple biochemical pathways; however, little is known about how these different pathways respond to temperature. We investigated the photosynthetic responses of eight C4 grasses belonging to three biochemical subtypes (NADP-ME, PEP-CK, and NAD-ME) to four leaf temperatures (18, 25, 32, and 40 °C). We also explored whether the biochemical subtype influences the thermal responses of (i) in vitro PEPC (Vpmax) and Rubisco (Vcmax) maximal activities, (ii) initial slope (IS) and CO2-saturated rate (CSR) derived from the A-Ci curves, and (iii) CO2 leakage out of the bundle sheath estimated from carbon isotope discrimination. We focussed on leakiness and the two carboxylases because they determine the coordination of the CO2-concentrating mechanism and are important for parameterizing the semi-mechanistic C4 photosynthesis model. We found that the thermal responses of Vpmax and Vcmax, IS, CSR, and leakiness varied among the C4 species independently of the biochemical subtype. No correlation was observed between Vpmax and IS or between Vcmax and CSR; while the ratios Vpmax/Vcmax and IS/CSR did not correlate with leakiness among the C4 grasses. Determining mesophyll and bundle sheath conductances in diverse C4 grasses is required to further elucidate how C4 photosynthesis responds to temperature.

The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests

Leaf quantity (i.e., canopy leaf area index, LAI), quality (i.e., per-area photosynthetic capacity), and longevity all influence the photosynthetic seasonality of tropical evergreen forests. However, these components of tropical leaf phenology are poorly represented in most terrestrial biosphere models (TBMs). Here, we explored alternative options for the representation of leaf phenology effects in TBMs that employ the Farquahar, von Caemmerer & Berry (FvCB) representation of CO₂ assimilation. We developed a two-fraction leaf (sun and shade), two-layer canopy (upper and lower) photosynthesis model to evaluate different modeling approaches and assessed three components of phenological variations (i.e., leaf quantity, quality, and within-canopy variation in leaf longevity). Our model was driven by the prescribed seasonality of leaf quantity and quality derived from ground-based measurements within an Amazonian evergreen forest. Modeled photosynthetic seasonality was not sensitive to leaf quantity, but was highly sensitive to leaf quality and its vertical distribution within the canopy, with markedly more sensitivity to upper canopy leaf quality. This is because light absorption in tropical canopies is near maximal for the entire year, implying that seasonal changes in LAI have little impact on total canopy light absorption; and because leaf quality has a greater effect on photosynthesis of sunlit leaves than light limited, shade leaves and sunlit foliage are more abundant in the upper canopy. Our two-fraction leaf, two-layer canopy model, which accounted for all three phenological components, was able to simulate photosynthetic seasonality, explaining ~90% of the average seasonal variation in eddy covariance-derived CO₂ assimilation. This work identifies a parsimonious approach for representing tropical evergreen forest photosynthetic seasonality in TBMs that utilize the FvCB model of CO₂ assimilation and highlights the importance of incorporating more realistic phenological mechanisms in models that seek to improve the projection of future carbon dynamics in tropical evergreen forests.

Leaf and canopy scale drivers of genotypic variation in soybean response to elevated carbon dioxide concentration

The atmospheric [CO2 ] in which crops grow today is greater than at any point in their domestication history and represents an opportunity for positive effects on seed yield that can counteract the negative effects of greater heat and drought this century. In order to maximize yields under future atmospheric [CO2 ], we need to identify and study crop cultivars that respond most favorably to elevated [CO2 ] and understand the mechanisms contributing to their responsiveness. Soybean (Glycine max Merr.) is a widely grown oilseed crop and shows genetic variation in response to elevated [CO2 ]. However, few studies have studied the physiological basis for this variation. Here, we examined canopy light interception, photosynthesis, respiration and radiation use efficiency along with yield and yield parameters in two cultivars of soybean (Loda and HS93-4118) previously reported to have similar seed yield at ambient [CO2 ], but contrasting responses to elevated [CO2 ]. Seed yield increased by 26% at elevated [CO2 ] (600 μmol/mol) in the responsive cultivar Loda, but only by 11% in HS93-4118. Canopy light interception and leaf area index were greater in HS93-4118 in ambient [CO2 ], but increased more in response to elevated [CO2 ] in Loda. Radiation use efficiency and harvest index were also greater in Loda than HS93-4118 at both ambient and elevated [CO2 ]. Daily C assimilation was greater at elevated [CO2 ] in both cultivars, while stomatal conductance was lower. Electron transport capacity was also greater in Loda than HS93-4118, but there was no difference in the response of photosynthetic traits to elevated [CO2 ] in the two cultivars. Overall, this greater understanding of leaf- and canopy-level photosynthetic traits provides a strong conceptual basis for modeling genotypic variation in response to elevated [CO2 ].