Satellite sun‐induced chlorophyll fluorescence detects early response of winter wheat to heat stress in the Indian Indo‐Gangetic Plains

Extremely high temperatures represent one of the most severe abiotic stresses limiting crop productivity. However, understanding crop responses to heat stress is still limited considering the increases in both the frequency and severity of heat wave events under climate change. This limited understanding is partly due to the lack of studies or tools for the timely and accurate monitoring of crop responses to extreme heat over broad spatial scales. In this work, we use novel spaceborne data of sun‐induced chlorophyll fluorescence (SIF), which is a new proxy for photosynthetic activity, along with traditional vegetation indices (Normalized Difference Vegetation Index NDVI and Enhanced Vegetation Index EVI) to investigate the impacts of heat stress on winter wheat in northwestern India, one of the world's major wheat production areas. In 2010, an abrupt rise in temperature that began in March adversely affected the productivity of wheat and caused yield losses of 6% compared to previous year. The yield predicted by satellite observations of SIF decreased by approximately 13.9%, compared to the 1.2% and 0.4% changes in NDVI and EVI, respectively. During early stage of this heat wave event in early March 2010, the SIF observations showed a significant reduction and earlier response, while NDVI and EVI showed no changes and could not capture the heat stress until late March. The spatial patterns of SIF anomalies closely tracked the temporal evolution of the heat stress over the study area. Furthermore, our results show that SIF can provide large‐scale, physiology‐related wheat stress response as indicated by the larger reduction in fluorescence yield (SIF_yield) than fraction of photosynthetically active radiation during the grain‐filling phase, which may have eventually led to the reduction in wheat yield in 2010. This study implies that satellite observations of SIF have great potential to detect heat stress conditions in wheat in a timely manner and assess their impacts on wheat yields at large scales.     

Solar‐induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO‐2 and flux tower observations

Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R² = 0.72, p < 0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R² = 0.57–0.79, p < 0.0001) except evergreen broadleaf forests (R² = 0.16, p < 0.05) at the daily timescale. A higher slope was found for C₄ grasslands and croplands than for C₃ ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies.     

Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4

Several studies have shown that satellite retrievals of solar‐induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux‐tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V_max) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.     

Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2

Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO₂ concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C₃ cereal crops. This decreased protein content in crops constrains the benefits of elevated CO₂ on crop yield and affects their nutritional value for humans. To support studies of photosynthetic nitrogen assimilation and its complex interaction with photosynthetic carbon metabolism for crop improvement, we developed a dynamic systems model of plant primary metabolism, which includes the Calvin–Benson cycle, the photorespiration pathway, starch synthesis, glycolysis–gluconeogenesis, the tricarboxylic acid cycle, and chloroplastic nitrogen assimilation. This model successfully captures responses of net photosynthetic CO₂ uptake rate (A), respiration rate, and nitrogen assimilation rate to different irradiance and CO₂ levels. We then used this model to predict inhibition of nitrogen assimilation under elevated CO₂. The potential mechanisms underlying inhibited nitrogen assimilation under elevated CO₂ were further explored with this model. Simulations suggest that enhancing the supply of α-ketoglutarate is a potential strategy to maintain high rates of nitrogen assimilation under elevated CO₂. This model can be used as a heuristic tool to support research on interactions between photosynthesis, respiration, and nitrogen assimilation. It also provides a basic framework to support the design and engineering of C₃ plant primary metabolism for enhanced photosynthetic efficiency and nitrogen assimilation in the coming high-CO₂ world.

Simulations with a dynamic systems model of C₃ primary metabolism show that the decreased supply of reducing equivalent and 2-oxoglutaric acid cause decreased nitrogen assimilation under elevated CO₂.     

Prospects of photosynthetic research for increasing agricultural productivity,with emphasis on the tropical C4Amaranthus and the cassava C3-C4 crops

Productivity of most improved major food crops showed stagnation in the past decades. As human population is projected to reach 9–10 billion by the end of the 21^st century, agricultural productivity must be increased to ensure their demands. Photosynthetic capacity is the basic process underlying primary biological productivity in green plants and enhancing it might lead to increasing potential of the crop yields. Several approaches may improve the photosynthetic capacity, including integrated systems management, in order to close wide gaps between actual farmer’s and the optimum obtainable yield. Conventional and molecular genetic improvement to increase leaf net photosynthesis (P_N) are viable approaches, which have been recently shown in few crops. Bioengineering the more efficient CC₄ into C₃ system is another ambitious approach that is currently being applied to the C₃ rice crop. Two under-researched, yet old important crops native to the tropic Americas (i.e., the CC₄ amaranths and the C₃-CC₄ intermediate cassava), have shown high potential P_N, high productivity, high water use efficiency, and tolerance to heat and drought stresses. These physiological traits make them suitable for future agricultural systems, particularly in a globally warming climate. Work on crop canopy photosynthesis included that on flowering genes, which control formation and decline of the canopy photosynthetic activity, have contributed to the climate change research effort. The plant breeders need to select for higher P_N to enhance the yield and crop tolerance to environmental stresses. The plant science instructors, and researchers, for various reasons, need to focus more on tropical species and to use the research, highlighted here, as an example of how to increase their yields.     

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R² = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower‐based measurement of SIF and leaf‐level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R² = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F_q’/F_m’, the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R² = 0.79; P < 0.0001). We also found that canopy SIF and SIF‐derived GPP (GPP_SIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R² = 0.65 for canopy GPP_SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R² = 0.35 for canopy GPP_SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R² = 0.36 for canopy GPP_SIF and NDVI; P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales.     

Estimation of vegetation photosynthetic capacity from space‐based measurements of chlorophyll fluorescence for terrestrial biosphere models

Photosynthesis simulations by terrestrial biosphere models are usually based on the Farquhar's model, in which the maximum rate of carboxylation (V_cmax) is a key control parameter of photosynthetic capacity. Even though V_cmax is known to vary substantially in space and time in response to environmental controls, it is typically parameterized in models with tabulated values associated to plant functional types. Remote sensing can be used to produce a spatially continuous and temporally resolved view on photosynthetic efficiency, but traditional vegetation observations based on spectral reflectance lack a direct link to plant photochemical processes. Alternatively, recent space‐borne measurements of sun‐induced chlorophyll fluorescence (SIF) can offer an observational constraint on photosynthesis simulations. Here, we show that top‐of‐canopy SIF measurements from space are sensitive to V_cmax at the ecosystem level, and present an approach to invert V_cmax from SIF data. We use the Soil‐Canopy Observation of Photosynthesis and Energy (SCOPE) balance model to derive empirical relationships between seasonal V_cmax and SIF which are used to solve the inverse problem. We evaluate our V_cmax estimation method at six agricultural flux tower sites in the midwestern US using spaced‐based SIF retrievals. Our V_cmax estimates agree well with literature values for corn and soybean plants (average values of 37 and 101 μmol m^?2 s^?1, respectively) and show plausible seasonal patterns. The effect of the updated seasonally varying V_cmax parameterization on simulated gross primary productivity (GPP) is tested by comparing to simulations with fixed V_cmax values. Validation against flux tower observations demonstrate that simulations of GPP and light use efficiency improve significantly when our time‐resolved V_cmax estimates from SIF are used, with R² for GPP comparisons increasing from 0.85 to 0.93, and for light use efficiency from 0.44 to 0.83. Our results support the use of space‐based SIF data as a proxy for photosynthetic capacity and suggest the potential for global, time‐resolved estimates of V_cmax.     

Cassava about‐FACE: Greater than expected yield stimulation of cassava (Manihot esculenta) by future CO2 levels

Globally, cassava is the second most important root crop after potatoes and the fifth most important crop overall in terms of human caloric intake. In addition to its growing global importance for feed, fuel, and starch, cassava has long been vital to food security in Sub‐Saharan Africa. Climate change is expected to have its most severe impact on crops in food insecure regions, yet little is known about how cassava productivity will respond to climate change. The most important driver of climate change is globally increasing atmospheric CO₂ concentration ([CO₂]). However, the potential for cassava to enhance food security in an elevated [CO₂] world is uncertain as greenhouse and open top chamber (OTC) study reports are ambiguous. Studies have yielded misleading results in the past regarding the effect of elevated [CO₂] on crop productivity, particularly in cases where pots restricted sink growth. To resolve these conflicting results, we compare the response of cassava to growth at ambient (ca. 385 ppm) and elevated [CO₂] (585 ppm) under field conditions and fully open air [CO₂] elevation. After three and half months of growth at elevated [CO₂], above ground biomass was 30% greater and cassava root tuber dry mass increased over 100% (fresh weight increased 89%). High photosynthetic rates and photosynthetic stimulation by elevated [CO₂], larger canopies, and a large sink capacity all contributed to cassava's growth and yield stimulation. Cassava exhibited photosynthetic acclimation via decreased Rubisco capacity early in the season prior to root tuber initiation when sink capacity was smaller. Importantly, and in contrast to a greenhouse study, we found no evidence of increased leaf N or total cyanide concentration in elevated [CO₂]. All of our results are consistent with theoretical expectations; however, the magnitude of the yield increase reported here surpasses all other C₃ crops and thus exceeds expectations.     

Photosynthetic characteristics of non‐foliar organs in main C3 cereals

Photosynthesis in non‐foliar organs plays an important role in crop growth and productivity, and it has received considerable research attention in recent years. However, compared with the capability of photosynthetic CO₂ fixation in leaves, the distinct attributes of photosynthesis in the non‐foliar organs of wheat (a C₃ species) are unclear. This review presents a comprehensive examination of the photosynthetic characteristics of non‐foliar organs in wheat. Compared with leaves, non‐foliar organs had a higher capacity to refix respired CO₂, higher tolerance to environmental stresses and slower terminal senescence after anthesis. Additionally, whether C₄ photosynthetic metabolism exists in the non‐foliar organs of wheat is discussed, as is the advantage of photosynthesis in non‐foliar organs during times of abiotic stress. Introducing the photosynthesis‐related genes of C₄ plants into wheat, which are specifically expressed in non‐foliar organs, can be a promising approach for improving wheat productivity.     

Phenology and Productivity of C3 and C4 Grasslands in Hawaii

Grasslands account for a large proportion of global terrestrial productivity and play a critical role in carbon and water cycling. Within grasslands, photosynthetic pathway is an important functional trait yielding different rates of productivity along environmental gradients. Recently, C₃-C₄ sorting along spatial environmental gradients has been reassessed by controlling for confounding traits in phylogenetically structured comparisons. C₃ and C₄ grasses should sort along temporal environmental gradients as well, resulting in differing phenologies and growing season lengths. Here we use 10 years of satellite data (NDVI) to examine the phenology and greenness (as a proxy for productivity) of C₃ and C₄ grass habitats, which reflect differences in both environment and plant physiology. We perform phylogenetically structured comparisons based on 3,595 digitized herbarium collections of 152 grass species across the Hawaiian Islands. Our results show that the clade identity of grasses captures differences in their habitats better than photosynthetic pathway. Growing season length (GSL) and associated productivity (GSP) were not significantly different when considering photosynthetic type alone, but were indeed different when considering photosynthetic type nested within clade. The relationship between GSL and GSP differed most strongly between C₃ clade habitats, and not between C₃-C₄ habitats. Our results suggest that accounting for the interaction between phylogeny and photosynthetic pathway can help improve predictions of productivity, as commonly used C₃-C₄ classifications are very broad and appear to mask important diversity in grassland ecosystem functions.     

Do all chlorophyll fluorescence emission wavelengths capture the spring recovery of photosynthesis in boreal evergreen foliage?

Chlorophyll a fluorescence (ChlF) is closely related to photosynthesis and can be measured remotely using multiple spectral features as solar‐induced fluorescence (SIF). In boreal regions, SIF shows particular promise as an indicator of photosynthesis, in part because of the limited variation of seasonal light absorption in these ecosystems. Seasonal spectral changes in ChlF could yield new information on processes such as sustained nonphotochemical quenching (NPQ_S) but also disrupt the relationship between SIF and photosynthesis. We followed ChlF and functional and biochemical properties of Pinus sylvestris needles during the photosynthetic spring recovery period to answer the following: (a) How ChlF spectra change over seasonal timescales? (b) How pigments, NPQ_S, and total photosynthetically active radiation (PAR) absorption drive changes of ChlF spectra? (c) Do all ChlF wavelengths track photosynthetic seasonality? We found seasonal ChlF variation in the red and far‐red wavelengths, which was strongly correlated with NPQ_S, carotenoid content, and photosynthesis (enhanced in the red), but not with PAR absorption. Furthermore, a rapid decrease in red/far‐red ChlF ratio occurred in response to a cold spell, potentially relating to the structural reorganization of the photosystems. We conclude that all current SIF retrieval features can track seasonal photosynthetic dynamics in boreal evergreens, but the full SIF spectra provides additional insight.     

Inter‐annual changes in detritus‐based food chains can enhance plant growth response to elevated atmospheric CO2

Elevated atmospheric CO₂ generally enhances plant growth, but the magnitude of the effects depend, in part, on nutrient availability and plant photosynthetic pathway. Due to their pivotal role in nutrient cycling, changes in abundance of detritivores could influence the effects of elevated atmospheric CO₂ on essential ecosystem processes, such as decomposition and primary production. We conducted a field survey and a microcosm experiment to test the influence of changes in detritus‐based food chains on litter mass loss and plant growth response to elevated atmospheric CO₂ using two wetland plants: a C₃ sedge (Scirpus olneyi) and a C₄ grass (Spartina patens). Our field study revealed that organism's sensitivity to climate increased with trophic level resulting in strong inter‐annual variation in detritus‐based food chain length. Our microcosm experiment demonstrated that increased detritivore abundance could not only enhance decomposition rates, but also enhance plant growth of S. olneyi in elevated atmospheric CO₂ conditions. In contrast, we found no evidence that changes in the detritus‐based food chains influenced the growth of S. patens. Considered together, these results emphasize the importance of approaches that unite traditionally subdivided food web compartments and plant physiological processes to understand inter‐annual variation in plant production response to elevated atmospheric CO_2.     

Deriving C4 photosynthetic parameters from combined gas exchange and chlorophyll fluorescence using an Excel tool: theory and practice

The higher photosynthetic potential of C₄ plants has led to extensive research over the past 50 years, including C₄‐dominated natural biomes, crops such as maize, or for evaluating the transfer of C₄ traits into C₃ lineages. Photosynthetic gas exchange can be measured in air or in a 2% Oxygen mixture using readily available commercial gas exchange and modulated PSII fluorescence systems. Interpretation of these data, however, requires an understanding (or the development) of various modelling approaches, which limit the use by non‐specialists. In this paper we present an accessible summary of the theory behind the analysis and derivation of C₄ photosynthetic parameters, and provide a freely available Excel Fitting Tool (EFT), making rigorous C₄ data analysis accessible to a broader audience. Outputs include those defining C₄ photochemical and biochemical efficiency, the rate of photorespiration, bundle sheath conductance to CO₂ diffusion and the in vivo biochemical constants for PEP carboxylase. The EFT compares several methodological variants proposed by different investigators, allowing users to choose the level of complexity required to interpret data. We provide a complete analysis of gas exchange data on maize (as a model C₄ organism and key global crop) to illustrate the approaches, their analysis and interpretation. © 2015 John Wiley & Sons Ltd     

Partitioning of river metabolism identifies phytoplankton as a major contributor in the regulated Murray River (Australia)

1. River metabolism was measured over an annual cycle at three sites distributed along a 1000 km length of the lowland Murray River, Australia. 2. Whole system metabolism was measured using water column changes in dissolved oxygen concentrations while planktonic and benthic metabolism were partitioned using light‐dark bottles and benthic chambers. 3. Annual gross primary production (GPP) ranged from 775 to 1126 g O₂ m^?2 year^?1 which in comparison with rivers of similar physical characteristics is moderately productive. 4. Community respiration (CR) ranged from 872 to 1284 g O₂ m^?2 year^?1 so that annual net ecosystem production (NEP) was near zero, suggesting photosynthesis and respiration were balanced and that allochthonous organic carbon played a minor role in fuelling metabolism. 5. Planktonic rates of gross photosynthesis and respiration were similar to those of the total channel, indicating that plankton were responsible for much of the observed metabolism. 6. Respiration rates correlated with phytoplankton standing crop (estimated as the sum of GPP plus the chlorophyll concentration in carbon units), yielding a specific respiration rate of ?1.1 g O₂ g C^?1 day^?1. The respiration rate was equivalent to 19% of the maximum rate of phytoplankton photosynthesis, which is typical of diatoms. 7. The daily GPP per unit phytoplankton biomass correlated with the mean irradiance of the water column giving a constant carbon specific photon fixation rate of 0.35 gO₂ g Chl a^?1 day^?1 per μmole photons m^?2 s^?1 (ca. 0.08 per mole photons m^?2 on a carbon basis) indicating that light availability determined daily primary production. 8. Annual phytoplankton net production (NP) estimates at two sites indicated 25 and 36 g C m^?2 year^?1 were available to support riverine food webs, equivalent to 6% and 11% of annual GPP. 9. Metabolised organic carbon was predominantly derived from phytoplankton and was fully utilised, suggesting that food‐web production was restricted by the energy supply.     

Can exploiting natural genetic variation in leaf photosynthesis contribute to increasing rice productivity? A simulation analysis

Rice productivity can be limited by available photosynthetic assimilates from leaves. However, the lack of significant correlation between crop yield and leaf photosynthetic rate (A) is noted frequently. Engineering for improved leaf photosynthesis has been argued to yield little increase in crop productivity because of complicated constraints and feedback mechanisms when moving up from leaf to crop level. Here we examined the extent to which natural genetic variation in A can contribute to increasing rice productivity. Using the mechanistic model GECROS, we analysed the impact of genetic variation in A on crop biomass production, based on the quantitative trait loci for various photosynthetic components within a rice introgression line population. We showed that genetic variation in A of 25% can be scaled up equally to crop level, resulting in an increase in biomass of 22–29% across different locations and years. This was probably because the genetic variation in A resulted not only from Rubisco (ribulose 1,5‐bisphosphate carboxylase/oxygenase)‐limited photosynthesis but also from electron transport‐limited photosynthesis; as a result, photosynthetic rates could be improved for both light‐saturated and light‐limited leaves in the canopy. Rice productivity could be significantly improved by mining the natural variation in existing germ‐plasm, especially the variation in parameters determining light‐limited photosynthesis.     

A cross-scale analysis to understand and quantify the effects of photosynthetic enhancement on crop growth and yield across environments

Photosynthetic manipulation provides new opportunities for enhancing crop yield. However, understanding and quantifying the importance of individual and multiple manipulations on the seasonal biomass growth and yield performance of target crops across variable production environments is limited. Using a state-of-the-art cross-scale model in the APSIM platform we predicted the impact of altering photosynthesis on the enzyme-limited (A_c) and electron transport-limited (A_j) rates, seasonal dynamics in canopy photosynthesis, biomass growth, and yield formation via large multiyear-by-location crop growth simulations. A broad list of promising strategies to improve photosynthesis for C₃ wheat and C₄ sorghum were simulated. In the top decile of seasonal outcomes, yield gains were predicted to be modest, ranging between 0% and 8%, depending on the manipulation and crop type. We report how photosynthetic enhancement can affect the timing and severity of water and nitrogen stress on the growing crop, resulting in nonintuitive seasonal crop dynamics and yield outcomes. We predicted that strategies enhancing A_c alone generate more consistent but smaller yield gains across all water and nitrogen environments, A_j enhancement alone generates larger gains but is undesirable in more marginal environments. Large increases in both A_c and A_j generate the highest gains across all environments. Yield outcomes of the tested manipulation strategies were predicted and compared for realistic Australian wheat and sorghum production. This study uniquely unpacks complex cross-scale interactions between photosynthesis and seasonal crop dynamics and improves understanding and quantification of the potential impact of photosynthesis traits (or lack of it) for crop improvement research.     

Using the rapid A‐Ci response (RACiR) in the Li‐Cor 6400 to measure developmental gradients of photosynthetic capacity in poplar

The rapid A‐C_i response (RACiR) technique alleviates limitations of measuring photosynthetic capacity by reducing the time needed to determine the maximum carboxylation rate (V_cmax) and electron transport rate (J_max) in leaves. Photosynthetic capacity and its relationships with leaf development are important for understanding ecological and agricultural productivity; however, our current understanding is incomplete. Here, we show that RACiR can be used in previous generation gas exchange systems (i.e., the LI‐6400) and apply this method to rapidly investigate developmental gradients of photosynthetic capacity in poplar. We compared RACiR‐determined V_cmax and J_max as well as respiration and stomatal conductance (g_s) across four stages of leaf expansion in Populus deltoides and the poplar hybrid 717‐1B4 (Populus tremula × Populus alba). These physiological data were paired with leaf traits including nitrogen concentration, chlorophyll concentrations, and specific leaf area. Several traits displayed developmental trends that differed between the poplar species, demonstrating the utility of RACiR approaches to rapidly generate accurate measures of photosynthetic capacity. By using both new and old machines, we have shown how more investigators will be able to incorporate measurements of important photosynthetic traits in future studies and further our understanding of relationships between development and leaf‐level physiology.     

Natural genetic variation in photosynthesis: an untapped resource to increase crop yield potential?

Raising crop yield potential is a major goal to ensure food security for the growing global population. Photosynthesis is the primary determinant of crop productivity and any gain in photosynthetic CO₂ assimilation per unit of leaf area (A) has the potential to increase yield. Significant intraspecific variation in A is known to exist in various autotrophic organs that represent an unexploited target for crop improvement. However, the large number of factors that influence photosynthetic rates often makes it difficult to measure or estimate A under dynamic field conditions (i.e. fluctuating light intensities or temperatures). This complexity often results in photosynthetic capacity, rather than realized photosynthetic rates being used to assess natural variation in photosynthesis. Here we review the work on natural variation in A, the different factors determining A and their interaction in yield formation. A series of drawbacks and perspectives are presented for the most common analyses generally used to estimate A. The different yield components and their determination based on different photosynthetic organs are discussed with a major focus on potential exploitation of various traits for crop improvement. To conclude, an example of different possibilities to increase yield in wheat through enhancing A is illustrated.     

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Leaf fluorescence can be used to track plant development and stress, and is considered the most direct measurement of photosynthetic activity available from remote sensing techniques. Red and far‐red sun‐induced chlorophyll fluorescence (SIF) maps were generated from high spatial resolution images collected with the HyPlant airborne spectrometer over even‐aged loblolly pine plantations in North Carolina (United States). Canopy fluorescence yield (i.e., the fluorescence flux normalized by the light absorbed) in the red and far‐red peaks was computed. This quantifies the fluorescence emission efficiencies that are more directly linked to canopy function compared to SIF radiances. Fluorescence fluxes and yields were investigated in relation to tree age to infer new insights on the potential of those measurements in better describing ecosystem processes. The results showed that red fluorescence yield varies with stand age. Young stands exhibited a nearly twofold higher red fluorescence yield than mature forest plantations, while the far‐red fluorescence yield remained constant. We interpreted this finding in a context of photosynthetic stomatal limitation in aging loblolly pine stands. Current and future satellite missions provide global datasets of SIF at coarse spatial resolution, resulting in intrapixel mixture effects, which could be a confounding factor for fluorescence signal interpretation. To mitigate this effect, we propose a surrogate of the fluorescence yield, namely the Canopy Cover Fluorescence Index (CCFI) that accounts for the spatial variability in canopy structure by exploiting the vegetation fractional cover. It was found that spatial aggregation tended to mask the effective relationships, while the CCFI was still able to maintain this link. This study is a first attempt in interpreting the fluorescence variability in aging forest stands and it may open new perspectives in understanding long‐term forest dynamics in response to future climatic conditions from remote sensing of SIF.     

Developing a diagnostic model for estimating terrestrial vegetation gross primary productivity using the photosynthetic quantum yield and Earth Observation data

This article develops a new carbon exchange diagnostic model [i.e. Southampton CARbon Flux (SCARF) model] for estimating daily gross primary productivity (GPP). The model exploits the maximum quantum yields of two key photosynthetic pathways (i.e. C₃ and C₄) to estimate the conversion of absorbed photosynthetically active radiation into GPP. Furthermore, this is the first model to use only the fraction of photosynthetically active radiation absorbed by photosynthetic elements of the canopy (i.e. FAPAR_ps) rather than total canopy, to predict GPP. The GPP predicted by the SCARF model was comparable to in situ GPP measurements (R² > 0.7) in most of the evaluated biomes. Overall, the SCARF model predicted high GPP in regions dominated by forests and croplands, and low GPP in shrublands and dry‐grasslands across USA and Europe. The spatial distribution of GPP from the SCARF model over Europe and conterminous USA was comparable to those from the MOD17 GPP product except in regions dominated by croplands. The SCARF model GPP predictions were positively correlated (R² > 0.5) to climatic and biophysical input variables indicating its sensitivity to factors controlling vegetation productivity. The new model has three advantages, first, it prescribes only two quantum yield terms rather than species specific light use efficiency terms; second, it uses only the fraction of PAR absorbed by photosynthetic elements of the canopy (FAPAR_ps) hence capturing the actual PAR used in photosynthesis; and third, it does not need a detailed land cover map that is a major source of uncertainty in most remote sensing based GPP models. The Sentinel satellites planned for launch in 2014 by the European Space Agency have adequate spectral channels to derive FAPAR_ps at relatively high spatial resolution (20 m). This provides a unique opportunity to produce global GPP operationally using the Southampton CARbon Flux (SCARF) model at high spatial resolution.