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At least 73 records · Page 4

Biological weighting function for the inhibition of phytoplankton photosynthesis by ultraviolet radiation

Severe reduction of stratospheric ozone over Antarctica has focused increasing concern on the biological effects of ultraviolet-B (UVB) radiation (280 to 320 nanometers). Measurements of photosynthesis from an experimental system, in which phytoplankton are exposed to a broad range of irradiance treatments, are fit to an analytical model to provide the spectral biological weighting function that can be used to predict the short-term effects of ozone depletion on aquatic photosynthesis. Results show that UVA (320 to 400 nanometers) significantly inhibits the photosynthesis of a marine diatom and a dinoflagellate, and that the effects of UVB are even more severe. Application of the model suggests that the Antarctic ozone hole might reduce near-surface photosynthesis by 12 to 15 percent, but less so at depth. The experimental system makes possible routine estimation of spectral weightings for natural phytoplankton.

Cullen, John J.↗

Impact of vertical and seasonal variation in leaf traits on simulating soybean canopy photosynthesis via 1D and 3D modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax 25 ), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax 25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax 25 profile achieved comparable performance to the scheme with the measured Vcmax 25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R 2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R 2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

Mineral nutrient signaling controls photosynthesis: focus on iron deficiency-induced chlorosis

Photosynthetic organisms convert light energy into chemical energy stored in carbohydrates. To perform this process, an adequate supply of essential mineral elements, such as iron, is required in the chloroplast. Because iron plays a crucial role during electron transport and chlorophyll formation, iron deficiency alters photosynthesis and promotes chlorosis, or the yellowing of leaves. Intriguingly, iron deficiency-induced chlorosis can be reverted by the depletion of other micronutrients [i.e., manganese (Mn)] or macronutrients [i.e., sulfur (S) or phosphorus (P)], raising the question of how plants integrate nutrient status to control photosynthesis. Here, in this work, we review how improving our understanding of the complex relationship between nutrient homeostasis and photosynthesis has great potential for crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗

Maize ANT1 modulates vascular development, chloroplast development, photosynthesis, and plant growth

Arabidopsis AINTEGUMENTA (ANT), an AP2 transcription factor, is known to control plant growth and floral organogenesis. In this study, our transcriptome analysis and in situ hybridization assays of maize embryonic leaves suggested that maize ANT1 (ZmANT1) regulates vascular development. To better understand ANT1 functions, we determined the binding motif of ZmANT1 and then showed that ZmANT1 binds the promoters of millet SCR1, GNC, and AN3, which are key regulators of Kranz anatomy, chloroplast development, and plant growth, respectively. We generated a mutant with a single-codon deletion and two frameshift mutants of the ANT1 ortholog in the C4 millet Setaria viridis by the CRISPR/Cas9 technique. The two frameshift mutants displayed reduced photosynthesis efficiency and growth rate, smaller leaves, and lower grain yields than wild-type (WT) plants. Moreover, their leaves sporadically exhibited distorted Kranz anatomy and vein spacing. Conducting transcriptomic analysis of developing leaves in the WT and the three mutants we identified differentially expressed genes (DEGs) in the two frameshift mutant lines and found many down-regulated DEGs enriched in photosynthesis, heme, tetrapyrrole binding, and antioxidant activity. In addition, we predicted many target genes of ZmANT1 and chose 13 of them to confirm binding of ZmANT1 to their promoters. Based on the above observations, we proposed a model for ANT1 regulation of cell proliferation and leaf growth, vascular and vein development, chloroplast development, and photosynthesis through its target genes. Furthermore, our study revealed biological roles of ANT1 in several developmental processes beyond its known roles in plant growth and floral organogenesis.

59 BASIC BIOLOGICAL SCIENCES↗

Improving leaf spring phenology modelling for temperate tree species: An integration of the Farquhar–Medlyn photosynthesis model with the optimality‐based approach

Spring leaf phenology in temperate tree species is highly sensitive to climate change and significantly affects plant photosynthetic performance, resource utilization, competition and trophic interactions, thereby impacting various ecosystem functions. Although optimality-based (OPT) approaches for modelling spring phenology are increasingly recognized, the optimal representation of the underlying principle (balancing photosynthesis gains with chilling risks) remains controversial. Here, we integrated a coupled Farquhar–Medlyn photosynthesis model into an existing OPT model, and termed the resulting model R-OPT, and evaluated its performance using the PEP725 dataset, which includes 409,144 site-species-year records from across Europe. Our results show that R-OPT outperforms both the default OPT and non-optimality-based models (e.g. the chilling-forcing trade-off and growing degree day models). This improved performance is consistent within and across five focal tree species but varies by region: R-OPT excels in lowland, moist environments but is less effective in high-altitude, cold, and dry areas, possibly due to an incomplete representation of environmental constraints on photosynthetic carbon gain in these regions. Our research advances leaf spring phenology modelling by emphasizing an optimality principle that balances photosynthetic carbon gain with chilling risk, improving the representation of plant photosynthesis processes and enhancing understanding of environmental factors influencing phenology in the context of climate change.

coupled Farquhar–Medlyn photosynthesis model↗

Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical assumptions at leaf and global scales

Abstract Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation ( A ). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO 2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi‐hypothesis methods (that account for both hypothesis and parameter variability) for process‐level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting‐rate selection. Each of the four processes comprises 1–3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high‐resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting‐rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting‐rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A . Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%–10%, equivalent to 50%–160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi‐hypothesis methods.

54 ENVIRONMENTAL SCIENCES↗

An exploratory steady–state redox model of photosynthetic linear electron transport for use in complete modelling of photosynthesis for broad applications

A photochemical model of photosynthetic electron transport (PET) is needed to integrate photophysics, photochemistry, and biochemistry to determine redox conditions of electron carriers and enzymes for plant stress assessment and mechanistically link sun-induced chlorophyll fluorescence to carbon assimilation for remotely sensing photosynthesis. Towards this goal, we derived photochemical equations governing the states and redox reactions of complexes and electron carriers along the PET chain. These equations allow the redox conditions of the mobile plastoquinone pool and the cytochrome b 6 f complex (Cyt) to be inferred with typical fluorometry. The equations agreed well with fluorometry measurements from diverse C 3 /C 4 species across environments in the relationship between the PET rate and fraction of open photosystem II reaction centres. We found the oxidation of plastoquinol by Cyt is the bottleneck of PET, and genetically improving the oxidation of plastoquinol by Cyt may enhance the efficiency of PET and photosynthesis across species. Redox reactions and photochemical and biochemical interactions are highly redundant in their complex controls of PET. Although individual reaction rate constants cannot be resolved, they appear in parameter groups which can be collectively inferred with fluorometry measurements for broad applications. The new photochemical model developed enables advances in different fronts of photosynthesis research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Using the red chromatic coordinate to characterize the phenology of forest canopy photosynthesis

Vegetation phenology has received increasing attention in climate change research. Near-surface sensing using digital repeat photography has proven to be useful for ecosystem-scale monitoring of vegetation phenology. However, our understanding of the link between phenological metrics derived from digital repeat photography and the phenology of forest canopy photosynthesis is still incomplete, especially for evergreen plant species. Using 49 site-years of digital images from the PhenoCam Network from eight evergreen needleleaf forest (ENF) and six deciduous broadleaf forest (DBF) sites in North America, we explored the potential of the green chromatic (GCC) and red chromatic coordinates (RCC) in tracking forest canopy photosynthesis by comparing camera-derived start- and end-of-growing season (SOS and EOS, respectively) with corresponding estimates derived from eddy covariance-derived daily gross primary productivity (GPP). We found that for DBF sites, both GCC and RCC performed comparable in capturing SOS and EOS. However, similar to earlier studies, GCC had limited potential in capturing GPP-based SOS or EOS for ENF sites. In contrast, we found RCC was a better predictor of both GPP-based SOS and EOS for ENF sites. Environmental and ecological explanations were both provided that phenological transitions derived from RCC were highly correlated with spring and autumn meteorological conditions, as well as having overall higher correlations with phenology based on LAI, a critical variable for describing canopy development. Our results demonstrate that RCC is an underappreciated metric for tracking vegetation phenology, especially for ENF sites where GCC failed to provide reliable estimates for GPP-based SOS or EOS. Our results improve confidence in using digital repeat photography to characterize the phenology of canopy photosynthesis across forest types.

54 ENVIRONMENTAL SCIENCES↗

Global variation in the fraction of leaf nitrogen allocated to photosynthesis

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.

54 ENVIRONMENTAL SCIENCES↗

Globally distributed Myxococcota with photosynthesis gene clusters illuminate the origin and evolution of a potentially chimeric lifestyle

Photosynthesis is a fundamental biogeochemical process, thought to be restricted to a few bacterial and eukaryotic phyla. However, understanding the origin and evolution of phototrophic organisms can be impeded and biased by the difficulties of cultivation. Here, we analyzed metagenomic datasets and found potential photosynthetic abilities encoded in the genomes of uncultivated bacteria within the phylum Myxococcota. A putative photosynthesis gene cluster encoding a type-II reaction center appears in at least six Myxococcota families from three classes, suggesting vertical inheritance of these genes from an early common ancestor, with multiple independent losses in other lineages. Analysis of metatranscriptomic datasets indicate that the putative myxococcotal photosynthesis genes are actively expressed in various natural environments. Furthermore, heterologous expression of myxococcotal pigment biosynthesis genes in a purple bacterium supports that the genes can drive photosynthetic processes. Given that predatory abilities are thought to be widespread across Myxococcota, our results suggest the intriguing possibility of a chimeric lifestyle (combining predatory and photosynthetic abilities) in members of this phylum.

59 BASIC BIOLOGICAL SCIENCES↗

Increased photosynthesis during spring drought in energy-limited ecosystems

Abstract Drought is often thought to reduce ecosystem photosynthesis. However, theory suggests there is potential for increased photosynthesis during meteorological drought, especially in energy-limited ecosystems. Here, we examine the response of photosynthesis (gross primary productivity, GPP) to meteorological drought across the water-energy limitation spectrum. We find a consistent increase in eddy covariance GPP during spring drought in energy-limited ecosystems (83% of the energy-limited sites). Half of spring GPP sensitivity to precipitation was predicted solely from the wetness index (R 2 = 0.47, p < 0.001), with weaker relationships in summer and fall. Our results suggest GPP increases during spring drought for 55% of vegetated Northern Hemisphere lands ( >30° N). We then compare these results to terrestrial biosphere model outputs and remote sensing products. In contrast to trends detected in eddy covariance data, model mean GPP always declined under spring precipitation deficits after controlling for air temperature and light availability. While remote sensing products captured the observed negative spring GPP sensitivity in energy-limited ecosystems, terrestrial biosphere models proved insufficiently sensitive to spring precipitation deficits.

54 ENVIRONMENTAL SCIENCES↗

Mechanical Regulation of Photosynthesis in Cyanobacteria

Photosynthetic organisms regulate their responses to many diverse stimuli in an effort to balance light harvesting with utilizable light energy for carbon fixation and growth (source–sink regulation). This balance is critical to prevent the formation of reactive oxygen species that can lead to cell death. However, investigating the molecular mechanisms that underlie the regulation of photosynthesis in cyanobacteria using ensemble-based measurements remains a challenge due to population heterogeneity. Here, to address this problem, we used long-term quantitative time-lapse fluorescence microscopy, transmission electron microscopy, mathematical modelling and genetic manipulation to visualize and analyse the growth and subcellular dynamics of individual wild-type and mutant cyanobacterial cells over multiple generations. We reveal that mechanical confinement of actively growing Synechococcus sp. PCC 7002 cells leads to the physical disassociation of phycobilisomes and energetic decoupling from the photosynthetic reaction centres. We suggest that the mechanical regulation of photosynthesis is a critical failsafe that prevents cell expansion when light and nutrients are plentiful, but when space is limiting. These results imply that cyanobacteria must convert a fraction of the available light energy into mechanical energy to overcome frictional forces in the environment, providing insight into the regulation of photosynthesis and how microorganisms navigate their physical environment.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

A hybrid inorganic–biological artificial photosynthesis system for energy-efficient food production

Artificial photosynthesis systems are proposed as an efficient alternative route to capture CO 2 to produce additional food for growing global demand. Here a two-step CO 2 electrolyser system was developed to produce a highly concentrated acetate stream with a 57% carbon selectivity (CO 2 to acetate), allowing its direct use for the heterotrophic cultivation of yeast, mushroom-producing fungus and a photosynthetic green alga, in the dark without inputs from biological photosynthesis. An evaluation of nine crop plants found that carbon from exogenously supplied acetate incorporates into biomass through major metabolic pathways. Coupling this approach to existing photovoltaic systems could increase solar-to-food energy conversion efficiency by about fourfold over biological photosynthesis, reducing the solar footprint required. This technology allows for a reimagination of how food can be produced in controlled environments.

59 BASIC BIOLOGICAL SCIENCES↗

A phytophotonic approach to enhanced photosynthesis

Photosynthesis is the dominant biotic carbon sink on earth and hence presents an opportunity for enhanced sequestration of CO 2 . If the average net carbon fixation efficiency of terrestrial plants could be increased by 3.3%, all anthropogenic CO 2 accumulating in the atmosphere could instead be reduced and incorporated into terrestrial biomass. Plants make inefficient use of the overly abundant sunlight available to them, a result of having evolved to be competitive and survive highly dynamic environmental conditions rather than maximize photosynthetic productivity. We explore herein a phytophotonic approach to enhanced photosynthesis, whereby sunlight is redistributed by means of luminescent or persistent luminescent (PersL) materials. Phytophotonics has potential at varied scales, ranging from photobioreactors to greenhouses all the way to crops in the field, the latter having the potential to impact planetary CO 2 levels. The approach is three-fold: a spectral redistribution to relieve high-light-stress at the top surface of leaves and increasingly drive photosynthesis deeper in leaves and canopies; a minute-scale temporal redistribution to bridge periods of intermittent shade and reduce shock associated with variable light conditions; and a multiple-hour temporal redistribution to shift a fraction of high-intensity midday lighting to evening hours. Based on simulations of photoluminescent materials and light quality experiments with a model algal system, it is shown that while lengthening daylight hours will require significant improvements in PersL materials, the other two approaches show more immediate promise. We demonstrate a means of concentrating PersL light from SrAl 2 O 4 :Eu,Dy, approaching levels needed to effectively bridge periods of natural shade, and outline the scientific questions and technical hurdles remaining to realize the benefits of the proposed spectral shift.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Photosynthesis Simulation Performance in ESMs with Machine Learning-Assisted Solvers

When simulating vegetation dynamics, photosynthesis accounts for a large fraction of the computational cost in most Earth System Models (ESMs). This is largely since photosynthesis is represented as a system of nonlinear equations, and the solution requires the use of an initial guess followed by many iterations of the numerical solver to obtain a solution. We use machine learning (ML) to replicate the response surface of the model’s numerical solver to improve the choice of initial guess, therefore requiring fewer iterations to obtain a final solution. We implemented this test on the leaf-level calculations as well as at the canopy scale, and for both we observed fewer iterations of the photosynthesis solver when a ML-based initial guess was implemented. The model tested here is the Energy Exascale Earth System Model - Land Model (ELM). The ML-based algorithms used here are trained on simulations from the model itself and used only to improve the initial guess for the solver; therefore, the model maintains its own set of physics to obtain the final solution. This work shows novel ways to utilize ML-based methods to improve the performance of numerical solvers in ESMs.

Massoud, Elias [ORNL] (ORCID:0000000217725361)↗

Limited thermal acclimation of photosynthesis in tropical montane tree species

Abstract The temperature sensitivity of physiological processes and growth of tropical trees remains a key uncertainty in predicting how tropical forests will adjust to future climates. In particular, our knowledge regarding warming responses of photosynthesis, and its underlying biochemical mechanisms, is very limited. We grew seedlings of two tropical montane rainforest tree species, the early‐successional species Harungana montana and the late‐successional species Syzygium guineense , at three different sites along an elevation gradient, differing by 6.8℃ in daytime ambient air temperature. Their physiological and growth performance was investigated at each site. The optimum temperature of net photosynthesis ( T optA ) did not significantly increase in warm‐grown trees in either species. Similarly, the thermal optima ( T optV and T optJ ) and activation energies ( E aV and E aJ ) of maximum Rubisco carboxylation capacity ( V cmax ) and maximum electron transport rate ( J max ) were largely unaffected by warming. However, V cmax , J max and foliar dark respiration ( R d ) at 25℃ were significantly reduced by warming in both species, and this decline was partly associated with concomitant reduction in total leaf nitrogen content. The ratio of J max / V cmax decreased with increasing leaf temperature for both species, but the ratio at 25℃ was constant across sites. Furthermore, in H . montana , stomatal conductance at 25℃ remained constant across the different temperature treatments, while in S . guineense it increased with warming. Total dry biomass increased with warming in H . montana but remained constant in S . guineense . The biomass allocated to roots, stem and leaves was not affected by warming in H . montana , whereas the biomass allocated to roots significantly increased in S . guineense . Overall, our findings show that in these two tropical montane rainforest tree species, the capacity to acclimate the thermal optimum of photosynthesis is limited while warming‐induced reductions in respiration and photosynthetic capacity rates are tightly coupled and linked to responses of leaf nitrogen.

54 ENVIRONMENTAL SCIENCES↗

New calculations for photosynthesis measurement systems: what’s the impact for physiologists and modelers?

Measurement of carbon dioxide (CO 2 ) and water vapor (H 2 O) exchanged by leaves has been tremendously important for advancing understanding of plant physiology. Typically, photosynthesis measurement systems estimate the concentration of CO 2 and H 2 O in air that has passed over a leaf inside a leaf chamber. Together with additional information such as flow rate, leaf area, and measurement of environmental variables, the calculations of von Caemmerer & Farquhar (1981), hereafter vCF1981, are used to estimate CO 2 and H 2 O fluxes between the leaf and atmosphere. Furthermore, the combination of the vCF1981 calculations and photosynthesis measurement systems has enabled significant advances in the understanding and model representation of leaf-level photosynthesis and respiration.

54 ENVIRONMENTAL SCIENCES↗

Amazon rainforest photosynthesis increases in response to atmospheric dryness

Earth system models predict that increases in atmospheric and soil dryness will reduce photosynthesis in the Amazon rainforest, with large implications for the global carbon cycle. Using in situ observations, solar-induced fluorescence, and nonlinear machine learning techniques, we show that, in reality, this is not necessarily the case: In many of the wettest parts of this region, photosynthesis and biomass tend to increase with increased atmospheric dryness, despite the associated reductions in canopy conductance to CO 2 . These results can be largely explained by changes in canopy properties, specifically, new leaves flushed during the dry season have higher photosynthetic capacity than the leaves they replace, compensating for the negative stomatal response to increased dryness. As atmospheric dryness will increase with climate change, our study highlights the importance of reframing how we represent the response of ecosystem photosynthesis to atmospheric dryness in very wet regions, to accurately quantify the land carbon sink.

54 ENVIRONMENTAL SCIENCES↗