Sun-induced fluorescence (SIF) has been found to be strongly correlated with gross primary production (GPP) in a quasi-linear pattern at the scales beyond leaves. However, the causes of the GPP:SIF relationship deviating from a linear pattern remain unclear. In the current study conducted at two maize sites in Nebraska in 2017 summer growing season, we investigated the relationship between GPP and SIF at 760 nm (F-760) at two temporal scales and quantified the contributions of incoming photosynthetically active radiation (PAR(in)), fraction of absorbed PAR (fPAR), light use efficiency (LUE), and F-760 yield (F-760,F-y, defined as F-760/(PAR(in)xfPAR)) to GPP and F-760 variabilities to further understand the linearity and deviations in the GPP:F-760 relationship. We found the following: (1) For individual growth stages when canopy structure and chlorophyll content were stable, GPP and F-760 were strongly controlled by PAR(in), while LUE and F-760,F-y had much lower contributions to the GPP:F-760 relationship; during this period, LUE and F-760,F-y had either a slightly negative or no clear relationship, which explained some deviations in the GPP:SIF relationship. (2) At the seasonal scale, the contribution of LUE to GPP variability as well as the contribution of F-760,F-y to F-760 variability increased and was comparable to the contribution of PAR(in); the LUE:F-760,F-y relationship showed a strong linear relationship, which strengthened the linear GPP:F-760 relationship. Both maize sites showed similar patterns. A framework was applied to estimate LUE at individual stages and as a result, significantly improved the GPP estimation, thus enhancing the SIF potential for inferring photosynthesis.

We test the relationship between canopy photosynthesis and reflected near-infrared radiation from vegetation across a range of functional (photosynthetic pathway and capacity) and structural conditions (leaf area index, fraction of green and dead leaves, canopy height, reproductive stage, and leaf angle inclination), weather conditions, and years using a network of field sites from across central California. We based our analysis on direct measurements of canopy photosynthesis, with eddy covariance, and measurements of reflected near-infrared and red radiation from vegetation, with light-emitting diode sensors. And we interpreted the observed relationships between photosynthesis and reflected near-infrared radiation using simulations based on the multilayer, biophysical model, CanVeg. Measurements of reflected near-infrared radiation were highly correlated with measurements of canopy photosynthesis on half-hourly, daily, seasonal, annual, and decadal time scales across the wide range of function and structure and weather conditions. Slopes of the regression between canopy photosynthesis and reflected near-infrared radiation were greatest for the fertilized and irrigated C(4)corn crop, intermediate for the C(3)tules on nutrient-rich organic soil and nitrogen fixing alfalfa, and least for the native annual grasslands and oak savanna on nutrient-poor, mineral soils. Reflected near-infrared radiation from vegetation has several advantages over other remotely sensed vegetation indices that are used to infer canopy photosynthesis; it does not saturate at high leaf area indices, it is insensitive to the presence of dead legacy vegetation, the sensors are inexpensive, and the reflectance signal is strong. Hence, information on reflected near-infrared radiation from vegetation may have utility in monitoring carbon assimilation in carbon sequestration projects or on microsatellites orbiting Earth for precision agriculture applications.

One century ago (1920), Otto Warburg (1883-1970) discovered that in liquid cultures of unicellular green algae (Chlorella sp.) molecular oxygen (O-2) exerts an inhibitory effect on photosynthesis. Decades later, O-2 dependent suppression of photosynthetic carbon dioxide (CO2) assimilation (the "green" Warbur geffect) was confirmed on the leaves of seed plants. Here, we summarize the history of this discovery and elucidate the consequences of the photorespiratory pathway in land plants with reference to unpublished CO2 exchange data measured on the leaves of sunflower (Helianthus annuus) plants. In addition, we discuss the inefficiency of the key enzyme Rubisco and analyze data concerning the productivity of C3 vs. C4 crop species (sunflower vs. maize, Zea mays). Warburg's discovery inaugurated a research agenda in the biochemistry of photosynthetic CO2 assimilation that continues to the present. In addition, we briefly discuss Warburg's model of metabolic processes in cancer, net primary production (global photosynthesis) with respect to climate change, trees and other land plants as CO2 removers, and potential climate mitigators in the Anthropocene.

The enhanced vegetation productivity driven by increased concentrations of carbon dioxide (CO2) [i.e., the CO2 fertilization effect (CFE)] sustains an important negative feedback on climate warming, but the temporal dynamics of CFE remain unclear. Using multiple long-term satellite- and ground-based datasets, we showed that global CFE has declined across most terrestrial regions of the globe from 1982 to 2015, correlating well with changing nutrient concentrations and availability of soil water. Current carbon cycle models also demonstrate a declining CFE trend, albeit one substantially weaker than that from the global observations. This declining trend in the forcing of terrestrial carbon sinks by increasing amounts of atmospheric CO2 implies a weakening negative feedback on the climatic system and increased societal dependence on future strategies to mitigate climate warming.

Greening represents a significant increase in vegetation activity. Accurate quantification of global greening in peak growth is vital for quantifying changes in terrestrial productivity. Normalized Difference Vegetation Index (NDVI) is the remote sensing indicator most commonly applied for this purpose. However, there is limited knowledge about how the applications of other improved or newly available products can impact global greening assessments. This study reports the first systematic investigation of the impact of vegetation indicator selection on global greening in peak growth. It examines the period from 2003 to 2017 using six indicators with a spatial resolution of 500 m: Near Infrared Reflectance of terrestrial vegetation (NIRv) and the coupled diagnostic biophysical modeled Gross Primary Production (PML-GPP), together with NDVI, Enhanced Vegetation Index with two bands (EVI2), Leaf Area Index (LAI) and Moderate Resolution Imaging Spectroradiometer (MODIS) GPP (MOD-GPP) calculated based on MODIS images. Vegetation trends were estimated using the Mann-Kendall test, the unanimous trends by six vegetation indicators were derived, and the concordance ratio in estimated trends by each pair of indicators was investigated among different biomes and their sensitivity to changes in climate were investigated. We found that the estimated greening and browning varied between 12-23% and 2-13% of the vegetated areas, respectively. There was more net greening estimated from NDVI and MOD-GPP (around 19%) compared to the other indicators (8-11%). The concordance ratio between EVI2 and NIRv was much higher (>94%) than other combinations (61-76%) at the global scale. The concordance ratio between one specific indicator and the other indicators gradually increased with its change magnitude. Unanimous results from these six indicators were exhibited in less than two-fifths (38.71%) of vegetated areas. Apart from the EVI2 and NIRv, the concordance ratio varied among different biomes: high in cropland (67-81%), but low in deciduous needle-leaf forest (51-62%) and very low in evergreen broadleaf forest between PML-GPP and others (37-49%). The diverse sensitivity to changes in climate contributed to the discrepancies: greening was more pronounced during warming conditions for the GPP products when compared with the greenness indices. At the global scale, the concordance ratio was higher during cooling conditions among all the indicators except between PML-GPP. Datasets supporing these findings are available online at https://github.com/FuzhouSIRC/Greening_6indicators.2

Here, we present a conceptual and quantitative model to describe the role of the Cytochrome b(6)f complex in controlling steady-state electron transport in C-3 leaves. The model is based on new experimental methods to diagnose the maximum activity of Cyt b(6)f in vivo, and to identify conditions under which photosynthetic control of Cyt b(6)f is active or relaxed. With these approaches, we demonstrate that Cyt b(6)f controls the trade-off between the speed and efficiency of electron transport under limiting light, and functions as a metabolic switch that transfers control to carbon metabolism under saturating light. We also present evidence that the onset of photosynthetic control of Cyt b(6)f occurs within milliseconds of exposure to saturating light, much more quickly than the induction of non-photochemical quenching. We propose that photosynthetic control is the primary means of photoprotection and functions to manage excitation pressure, whereas non-photochemical quenching functions to manage excitation balance. We use these findings to extend the Farquhar et al. (Planta 149:78-90, 1980) model of C-3 photosynthesis to include a mechanistic description of the electron transport system. This framework relates the light captured by PS I and PS II to the energy and mass fluxes linking the photoacts with Cyt b(6)f, the ATP synthase, and Rubisco. It enables quantitative interpretation of pulse-amplitude modulated fluorometry and gas-exchange measurements, providing a new basis for analyzing how the electron transport system coordinates the supply of Fd, NADPH, and ATP with the dynamic demands of carbon metabolism, how efficient use of light is achieved under limiting light, and how photoprotection is achieved under saturating light. The model is designed to support forward as well as inverse applications. It can either be used in a stand-alone mode at the leaf-level or coupled to other models that resolve finer-scale or coarser-scale phenomena.

High temperature and accompanying high vapor pressure deficit often stress plants without causing distinctive changes in plant canopy structure and consequential spectral signatures. Sun-induced chlorophyll fluorescence (SIF), because of its mechanistic link with photosynthesis, may better detect such stress than remote sensing techniques relying on spectral reflectance signatures of canopy structural changes. However, our understanding about physiological mechanisms of SIF and its unique potential for physiological stress detection remains less clear. In this study, we measured SIF at a high-temperature experiment, Temperature Free-Air Controlled Enhancement, to explore the potential of SIF for physiological investigations. The experiment provided a gradient of soybean canopy temperature with 1.5, 3.0, 4.5, and 6.0 degrees C above the ambient canopy temperature in the open field environments. SIF yield, which is normalized by incident radiation and the fraction of absorbed photosynthetically active radiation, showed a high correlation with photosynthetic light use efficiency (r = 0.89) and captured dynamic plant responses to high-temperature conditions. SIF yield was affected by canopy structural and plant physiological changes associated with high-temperature stress (partial correlation r = 0.60 and -0.23). Near-infrared reflectance of vegetation, only affected by canopy structural changes, was used to minimize the canopy structural impact on SIF yield and to retrieve physiological SIF yield (phi(F)) signals. phi(F) further excludes the canopy structural impact than SIF yield and indicates plant physiological variability, and we found that phi(F) outperformed SIF yield in responding to physiological stress (r = -0.37). Our findings highlight that phi(F) sensitively responded to the physiological downregulation of soybean gross primary productivity under high temperature. phi(F), if reliably derived from satellite SIF, can support monitoring regional crop growth and different ecosystems' vegetation productivity under environmental stress and climate change.

Our study suggests that the global CO2 fertilization effect (CFE) on vegetation photosynthesis has declined during the past four decades. The Comments suggest that the temporal inconsistency in AVHRR data and the attribution method undermine the results' robustness. Here, we provide additional evidence that these arguments did not affect our finding and that the global decline in CFE is robust.

Here, we describe a model of C-3, C-3-C-4 intermediate, and C-4 photosynthesis that is designed to facilitate quantitative analysis of physiological measurements. The model relates the factors limiting electron transport and carbon metabolism, the regulatory processes that coordinate these metabolic domains, and the responses to light, carbon dioxide, and temperature. It has three unique features. First, mechanistic expressions describe how the cytochrome b(6)f complex controls electron transport in mesophyll and bundle sheath chloroplasts. Second, the coupling between the mesophyll and bundle sheath expressions represents how feedback regulation of Cyt b(6)f coordinates electron transport and carbon metabolism. Third, the temperature sensitivity of Cyt b(6)f is differentiated from that of the coupling between NADPH, Fd, and ATP production. Using this model, we present simulations demonstrating that the light dependence of the carbon dioxide compensation point in C-3-C-4 leaves can be explained by co-occurrence of light saturation in the mesophyll and light limitation in the bundle sheath. We also present inversions demonstrating that population-level variation in the carbon dioxide compensation point in a Type I C-3-C-4 plant, Flaveriachloraefolia, can be explained by variable allocation of photosynthetic capacity to the bundle sheath. These results suggest that Type I C-3-C-4 intermediate plants adjust pigment and protein distributions to optimize the glycine shuttle under different light and temperature regimes, and that the malate and aspartate shuttles may have originally functioned to smooth out the energy supply and demand associated with the glycine shuttle. This model has a wide range of potential applications to physiological, ecological, and evolutionary questions.

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% similar to 82%) and physiological information (i.e. physiological SIF yield, Phi(F), 17% similar to 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Phi(F) indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that phi(F) responded to the proxy for physiological stress (partial correlation coefficient, r(p)= 0.40, p< 0.001) while non-physiological signals of SIF did not respond (p> 0.1). The field-scale Phi(F) data showed water deficit stress from the comparison between irrigated and rainfed fields, and Phi(F) was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r= 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Phi(F) was more strongly correlated spatially with air temperature and VPD (r= 0.23 and 0.39) than SIF (r= 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Phi(F) reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Phi(F) is spatially scalable. Utilizing Phi(F) for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.