Photosynthetically Active Research Articles

Transgenerational salinity tolerance plasticity in rice: Unraveling nongenetic phenotypic modifications and environmental influences.

Transgenerational plasticity in plants enables rapid adaptation to environmental changes, allowing organisms and their offspring to adapt to the environment without altering their underlying DNA. In this study, we investigated the plasticity of transgenerational salinity tolerance of rice plants using a reciprocal transplant experimental strategy. Our aim was to assess whether nongenetic environment-induced phenotypic modifications and transgenerational salinity affect the salinity tolerance of progeny while excluding nuclear genomic factors for two generations. Using salt-tolerant and salt-sensitive rice genotypes, we observed that the parentally salt-stressed salt-sensitive genotype displayed greater growth performance, photosynthetic activity, yield performance, and transcriptional responses than did the parentally nonstressed salt-sensitive plants under salt stress conditions. Surprisingly, salt stress-exposed salt-tolerant progeny did not exhibit as much salinity tolerance as salt stress-exposed salt-sensitive progeny under salt stress. Our findings indicate that the phenotypes of offspring plants differed based on the environment experienced by their ancestors, resulting in heritable transgenerational phenotypic modifications in salt-sensitive genotypes via maternal effects. These results elucidated the mechanisms underlying transgenerational plasticity in salinity tolerance, providing valuable insights into how plants respond to changing environmental conditions.

Ratio of photosynthetically active radiation to global solar radiation above forest canopy in complex terrain: measurements and analyses based on Qingyuan Ker Towers

BackgroundUnderstanding of the ratio of photosynthetic photon flux density (Qp) to global solar radiation (Rs) (Qp/Rs) is crucial for applying Rs to ecology-related studies. Previous studies reported Qp/Rs and its variations based on measurements from a single observatory tower, instead of multi-site-based measurements over complex terrains. This may neglect spatial heterogeneity in the terrain, creating a gap in an understanding of how terrain affects Qp/Rs and how this effect interacts with meteorological factors.MethodsHere the Qingyuan Ker Towers (three towers in a valley with different terrains: T1, T2, and T3) were utilized to measure Qp and Rs over mountainous forests of Northeast China. An airborne LiDAR system was used to generate a digital elevation model, and sky view factor of sectors (SVFs) divided from the field of view of tower’s pyranometer was calculated as a topographic factor to explain the variations of Qp/Rs.ResultsThe results identified significant differences in Qp/Rs of the three towers at both daily and half-hour scales, with larger differences on clear days than on overcast days. Qp/Rs was positively correlated with SVFs of T1 and T3, while this correlation was negative with that of T2. The effect of SVFs on Qp/Rs interacted with clearness index, water vapor pressure and solar zenith angle. Random forest-based importance assessment demonstrated that explanation (R2) on Qp/Rs was improved when SVFs was included in the predictor variable set, indicating that incorporating terrain effects enhances the prediction accuracy of Qp/Rs. The improvement in the R2 values was more pronounced on clear days than on overcast days, suggesting that the effect of terrain on Qp/Rs depended on sky conditions.ConclusionsAll findings suggested that Qp/Rs is affected by terrain, and integrating terrain information into existing Qp/Rs models is a feasible solution to improve Qp/Rs estimates in mountainous areas.

Regulating the Topology of Covalent Organic Frameworks for Boosting Overall H2O2 Photogeneration

AbstractPhotocatalytic oxygen reduction reactions and water oxidation reactions are extremely promising green approaches for massive H2O2 production. Nonetheless, constructing effective photocatalysts for H2O2 generation is critical and still challenging. Since the network topology has significant impacts on the electronic properties of two dimensional (2D) polymers, herein, for the first time, we regulated the H2O2 photosynthetic activity of 2D covalent organic frameworks (COFs) by topology. Through designing the linking sites of the monomers, we synthesized a pair of novel COFs with similar chemical components on the backbones but distinct topologies. Without sacrificial agents, TBD‐COF with cpt topology exhibited superior H2O2 photoproduction performance (6085 and 5448 μmol g−1 h−1 in O2 and air) than TBC‐COF with hcb topology through the O2‐O2⋅−‐H2O2, O2‐O2⋅−‐O21‐H2O2, and H2O‐H2O2 three paths. Further experimental and theoretical investigations confirmed that during the H2O2 photosynthetic process, the charge carrier separation efficiency, O2⋅− generation and conversion, and the energy barrier of the rate determination steps in the three channels, related to the formation of *OOH, *O21, and *OH, can be well tuned by the topology of COFs. The current study enlightens the fabrication of high‐performance photocatalysts for H2O2 production by topological structure modulation.

The effects of turbulence on the growth of three different diatom species

The effects of turbulence on phytoplankton growth have received considerable attentions. However, the complexity of turbulence poses a significant challenge to its systematic characterization in the laboratory, resulting in relatively limited data on the effects of turbulence on several algal species. Here, a laboratory turbulence simulation system was set up to systematically investigate the growth of three common diatom species (Thalassiosira pseudonana, Skeletonema costatum, and Phaeodactylum tricornutum) under stationary and turbulent conditions (at 60, 120, 180 rpm), and measurements were taken for the algal biomass, algal photosynthetic activity, and nutrients consumption. By comparing the growth of three algae species under different turbulence exposure intensities, this study found that different algae exhibit varying sensitivities to turbulence, and therefore have different shear thresholds. Meanwhile, cell morphology is the key factor influencing the different shear threshold values observed in the three diatom species. Additionally, turbulence could impact algal aggregation and light availability, and dramatically improve nutrient uptake by phytoplankton. Our study will provides theoretical support for future endeavors in using turbulence to cultivate phytoplankton or combat algal blooms.

Integrated sensing and machine learning: Predicting saccharine and bioenergy feedstocks in sugarcane

Predicting saccharine and bioenergy feedstocks in sugarcane enables growers and industries to determine the precise time and location for harvesting a better-quality product in the field. On one hand, Brix, Purity, and total recoverable sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for first-generation (1 G) bioethanol. Conversely, Cellulose, Hemicellulose, and Lignin are the primary constituents of straw, directly contributing to second-generation (2G) bioethanol. However, analyzing these materials in the laboratory is a time-consuming and non-scalable task. Therefore, we propose an approach based on a multi-sensor framework, which includes multispectral unmanned aerial vehicle (UAV) imagery, thermal, photosynthetic active radiation (PAR), and chlorophyll fluorescence (ChlF) data, along with machine learning (ML) algorithms namely random forest (RF), multiple linear regression (MLR), decision tree (DT), and support vector machine (SVM), to develop a non-invasive and predictive framework for mapping sugarcane feedstocks. We collected samples of stalks and leaves/straw during the maturity stage while simultaneously collecting remote sensing data. The ML models played a crucial role in predicting 1 G (R2 = 0.88–0.93) and 2 G (R2 = 0.56–0.82) feedstocks. Notably, remote sensing data could serve as important features for the models, mainly through the spectral bands (Blue, Green, and RedEdge), DTemp and ChlF. Hence, the best features can be further implemented within a framework to predict sugarcane feedstocks. Our study marks a significant advancement in the industrial-scale prediction of sugarcane feedstocks, providing stakeholders with invaluable prescriptive harvesting strategies for both primary products and by-products.

Photoelectrochemical Communication Between Cyanobacteria and Electrospun Cellulose‐Acetate–Graphene‐Based Electrodes for Photosynthetic and Respiratorial Photocurrent and Hydrogen Generations via Sustainable Solar Energy

In this article, the potential of biophotovoltaic devices (BPVs) as a sustainable solution for addressing the global energy crisis and combating climate change is explored. BPVs harness renewable electricity from sunlight and water through the photosynthetic activity of microorganisms, such as cyanobacteria and algae, serving as living photocatalysts. The focus is primarily on enhancing photocurrent outputs by developing efficient anode materials. Carbon‐based electrodes, particularly graphene (Gr), emerge as promising candidates due to their cost‐effectiveness, electrical conductivity, and mechanical strength. Despite reduced graphene oxide being commonly used, unoxidized Gr has not been extensively explored until recent research demonstrating its excellent current harvesting capacities. Additionally, 1D‐structured nanomaterials, such as electrospun nanofibers, show potential in promoting electron transport and enhancing charge collection efficiency. An innovative photoanode design is introduced, utilizing cyanobacteria immobilized on a cellulose acetate/Gr electrospun mat, offering a porous structure conducive to cyanobacterial attachment and efficient electron transfer. A complementary cathode structure, employing aniline‐modified Pt nanoparticles, facilitates the reduction of protons to yield hydrogen gas. Overall, in this study, BPVs’ potential is highlighted as a viable clean energy technology and novel approaches to enhance their efficiency and sustainability are presented.

Optimizing photosynthetic photon flux density and light quality for maximizing space use efficacy in edamame at the vegetative growth stage

Compared with conventional crop cultivation in greenhouses or fields, plant factories with artificial light (PFAL) have advantages in the highly efficient use of space, energy, and resources available for cultivation. However, few studies on environmental controls for improving the space use efficacy (SUE) of PFAL in the production of edamame, a vegetable soybean, have been reported. Therefore, developing an environmental control method for high productivity with minimal space and energy requirements is of high priority. The aims of this study were to (1) identify the optimal photosynthetic photon flux density (PPFD) and light quality to enhance the SUE of edamame at the vegetative growth stage, and (2) examine the effects of PPFD, light quality, and their interaction on edamame plant growth at the vegetative stage. SUE is defined as the crop biomass produced per unit cubic volume of cultivation during the growth period. We examined three PPFD treatments (300, 500, and 700 μmol m−2 s−1) with three color temperature LED lamps (3,000, 5,000, and 6,500 K), for a total of nine treatments. The results demonstrated that, under the same light quality treatment, higher PPFDs resulted in larger fresh and dry weights of all organs, higher stem length, and lower specific leaf area. Under the same PPFD treatment, a high ratio of blue (400–499 nm) to red (600–699 nm) photon flux density increased the plant height but decreased the projected leaf area. The values of SUE at 700 μmol m−2 s−1 increased by 213, 163, and 92% with 3,000, 5,000, and 6,500 K, respectively compared with those at 300 μmol m−2 s−1. The values of SUE at 700 μmol m−2 s−1 increased by 34 and 23% in 5,000 and 6,500 K treatments, respectively compared with that in the 3,000 K treatment. In conclusion, a combination of 700 μmol m−2 s−1 PPFD and 5,000 K color temperature is the suitable condition to increase the SUE of edamame at the vegetative growth stage in a PFAL.

The Impact of Genotype and Controlled Environment Cultivation Parameters on Tomato-Leaf-Derived Exosome-like Nanoparticle Yield and Properties

Horticultural plant material offers several advantages for isolating exosomes and other natural plant-derived exosome-like nanoparticles (PDENs) due to the accessibility and affordability of plant material for widespread applications. This study aims to explore the impacts of the tomato genotype (‘Admiro’, ‘Roma’, ‘Brooklyn’, ‘Marmande’ and ‘Betalux’) and the main cultivation parameters in controlled environment agriculture on the yield and properties of their PDENs for pharmaceutical and cosmeceutical applications. The PDEN yield, size distribution, and antioxidative properties of young tomato seedlings were evaluated. The ‘Betalux’ tomato was distinguished by a remarkably higher nanoparticle concentration and a uniform size distribution and was selected for further experiments. The impact of cultivation temperature (18, 22, and 26 °C), nitrogen nutrition (0, 250, and 500 mg L−1), and the lighting photosynthetic photon flux density (PPFD; 150, 250, and 450 µmol m−2 s−1) on nanoparticle properties was investigated. Optimal conditions consisting of a temperature of 22 °C, 250 mg L−1 nitrogen nutrition, and 250 µmol m−2 s−1 lighting PPFD were used as a reference. Optimal temperature, nitrogen nutrition, and lighting intensity resulted in the highest nanoparticle yield, the most uniform particle distribution, and the highest impact of PDEN preparations on keratinocyte metabolic activity. Deviation from optimal cultivation conditions reduced the tomato biomass and the PDEN protein and yield.

Exploring the impact of organic and inorganic amendments, with foliar application of iron nanoparticles, on cadmium stabilization and growth of maize in wastewater irrigated-soil

ObjectivesThis study addresses the critical issue of Cd contamination in agricultural soils, posing substantial risks to crop productivity and food safety. While prior pot experiment has undertook this issue on a small scale, this study aims to evaluate the efficacy of selected best soil amendments, at a large-scale field experiment. MethodologyPress mud and humic acid were applied at 0.5%, while gypsum and Fe2O3 were applied at 5 mg/kg alone and with foliar application of Fe nanoparticles at 5 mg/L. AnalysisComparative analysis with control revealed the immobilization efficiency of all amendments in descending order of effectiveness as follows: 100, 102, 104, 104, 105, 102, 105, and 105% for PM, HA, GYP, Fe, PM + Fe Nps, HA + Fe Nps, GYP + Fe Nps, and Fe + Fe Nps. Additionally, reduced growth, photosynthetic activities, and elevated levels of malondialdehyde and hydrogen peroxide, indicative of oxidative damage in control plant. FindingsApplication of these amendments with foliar spraying of Fe Nps effectively mitigates Cd toxicity in maize crops, leading to improved growth, biomass, photosynthetic pigments, and antioxidant enzyme activities. Novelty/ImprovementThese findings highlight the significance of exploring innovative approach of combining different amendments with foliar application of nanoparticles to mitigate Cd contamination and enhance soil health, thereby contributing to global efforts in ensuring food safety and security.

Effects of sulfamonomethoxine and trimethoprim co-exposures at different environmentally relevant concentrations on microalgal growth and nutrient assimilation

In aquaculture around the world, sulfamonomethoxine (SMM), a long-acting antibiotic that harms microalgae, is widely employed in combination with trimethoprim (TMP), a synergist. However, their combined toxicity to microalgae under long-term exposures at environmentally relevant concentrations remains poorly understood. Therefore, we studied the effects of SMM single-exposures and co-exposures (SMM:TMP=5:1) at concentrations of 5 μg/L and 500 μg/L on Chlorella pyrenoidosa within one aquacultural drainage cycle (15 days). Photosynthetic activity and N assimilating enzyme activities were employed to evaluate microalgal nutrient assimilation. Oxidative stress and flow cytometry analysis for microalgal proliferation and death jointly revealed mechanisms of inhibition and subsequent self-adaptation. Results showed that exposures at 5 μg/L significantly inhibited microalgal nutrient assimilation and induced oxidative stress on day 7, with a recovery to levels comparable to the control by day 15. This self-adaptation and over 95 % removal of antibiotics jointly contributed to promoting microalgal growth and proliferation while reducing membrane-damaged cells. Under 500 μg/L SMM single-exposure, microalgae self-adapted to interferences on nutrient assimilation, maintaining unaffected growth and proliferation. However, over 60 % of SMM remained, leading to sustained oxidative stress and apoptosis. Remarkably, under 500 μg/L SMM-TMP co-exposure, the synergistic toxicity of SMM and TMP significantly impaired microalgal nutrient assimilation, reducing the degradation efficiency of SMM to about 20 %. Consequently, microalgal growth and proliferation were markedly inhibited, with rates of 9.15 % and 17.7 %, respectively, and a 1.36-fold increase in the proportion of cells with damaged membranes was observed. Sustained and severe oxidative stress was identified as the primary cause of these adverse effects. These findings shed light on the potential impacts of antibiotic mixtures at environmental concentrations on microalgae, facilitating responsible evaluation of the ecological risks of antibiotics in aquaculture ponds.

Silicon regulates phosphate deficiency through involvement of auxin and nitric oxide in barley roots.

Silicon application mitigates phosphate deficiency in barley through an interplay with auxin and nitric oxide, enhancing growth, photosynthesis, and redox balance, highlighting the potential of silicon as a fertilizer for overcoming nutritional stresses. Silicon (Si) is reported to attenuate nutritional stresses in plants, but studies on the effect of Si application to plants grown under phosphate (Pi) deficiency are still very scarce, especially in barley. Therefore, the present work was undertaken to investigate the potential role of Si in mitigating the adverse impacts of Pi deficiency in barleyHordeum vulgareL. (var. BH902). Further, the involvement of two key regulatory signaling molecules--auxin and nitric oxide (NO)--in Si-induced tolerance against Pi deficiency in barley was tested. Morphological attributes, photosynthetic parameters, oxidative stress markers (O2·-, H2O2, and MDA), antioxidant system (enzymatic--APX, CAT, SOD, GR, DHAR, MDHAR as well as non-enzymatic--AsA and GSH), NO content, and proline metabolism were the key traits that were assessed under different treatments. The P deficiency distinctly declined growth of barley seedlings, which was due to enhancement in oxidative stress leading to inhibition of photosynthesis. These results were also in parallel with an enhancement in antioxidant activity, particularly SOD and CAT, and endogenous proline level and its biosynthetic enzyme (P5CS). The addition of Si exhibited beneficial effects on barley plants grown in Pi-deficient medium as reflected in increased growth, photosynthetic activity, and redox balance through the regulation of antioxidant machinery particularly ascorbate-glutathione cycle. We noticed that auxin and NO were also found to be independently participating in Si-mediated improvement of growth and other parameters in barley roots under Pi deficiency. Data of gene expression analysis for PHOSPHATE TRANSPORTER1 (HvPHT1) indicate that Si helps in increasing Pi uptake as per the need of Pi-deficient barley seedlings, and also auxin and NO both appear to help Si in accomplishing this task probably by inducing lateral root formation. These results are suggestive of possible application of Si as a fertilizer to correct the negative effects of nutritional stresses in plants. Further research at genetic level to understand Si-induced mechanisms for mitigating Pi deficiency can be helpful in the development of new varieties with improved tolerance against Pi deficiency, especially for cultivation in areas with Pi-deficient soils.

Assessing plasma activated water irrigation effects on tomato seedlings

Assessing plasma activated water irrigation effects on tomato seedlings

Net O2 exchange rates under dark and light conditions across different stem compartments.

Woody plants display some photosynthetic activity in stems, but the biological role of stem photosynthesis and the specific contributions of bark and wood to carbon uptake and oxygen evolution remain poorly understood. We aimed to elucidate the functional characteristics of chloroplasts in stems of different ages in Fraxinus ornus. Our investigation employed diverse experimental approaches, including microsensor technology to assess oxygen production rates in whole stem, bark, and wood separately. Additionally, we utilized fluorescence lifetime imaging microscopy (FLIM) to characterize the relative abundance of photosystems I and II (PSI : PSII chlorophyll ratio) in bark and wood. Our findings revealed light-induced increases in O2 production in whole stem, bark, and wood. We present the radial profile of O2 production in F. ornus stems, demonstrating the capability of stem chloroplasts to perform light-dependent electron transport. Younger stems exhibited higher light-induced O2 production and dark respiration rates than older ones. While bark emerged as the primary contributor to net O2 production under light conditions, our data underscored that wood chloroplasts are also photosynthetically active. The FLIM analysis unveiled a lower PSI abundance in wood than in bark, suggesting stem chloroplasts are not only active but also acclimate to the spectral composition of light reaching inner compartments.

Effects of different light conditions on morphological, anatomical, photosynthetic and biochemical parameters of Cypripedium macranthos Sw.

In this study, the morphological (plant height, leaf length and width, stem diameter and leaf number), anatomical (epidermal cell density and thickness, Stomatal length and width), photosynthetic (net photosynthetic rate, transpiration rate, stomatal conductance, intercellular CO2 concentration, relative humidity, leaf temperature and chlorophyll fluorescence parameters) and biochemical parameters (the content of soluble sugar, soluble protein, proline, malondialdehyde and electrical conductivity) of Cypripedium macranthos Sw. in Changbai Mountain were determined under different light conditions (L10, L30, L50, L100). The results showed that morphological values including plant height, leaf area, stem diameter and leaf number of C. macranthos were smaller under the condition of full light at L100. The epidermal cell density and epidermal thickness of C. macranthos were the highest under L30 and L50 treatments, respectively. It had the highest net photosynthetic rate (Pn) and chlorophyll content under L50 treatment. Meanwhile, correlation analysis indicated that photosynthetically active radiation (PAR) and water use efficiency (WUE) were the main factors influencing Pn. C. macranthos accumulated more soluble sugars and soluble proteins under L100 treatment, while the degree of membrane peroxidation was the highest and the plant was severely damaged. In summary, the adaptability of C. macranthos to light conditions is ranked as follows L50 > L30 > L10 > L100. Appropriate light conditions for C. macranthos are 30%-50% of full light, which should be taken into account in protection and cultivation.

Photosynthetic variation and detoxification strategies based on cadmium uptake, non-protein thiols, and secondary metabolites in Miscanthus sacchariflorus under cadmium exposure

ABSTRACT Miscanthus sacchariflorus is previously demonstrated to be a potential candidate for remediation of cadmium (Cd) pollution. To explore its resistance strategy to Cd, a hydroponic experiment was conducted to determine the variations of photosynthetic activity in leaves and physiological response in roots of this plant. Results showed that the root of M. sacchariflorus was the primary location for Cd accumulation. The bio-concentration factor in the roots and rhizomes was >1, and the translocation factor from underground to aboveground was <1. Throughout the experimental period, treatment with 0.06 mM Cd2+ did not significantly alter the contents of chlorophyll a, chlorophyll b, or carotenoid. By contrast, treatment with 0.15 and 0.30 mM Cd2+ decreased the contents of chlorophyll a, chlorophyll b, and carotenoid; caused the deformation of the chlorophyll fluorescence transient curve; reduced the photochemical efficiency of photosystem II; and increased the contents of non-protein thiols, total flavone, and total phenol. These results indicate that M. sacchariflorus has good adaptability to 0.06 mM Cd2+. Moreover, the accumulation of the non-protein thiols, total flavone, and total phenol in roots may promote the chelation of Cd2+, thus alleviating Cd toxicity. This study provides theoretical support for using M. sacchariflorus to remediate Cd-polluted wetlands.

Complex environmental control of growth in a dominant Mediterranean‐alpine shrub species

Abstract Mediterranean‐alpine plants are exposed to harsh conditions, forcing them to perform with well‐adapted physiological strategies to withstand the dual stressors that arise from winter cold and summer drought. Such growth strategies are not yet fully understood, although they gain importance with regard to the resilience of species in the face of ongoing climate variability. Here, we aimed at understanding shrub growth in a widespread Mediterranean‐alpine species, Cytisus galianoi Talavera & Gibbs. Using long‐term time series of stem diameter change obtained from dendrometer measurements across the species´ range, we were able to characterise its spatiotemporal growth plasticity. Furthermore, separating water‐related fluctuations in stem diameter from irreversible stem increment allowed us to disentangle the species´ seasonal growth patterns. Using fine‐scale measurements of on‐site environmental conditions, we were then able to identify micro‐ecological drivers controlling the species´ growth processes by applying correlation analysis and partial least squares regressions. We show the species´ adaptation to the spatial heterogeneity across its range for the first time. Our findings highlight that the combination of bimodality and overall high growth plasticity likely allows the species to cover a wide geographical range across alpine areas and over a wide range of weather conditions. We show the environmental control of bimodal growth in C. galianoi, and the importance of pre‐growth environmental control, leading to pronounced carry‐over effects. These lead to a major advantage in resisting adverse growth conditions and adapting to changing conditions. Synthesis: Overall, our findings improve the understanding of the species´ ecological niche and show that preceding photosynthetic activity helps C. galianoi to perform even under unfavourable conditions in winter and during the active growth phase, challenging the general assumption on the coupling of growth to specific seasons and suggesting that the species is capable of adapting to future climate variability.

Modeling attenuation of photosynthetically active radiation across the optical gradient in the Laurentian Great Lakes with application to Lake Erie

Representation of subsurface photosynthetically active radiation (PAR) in biophysical models of the Laurentian Great Lakes (LGL) is imperative to their utility as tools for research and management. Here we consolidated measured vertical profiles of subsurface PAR with concurrent water quality (WQ) data from four LGL. We estimated the diffuse attenuation coefficient of PAR (Kd(PAR)) by fitting an exponential function to measured PAR over depth, and evaluated 68 regressions predicting Kd(PAR) as a function of water quality variables (Kd-WQ regressions). We compare four of the top cross-lake calibrated regressions against two published regressions trained on western Lake Erie (WLE) data. Then, as a case study, we demonstrate the utility of our cross-lake calibrated Kd-WQ regressions with a simplified biophysical model of Lake Erie consisting of the Finite Volume Community Ocean Model with submodules for simulating suspended sediment and dissolved organic carbon (FVCOM-SS-DOC). Twenty-five Kd-WQ regressions were identified as candidates for use in biophysical models based on their skill determined via cross-validation. WLE-trained Kd-WQ regressions were less able to simulate Kd(PAR) and PAR in more transparent waters compared to cross-lake calibrated Kd-WQ regressions, which translated to considerable differences in primary production estimates for the central and eastern basins when using WQ data simulated by FVCOM-SS-DOC. A cross-lake calibrated Kd-WQ regression was installed into FVCOM-SS-DOC, which then simulated spatial patterns of suspended sediments and Kd(PAR). These calibrated Kd-WQ regressions can be used in a variety of biophysical models across optically-distinct waters of the LGL to support adaptive management of nutrient inputs and fisheries

Light Environment and Photosynthetic Capacities of Leaves at Different Locations within Eggplant Canopies in a Greenhouse in Ontario, Canada

To effectively manage crop production in a greenhouse, it is essential to understand the natural light environment and physiological responses of the plants to light. This study investigated the dynamics of photosynthetic photon flux densities (PPFD) and light quality within the canopies of greenhouse-grown eggplant (Solanum melongena) and the photosynthetic capacities of leaves at different locations within the canopies. The light environment was quantified at 0.2-m intervals within (intra-canopy) and adjacent to (extra-canopy) the crop canopy on both sunny and cloudy days within a commercial greenhouse located in Leamington, Ontario, Canada. Our results indicated a linear decline in extra-canopy PPFD on both sunny and cloudy days, but an exponential decrease in intra-canopy PPFD. The intra-canopy PPFD decreased by 91% and 76% between 0 m and 0.4 m from the canopy apex on sunny and cloudy days, respectively. The lower canopy (0.6–1.2 m) light spectrum consisted largely of far-red light, equal amounts of red light and green light, with a lower percentage of blue light. Parameters derived from leaf-level light response curves indicated that the light-saturated net carbon exchange rate, light saturation point, and light compensation point decreased as the distance from canopy apex increased, whereas quantum yield was unaffected. Thus, leaves in the lower canopy were less efficient at using high PPFD, but they displayed no deterioration of photosynthetic machinery. Based solely on photosynthetic capabilities, leaves between 0 and 1.0 m from the canopy apex should not be removed to decrease the total plant sink strength.

A spatiotemporal attention-augmented ConvLSTM model for ocean remote sensing reflectance prediction

Remote sensing reflectance (Rrs) is an essential parameter in ocean color remote sensing and a fundamental input for the estimation of ocean color elements. Predicting Rrs has the potential to enable simultaneous prediction of multiple marine environmental parameters, facilitating multi-perspective analysis of marine environmental changes. This paper proposes a spatiotemporal attention-augmented ConvLSTM-based model for ocean Rrs prediction. The developed model can predict Rrs for up to seven days by simultaneously learning spatiotemporal features from time series Rrs and auxiliary environmental variables. According to the experiments, the proposed model achieves optimal performances on Rrs predictions at 443, 488, and 555 nm, with Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE) for the first four prediction days less than 5.6*10-4 sr-1 and 8.6 %, respectively, which are better than the performance of the convolutional neural network (CNN), the LSTM, CNN-LSTM, and the ConvLSTM. The spatial and temporal variations of Rrs are also compared to evaluate the effectiveness of the model, presenting a consistent spatiotemporal pattern between predicted and observed Rrs. We also found that integrating sea surface temperature (SST), photosynthetically available radiation (PAR), and aerosol optical thickness at 869 nm (AOT869) into the model can improve the prediction accuracy in various degrees. This work suggests the proposed deep learning model can predict Rrs for 7 days with a convincing performance, providing critical data and technical support for ocean-related applications, such as algae bloom monitoring.

Spatiotemporal Patterns and Environmental Drivers of Particulate Inorganic Carbon (PIC) Variability in the Southern Waters of Sumatra‐Java Islands

AbstractThe southern waters of the Sumatra‐Java Islands, within the Indo‐Pacific Warm Pool, are highly susceptible to global climate change impacts. Understanding particulate inorganic carbon (PIC) dynamics and environmental responses in this region is critical for assessing climate change effects on marine ecosystems. Utilizing two decades of remote sensing PIC data (2003–2022), we identified five sub‐regions via K‐means clustering: the Sunda Strait, southern coastal/offshore waters of Sumatra Island, and southern coastal/offshore waters of Java Island. Self‐Organizing Map explored interannual PIC variations, while Generalized Additive Models delineated driving factors. In the Sunda Strait, PIC dynamics are influenced by water exchanges between the Indonesian Seas (ISs) and eastern Indian Ocean (EIO). Seasonally, PIC concentrations peak during the east monsoon (boreal summer); decreasing during positive Indian Ocean Dipole (+IOD) and El Niño events. Along the southern Sumatra, PIC variations positively correlate with rainfall and photosynthetically active radiation (PAR). Along the southern Sumatra, upwelling drives PIC variations, with higher concentrations during mature summer monsoon induced upwelling periods. PIC increases during +IOD and decreases during El Niño. Our study highlights the nexus between nutrients, physical factors (e.g., rainfall), and climatic events (e.g., El Niño) on PIC concentrations. Climate‐induced changes in oceanic physical processes modulate nutrient concentrations, thereby governing PIC variations. We propose a mechanistic model to elucidate PIC variations in upwelling areas. Findings suggest that prospective climate variability, encompassing alterations in climate events, rainfall, and temperature, may escalate PIC concentrations within the study area, advocating PIC as a forward‐looking climate change indicator.