Variation In Photosynthetic Capacity Research Articles

Variation in photosynthetic capacity of Salvia przewalskii along elevational gradients on the eastern Qinghai-Tibetan Plateau, China

Elevational variation in plant growing environment drives diversification of photosynthetic capacity, however, the mechanism behind this reaction is poorly understood. We measured leaf gas exchange, chlorophyll fluorescence, anatomical characteristics, and biochemical traits of Salvia przewalskii at elevations ranging from 2400 m to 3400 m above sea level (a.s.l) on the eastern Qinghai-Tibetan Plateau, China. We found that photosynthetic capacity showed an initial increase and then a decrease with rising elevation, and the best state observed at 2800 m a.s.l. Environmental factors indirectly regulated photosynthetic capacity by affecting stomatal conductance (gs), mesophyll conductance (gm), maximum velocity of carboxylation (Vc max), and maximum capacity for photosynthetic electron transport (Jmax). The average temperature (T) and total precipitation (P) during the growing season had the highest contribution to the variation of photosynthetic capacity of S. przewalskii in subalpine areas, which were 25% and 24%, respectively. Photosynthetic capacity was mainly affected by diffusional limitations (71%–89%), and mesophyll limitation (lm) played a leading role. The variation of gm was attributed to the effects of environmental factors on the volume fraction of intercellular air space (fias), the thickness of cell wall (Tcw), the surface of mesophyll cells and chloroplasts exposed to intercellular airspace (Sm, Sc), and plasma membrane intrinsic protein (PIPs, PIP1, PIP2), independent of carbonic anhydrase (CA). Optimization of leaf tissue structure and adaptive physiological responses enabled plants to efficiently cope with variable climate conditions of high-elevation areas, and the while maintaining high levels of carbon assimilation.

Temporal Dynamics of Canopy Properties and Carbon and Water Fluxes in a Temperate Evergreen Angiosperm Forest

The forest–atmosphere exchange of carbon and water is regulated by meteorological conditions as well as canopy properties such as leaf area index (LAI, m2 m−2), photosynthetic capacity (PC μmol m−2 s−1), or surface conductance in optimal conditions (Gs,opt, mmol m−2 s−1), which can vary seasonally and inter-annually. This variability is well understood for deciduous species but is poorly characterized in evergreen forests. Here, we quantify the seasonal dynamics of a temperate evergreen eucalypt forest with estimates of LAI, litterfall, carbon and water fluxes, and meteorological conditions from measurements and model simulations. We merged MODIS Enhanced Vegetation Index (EVI) values with site-based LAI measurements to establish a 17-year sequence of monthly LAI. We ran the Community Atmosphere Biosphere Land Exchange model (CABLE-POP (version r5046)) with constant and varying LAI for our site to quantify the influence of seasonal canopy dynamics on carbon and water fluxes. We observed that the peak of LAI occurred in late summer–early autumn, with a higher and earlier peak occurring in years when summer rainfall was greater. Seasonality in litterfall and allocation of net primary productivity (FNPP) to leaf growth (af, 0–1) drove this pattern, suggesting a complete renewal of the canopy before the timing of peak LAI. Litterfall peaked in spring, followed by a high af in summer, at the end of which LAI peaked, and PC and Gs,opt reached their maximum values in autumn, resulting from a combination of high LAI and efficient mature leaves. These canopy dynamics helped explain observations of maximum gross ecosystem production (FGEP) in spring and autumn and net ecosystem carbon loss in summer at our site. Inter-annual variability in LAI was positively correlated with Net Ecosystem Production (FNEP). It would be valuable to apply a similar approach to other temperate evergreen forests to identify broad patterns of seasonality in leaf growth and turnover. Because incorporating dynamic LAI was insufficient to fully capture the dynamics of FGEP, observations of seasonal variation in photosynthetic capacity, such as from solar-induced fluorescence, should be incorporated in land surface models to improve ecosystem flux estimates in evergreen forests.

Quantified trend of photosynthetic rate along the depth of microalgae biofilm

Compared with suspended microalgae cultivation, attached microalgae cultivation for wastewater treatment has advantages of low biomass recovery costs and high robustness. As a heterogeneous system, the variation of photosynthetic capacity along biofilm depth lacks quantitative conclusions. The distribution curve of oxygen concentration along the depth of attached microalgae biofilm (f(x)) was detected by dissolved oxygen (DO) microelectrode, and a quantified model was built based on mass conservation and Fick's law. It revealed that the net photosynthetic rate at a certain depth (x) in the biofilm showed a linear relationship with the second derivatives of the distribution curve of oxygen concentration (f″(x)). In addition, the declining trend of photosynthetic rate along attached microalgae biofilm was relatively slow compared with the suspended system. The photosynthetic rate at 150–200 μm depth of algae biofilm was only 3.60 %–17.86 % of that at the surface layer. Moreover, the light saturation points of the attached microalgae got lower along the depth of biofilm. Compared to 400 lx light intensity, the net photosynthetic rate of microalgae biofilm at the depths of 100–150 μm and 150–200 μm increased by 389 % and 956 % under 5000 lx, respectively, showing the high photosynthesis potential with increasing light.

Variation, coordination, and trade-offs between needle structures and photosynthetic-related traits across five Picea species: consequences on plant growth

BackgroundPicea species are distributed and planted world-wide due to their great ecological and economic values. It has been reported that Picea species vary widely in growth traits in a given environment, which reflects genetic and phenotypic differences among species. However, key physiological processes underlying tree growth and the influencing factors on them are still unknown.ResultsHere, we examined needle structures, needle chemical components, physiological characteristics and growth traits across five Picea species in a common garden in Tianshui, Gansu province in China: Picea glauca, P. mariana, P. likiangensis, P. koraiensis, and P. crassifolia, among which P. glauca and P. mariana were introduced from North America, P. likiangensis was from Lijiang, Yunan province in China, P. koraiensis was from Yichun, Heilongjiang province in China, and P. crassifolia was native to the experimental site. It was found that nearly all traits varied significantly among species. Tissue-level anatomical characteristics and leaf mass per area (LMA) were affected by needle size, but the variations of them were not associated with the variations in photosynthetic and biochemical capacity among species. Variations in area-based maximum photosynthesis (Pnmax) were affected by stomatal conductance (gs), mesophyll conductance (gm) and biochemical parameters including maximum carboxylation rate (Vcmax), and maximum electron transport rate (Jmax). The fraction of N allocated to different photosynthetic apparatus displayed contrasting values among species, which contributed to the species variations in photosynthetic nitrogen use efficiency (PNUE) and Pnmax. Additionally, all growth traits were positively correlated with Pnmax and PNUE.ConclusionNeedle structures are less important than needle biochemical parameters in determining the variations in photosynthetic capacity across the five Picea species. Pnmax and PNUE are closedly associated with the fraction of N allocated to photosynthetic apparatus (Pphoto) compared with leaf N content per area (Narea). The tremendous growth differences among the five Picea species were substantially related to the interspecies variation in Pnmax and PNUE.

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

Main conclusionBy 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.

Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum

Sorghum, a genetically diverse C4 cereal, is an ideal model to study natural variation in photosynthetic capacity. Specific leaf nitrogen (SLN) and leaf mass per leaf area (LMA), as well as, maximal rates of Rubisco carboxylation (Vcmax), phosphoenolpyruvate (PEP) carboxylation (Vpmax), and electron transport (Jmax), quantified using a C4 photosynthesis model, were evaluated in two field-grown training sets (n = 169 plots including 124 genotypes) in 2019 and 2020. Partial least square regression (PLSR) was used to predict Vcmax (R2 = 0.83), Vpmax (R2 = 0.93), Jmax (R2 = 0.76), SLN (R2 = 0.82), and LMA (R2 = 0.68) from tractor-based hyperspectral sensing. Further assessments of the capability of the PLSR models for Vcmax, Vpmax, Jmax, SLN, and LMA were conducted by extrapolating these models to two trials of genome-wide association studies adjacent to the training sets in 2019 (n = 875 plots including 650 genotypes) and 2020 (n = 912 plots with 634 genotypes). The predicted traits showed medium to high heritability and genome-wide association studies using the predicted values identified four QTL for Vcmax and two QTL for Jmax. Candidate genes within 200 kb of the Vcmax QTL were involved in nitrogen storage, which is closely associated with Rubisco, while not directly associated with Rubisco activity per se. Jmax QTL was enriched for candidate genes involved in electron transport. These outcomes suggest the methods here are of great promise to effectively screen large germplasm collections for enhanced photosynthetic capacity.

Jeannine Cavender-Bares.

Jeannine Cavender-Bares.

Genotypic variation in intrinsic transpiration efficiency correlates with sugarcane yield under rainfed and irrigated field conditions.

Intrinsic transpiration efficiency (i TE), the ratio of photosynthesis (A) to stomatal conductance (g s), is considered a useful trait for improving productivity; however, higher i TE with high A is more desirable than that with low g s. This study dissects i TE of 20 sugarcane genotypes to understand its relationship with total dry matter (TDM) and cane yield (TCH) under irrigated and rainfed conditions. Water stress reduced mean A and g s by 56 and 61%, and mean TDM and TCH by 55 and 59%, respectively; however, genotype × irrigation treatment interaction was smaller than genotype variance. Mean i TE increased from 117.4 μmol mol−1 in the irrigated treatment to 130.6 μmol mol−1 in the rainfed treatment. In irrigated conditions, i TE had high heritability (H 2 b = 0.67) and significant genetic correlation with TDM (r g = 0.58) and TCH (r g = 0.72). Under water stress, at g s below 0.1 mol m−2 s−1, non‐stomatal limitation to A was evident and i TE had low heritability (H 2 b = 0.2). Whereas in the g s range of 0.1–0.4 mol m−2 s−1, heritability of i TE (H 2 b = 0.63) and its genetic correlation with TDM (r g = 0.78) and TCH (r g = 0.75) were maximised. There was significant genotypic variation in photosynthetic capacity (A c), and the differences were related to TDM and i TE. Selecting genotypes with higher i TE and A c could offer potential for improving productivity without the unfavourable effect of low g s.

Comparison of the Photosynthetic Capacity of Phragmites australis in Five Habitats in Saline‒Alkaline Wetlands.

Water shortages have an important impact on the photosynthetic capacity of Phragmites australis. However, this impact has not been adequately studied from the perspective of photosynthesis. An in-depth study of the photosynthetic process can help in better understanding the impact of water shortages on the photosynthetic capacity of P. australis, especially on the microscale. The aim of this study is to explore the photosynthetic adaptation strategies to environmental changes in saline‒alkaline wetlands. The light response curves and CO2 response curves of P. australis in five habitats (hygrophilous, xerophytic, psammophytic, abandoned farmland, paddy field drainage) in saline‒alkaline wetlands were measured at different stages of their life history, and we used a nonrectangular hyperbolic model to fit the data. It was concluded that P. australis utilized coping strategies that differed between the growing and breeding seasons. P. australis in abandoned farmland during the growing season had the highest apparent quantum efficiency (AQE) and photosynthetic utilization efficiency for weak light because of the dark environment. The dark respiration rate of P. australis in the drainage area of paddy fields was the lowest, and it had the highest values for photorespiration rate, maximum photosynthetic rate (Pmax), photosynthetic capacity (Pa), biomass, maximum carboxylation rate (Vcmax), and maximum electron transfer rate (Jmax). The light insensitivity of P. australis increased with the transition from growing to breeding season, and the dark respiration rate also showed a downward trend. Moreover, Vcmax and Jmax would decline when Pmax and Pa showed a declining trend, and vice versa. In other words, Vcmax and Jmax could explain changes in the photosynthetic capacity to some extent. These findings contribute to providing insights that Vcmax and Jmax can directly reflect the variation in photosynthetic capacity of P. australis under water shortages in saline‒alkaline wetlands and in other parts of world where there are problems with similarly harmful environmental conditions.

Contrasting Dependencies of Photosynthetic Capacity on Leaf Nitrogen in Early- and Late-Successional Tropical Montane Tree Species

Differences in photosynthetic capacity among tree species and tree functional types are currently assumed to be largely driven by variation in leaf nutrient content, particularly nitrogen (N). However, recent studies indicate that leaf N content is often a poor predictor of variation in photosynthetic capacity in tropical trees. In this study, we explored the relative importance of area-based total leaf N content (Ntot) and within-leaf N allocation to photosynthetic capacity versus light-harvesting in controlling the variation in photosynthetic capacity (i.e. V cmax, J max) among mature trees of 12 species belonging to either early (ES) or late successional (LS) groups growing in a tropical montane rainforest in Rwanda, Central Africa. Photosynthetic capacity at a common leaf temperature of 25˚C (i.e. maximum rates of Rubisco carboxylation, V cmax25 and of electron transport, J max25) was higher in ES than in LS species (+ 58% and 68% for V cmax25 and J max25, respectively). While Ntot did not significantly differ between successional groups, the photosynthetic dependency on Ntot was markedly different. In ES species, V cmax25 was strongly and positively related to Ntot but this was not the case in LS species. However, there was no significant trade-off between relative leaf N investments in compounds maximizing photosynthetic capacity versus compounds maximizing light harvesting. Both leaf dark respiration at 25˚C (+ 33%) and, more surprisingly, apparent photosynthetic quantum yield (+ 35%) was higher in ES than in LS species. Moreover, Rd25 was positively related to Ntot for both ES and LS species. Our results imply that efforts to quantify carbon fluxes of tropical montane rainforests would be improved if they considered contrasting within-leaf N allocation and photosynthetic Ntot dependencies between species with different successional strategies.

Estimating canopy gross primary production by combining phloem stable isotopes with canopy and mesophyll conductances.

Gross primary production (GPP) is a key component of the forest carbon cycle. However, our knowledge of GPP at the stand scale remains uncertain, because estimates derived from eddy covariance (EC) rely on semi-empirical modelling and the assumptions of the EC technique are sometimes not fully met. We propose using the sap flux/isotope method as an alternative way to estimate canopy GPP, termed GPPiso/SF , at the stand scale and at daily resolution. It is based on canopy conductance inferred from sap flux and intrinsic water-use efficiency estimated from the stable carbon isotope composition of phloem contents. The GPPiso/SF estimate was further corrected for seasonal variations in photosynthetic capacity and mesophyll conductance. We compared our estimate of GPPiso/SF to the GPP derived from PRELES, a model parameterized with EC data. The comparisons were performed in a highly instrumented, boreal Scots pine forest in northern Sweden, including a nitrogen fertilized and a reference plot. The resulting annual and daily GPPiso/SF estimates agreed well with PRELES, in the fertilized plot and the reference plot. We discuss the GPPiso/SF method as an alternative which can be widely applied without terrain restrictions, where the assumptions of EC are not met.

Differences in isoprenoid-mediated energy dissipation pathways between coastal and interior Douglas-fir seedlings in response to drought.

Plants have evolved energy dissipation pathways to reduce photooxidative damage under drought when photosynthesis is hampered. Non-volatile and volatile isoprenoids are involved in non-photochemical quenching of excess light energy and scavenging of reactive oxygen species. A better understanding of trees' ability to cope with and withstand drought stress will contribute to mitigate the negative effects of prolonged drought periods expected under future climate conditions. Therefore we investigated if Douglas-fir (Pseudotsuga menziesii(Mirb.)) provenances from habitats with contrasting water availability reveal intraspecific variation in isoprenoid-mediated energy dissipation pathways. In a controlled drought experiment with 1-year-old seedlings of an interior and a coastal Douglas-fir provenance, we assessed the photosynthetic capacity, pool sizes of non-volatile isoprenoids associated with the photosynthetic apparatus, as well as pool sizes and emission of volatile isoprenoids. We observed variation in the amount and composition of non-volatile and volatile isoprenoids among provenances, which could be linked to variation in photosynthetic capacity under drought. The coastal provenance exhibited an enhanced biosynthesis and emission of volatile isoprenoids, which is likely sustained by generally higher assimilation rates under drought. In contrast, the interior provenance showed an enhanced photoprotection of the photosynthetic apparatus by generally higher amounts of non-volatile isoprenoids and increased amounts of xanthophyll cycle pigments under drought. Our results demonstrate that there is intraspecific variation in isoprenoid-mediated energy dissipation pathways among Douglas-fir provenances, which may be important traits when selecting provenances suitable to grow under future climate conditions.

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

Estimates of seasonal variation in photosynthetic capacity (Pc ) are critical for modeling the time course of carbon fluxes. Given the time-intensive nature of calculating Pc parameters via gas exchange, it is appealing to calculate parameter variation via changes in chlorophyll (Chl) and nitrogen (N) content by assuming that Pc scales with these variables. Although seasonal changes in Pc and the relationships between N and Pc have been evaluated in forest canopies, there is limited data on seasonal parameter values in crops, nor is it clear if seasonal changes in Pc 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 (Vcmax ) and electron transport (Jmax ) 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-Vcmax relationships were not significant for either crop. Mass-based N-Vcmax relationships were weak in sunflower, but highly significant in maize. Our results suggest that Pc can be seasonally adjusted in maize with reliable estimates of changes in LMA.

Seasonal variation in photosynthesis performance of cassava at two different growth stages under irrigated and rain-fed conditions in a tropical savanna climate

Seasonal variations in photosynthesis of cassava cv. Rayong 9 (RY9) under irrigated and rain-fed conditions were evaluated at the age of three and six months after planting (MAP). Photosynthetic light-response (PN/I) curves revealed that cassava leaves attained the highest maximum net photosynthetic rates (PNmax) in the rainy season, followed by the hot one, while the lowest PNmax was found in the cool season. Photosynthetic potential of the 3-month-old plants was mostly higher than that of the 6-month-old plants, and the seasonal variation in photosynthetic capacity was also more apparent in the younger plants. PN/I curves were used to predict daily net photosynthetic rate (PN) for each season based on daily average solar radiation data. The predicted PN were considerably lower than the PNmax values. This indicated that solar radiation is a limiting factor for photosynthesis, particularly in the rainy season. The data provided basic information for breeding cassava genotypes with enhanced photosynthesis during the period of unfavorable environment. Furthermore, the data are potentially useful in modeling photosynthesis and crop growth as affected by environmental factors.

An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah‐MP

AbstractIn the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah‐MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions—two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah‐MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, and the amount of GPP and ER in the growing season. Furthermore, the augmented Noah‐MP performed reasonably well in simulating the spatial distributions of LAI, GPP, and NPP in East Asia, consistent with the satellite observations.

Machine Learning Techniques for Predicting Crop Photosynthetic Capacity from Leaf Reflectance Spectra

Harnessing natural variation in photosynthetic capacity is a promising route toward yield increases, but physiological phenotyping is still too laborious for large-scale genetic screens. Here, we evaluate the potential of leaf reflectance spectroscopy to predict parameters of photosynthetic capacity in Brassica oleracea and Zea mays, a C3 and a C4 crop, respectively. To this end, we systematically evaluated properties of reflectance spectra and found that they are surprisingly similar over a wide range of species. We assessed the performance of a wide range of machine learning methods and selected recursive feature elimination on untransformed spectra followed by partial least squares regression as the preferred algorithm that yielded the highest predictive power. Learning curves of this algorithm suggest optimal species-specific sample sizes. Using the Brassica relative Moricandia, we evaluated the model transferability between species and found that cross-species performance cannot be predicted from phylogenetic proximity. The final intra-species models predict crop photosynthetic capacity with high accuracy. Based on the estimated model accuracy, we simulated the use of the models in selective breeding experiments, and showed that high-throughput photosynthetic phenotyping using our method has the potential to greatly improve breeding success. Our results indicate that leaf reflectance phenotyping is an efficient method for improving crop photosynthetic capacity.

Genotypic variation in transpiration efficiency due to differences in photosynthetic capacity among sugarcane-related clones.

Sugarcane, derived from the hybridization of Saccharum officinarum×Saccharum spontaneum, is a vegetative crop in which the final yield is highly driven by culm biomass production. Cane yield under irrigated or rain-fed conditions could be improved by developing genotypes with leaves that have high intrinsic transpiration efficiency, TEi (CO2 assimilation/stomatal conductance), provided this is not offset by negative impacts from reduced conductance and growth rates. This study was conducted to partition genotypic variation in TEi among a sample of diverse clones from the Chinese collection of sugarcane-related germplasm into that due to variation in stomatal conductance versus that due to variation in photosynthetic capacity. A secondary goal was to define protocols for optimized larger-scale screening of germplasm collections. Genotypic variation in TEi was attributed to significant variation in both stomatal and photosynthetic components. A number of genotypes were found to possess high TEi as a result of high photosynthetic capacity. This trait combination is expected to be of significant breeding value. It was determined that a small number of observations (16) is sufficient for efficiently screening TEi in larger populations of sugarcane genotypes The research methodology and results reported are encouraging in supporting a larger-scale screening and introgression of high transpiration efficiency in sugarcane breeding. However, further research is required to quantify narrow sense heritability as well as the leaf-to-field translational potential of genotypic variation in transpiration efficiency-related traits observed in this study.

Stay-green characterization in Belgian forage maize

SUMMARYThe term ‘stay-green’ (SG) is used in studies with varieties showing delayed senescence in the field. However, delayed appearance of visual symptoms of leaf senescence does not guarantee a longer duration of photosynthesis. The question arises whether the variation in photosynthetic capacity between silage maize varieties currently on the Belgian market is large enough to define different SG types. Furthermore, physiological traits were investigated as proxies for photosynthesis, including chlorophyll concentration, nitrogen (N) concentration, SPAD readings and greenness score. Finally, the functionality of the SG trait was determined by studying dry matter (DM) and N partitioning in the plants. To address these questions, eight silage maize varieties were monitored at two sites in Belgium over 2 years (2013–2014). Two plant types were found: hereafter called ‘normal’ and ‘SG’. The SG varieties had higher values for photosynthetic capacity and they coincided with higher values for the proxies. Because a higher photosynthetic capacity did not provoke higher assimilate accumulation in the leaves, the SG trait was characterized as a cosmetic one. The SG trait influenced N dynamics in the plant: lower N translocation from the leaves to the ear resulted in lower ear N concentration and lower ear DM yield. No differences in whole-crop N concentration and whole-crop DM yield were found. As the SG trait mainly provokes shifts in partition of DM and N between vegetative and generative tissues, the energy source also shifts from starch (provided by the ear) to cell wall material (provided by the stover).

Leaf-level photosynthetic capacity in lowland Amazonian and high-elevation Andean tropical moist forests of Peru.

We examined whether variations in photosynthetic capacity are linked to variations in the environment and/or associated leaf traits for tropical moist forests (TMFs) in the Andes/western Amazon regions of Peru. We compared photosynthetic capacity (maximal rate of carboxylation of Rubisco (Vcmax ), and the maximum rate of electron transport (Jmax )), leaf mass, nitrogen (N) and phosphorus (P) per unit leaf area (Ma , Na and Pa , respectively), and chlorophyll from 210 species at 18 field sites along a 3300-m elevation gradient. Western blots were used to quantify the abundance of the CO2 -fixing enzyme Rubisco. Area- and N-based rates of photosynthetic capacity at 25°C were higher in upland than lowland TMFs, underpinned by greater investment of N in photosynthesis in high-elevation trees. Soil [P] and leaf Pa were key explanatory factors for models of area-based Vcmax and Jmax but did not account for variations in photosynthetic N-use efficiency. At any given Na and Pa , the fraction of N allocated to photosynthesis was higher in upland than lowland species. For a small subset of lowland TMF trees examined, a substantial fraction of Rubisco was inactive. These results highlight the importance of soil- and leaf-P in defining the photosynthetic capacity of TMFs, with variations in N allocation and Rubisco activation state further influencing photosynthetic rates and N-use efficiency of these critically important forests.

Separating the effects of phenology and diffuse radiation on gross primary productivity in winter wheat

AbstractGross primary productivity (GPP) has been reported to increase with the fraction of diffuse solar radiation, for a given total irradiance. The correlation between GPP and diffuse radiation suggests effects of diffuse radiation on canopy light‐use efficiency, but potentially confounding effects of vegetation phenology have not been fully explored. We applied several approaches to control for phenology, using 8 years of eddy‐covariance measurements of winter wheat in the U.S. Southern Great Plains. The apparent enhancement of daily GPP due to diffuse radiation was reduced from 260% to 75%, after subsampling over the peak growing season or by subtracting a 15 day moving average of GPP, suggesting a role of phenology. The diffuse radiation effect was further reduced to 22% after normalizing GPP by a spectral reflectance index to account for phenological variations in leaf area index LAI and canopy photosynthetic capacity. Canopy photosynthetic capacity covaries with diffuse fraction at a given solar irradiance at this site because both factors are dependent on day of year or solar zenith angle. Using a two‐leaf Sun‐shaded canopy radiative transfer model, we confirmed that the effects of phenological variations in photosynthetic capacity can appear qualitatively similar to the effects of diffuse radiation on GPP and therefore can be difficult to distinguish using observations. The importance of controlling for phenology when inferring diffuse radiation effects on GPP raises new challenges and opportunities for using radiation measurements to improve carbon cycle models.