Leaf chlorophyll content is the crucial factor for the temporal and spatial variation of global plants leaf maximum carboxylation rate.

Photosynthesis plays an important role in the terrestrial carbon and water cycles which are often studied using terrestrial biosphere models (TBMs). The maximum carboxylation rate at 25 °C (Vcmax25) is a key parameter in the photosynthesis module of TBMs, yet the spatiotemporal distribution of Vcmax25 and the driving mechanism are not fully understood. In this study, Enzyme Kinetics response model, leaf chlorophyll content response model and partial correlation analysis were used to analyze the temporal and spatial changes patterns of atmospheric environment, enzyme dynamic and soil nutrition on Vcmax25 and the driving mechanism, and has made a few useful conclusions: (1) Vcmax25 varies significantly with latitude and between- and within-plant function types (PFTs), which mainly dependent on leaf chlorophyll content (LCC). Under the influence of temperature, the contribution of LCC to the seasonal variation of Vcmax25 is very different among the eight main biomes, with an average contribution of 21 %. (2) The relationship between meteorological variables and Vcmax25 was significant, due to the fact that meteorological variables drive the Rubisco enzyme content that have a significant relationship with Vcmax25, rather than directly acting on Vcmax25. (3) Soil nutrient elements had significant influence on the spatiotemporal variation of Vcmax25 and LCC. The results showed that soil total carbon, soil nitrogen and organic carbon not only affect the temporal and spatial pattern of Vcmax25, but also are the key factors of LCC temporal-spatial variation. These findings provide useful information for better parameterization of Vcmax25 in TBMs.

Comparative assessment of leaf photosynthetic capacity datasets for estimating terrestrial gross primary productivity.

The maximum Rubisco carboxylation rate normalized to 25 °C (Vcmax25) is a key parameter in terrestrial biosphere models for simulating carbon cycling. Recently, global distributions of Vcmax25 have been derived through various methods and different data, including field measurements, ecological optimality theory (EOT), leaf chlorophyll content (LCC), and solar-induced chlorophyll fluorescence (SIF). However, direct validation poses challenges due to high uncertainty arising from limited ground-based observations. This study conducted an indirect evaluation of four Vcmax25 datasets by assessing the accuracy of gross primary productivity (GPP) simulated using the Biosphere-atmosphere Exchange Process Simulator (BEPS) at both site and global scales. Results indicate that, compared to utilizing Vcmax25 fixed by plant functional types (PFT) derived from field measurements, incorporating Vcmax25 derived from SIF and LCC (SIF + LCC), or solely LCC, into BEPS significantly reduces simulated errors in the annual total GPP, with a 23.2 %-25.1 % decrease in the average absolute bias across 196 FLUXNET2015 sites. Daily GPP for evergreen needleleaf forests, deciduous broadleaf forests, shrublands, grasslands, and croplands shows a 7.8 %-27.6 % decrease in absolute bias, primarily attributed to reduced simulation errors during off-peak seasons of vegetation growth. Conversely, the annual total GPP error simulated using EOT-derived Vcmax25 increases slightly (2.2 %) compared to that simulated using PFT-fixed Vcmax25. This is primarily due to a significant overestimation in evergreen broadleaf forests and underestimation in croplands, despite slight increased accuracy for other PFTs. The global annual GPP simulated using Vcmax25 with seasonal variations (i.e., LCC Vcmax25 and SIF + LCC Vcmax25) yields a 4.3 %-7.3 % decrease compared to that simulated using PFT-fixed Vcmax25. Compared to FLUXCOM and GOSIF GPP products, the GPP simulated based on SIF + LCC Vcmax25 and LCC Vcmax25 demonstrates better consistency (R2 = 0.91-0.93, RMSE = 314.2-376.6 g C m-2 yr-1). This study underscores the importance of accurately characterizing the spatiotemporal variations in Vcmax25 for the accurate simulation of global vegetation productivity.

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.

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

Using steady-state photosynthesis-intercellular CO2 concentration (A-Ci) response curves to obtain the maximum rates of ribulose-1,5-bisphosphate carboxylase oxygenase carboxylation (Vcmax) and electron transport (Jmax) is time-consuming and labour-intensive. Instead, the rapid A-Ci 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-Ci and RACiR curves. We found that Vcmax and Jmax calculated by steady-state A-Ci 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 Vcmax and Jmax of evergreen broadleaved species.

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.

MAIN CONCLUSION: By combining hyperspectral signatures of peanut and soybean, we predicted Vcmax and Jmax with 70 and 50% accuracy. The PLS was the model that better predicted these photosynthetic parameters. One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.

Changes in leaf functional traits with leaf age: when do leaves decrease their photosynthetic capacity in Amazonian trees?

Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from -0.003 to -0.065 µmol CO2 m-2 s-1 day-1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees.

Selecting informative bands for partial least squares regressions improves their goodness-of-fits to estimate leaf photosynthetic parameters from hyperspectral data.

The plant photosynthetic capacity determines the photosynthetic rates of the terrestrial biosphere. Timely approaches to obtain the spatiotemporal variations of the photosynthetic parameters are urgently needed to grasp the gas exchange rhythms of the terrestrial biosphere. While partial least squares regression (PLSR) is a promising way to predict the photosynthetic parameters maximum carboxylation rate (Vcmax) and maximum electron transport rate (Jmax) rapidly and non-destructively from hyperspectral data, the approach, however, faces a high risk of overfitting and remains a high hurdle for applications. In this study, we propose to incorporate proper band selection techniques for PLSR analysis to refine the goodness-of-fit (GoF) in estimating Vcmax and Jmax. Different band selection procedures coupled with different hyperspectral forms (reflectance, apparent absorption, as well as derivatives) were examined. Our results demonstrate that the GoFs of PLSR models could be greatly improved by combining proper band selection methods (especially the iterative stepwise elimination approach) rather than using full bands as commonly done with PLSR. The results also show that the 1st order derivative spectra had a balance between accuracy (R2 = 0.80 for Vcmax, and 0.94 for Jmax) and denoising (when a Gaussian noise was added to each leaf reflectance spectrum at each wavelength with a standard deviation of 1%) on retrieving photosynthetic parameters from hyperspectral data. Our results clearly illustrate the advantage of using the band selection approach for PLSR dimensionality reduction and model optimization, highlighting the superiority of using derivative spectra for Vcmax and Jmax estimations, which should provide valuable insights for retrieving photosynthetic parameters from hyperspectral remotely sensed data.

Warming and elevated CO2 alter tamarack C fluxes, growth and mortality: evidence for heat stress-related C starvation in the absence of water stress.

Climate warming is increasing the frequency of climate-induced tree mortality events. While drought combined with heat is considered the primary cause of this mortality, little is known about whether moderately high temperatures alone can induce mortality, or whether rising CO2 would prevent mortality at high growth temperatures. We grew tamarack (Larix laricina) under ambient (400 p.p.m.) and elevated (750 p.p.m.) CO2 concentrations combined with ambient, ambient +4 °C and ambient +8 °C growth temperatures to investigate whether high growth temperatures lead to carbon (C) limitations and mortality. Growth at +8 °C led to 40% mortality in the ambient CO2 (8TAC) treatment, but no mortality in the elevated CO2 treatment. Thermal acclimation of respiration led to similar leaf C balances across the warming treatments, despite a lack of photosynthetic acclimation. Photosynthesis was stimulated under elevated CO2, increasing seedling growth, but not leaf C concentrations. However, growth and foliar C concentrations were lowest in the +8 °C treatments, even with elevated CO2. Dying 8TAC seedlings had lower needle C concentrations and lower ratios of photosynthesis to respiration than healthy 8TAC seedlings, indicating that C limitations were likely the cause of seedling mortality under high growth temperatures.

Predicting photosynthetic capacity in tobacco using shortwave infrared spectral reflectance.

Plateauing yield and stressful environmental conditions necessitate selecting crops for superior physiological traits with untapped potential to enhance crop performance. Plant productivity is often limited by carbon fixation rates that could be improved by increasing maximum photosynthetic carboxylation capacity (Vcmax). However, Vcmax measurements using gas exchange and biochemical assays are slow and laborious, prohibiting selection in breeding programs. Rapid hyperspectral reflectance measurements show potential for predicting Vcmax using regression models. While several hyperspectral models have been developed, contributions from different spectral regions to predictions of Vcmax have not been clearly identified or linked to biochemical variation contributing to Vcmax. In this study, hyperspectral reflectance data from 350-2500 nm were used to build partial least squares regression models predicting in vivo and in vitro Vcmax. Wild-type and transgenic tobacco plants with antisense reductions in Rubisco content were used to alter Vcmax independent from chlorophyll, carbon, and nitrogen content. Different spectral regions were used to independently build partial least squares regression models and identify key regions linked to Vcmax and other leaf traits. The greatest Vcmax prediction accuracy used a portion of the shortwave infrared region from 2070 nm to 2470 nm, where the inclusion of fewer spectral regions resulted in more accurate models.

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.

Short- and long-term responses of photosynthetic capacity to temperature in four boreal tree species in a free-air warming and rainfall manipulation experiment.

High latitude forests cope with considerable variation in moisture and temperature at multiple temporal scales. To assess how their photosynthetic physiology responds to short- and long-term temperature variation, we measured photosynthetic capacity for four tree species growing in an open-air experiment in the boreal-temperate ecotone `Boreal Forest Warming at an Ecotone in Danger' (B4WarmED). The experiment factorially manipulated temperature above- and below-ground (ambient, +3.2 °C) and summer rainfall (ambient, 40% removal). We measured A/Ci curves at 18, 25 and 32 °C for individuals of two boreal (Pinus banksiana Lamb., Betula papyrifera Marsh.) and two temperate species (Pinus strobus L., Acer rubrum L.) experiencing the long-term warming and/or reduced-rainfall conditions induced by our experimental treatments. We calculated the apparent photosynthetic capacity descriptors VCmax,Ci and Jmax,Ci and their ratio for each measurement temperate. We hypothesized that (i) VCmax,Ci and Jmax,Ci would be down-regulated in plants experiencing longer term (e.g., weeks to months) warming and reduced rainfall (i.e., have lower values at a given measurement temperature), as is sometimes found in the literature, and that (ii) plants growing at warmer temperatures or from warmer ranges would show greater sensitivity (steeper slope) to short-term (minutes to hours) temperature variation. Neither hypothesis was supported as a general trend across the four species, as there was not a significant main effect (across species) of either warming or rainfall reduction on VCmax,Ci and Jmax,Ci. All species markedly increased VCmax,Ci and Jmax,Ci (and decreased their ratio) with short-term increases in temperature (i.e., contrasting values at 18, 25 and 32 °C), and those responses were independent of long-term treatments and did not differ among species. The Jmax,Ci:VCmax,Ci ratio was, however, significantly lower across species in warmed and reduced rainfall treatments. Collectively, these results suggest that boreal trees possess considerable short-term plasticity that may allow homeostasis of VCmax,Ci and Jmax,Ci to a longer term temperature treatment. Our results also caution against extrapolating results obtained under controlled and markedly contrasting temperature treatments to responses of photosynthetic parameters to more modest temperature changes expected in the near-term with climate warming in field conditions.

Seasonal variations in the relationship between sun-induced chlorophyll fluorescence and photosynthetic capacity from the leaf to canopy level in a rice crop.

Photosynthetic capacity (leaf maximum carboxylation rate, Vcmax) is a critical parameter for accurately assessing carbon assimilation by plant canopies. Recent studies of sun-induced chlorophyll fluorescence (SIF) have shown potential for estimating Vcmax at the ecosystem level. However, the relationship between SIF and Vcmax at the leaf and canopy levels is still poorly understood. In this study, we investigated the dynamic relationship between SIF and Vcmax and its controlling factors using SIF and CO2 response measurements in a rice paddy. We found that SIF and its yield (SIFy) were strongly correlated with Vcmax during the growing season, although the relationship varied with plant growth stages. After flowering, SIFy showed a stronger relationship with Vcmax than SIF flux at both the leaf and canopy levels. Further analysis suggested that the divergence of the link between SIF and Vcmax from leaf to canopy are the result of changes in canopy structure and leaf physiology, highlighting that these need to be considered when interpreting the SIF signal across spatial scales. Our results provide evidence that remotely sensed SIF observations can be used to track seasonal variations in Vcmax at the leaf and canopy levels.

The maximum carboxylation rate of Rubisco affects CO2 refixation in temperate broadleaved forest trees.

Mesophyll resistance to CO2 diffusion (rm) and the maximum carboxylation rate of Rubisco (Vcmax) affect photosynthetic rates, and can potentially also influence the percentage of respiratory and photorespiratory CO2 being refixated (Pr) by mesophyll cells. Here we investigated how various leaf anatomical traits (e.g. leaf mass per area [LMA] and leaf dry matter content [LDMC]) influenced rm in leaves of mature forest trees. We further explored how rm and Vcmax in turn affected Pr, and if these traits varied among species and leaves along a light gradient. Photosynthetic CO2 response of leaves grown in high-, medium-, and low-light environments was measured, from Pinus sylvestris [Scots pine], Picea abies [Norway spruce], Quercus robur [English oak], and Betula pendula [Silver birch] in southern Sweden. A modified version of the Farquhar-von Caemmerer-Berry model was fitted to the leaf gas exchange data to estimate Vcmax, rm and Pr. We found that of all leaf traits measured, only LMA for Q. robur was significantly higher in leaves from high-light environments. When comparing species, both rm and LMA were significantly higher in the conifers, and rm had a negative correlation with Vcmax. We found that Pr was similar between different species and functional groups, with an average of 73.2% (and SD of ±10.4) across all species. There was a strong, positive correlation between Pr and Vcmax in broadleaves, and we hypothesise that this effect might derive from a higher CO2 drawdown near Rubisco in leaves with high Vcmax.

An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity.

The maximum rate of carboxylation (Vcmax ) is an essential leaf trait determining the photosynthetic capacity of plants. Existing approaches for estimating Vcmax at large scale mainly rely on empirical relationships with proxies such as leaf nitrogen/chlorophyll content or hyperspectral reflectance, or on complicated inverse models from gross primary production or solar-induced fluorescence. A novel mechanistic approach based on the assumption that plants optimize resource investment coordinating with environment and growth has been shown to accurately predict C3 plant Vcmax based on mean growing season environmental conditions. However, the ability of optimality theory to explain seasonal variation in Vcmax has not been fully investigated. Here, we adapt an optimality-based model to simulate daily Vcmax,25C (Vcmax at a standardized temperature of 25°C) by incorporating the effects of antecedent environment, which affects current plant functioning, and dynamic light absorption, which coordinates with plant functioning. We then use seasonal Vcmax,25C field measurements from 10 sites across diverse ecosystems to evaluate model performance. Overall, the model explains about 83% of the seasonal variation in C3 plant Vcmax,25C across the 10 sites, with a medium root mean square error of 12.3 µmol m-2  s-1 , which suggests that seasonal changes in Vcmax,25C are consistent with optimal plant function. We show that failing to account for acclimation to antecedent environment or coordination with dynamic light absorption dramatically decreases estimation accuracy. Our results show that optimality-based approach can accurately reproduce seasonal variation in canopy photosynthetic potential, and suggest that incorporating such theory into next-generation trait-based terrestrial biosphere models would improve predictions of global photosynthesis.

Effect of elevated ozone, nitrogen availability and mesophyll conductance on the temperature responses of leaf photosynthetic parameters in poplar.

Although ozone (O3) concentration and nitrogen (N) availability are well known to affect plant physiology, their impacts on the photosynthetic temperature response are poorly understood. We addressed this knowledge gap by exposing seedlings of hybrid poplar clone '107' (Populous euramericana cv. '74/76') to elevated O3 (E-O3) and N availability variation in a factorial experiment. E-O3 decreased light-saturated net photosynthesis (Asat), mesophyll conductance (gm) and apparent maximum rate of carboxylation (Vcmax, based on intercellular CO2 concentration) but not actual Vcmax (based on chloroplast CO2 concentration) and increased respiration in light (Rd) at 25 °C. Nitrogen fertilization increased Asat, gm, Vcmax and the maximum rate of electron transport (Jmax) and reduced Rd at 25 °C and the activation energy of actual Vcmax. No E-O3 or E-O3 x N interaction effects on the temperature response parameters were detected, simplifying the inclusion of O3 impacts on photosynthesis in vegetation models. gm peaked at 30 °C, apparent Vcmax and Jmax at 32-33 °C, while the optimum temperatures of actual Vcmax and Jmax exceeded the measured temperature range (15-35 °C). Ignoring gm would, thus, have resulted in mistakenly attributing the decrease in Asat at high temperatures to reduced biochemical capacity rather than to greater diffusion limitation.

Similar temperature dependence of photosynthetic parameters in sun and shade leaves of three tropical tree species.

Photosynthetic carbon uptake by tropical forests is of critical importance in regulating the earth's climate, but rising temperatures threaten this stabilizing influence of tropical forests. Most research on how temperature affects photosynthesis focuses on fully sun-exposed leaves, and little is known about shade leaves, even though shade leaves greatly outnumber sun leaves in lowland tropical forests. We measured temperature responses of light-saturated photosynthesis, stomatal conductance, and the biochemical parameters VCMax (maximum rate of RuBP carboxylation) and JMax (maximum rate of RuBP regeneration, or electron transport) on sun and shade leaves of mature tropical trees of three species in Panama. As expected, biochemical capacities and stomatal conductance were much lower in shade than in sun leaves, leading to lower net photosynthesis rates. However, the key temperature response traits of these parameters-the optimum temperature (TOpt) and the activation energy-did not differ systematically between sun and shade leaves. Consistency in the JMax to VCMax ratio further suggested that shade leaves are not acclimated to lower temperatures. For both sun and shade leaves, stomatal conductance had the lowest temperature optimum (~25 °C), followed by net photosynthesis (~30 °C), JMax (~34 °C) and VCMax (~38 °C). Stomatal conductance of sun leaves decreased more strongly with increasing vapor pressure deficit than that of shade leaves. Consistent with this, modeled stomatal limitation of photosynthesis increased with increasing temperature in sun but not shade leaves. Collectively, these results suggest that modeling photosynthetic carbon uptake in multi-layered canopies does not require independent parameterization of the temperature responses of the biochemical controls over photosynthesis of sun and shade leaves. Nonetheless, to improve the representation of the shade fraction of carbon uptake dynamics in tropical forests, better understanding of stomatal sensitivity of shade leaves to temperature and vapor pressure deficit will be required.

Surprising lack of sensitivity of biochemical limitation of photosynthesis of nine tree species to open-air experimental warming and reduced rainfall in a southern boreal forest.

Photosynthetic biochemical limitation parameters (i.e., Vcmax , Jmax and Jmax :Vcmax ratio) are sensitive to temperature and water availability, but whether these parameters in cold climate species at biome ecotones are positively or negatively influenced by projected changes in global temperature and water availability remains uncertain. Prior exploration of this question has largely involved greenhouse based short-term manipulative studies with mixed results in terms of direction and magnitude of responses. To address this question in a more realistic context, we examined the effects of increased temperature and rainfall reduction on the biochemical limitations of photosynthesis using a long-term chamber-less manipulative experiment located in northern Minnesota, USA. Nine tree species from the boreal-temperate ecotone were grown in natural neighborhoods under ambient and elevated (+3.4°C) growing season temperatures and ambient or reduced (≈40% of rainfall removed) summer rainfall. Apparent rubisco carboxylation and RuBP regeneration standardized to 25°C (Vcmax25°C and Jmax25°C , respectively) were estimated based on ACi curves measured in situ over three growing seasons. Our primary objective was to test whether species would downregulate Vcmax25°C and Jmax25°C in response to warming and reduced rainfall, with such responses expected to be greatest in species with the coldest and most humid native ranges, respectively. These hypotheses were not supported, as there were no overall main treatment effects on Vcmax25°C or Jmax25°C (p > .14). However, Jmax :Vcmax ratio decreased significantly with warming (p = .0178), whereas interactions between warming and rainfall reduction on the Jmax25°C to Vcmax25°C ratio were not significant. The insensitivity of photosynthetic parameters to warming contrasts with many prior studies done under larger temperature differentials and often fixed daytime temperatures. In sum, plants growing in relatively realistic conditions under naturally varying temperatures and soil moisture levels were remarkably insensitive in terms of their Jmax25°C and Vcmax25°C when grown at elevated temperatures, reduced rainfall, or both combined.

Estimating photosynthetic capacity from leaf reflectance and Chl fluorescence by coupling radiative transfer to a model for photosynthesis.

In photosynthesis models following the Farquhar formulation, the maximum carboxylation rate Vcmax is the key parameter. Remote-sensing indicators, such as reflectance ρ and Chl fluorescence (ChlF), have been proven as valuable estimators of photosynthetic capacity and can be used as a constraint to Vcmax estimation. We present a methodology to retrieve Vcmax from leaf ρ and ChlF by coupling a radiative transfer model, Fluspect, to a model for photosynthesis. We test its performance against a unique dataset, with combined leaf spectral, gas exchange and pulse-amplitude-modulated measurements. Our results show that the method can estimate the magnitude of Vcmax estimated from the far-red peak of ChlF and green ρ or transmittance τ, with values of root-mean-square error below 10 µmol CO2  m-2  s-1 . At the leaf level, the method could be used for detection of plant stress and tested against more extensive datasets. With a similar scheme devised for the higher spatial scales, such models could provide a comprehensive method to estimate the actual photosynthetic capacity of vegetation.