The fertilization effect of global dimming on crop yields is not attributed to an improved light interception

Effects of diffuse radiation fraction on crop light absorption, light use efficiency and gross primary production on an instantaneous scale in South China

The fraction of absorbed photosynthetically active radiation (FAPAR), light use efficiency (LUE), and gross primary productivity (GPP) are the key driving factors of crop production and ecological models. Diffuse radiation fraction (DF) has been reported to profoundly affect FAPAR, LUE and GPP, and its impact on a short time scale needs to be emphasized. Based on the field observations at noon local time during 2021-2022 and the Two-Leaf light use efficiency model, this study investigated the magnitudes of the DF effect on the canopy FAPAR, LUE, and GPP for the three different crops (peanut, soybean and corn) on an instantaneous scale in South China. Different from that of peanut and soybean, the FAPAR of corn increased linearly with the rise of DF. The instantaneous LUE of each crop was highly sensitive to DF, and its linear regression slope was greater than 1.0 g C MJ- 1. On average, the DF accounted for around 69-74% of the variations in the instantaneous LUE and 59-64% of the variations in the instantaneous GPP over the entire observation period. The sky conditions with a DF value between 0.45 and 0.66 were favorable for the carbon fixation of the three crops. The linear coupling strength between GPP and PAR under diffuse radiation (DF ≥ 0.5) was stronger than that under direct radiation (DF < 0.5). The results will be helpful in accurate estimating of FAPAR, LUE, GPP and even crop production in both South China and other similar regions.

Improving light use efficiency models via the introduction of both the diffuse fraction and radiation scalar

Surface solar radiation, both its components and intensity, is pivotal in determining vegetation light use efficiency (LUE) and is essential for accurately estimating gross primary production (GPP) in ecosystems. This study introduces two key parameters: the diffuse photosynthetic photon flux density fraction (fdPPFD) to account for the diffuse fertilization effect (DFE) and the radiation scalar to reflect the impact of radiation intensity on leaf-level LUE. Leveraging these parameters, we developed two novel LUE models: the Big-leaf Diffuse-fraction Radiation-scalar LUE (BDR-LUE) model, adapted from traditional big-leaf LUE models, and the Two-leaf Diffuse-fraction Radiation-scalar LUE (TDR-LUE) model, based on conventional two-leaf LUE frameworks. These models were calibrated and validated using data from 32 FLUXNET sites representing six vegetation types with available diffuse PPFD measurements. The results reveal the following key findings: (1) Both new models, particularly the TDR-LUE model, deliver superior performance compared to conventional big-leaf and two-leaf LUE models; (2) The BDR-LUE model reduces the root mean square error (RMSE) by at least 12.75 % compared to the conventional Eddy Covariance-LUE (EC-LUE) model; (3) The TDR-LUE model achieves an RMSE reduction of at least 13.54 % compared to the established Two-Leaf LUE (TL-LUE) model; (4) Both models effectively capture annual and monthly variations in vegetation GPP; (5) While the BDR-LUE model outperforms the TDR-LUE model for croplands, it shows lower accuracy for other vegetation types. These findings underscore the importance of integrating fdPPFD and the radiation scalar into LUE models. The proposed models demonstrate substantial potential for enhancing GPP estimates in terrestrial ecosystems.

Shade tolerance in wheat is related to photosynthetic limitation and morphological and physiological acclimations

Low solar irradiance reaching the canopy due to fog and heavy haze is a significant yield-limiting factor worldwide. However, how plants adapt to shade stress and the mechanisms underlying the reduction in leaf photosynthetic capacity and grain yield remain unclear. In this study (conducted during 2018-2021), we investigated the impact of light deprivation (60%) at the pre-anthesis and post-anthesis stages on leaf carboxylation efficiency, source-to-sink relationships, sucrose metabolism, and grain yield of wheat cultivars with contrasting shade tolerance. Shade stress decreased stomatal conductance, stomatal limitation value, intrinsic water use efficiency, rubisco activity, and carboxylation efficiency of flag leaves during grain-filling, whereas intercellular CO2 concentration increased. These findings indicate that non-stomatal limitation reduces the net photosynthesis rate in a weak-light environment. Shade-tolerant cultivars (MM-51 and CM-39) adapted to low-light conditions via a higher leaf area of flag leaves, light interception rate, and chlorophyll a and b contents; this increased non-structural carbohydrates and sucrose contents in developing grains, ultimately decreasing yield loss by shade stress. Pre-anthesis shading resulted in a greater yield loss than post-anthesis shading because of decreased plant biomass, grain number per spike and 1,000-kernel weight. This study indicates that Rubisco-mediated non-stomatal limitation reduces P N and sucrose content in plants exposed to low-light stress, contributing to decreased grain yield. Our study provides information on the mechanism underlying shade stress tolerance, which will help design future strategies for reducing yield loss in the context of global dimming.

Unveiling geospatial heterogeneity in climate's impacts on wheat production to advance spatially-matched climate-adaptive agricultural management in the North China plain

Influence of climate change on the geospatial heterogeneity in agricultural production remains poorly understood. In this study, heterogeneity in climate's impacts on wheat production across the North China Plain (NCP) was explored by integrating APSIM model, process-based factor-control quantitative approach, and geostatistical analyses. The results indicated that increased precipitation and minimum temperature boosted yields, while elevated maximum temperature and reduced radiation exerted adverse effects. The most pronounced negative impact arose from the coupling variation between maximum temperature and radiation, contributing to yields' variations of -5.84% from 2000 to 2010 and -5.22% from 2010 to 2020. In last two decades, climate change has augmented the overall geospatial heterogeneity degree in wheat yields. The chief factor contributing to yields' heterogeneity was the maximum temperature during anthesis-maturation stage, explaining an average of 37.6% of yields' heterogeneity, followed by precipitation throughout the whole growth period and the anthesis-maturation stage, explaining 36.1% and 34.5% respectively. A reciprocal enhancement mechanism exists between factors in driving yields' heterogeneity. Wheat yields in the southwestern NCP benefited more from increased precipitation and minimum temperature. Between 2000 and 2010, yields in the central NCP (junctions of Henan, Hebei, and Shandong) experienced the most pronounced adverse impact from increased maximum temperature. However, by 2010-2020, significant adverse impact shifted to western NCP, expanding spatially. During 2010-2020, the geospatial scope of radiation's significant negative impact expanded compared to the preceding decade, particularly affecting the yields in central and eastern NCP. The identified geospatial heterogeneity pattern of climate's impacts can guide spatially-matched climate-adaptive management adjustments. For instance, intensifying the defense against high-temperature's impacts in northwestern Henan, southern Hebei, and western Shandong, while improving the adaptation to radiation reduction in the central and eastern NCP. The findings are expected to advance regional-scale climate-smart agricultural development.

Benefit of aerosol reduction to winter wheat during China's clean air action: A case study of Henan Province

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action, yet its impact on wheat (Triticum aestivum L.) production remains unclear. We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018. After calibrating parameters with the extended Fourier Amplitude Sensitivity Test (EFAST) and the generalized likelihood uncertainty estimation (GLUE) method, the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately. We found that the aerosol negatively impacted wheat biomass by 21.87% and yield by 22.48% from 2006 to 2018, and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity. Due to the strict clean air action, under all-sky conditions, the surface solar shortwave radiation (SSR) in 2018 increased by about 7.08% over 2006-2013 during the wheat growing seasons. As a result of the improvement of crop photosynthesis, winter wheat biomass and yield increased by an average of 5.46% and 2.9%, respectively. Our findings show that crop carbon uptake and yield will benefit from the clean air action in China, helping to ensure national food and health security.

Shedding light on the increased carbon uptake by a boreal forest under diffuse solar radiation across multiple scales

Solar radiation is scattered by cloud cover, aerosols and other particles in the atmosphere, all of which are affected by global changes. Furthermore, the diffuse fraction of solar radiation is increased by more frequent forest fires and likewise would be if climate interventions such as stratospheric aerosol injection were adopted. Forest ecosystem studies predict that an increase in diffuse radiation would result in higher productivity, but ecophysiological data are required to identify the processes responsible within the forest canopy. In our study, the response of a boreal forest to direct, diffuse and heterogeneous solar radiation conditions was examined during the daytime in the growing season to determine how carbon uptake is affected by radiation conditions at different scales. A 10-year data set of ecosystem, shoot and forest floor vegetation carbon and water-flux data was examined. Ecosystem-level carbon assimilation was higher under diffuse radiation conditions in comparison with direct radiation conditions at equivalent total photosynthetically active radiation (PAR). This was driven by both an increase in shoot and forest floor vegetation photosynthetic rate. Most notably, ecosystem-scale productivity was strongly related to the absolute amount of diffuse PAR, since it integrates both changes in total PAR and diffuse fraction. This finding provides a gateway to explore the processes by which absolute diffuse PAR enhances productivity, and the long-term persistence of this effect under scenarios of higher global diffuse radiation.

Regulating the composition and secondary structure of wheat protein through canopy shading to improve dough performance and nutritional index

Viscoelastic properties of gluten proteins critically determine the biscuit-making quality. However, cultivar genetics and light conditions closely regulate the composition of the gluten proteins. The impact of pre- and post-anthesis shading (60 %) on amino acid profile, gluten protein composition, secondary structure, dough performance, and biscuit-making quality were evaluated using four wheat cultivars that differ in gluten protein composition. Pre- and post-anthesis shading increased the contents of gliadin, by 35.8 and 3.1 %; glutenin, by 27.6 and 7.3 %; and total protein, by 21.7 and 10.6 %, respectively, compared with those of unshaded plants. Conversely, the ratios of glutenin/gliadin, ω-/(α,β + γ)-gliadin, and high-molecular-weight/low-molecular-weight glutenin subunits decreased with shading. Strong-gluten cultivars exhibited smaller declines in these parameters than weak-gluten cultivars. Secondary structure analysis of the wheat protein revealed that shading increased β-sheet content but decreased β-turn content. Changes in protein components and their secondary structures caused an increase in wet gluten content, dough development time, and gluten performance index, thereby decreasing the biscuit spread ratio. Shading stress increased the protein content and nutrition index but decreased the biological value of protein by 2.5 %. Transcriptomic results revealed that shading induced 139 differentially expressed genes that decreased carbohydrate metabolism and increased amino acid metabolism, involved in increased protein content. Thus, canopy shading improves dough performance and nutrition index by regulating the amino acid profiles, protein compositions, and secondary structures. The study provides key insights for achieving superior grain quality under global dimming.

RGA1 alleviates low-light-repressed pollen tube elongation by improving the metabolism and allocation of sugars and energy

Low-light stress compromises photosynthetic and energy efficiency and leads to spikelet sterility; however, the effect of low-light stress on pollen tube elongation in the pistil remains poorly understood. The gene RGA1, which encodes a Gα-subunit of the heterotrimeric G-protein, enhanced low-light tolerance at anthesis by preventing the cessation of pollen tube elongation in the pistil of rice plants. In this process, marked increases in the activities of acid invertase (INV), sucrose synthase (SUS) and mitochondrial respiratory electron transport chain complexes, as well as the relative expression levels of SUTs (sucrose transporter), SWEETs (sugars will eventually be exported transporters), SUSs, INVs, CINs (cell-wall INV 1), SnRK1A (sucrose-nonfermenting 1-related kinase 1) and SnRK1B, were observed in OE-1 plants. Accordingly, notable increases in contents of ATP and ATPase were presented in OE-1 plants under low-light conditions, while they were decreased in d1 plants. Importantly, INV and ATPase activators (sucrose and Na₂ SO₃ , respectively) increased spikelet fertility by improving the energy status in the pistil under low-light conditions, and the ATPase inhibitor Na₂ VO₄ induced spikelet sterility and decreased ATPase activity. These results suggest that RGA1 could alleviate the low-light stress-induced impairment of pollen tube elongation to increase spikelet fertility by promoting sucrose unloading in the pistil and improving the metabolism and allocation of energy.

Rice (Oryza sativa) alleviates photosynthesis and yield loss by limiting specific leaf weight under low light intensity

The physiological mechanisms of shade tolerance and trait plasticity variations under shade remain poorly understood in rice (Oryza sativa L.). Twenty-five genotypes of rice were evaluated under open and shade conditions. Various parameters to identify variations in the plasticity of these traits in growth irradiance were measured. We found wide variations in specific leaf weight (SLW) and net assimilation rate measured at 400µmolm-2 s-1 photosynthetic photon flux density (PPFD; referred to as A 400 ) among the genotypes. Under shade, tolerant genotypes maintained a high rate of net photosynthesis by limiting specific leaf weight accompanied by increased intercellular CO2 concentration (C i ) compared with open-grown plants. On average, net photosynthesis was enhanced by 20% under shade, with a range of 2-30%. Increased accumulation of biomass under shade was observed, but it showed no correlation with photosynthetic plasticity. Chlorophyll a /b ratio also showed no association with photosynthetic rate and yield. Analysis of variance showed that 11%, 16%, and 37% of the total variance of A 400 , SLW, and C i were explained due to differences in growth irradiance. SLW and A 400 plasticity in growth irradiance was associated with yield loss alleviation with R 2 values of 0.37 and 0.16, respectively. Biomass accumulation was associated with yield loss alleviation under shade, but no correlation was observed between A 400 and leaf-N concentration. Thus, limiting specific leaf weight accompanied by increased C i rather than leaf nitrogen concentration might have allowed rice genotypes to maintain a high net photosynthesis rate per unit leaf area and high yield under shade.

Shading affects the starch structure and digestibility of wheat by regulating the photosynthetic light response of flag leaves

Heavy haze-induced decreases in solar radiation represent an important factor that affects the structural properties of starch macromolecules. However, the relationship between the photosynthetic light response of flag leaves and the structural properties of starch remains unclear. In this study, we investigated the impact of light deprivation (60 %) during the vegetative-growth or grain-filling stage on the leaf light response, starch structure, and biscuit-baking quality of four wheat cultivars with contrasting shade tolerance. Shading decreased the apparent quantum yield and maximum net photosynthetic rate of flag leaves, resulting in a lower grain-filling rate and starch content and higher protein content. Shading decreased the starch, amylose, and small starch granule amount and swelling power but increased the larger starch granule amount. Under shade stress, the lower amylose content decreased the resistant starch content while increasing the starch digestibility and estimated glycemic index. Shading during the vegetative-growth stage increased starch crystallinity, 1045/1022 cm^-1 ratio, starch viscosity, and the biscuit spread ratio, while shading during the grain-filling stage decreased these values. Overall, this study indicated that low light affects the starch structure and biscuit spread ratio by regulating the photosynthetic light response of flag leaves.

Improved air quality leads to enhanced vegetation growth during the COVID-19 lockdown in India

The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, -19.27%) and Particulate Matter (PM 2.5, -23%) during LD (2020)from pre-LD (March-September months for the period 2017-2019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (March-May) and Kharif (June-September). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.

Environmental Stimuli: A Major Challenge during Grain Filling in Cereals

Light, temperature, water, and fertilizer are arguably the most important environmental factors regulating crop growth and productivity. Environmental stimuli, including low light, extreme temperatures, and water stresses caused by climate change, affect crop growth and production and pose a growing threat to sustainable agriculture. Furthermore, soil salinity is another major environmental constraint affecting crop growth and threatening global food security. The grain filling stage is the final stage of growth and is also the most important stage in cereals, directly determining the grain weight and final yield. However, the grain filling process is extremely vulnerable to different environmental stimuli, especially for inferior spikelets. Given the importance of grain filling in cereals and the deterioration of environmental problems, understanding environmental stimuli and their effects on grain filling constitutes a major focus of crop research. In recent years, significant advances made in this field have led to a good description of the intricate mechanisms by which different environmental stimuli regulate grain filling, as well as approaches to adapt cereals to changing climate conditions and to give them better grain filling. In this review, the current environmental stimuli, their dose-response effect on grain filling, and the physiological and molecular mechanisms involved are discussed. Furthermore, what we can do to help cereal crops adapt to environmental stimuli is elaborated. Overall, we call for future research to delve deeper into the gene function-related research and the commercialization of gene-edited crops. Meanwhile, smart agriculture is the development trend of the future agriculture under environmental stimuli.

The ÓMICAS alliance, an international research program on multi-omics for crop breeding optimization

The OMICAS alliance is part of the Colombian government's Scientific Ecosystem, established between 2017-2018 to promote world-class research, technological advancement and improved competency of higher education across the nation. Since the program's kick-off, OMICAS has focused on consolidating and validating a multi-scale, multi-institutional, multi-disciplinary strategy and infrastructure to advance discoveries in plant science and the development of new technological solutions for improving agricultural productivity and sustainability. The strategy and methods described in this article, involve the characterization of different crop models, using high-throughput, real-time phenotyping technologies as well as experimental tissue characterization at different levels of the omics hierarchy and under contrasting conditions, to elucidate epigenome-, genome-, proteome- and metabolome-phenome relationships. The massive data sets are used to derive in-silico models, methods and tools to discover complex underlying structure-function associations, which are then carried over to the production of new germplasm with improved agricultural traits. Here, we describe OMICAS' R&D trans-disciplinary multi-project architecture, explain the overall strategy and methods for crop-breeding, recent progress and results, and the overarching challenges that lay ahead in the field.

Low Light Stress Increases Chalkiness by Disturbing Starch Synthesis and Grain Filling of Rice

Low light stress increases the chalkiness of rice; however, this effect has not been fully characterized. In this study, we demonstrated that low light resulted in markedly decreased activity of ADP-glucose pyrophosphorylase in the grains and those of sucrose synthase and soluble starch synthase in the early period of grain filling. Furthermore, low light also resulted in decreased activities of granule-bound starch synthase and starch branching enzyme in the late period of grain filling. Therefore, the maximum and mean grain filling rates were reduced but the time to reach the maximum grain filling rates and effective grain filling period were increased by low light. Thus, it significantly decreased the grain weight at the maximum grain filling rate and grain weight and retarded the endosperm growth and development, leading to a loose arrangement of the amyloplasts and an increase in the chalkiness of the rice grains. Compared to the grains at the top panicle part, low light led to a greater decrease in the grain weight at the maximum grain filling rate and time to reach the grain weight at the maximum grain filling rate at the bottom panicle part, which contributed to an increase in chalkiness by increasing the rates of different chalky types at the bottom panicle part. In conclusion, low light disturbed starch synthesis in grains, thereby impeding the grain filling progress and increasing chalkiness, particularly for grains at the bottom panicle part.

Changes in chemical composition and starch structure in rice noodle cultivar influence Rapid Visco analysis and texture analysis profiles under shading

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The pasting property of rice noodles which decreased under shade stress.

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Pasting property is related to amylose, short chain amylopectin and crystallinity of starch.

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Protein content and swelling factor had significant correlation with the quality of rice noodle.

GuichaoII, a rice variety with high amylose content widely used to make rice noodles, exhibits high hardness (631.07–729.43), gel consistency (8.47–9.47 mm), and hold viscosity/peak viscosity (HPV/PKV) (0.85–0.88); however, it has a low protein content (5.74–6.96%) and swelling factor (5.49–9.77). Herein, GuichaoII was subjected to low-light stress (53% reduction) during the grain filling stage. The amylose content and crystallinity of GuichaoII and the control variety Shuhui 498 decreased while the protein content, short-chain branch ratio, and degree of branching increased, which affected the ability of the rice flour to absorb water and expand during the gelatinization process. The PKV, HPV, breakdown viscosity, and final viscosity were significantly reduced, while the hardness was significantly increased, and the gel consistency and the gelatinization quality of the rice were reduced, severely limiting the processing and production of rice noodles.

Estimation of Aerosol Optical Depth at 30 m Resolution Using Landsat Imagery and Machine Learning

Current remote sensing-based aerosol optical depth (AOD) products have coarse spatial resolutions, which are useful for studies at continental and global scales, but unsatisfactory for local scale applications, such as urban air pollution monitoring. In this study, we investigated the possibility of using Landsat imagery to develop high-resolution AOD estimations at 30 m based on machine learning algorithms. We assessed the performance of six machine learning algorithms, including Extreme Gradient Boosting, Random Forest, Cascade Random Forest, Gradient Boosted Decision Trees, Extremely Randomized Trees, and Multiple Linear Regression. To obtain accurate AOD estimations, we used prior knowledge from multiple sources as inputs to the machine learning models, including the Global Land Surface Satellite (GLASS) albedo, the 1-km AOD product from MODIS data using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, and meteorological and surface elevation data. A total of 13,624 AOD measurements from Aerosol Robotic Network (AERONET) sites were used for model training and validation. We found that all six algorithms exhibited good performance, with R2 values ranging from 0.73 to 0.78 and AOD root-mean-square errors (RMSE) ranging from 0.089 to 0.098. The extremely randomized trees algorithm, however, demonstrated marginally superior performance as compared to the other algorithms; hence, it was used to produce AOD estimates at a 30 m resolution for one Landsat scene coving Beijing in 2013–2019. Through a comparison with overlapping AERONET observations, a high level of accuracy was achieved, with an R2 = 0.889 and an RMSE = 0.156. Our method can be potentially used to generate a global high-resolution AOD dataset based on Landsat imagery.

Hyperspectral Reflectance Characteristics of Rice Canopies under Changes in Diffuse Radiation Fraction

To analyze the hyperspectral reflectance characteristics of rice canopies under changes in diffuse radiation fraction, experiments using different cover materials were performed in Nanjing, China, during 2016 and 2017. Each year, two treatments with different reduction ratios of diffuse radiation fraction but with similar shading rates were set in the field experiment: In T1, total solar radiation shading rate was 14.10%, and diffuse radiation fraction was 31.09%; in T2, total solar radiation shading rate was 14.42%, and diffuse radiation fraction was 39.98%, respectively. A non-shading treatment was included as a control (CK). Canopy hyperspectral reflectance, soil and plant analyzer development (SPAD), and leaf area index (LAI) were measured under shading treatments on different days after heading. The red-edge parameters (position, λ0; maximum amplitude, Dλ; area, α0; width, σ) were calculated, as well as the area, depth, and width of three absorption bands. The location of the first absorption band appeared in the range of 553–788 nm, and the second and third absorption bands appeared in the range of 874–1257 nm. The results show that the shading treatment had a significant effect on the rice canopy’s hyperspectral reflectance. Compared with CK, the canopy reflectance of T1 (the diffuse radiation fraction was 31.09%) and T2 (the diffuse radiation fraction was 39.98%) decreased in the visible light range (350–760 nm) and increased in the near-infrared range (800–1350 nm), while the red-edge parameters (λ0, Dλ, α0), SPAD, and LAI increased. On the other hand, under shading treatment, the increase in diffuse radiation fraction also had a significant impact on the hyperspectral spectra of the rice canopy, especially at 14 days after heading. Compared with T1, the green peak (550 nm) of T2 reduced by 16.12%, and the average reflectance at 800–900 nm increased by 10%. Based on correlation analysis, it was found that these hyperspectral reflectance characteristics were mainly due to the increase in SPAD (2.31%) and LAI (7.62%), which also led to the increase in Dλ (8.70%) and α0 (13.89%). Then, the second and third absorption features of T2 were significantly different from that of T1, which suggests that the change in diffuse radiation fraction could affect the process of water vapor absorption by rice.

Aerosol-induced direct radiative forcing effects on terrestrial ecosystem carbon fluxes over China

Atmospheric aerosols can change vegetation photosynthesis through the effects of aerosols on radiation, which will affect the peak carbon dioxide emissions and carbon neutrality at global scales. In this study, we quantify the aerosol-induced direct radiation forcing (ADRF) in China from 2001 to 2014 based on the radiation flux simulation used by the Fu-Liou radiation transfer model under with-aerosols and no-aerosols scenarios. Using the radiation simulation results, we modify the atmospheric forcing datasets to drive Community Land Model 4.5 (CLM4.5) to gain the changes in carbon fluxes in China caused by ADRF. The results show that these two models are accurate in estimating radiation (R² = 0.78-0.88) and carbon fluxes (R² = 0.73-0.75) in China. High levels of ADRFs were captured in China, especially with increasing diffuse fraction, resulting in the diffusing fertilization effect occurring in most areas of China. The ADRF can increase cumulative gross primary productivity (GPP) and total ecosystem respiration (ER) by 3.20 gC m^-2 and 5.13 gC m^-2 per year, respectively. From 2001 to 2014, the diffusing fertilization effects experienced trends of increasing first and then decreasing. However, ADRFs in some regions of China show negative effects on carbon fluxes due to vulnerable vegetation functional types and high aerosol loading. The ADRF will also enable soil temperature decreases and volumetric soil water increases, which is closely related to changes in carbon fluxes. Meanwhile, due to changes in soil water and heat conditions, N₂O and CH₄ production will also be disturbed, and ADRF increases the global warming potential (GWP) for both greenhouse gases. This phenomenon indicated that atmospheric aerosol pollution control is far-reaching significance for peaking carbon dioxide emissions before 2030.

Solar geoengineering can alleviate climate change pressures on crop yields

Solar geoengineering (SG) and CO₂ emissions reduction can each alleviate anthropogenic climate change, but their impacts on food security are not yet fully understood. Using an advanced crop model within an Earth system model, we analysed the yield responses of six major crops to three SG technologies (SGs) and emissions reduction when they provide roughly the same reduction in radiative forcing and assume the same land use. We found sharply distinct yield responses to changes in radiation, moisture and CO₂, but comparable significant cooling benefits for crop yields by all four methods. Overall, global yields increase ~10% under the three SGs and decrease 5% under emissions reduction, the latter primarily due to reduced CO₂ fertilization, relative to business as usual by the late twenty-first century. Relative humidity dominates the hydrological effect on yields of rainfed crops, with little contribution from precipitation. The net insolation effect is negligible across all SGs, contrary to previous findings.

Atmospheric opacity has a nonlinear effect on global crop yields

Agricultural impacts of air pollution, climate change and geoengineering remain uncertain due to potentially offsetting changes in the quantity and quality of sunlight. By leveraging year-to-year variation in growing-season cloud optical thickness, I provide nonlinear empirical estimates of how increased atmospheric opacity alters sunlight across the Earth's surface and how this affects maize and soy yields in the United States, Europe, Brazil and China. I find that the response of yields to changes in sunlight from cloud scattering and absorption is consistently concave across crops and regions. An additional day of optimal cloud cover, relative to a clear-sky day, increases maize and soy yields by 0.4%. Changes in sunlight due to changes in clouds have decreased the global average maize and soy yields by 1% and 0.1% due to air pollution and may further decrease yields by 1.8% and 0.4% due to climate change.

The impact of global dimming on crop yields is determined by the source-sink imbalance of carbon during grain filling

Global dimming reduces incident global radiation but increases the fraction of diffuse radiation, and thus affects crop yields; however, the underlying mechanisms of such an effect have not been revealed. We hypothesized that crop source-sink imbalance of either carbon (C) or nitrogen (N) during grain filling is a key factor underlying the effect of global dimming on yields. We presented a practical framework to assess both C and N source-sink relationships, using data of biomass and N accumulation from periodical sampling conducted in field experiments for wheat and rice from 2013 to 2016. We found a fertilization effect of the increased diffuse radiation fraction under global dimming, which alleviated the negative impact of decreased global radiation on source supply and sink growth, but the source supply and sink growth were still decreased by dimming, for both C and N. In wheat, the C source supply decreased more than the C sink demand, and as a result, crops remobilized more pre-heading C reserves, in response to dimming. However, these responses were converse in rice, which presumably stemmed from the more increment in radiation use efficiency and the more limited sink size in rice than wheat. The global dimming affected source supply and sink growth of C more significantly than that of N. Therefore, yields in both crops were dependent more on the source-sink imbalance of C than that of N during grain filling. Our revealed source-sink relationships, and their differences and similarities between wheat and rice, provide a basis for designing strategies to alleviate the impact of global dimming on crop productivity.

Relationship between chalkiness and the structural and thermal properties of rice starch after shading during grain-filling stage

Chalkiness is a major concern in rice production and its acceptance and is increased by shade stress. However, the relationship between rice chalkiness and the structural and thermal properties of starch is unclear. Here, we investigated the effect of shade stress on rice starch properties. The chalky grain rate and chalkiness degree significantly decreased with the amylose content, Mn, and ΔH and increased with surface area- and volume-weighted mean diameters, branching degree, ratio of 1022/995 cm^-1, and molecular weight polydispersity. Shade stress significantly increased the volume- and surface area-weighted mean diameters and Mw and decreased the amylose content, A chain proportion of amylopectin, Mn, and regularity of starch. These effects led to an increase in the molecular weight polydispersity and branching degree and a decrease in the crystallinity degree and 1045/1022 cm^-1 ratio, thereby reducing starch ΔH and uniformity. These factors contributed to increased chalkiness of rice under shade stress.