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

Summary: Terrestrial CAM plants typically occur in hot semiarid regions, yet can show high crop productivity under favorable conditions.To achieve a more mechanistic understanding of CAM plant productivity, a biochemical model of diel metabolism was developed and integrated with 3‐D shoot morphology to predict the energetics of light interception and photosynthetic carbon assimilation.Using Agave tequilana as an example, this biochemical model faithfully simulated the four diel phases of CO2 and metabolite dynamics during the CAM rhythm. After capturing the 3‐D form over an 8‐yr production cycle, a ray‐tracing method allowed the prediction of the light microclimate across all photosynthetic surfaces. Integration with the biochemical model thereby enabled the simulation of plant and stand carbon uptake over daily and annual courses.The theoretical maximum energy conversion efficiency of Agave spp. is calculated at 0.045–0.049, up to 7% higher than for C3 photosynthesis. Actual light interception, and biochemical and anatomical limitations, reduced this to 0.0069, or 15.6 Mg ha−1 yr−1 dry mass annualized over an 8‐yr cropping cycle, consistent with observation. This is comparable to the productivity of many C3 crops, demonstrating the potential of CAM plants in climates where little else may be grown while indicating strategies that could raise their productivity. [ABSTRACT FROM AUTHOR]

Summary: Carbonyl sulfide (COS) has emerged as a multi‐scale tracer for terrestrial photosynthesis. To infer ecosystem‐scale photosynthesis from COS fluxes often requires knowledge of leaf relative uptake (LRU), the concentration‐normalized ratio between leaf COS uptake and photosynthesis. However, current mechanistic understanding of LRU variability remains inadequate for deriving robust COS‐based estimates of photosynthesis.We derive a set of closed‐form equations to describe LRU responses to light, humidity and CO2 based on the Ball–Berry stomatal conductance model and the biochemical model of photosynthesis. This framework reproduces observed LRU responses: decreasing LRU with increasing light or decreasing humidity; it also predicts that LRU increases with ambient CO2.By fitting the LRU equations to flux measurements on a C3 reed (Typha latifolia), we obtain physiological parameters that control LRU variability, including an estimate of the Ball–Berry slope of 7.1 without using transpiration measurements. Sensitivity tests reveal that LRU is more sensitive to photosynthetic capacity than to the Ball–Berry slope, indicating stomatal response to photosynthesis.This study presents a simple framework for interpreting observed LRU variability and upscaling LRU. The stoma‐regulated LRU response to CO2 suggests that COS may offer a unique window into long‐term stomatal acclimation to elevated CO2. See also the Commentary on this article by Whelan, 235: 1686–1688. [ABSTRACT FROM AUTHOR]

Terrestrial biosphere models typically use the biochemical model of Farquhar, von Caemmerer, and Berry (1980) to simulate photosynthesis, which requires accurate values of photosynthetic capacity of different biomes. However, data on tropical forests are sparse and highly variable due to the high species diversity, and it is still highly uncertain how these tropical forests respond to nutrient limitation in terms of C uptake. Tropical forests often grow on soils low in phosphorus (P) and are, in general, assumed to be P rather than nitrogen (N) limited. However, the relevance of P as a control of photosynthetic capacity is still debated. Here, we provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two 3-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N , P , and other leaf nutrients in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C) and nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests. The data are available at 10.5281/zenodo.5638236 (Verryckt, 2021). [ABSTRACT FROM AUTHOR]

Terrestrial biosphere models typically use the biochemical model of Farquhar, von Caemmerer and Berry (1980) to simulate photosynthesis, which requires accurate values of photosynthetic capacity of different biomes. However, data on tropical forests are sparse and highly variable due to the high species diversity, and it is still highly uncertain how these tropical forests respond to nutrient limitation in terms of C uptake. Tropical forests often grow on phosphorus (P)-poor soils and are, in general, assumed to be P- rather than nitrogen (N)-limited. However, the relevance of P as a control of photosynthetic capacity is still debated. Here, we provide a comprehensive dataset of vertical profiles of photosynthetic capacity and important leaf traits, including leaf N and P concentrations, from two three-year, large-scale nutrient addition experiments conducted in two tropical rainforests in French Guiana. These data present a unique source of information to further improve model representations of the roles of N, P, and other leaf nutrients, in photosynthesis in tropical forests. To further facilitate the use of our data in syntheses and model studies, we provide an elaborate list of ancillary data, including important soil properties and nutrients, along with the leaf data. As environmental drivers are key to improve our understanding of carbon (C)-nutrient cycle interactions, this comprehensive dataset will aid to further enhance our understanding of how nutrient availability interacts with C uptake in tropical forests. The data are available at DOI 10.5281/zenodo.4719242 (Verryckt, 2021). [ABSTRACT FROM AUTHOR]

Environmental controls in a greenhouse improve microclimates, thereby enhancing photosynthesis, but they create spatiotemporal non-uniformity of photosynthesis, with implications for unstable crop production. However, there has been no research focussing on the spatiotemporal variability of photosynthesis arising from greenhouse environmental controls. Here we visualise spatiotemporal distributions of leaf photosynthetic rate (A) and assess its linkages with microclimates [air temperature (T a), water vapour concentration (W a), CO 2 concentration (C a), and leaf-boundary-layer conductance (g a)] across a strawberry greenhouse during daytime under roof ventilation and CO 2 enrichment, using physical, physiological, and biochemical models for A and mobile observations of the microclimates. The distributions of A were variable during the daytime and were non-uniform across the greenhouse under the influence of the microclimate distributions arising from the environmental controls. In particular, with the roof ventilation, spatial variations of T a and g a were most associated with non-uniformity in A through the physical process of the energy budget determining the leaf temperature and thus affecting leaf physiological properties (photosynthetic capacities and stomatal conductance). With CO 2 enrichment, in addition to the roof ventilation, spatial variations of C a further increased non-uniformity in A through large variations of Rubisco-limited and RuBP-limited rates in the biochemical process of leaf photosynthesis. Spatial non-uniformity of A arising from the environmental controls ranged from 15% to 69% during the daytime. These findings indicate the importance of considering the spatiotemporal variability of photosynthesis with respect to its physical, physiological, and biochemical processes, in addition to that due to microclimates, for optimising greenhouse environmental controls. • Spatiotemporal variability of leaf photosynthetic rate (A) in a daytime greenhouse. • Multipoint model simulation of A was assisted by mobile observation of microclimates. • Greenhouse environmental controls varied microclimates in space and time. • Microclimate distributions enhanced spatiotemporal non-uniformity in A. • Spatial non-uniformity in A varied from 15% to 69% during the daytime. [ABSTRACT FROM AUTHOR]

Crops show considerable capacity to adjust their photosynthetic characteristics to seasonal changes in temperature. However, how photosynthesis acclimates to changes in seasonal temperature under future climate conditions has not been revealed. We measured leaf photosynthesis (An) of wheat (Triticum aestivum L.) and rice (Oryza sativa L.) grown under four combinations of two levels of CO2 (ambient and enriched up to 500 µmol/mol) and two levels of canopy temperature (ambient and increased by 1.5–2.0°C) in temperature by free‐air CO2 enrichment (T‐FACE) systems. Parameters of a biochemical C3‐photosynthesis model and of a stomatal conductance (gs) model were estimated for the four conditions and for several crop stages. Some biochemical parameters related to electron transport and most gs parameters showed acclimation to seasonal growth temperature in both crops. The acclimation response did not differ much between wheat and rice, nor among the four treatments of the T‐FACE systems, when the difference in the seasonal growth temperature was accounted for. The relationships between biochemical parameters and leaf nitrogen content were consistent across leaf ranks, developmental stages, and treatment conditions. The acclimation had a strong impact on gs model parameters: when parameter values of a particular stage were used, the model failed to correctly estimate gs values of other stages. Further analysis using the coupled gs–biochemical photosynthesis model showed that ignoring the acclimation effect did not result in critical errors in estimating leaf photosynthesis under future climate, as long as parameter values were measured or derived from data obtained before flowering. [ABSTRACT FROM AUTHOR]

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. We demonstrate that triose phosphate utilization rate does not limit leaf photosynthesis at the current ambient atmospheric CO2 concentration. Our results do not support the hypothesis that the light‐saturated photosynthetic rates of plants growing in cold environments are more often limited by triose phosphate utilization rate than those of plants growing in warmer environments. In addition, we showed that instantaneous temperature responses of triose phosphate utilization rate are distinct from temperature responses of the maximum rate of Rubisco carboxylation. [ABSTRACT FROM AUTHOR]

Dryland ecosystems largely control the inter-annual variability of the global carbon cycle. Unfortunately, there is a paucity of data on key biochemical parameters, such as maximum carboxylation velocity (V cmax25 ) and electron transport rate (J max25 ), from species in these ecosystems which limits our capacity to model photosynthesis across ecological scales. We studied six dominant C 3 shrub and tree species from the Sonoran Desert with different leaf traits and phenological strategies. We characterized V cmax25 and J max25 for each species and assessed which traits or trait combinations were the best predictors of these parameters for biochemical models of photosynthesis. All species had high values of V cmax25 and J max25 , mostly explained by high leaf nitrogen content (N area ) and high nitrogen allocation to photosynthetic enzymes comparable to those reported for herbs and crop species but higher than those of shrubs and other functional types in world databases. We found that the high values of V cmax25 and J max25 , by increasing rates of photosynthetic reactions, enhance photosynthetic water and nitrogen-use efficiencies and may favor carbon gain under typical conditions in drylands. Our findings improve the parameterization of photosynthesis models, and provide novel implications to common findings of high N area in dryland species. [ABSTRACT FROM AUTHOR]

Crops specific proper concentration of micronutrient application is necessary to improve the yield and quality of crops. Therefore, an experiment was conducted to identify the optimum dose of boron for groundnut plant. Six level of boron (B) application, B0(0 ppm), B1(0.5 ppm), B2(1 ppm), B3(2 ppm), B4(4 ppm) and B5(8 ppm) were evaluated. Photosynthetic rate, transpiration and stomatal conductance were increased for boron application but leaf vapor pressure deficit decreased. Physiological growth parameters, yield and yield contributing character, and shelling percentage was highest for B3. The values of biochemical traits including protein, oil and vitamin E content were higher for B4. Thus, leaf gas exchange showed that boron can be used to culture groundnut as it provides high yield and biochemical properties. [ABSTRACT FROM PUBLISHER]

Extreme temperature and drought stress are major environmental factors limiting agriculture worldwide. A comprehensive understanding of plant behavior under different environmental conditions can be gained through experiments and through the application of biophysical crop models. This study presents a field experiment conducted with bean exposed to heat and drought stress. Based on an experimental data collection a crop model was set up, calibrated and validated. Hereby, the two different photosynthesis model approaches already implemented in the model, a simple empirical (the Goudriaan and van Laar or GvL model) and a biochemical photosynthesis model approach (the Farquhar-Ball-Collatz or FBC model), were tested. Both photosynthesis model approaches performed adequately under no stress conditions. Under heat stress conditions, yield was underestimated by both models. However, the FBC model performed better than the simpler photosynthesis model approach of the GvL model. The FBC crop model was able to predict the soil water dynamics, the plant growth and the stomatal conductance. [ABSTRACT FROM AUTHOR]

Understanding how high-latitude terrestrial productivity and evapotranspiration change in association with rising atmospheric CO 2 concentration ([CO 2 ]), also known as ‘CO 2 fertilization’, is important for predicting future climate change. To quantify the magnitude of this fertilization effect, we have developed a big-leaf model that couples photosynthesis and stomatal conductance processes. This model was inverted by inputting eddy covariance CO 2 and H 2 O fluxes from four black spruce forests in Alaska to infer spatially representative ecophysiological parameters using a global optimization technique. Inferred seasonal variations in a maximum carboxylation rate at 25 °C per unit leaf area and stomatal conductance suggest greater photosynthetic capacity per unit leaf area during the mid-growing season, compared to spring and autumn. The interannual variability of parameters suggest that warm summers stimulate photosynthetic capacity and dry summers force stomatal regulation. Based on the model with optimized parameters, small but clear increases in gross primary productivity (GPP) and decreases in latent heat flux (LE) were estimated to be associated with rising [CO 2 ] from 2002 to 2014 ( p < 0.01). With a 23 ppm increase in summertime (June–August) [CO 2 ] from 2002 to 2014, the rates of increase per unit [CO 2 ] were approximately 0.16 ± 0.04% ppm −1 for GPP and −0.06 ± 0.03% ppm −1 for LE from 2002 to 2014. However, considerable uncertainties (greater than 100%) were estimated in the magnitude of the fertilization effect associated with different parameterizations in the biochemical model, indicating the need for ecophysiological studies for boreal plants. A network of eddy covariance instrumentation installed across similar ecosystem types, such as the one used in this study, can be particularly useful for evaluating ecosystem-scale ecophysiological traits and their role under changing environmental conditions. [ABSTRACT FROM AUTHOR]