Eco-physiology and environmental impacts of newly developed rice genotypes for improved yield and nitrogen use efficiency coordinately

Significant advancements have been made in understanding the genetic regulation of nitrogen use efficiency (NUE) and identifying crucial NUE genes in rice. However, the development of rice genotypes that simultaneously exhibit high yield and NUE has lagged behind these theoretical advancements. The grain yield, NUE, and greenhouse gas (GHG) emissions of newly-bred rice genotypes under reduced nitrogen application remain largely unknown. To address this knowledge gap, field experiments were conducted, involving 80 indica (14 to 19 rice genotypes each year in Wuxue, Hubei) and 12 japonica (8 to 12 rice genotypes each year in Yangzhou, Jiangsu). Yield, NUE, agronomy, and soil parameters were assessed, and climate data were recorded. The experiments aimed to assess genotypic variations in yield and NUE among these genotypes and to investigate the eco-physiological basis and environmental impacts of coordinating high yield and high NUE. The results showed significant variations in yield and NUE among the genotypes, with 47 genotypes classified as moderate-high yield with high NUE (MHY_HNUE). These genotypes demonstrated the higher yields and NUE levels, with 9.6 t ha-1, 54.4 kg kg-1, 108.1 kg kg-1, and 64 % for yield, NUE for grain and biomass production, and N harvest index, respectively. Nitrogen uptake and tissue concentration were key drivers of the relationship between yield and NUE, particularly N uptake at heading and N concentrations in both straw and grain at maturity. Increase in pre-anthesis temperature consistently lowered yield and NUE. Genotypes within the MHY_HNUE group exhibited higher methane emissions but lower nitrous oxide emissions compared to those in the low to middle yield and NUE group, resulting in a 12.8 % reduction in the yield-scaled greenhouse gas balance. In conclusion, prioritizing crop breeding efforts on yield and resource use efficiency, as well as developing genotypes resilient to high temperatures with lower GHGs, can mitigate planetary warming.

Subsurface fertilization boosts crop yields and lowers greenhouse gas emissions: A global meta-analysis

The subsurface application (SA) of nitrogenous fertilizers is a potential solution to mitigate climate change and improve food security. However, the impacts of SA technology on greenhouse gas (GHG) emissions and agronomic yield are usually evaluated separately and their results are inconsistent. To address this gap, we conducted a meta-analysis synthesizing 40 peer-reviewed studies on the effects of SA technology on GHG and ammonia (NH₃) emissions, nitrogen uptake (NU), crop yield, and soil residual NO₃-N in rice paddies and upland cropping system. Compared to the surface application of N, SA technology significantly increased rice yields by 32 % and crop yield in upland systems by 62 %. The largest SA-induced increases in crop yield were found at low N input rates (<100 kg Nha^-1) in rice paddies and medium N input rates (100-200 kg Nha^-1) in upland systems, suggesting that soil moisture is a key factor determining the efficiency of SA technology. SA treatments increased yields by more at reduced fertilizer rates (~30 % less N), a shallow depth (<10 cm), and with urea in both cropping systems than at the full (recommended) N rate, a deeper depth (10-20 cm), and with ammonical fertilizer. SA treatments significantly increased NU in rice paddies (34 %) and upland systems (18 %), and NO₃-N (40 %) in paddyland; however, NO₃-N decreased (28 %) in upland conditions. Ammonia mitigation was greater in paddyland than in upland conditions. SA technology decreased the carbon footprint (CF) in paddyland by 29 % and upland systems by 36 %, and overall by 33 %. Compared with broadcasting, SA significantly reduced CH₄ emissions by 16 %, N₂O emissions by 30 %, and global warming potential (GWP) by 10 % in paddy cultivation. Given SA increased grain yield and NU while reducing NH₃, CF, and GWP, this practice provides dual benefits - mitigating climate change and ensuring food security.

Revisiting the growth rate hypothesis: Towards a holistic stoichiometric understanding of growth

The growth rate hypothesis (GRH) posits that variation in organismal stoichiometry (C:P and N:P ratios) is driven by growth-dependent allocation of P to ribosomal RNA. The GRH has found broad but not uniform support in studies across diverse biota and habitats. We synthesise information on how and why the tripartite growth-RNA-P relationship predicted by the GRH may be uncoupled and outline paths for both theoretical and empirical work needed to broaden the working domain of the GRH. We found strong support for growth to RNA (r²  = 0.59) and RNA-P to P (r²  = 0.63) relationships across taxa, but growth to P relationships were relatively weaker (r²  = 0.09). Together, the GRH was supported in ~50% of studies. Mechanisms behind GRH uncoupling were diverse but could generally be attributed to physiological (P accumulation in non-RNA pools, inactive ribosomes, translation elongation rates and protein turnover rates), ecological (limitation by resources other than P), and evolutionary (adaptation to different nutrient supply regimes) causes. These factors should be accounted for in empirical tests of the GRH and formalised mathematically to facilitate a predictive understanding of growth.

Dynamics and growth rate implications of ribosomes and mRNAs interaction in E. coli

Understanding how cells grow and adapt under various nutrient conditions is pivotal in the study of biological stoichiometry. Recent studies provide empirical evidence that cells use multiple strategies to maintain an optimal protein production rate under different nutrient conditions. Mathematical models can provide a solid theoretical foundation that can explain experimental observations and generate testable hypotheses to further our understanding of the growth process. In this study, we generalize a modeling framework that centers on the translation process and study its asymptotic behaviors to validate algebraic manipulations involving the steady states. Using experimental results on the growth of E. coli under C-, N-, and P-limited environments, we simulate the expected quantitative measurements to show the feasibility of using the model to explain empirical evidence. Our results support the findings that cells employ multiple strategies to maintain a similar protein production rate across different nutrient limitations. Moreover, we find that the previous study underestimates the significance of certain biological rates, such as the binding rate of ribosomes to mRNA and the transition rate between different ribosomal stages. Furthermore, our simulation shows that the strategies used by cells under C- and P-limitations result in a faster overall growth dynamics than under N-limitation. In conclusion, the general modeling framework provides a valuable platform to study cell growth under different nutrient supply conditions, which also allows straightforward extensions to the coupling of transcription, translation, and energetics to deepen our understanding of the growth process.

Improving the accuracy of meta-analysis for datasets with missing measures of variance: Elevated [CO2] effect on plant growth as a case study

Ongoing increases in atmospheric carbon dioxide (CO₂) are expected to stimulate biomass and yield of plants possessing the C3 photosynthetic pathway; however, the extent of stimulation is likely to vary both intra- and inter-species specifically. Meta-analytic approaches can be applied to decrease variation and uncertainty by delineating and characterizing variation, allowing results to be used in modeling plant responses to elevated [CO₂]. However, the use of meta-analysis in this effort could be limited by missing measures of variance, including standard deviations (SDs) of the compiled dataset. Here, we examined whether there were differences in effect sizes of elevated [CO₂] on plant growth using various weighting and imputation approaches. Our results showed that the efficacy of different weighting functions and data interpolation methods on meta-analysis outcomes depended on the SDs provided by the studies. Comparing different methodologies for [CO₂] fumigation as a case study, if the ratio of missing SD was low, the overall trend of effect values and 95% confidence interval (CI) were not changed. For datasets of greenhouse and growth chamber [CO₂] methodologies, which had a high ratio of missing SDs, effect sizes and 95% confidence intervals using different weighing and imputation methods were influenced relative to that of the raw dataset, with reduced effect sizes and broader CI. Overall these results suggest that application of meta-analysis to discern general biological responses could be influenced by the number of missing SDs. As such, efforts should be made to check the proportion of missing SDs of the compiled dataset and if necessary, to apply various weighting functions and imputation methods to fully discern meta-analysis implications. Our findings could improve the assessment of methodological choices for future [CO₂] experimentation and discerning long-term trends for agricultural productivity and food security.

Climate Change, Crop Yields, and Grain Quality of C3 Cereals: A Meta-Analysis of [CO2], Temperature, and Drought Effects

Cereal yield and grain quality may be impaired by environmental factors associated with climate change. Major factors, including elevated CO2 concentration ([CO2]), elevated temperature, and drought stress, have been identified as affecting C3 crop production and quality. A meta-analysis of existing literature was performed to study the impact of these three environmental factors on the yield and nutritional traits of C3 cereals. Elevated [CO2] stimulates grain production (through larger grain numbers) and starch accumulation but negatively affects nutritional traits such as protein and mineral content. In contrast to [CO2], increased temperature and drought cause significant grain yield loss, with stronger effects observed from the latter. Elevated temperature decreases grain yield by decreasing the thousand grain weight (TGW). Nutritional quality is also negatively influenced by the changing climate, which will impact human health. Similar to drought, heat stress decreases starch content but increases grain protein and mineral concentrations. Despite the positive effect of elevated [CO2], increases to grain yield seem to be counterbalanced by heat and drought stress. Regarding grain nutritional value and within the three environmental factors, the increase in [CO2] is possibly the more detrimental to face because it will affect cereal quality independently of the region.

Climate Change, Crop Yields, and Grain Quality of C3 Cereals: A Meta-Analysis of [CO2], Temperature, and Drought Effects

Cereal yield and grain quality may be impaired by environmental factors associated with climate change. Major factors, including elevated CO₂ concentration ([CO₂]), elevated temperature, and drought stress, have been identified as affecting C₃ crop production and quality. A meta-analysis of existing literature was performed to study the impact of these three environmental factors on the yield and nutritional traits of C₃ cereals. Elevated [CO₂] stimulates grain production (through larger grain numbers) and starch accumulation but negatively affects nutritional traits such as protein and mineral content. In contrast to [CO₂], increased temperature and drought cause significant grain yield loss, with stronger effects observed from the latter. Elevated temperature decreases grain yield by decreasing the thousand grain weight (TGW). Nutritional quality is also negatively influenced by the changing climate, which will impact human health. Similar to drought, heat stress decreases starch content but increases grain protein and mineral concentrations. Despite the positive effect of elevated [CO₂], increases to grain yield seem to be counterbalanced by heat and drought stress. Regarding grain nutritional value and within the three environmental factors, the increase in [CO₂] is possibly the more detrimental to face because it will affect cereal quality independently of the region.

Elevated CO2 affects kelp nutrient quality: A case study of Saccharina japonica from CO2 -enriched coastal mesocosm systems

Kelps provide critical services for coastal food chains and ecosystem, and they are important food source for some segments of human population. Despite their ecological importance, little is known about long-term impacts of elevated CO2 (eCO2 ) on nutrient metabolites in kelps and the underlying regulation mechanisms. In this study, the kelp Saccharina japonica was cultured in CO2 -enriched coastal mesocosm systems for up to 3 months. We found that, although eCO2 significantly increased the growth rate, carbon concentrations, and C/N ratio of S. japonica, and it had no effect on total nitrogen and protein contents at the end of cultivation period. Meanwhile, it decreased the lipid, magnesium, sodium, and calcium content and changed the amino acid and fatty acid composition. Combining the genome-wide transcriptomic and metabolic evidence, we obtained a system-level understanding of metabolic response of S. japonica to eCO2 . The unique ornithine-urea cycle (OUC) and aspartate-argininosuccinate shunt (AAS), coupled with TCA cycle, balanced the carbon and nitrogen metabolism under eCO2 by providing carbon skeleton for amino acid synthesis and reduced power for nitrogen assimilation. This research provides a major advance in the understanding of kelp nutrient metabolic mechanism in the context of global climate change, and such CO2 -induced shifts in nutritional value may induce changes in the structure and stability of marine trophic webs and affect the quality of human nutrition resources.

Iterative chemostat: A modelling framework linking biosynthesis to nutrient cycling on ecological and evolutionary time scales

In the classical chemostat, the output of the system has no effect on its input. This contrasts with many ecological systems, where the output at the end of a growing season affects nutrient inputs for subsequent seasons. Here, an iterative-continuous modelling framework is introduced that retains the structure of classical ecological models within each iteration but accounts for nutrient feedbacks between iterations. As an example, the framework is applied to the classical chemostat model, where nutrient outputs affect the supply ratio at each iteration. Furthermore, the biotic parameters in the model, including organismal demands for nitrogen (N) and phosphorus (P), are linked to core biogenic processes-protein and rRNA synthesis. This biosynthesis is further deconstructed into 11 biological constants and rates, most of which are deeply shared among all organisms. By linking the fundamental macromolecular machinery to the cycling of nutrients on the ecosystem scale, the framework enables to rigorously formulate qualitative and quantitative questions about the evolution of nutrient ratios and the existence of stoichiometric attractors, such as the puzzling persistence of the Redfield N:P ratio of 16 in the ocean. While the framework presented here is theoretical, it readily permits setting up empirical experiments for testing its predictions.

Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries

Declines of protein and minerals essential for humans, including iron and zinc, have been reported for crops in response to rising atmospheric carbon dioxide concentration, [CO₂]. For the current century, estimates of the potential human health impact of these declines range from 138 million to 1.4 billion, depending on the nutrient. However, changes in plant-based vitamin content in response to [CO₂] have not been elucidated. Inclusion of vitamin information would substantially improve estimates of health risks. Among crop species, rice is the primary food source for more than 2 billion people. We used multiyear, multilocation in situ FACE (free-air CO₂ enrichment) experiments for 18 genetically diverse rice lines, including Japonica, Indica, and hybrids currently grown throughout Asia. We report for the first time the integrated nutritional impact of those changes (protein, micronutrients, and vitamins) for the 10 countries that consume the most rice as part of their daily caloric supply. Whereas our results confirm the declines in protein, iron, and zinc, we also find consistent declines in vitamins B1, B2, B5, and B9 and, conversely, an increase in vitamin E. A strong correlation between the impacts of elevated [CO₂] on vitamin content based on the molecular fraction of nitrogen within the vitamin was observed. Finally, potential health risks associated with anticipated CO₂-induced deficits of protein, minerals, and vitamins in rice were correlated to the lowest overall gross domestic product per capita for the highest rice-consuming countries, suggesting potential consequences for a global population of approximately 600 million.

Rising atmospheric CO2 is reducing the protein concentration of a floral pollen source essential for North American bees

At present, there is substantive evidence that the nutritional content of agriculturally important food crops will decrease in response to rising levels of atmospheric carbon dioxide, Ca However, whether Ca-induced declines in nutritional quality are also occurring for pollinator food sources is unknown. Flowering late in the season, goldenrod (Solidago spp.) pollen is a widely available autumnal food source commonly acknowledged by apiarists to be essential to native bee (e.g. Bombus spp.) and honeybee (Apis mellifera) health and winter survival. Using floral collections obtained from the Smithsonian Natural History Museum, we quantified Ca-induced temporal changes in pollen protein concentration of Canada goldenrod (Solidago canadensis), the most wide spread Solidago taxon, from hundreds of samples collected throughout the USA and southern Canada over the period 1842-2014 (i.e. a Ca from approx. 280 to 398 ppm). In addition, we conducted a 2 year in situtrial of S. Canadensis populations grown along a continuous Ca gradient from approximately 280 to 500 ppm. The historical data indicated a strong significant correlation between recent increases in Ca and reductions in pollen protein concentration (r(2)= 0.81). Experimental data confirmed this decrease in pollen protein concentration, and indicated that it would be ongoing as Ca continues to rise in the near term, i.e. to 500 ppm (r(2)= 0.88). While additional data are needed to quantify the subsequent effects of reduced protein concentration for Canada goldenrod on bee health and population stability, these results are the first to indicate that increasing Ca can reduce protein content of a floral pollen source widely used by North American bees.

Hidden shift of the ionome of plants exposed to elevated CO₂depletes minerals at the base of human nutrition

Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C3 plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO2) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO2 on the ionome-the mineral and trace-element composition-of plants. Consequently, CO2-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO2 reduces the overall mineral concentrations (-8%, 95% confidence interval: -9.1 to -6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C3 plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of 'hidden hunger' and obesity is discussed.DOI: http://dx.doi.org/10.7554/eLife.02245.001.

Hidden shift of the ionome of plants exposed to elevated CO₂depletes minerals at the base of human nutrition

Mineral malnutrition stemming from undiversified plant-based diets is a top global challenge. In C3 plants (e.g., rice, wheat), elevated concentrations of atmospheric carbon dioxide (eCO2) reduce protein and nitrogen concentrations, and can increase the total non-structural carbohydrates (TNC; mainly starch, sugars). However, contradictory findings have obscured the effect of eCO2 on the ionome-the mineral and trace-element composition-of plants. Consequently, CO2-induced shifts in plant quality have been ignored in the estimation of the impact of global change on humans. This study shows that eCO2 reduces the overall mineral concentrations (-8%, 95% confidence interval: -9.1 to -6.9, p<0.00001) and increases TNC:minerals > carbon:minerals in C3 plants. The meta-analysis of 7761 observations, including 2264 observations at state of the art FACE centers, covers 130 species/cultivars. The attained statistical power reveals that the shift is systemic and global. Its potential to exacerbate the prevalence of 'hidden hunger' and obesity is discussed.DOI: http://dx.doi.org/10.7554/eLife.02245.001.

Dynamics of a mechanistically derived stoichiometric producer-grazer model

One of the simplest predator-prey models that tracks the quantity and the quality of prey is the one proposed by [I. Loladze, Y. Kuang, and J.J. Elser, Stoichiometry in producer-grazer systems: Linking energy flow with element cycling, Bull. Math. Biol. 62 (2000) pp. 1137-1162.] (LKE model). In it, the ratio of two essential chemical elements, carbon to phosphorus, C:P, represents prey quality. However, that model does not explicitly track P neither in the prey nor in the media that supports the prey. Here, we extend the LKE model by mechanistically deriving and accounting for P in both the prey and the media. Bifurcation diagrams and simulations show that our model behaves similarly to the LKE model. However, in the intermediate range of the carrying capacity, especially near the homoclinic bifurcation point for the carrying capacity, quantitative behaviour of our model is different. We analyze positive invariant region and stability of boundary steady states. We show that as the uptake rate of P by producer becomes infinite, LKE models become the limiting case of our model. Furthermore, our model can be readily extended to multiple producers and consumers.

Competitive coexistence in stoichiometric chaos

Classical predator-prey models, such as Lotka-Volterra, track the abundance of prey, but ignore its quality. Yet, in the past decade, some new and occasionally counterintuitive effects of prey quality on food web dynamics emerged from both experiments and mathematical modeling. The underpinning of this work is the theory of ecological stoichiometry that is centered on the fact that each organism is a mixture of multiple chemical elements such as carbon (C), nitrogen (N), and phosphorus (P). The ratios of these elements can vary within and among species, providing simple ways to represent prey quality as its C:N or C:P ratios. When these ratios modeled to vary, as they frequently do in nature, seemingly paradoxical results can arise such as the extinction of a predator that has an abundant and accessible prey. Here, for the first time, we show analytically that the reduction in prey quality can give rise to chaotic oscillations. In particular, when competing predators differ in their sensitivity to prey quality then all species can coexist via chaotic fluctuations. The chaos generating mechanism is based on the existence of a junction-fold point on the nullcline surfaces of the species. Conditions on parameters are found for such a point, and the singular perturbation method and the kneading sequence analysis are used to demonstrate the existence of a period-doubling cascade to chaos as a result of the point.

The dynamics of a stoichiometric plant-herbivore model and its discrete analog

Stoichiometry-based models brought into sharp focus the importance of the nutritional quality of plant for herbivore-plant dynamics. Plant quality can dramatically affect the growth rate of the herbivores and may even lead to its extinction. These results stem from models continuous in time, which raises the question of how robust they are to time discretization. Discrete time can be more appropriate for herbivores with non-overlapping generations, annual plants, and experimental data collected periodically. We analyze a continuous stoichiometric plant-herbivore model that is mechanistically formulated. We then introduce its discrete analog and compare the dynamics of the continuous and discrete models. This discrete model includes the discrete LKE model (Loladze, Kuang and Elser (2000)) as a limiting case.

Competition and stoichiometry: coexistence of two predators on one prey

The competitive exclusion principle (CEP) states that no equilibrium is possible if n species exploit fewer than n resources. This principle does not appear to hold in nature, where high biodiversity is commonly observed, even in seemingly homogenous habitats. Although various mechanisms, such as spatial heterogeneity or chaotic fluctuations, have been proposed to explain this coexistence, none of them invalidates this principle. Here we evaluate whether principles of ecological stoichiometry can contribute to the stable maintenance of biodiverse communities. Stoichiometric analysis recognizes that each organism is a mixture of multiple chemical elements such as carbon (C), nitrogen (N), and phosphorus (P) that are present in various proportions in organisms. We incorporate these principles into a standard predator-prey model to analyze competition between two predators on one autotrophic prey. The model tracks two essential elements, C and P, in each species. We show that a stable equilibrium is possible with two predators on this single prey. At this equilibrium both predators can be limited by the P content of the prey. The analysis suggests that chemical heterogeneity within and among species provides new mechanisms that can support species coexistence and that may be important in maintaining biodiversity.

Biodiversity, habitat area, resource growth rate and interference competition

For the majority of species, per capita growth rate correlates negatively with population density. Although the popular logistic equation for the growth of a single species incorporates this intraspecific competition, multi-trophic models often ignore self-limitation of the consumers. Instead, these models often assume that the predator-prey interactions are purely exploitative, employing simple Lotka-Volterra forms in which consumer species lack intraspecific competition terms. Here we show that intraspecific interference competition can account for the stable coexistence of many consumer species on a single resource in a homogeneous environment. In addition, our work suggests a potential mechanism for field observations demonstrating that habitat area and resource productivity strongly positively correlate to biodiversity. In the special case of a modified Lotka-Volterra model describing multiple predators competing for a single resource, we present an ordering procedure that determines the deterministic fate of each specific consumer. Moreover, we find that the growth rate of a resource species is proportional to the maximum number of consumer species that resource can support. In the limiting case, when the resource growth rate is infinite, a model with intraspecific interference reduces to the conventional Lotka-Volterra competition model where there can be an unlimited number of coexisting consumers. This highlights the crucial role that resource growth rates may play in promoting coexistence of consumer species.

Stoichiometry in producer-grazer systems: linking energy flow with element cycling

All organisms are composed of multiple chemical elements such as carbon, nitrogen and phosphorus. While energy flow and element cycling are two fundamental and unifying principles in ecosystem theory, population models usually ignore the latter. Such models implicitly assume chemical homogeneity of all trophic levels by concentrating on a single constituent, generally an equivalent of energy. In this paper, we examine ramifications of an explicit assumption that both producer and grazer are composed of two essential elements: carbon and phosphorous. Using stoichiometric principles, we construct a two-dimensional Lotka-Volterra type model that incorporates chemical heterogeneity of the first two trophic levels of a food chain. The analysis shows that indirect competition between two populations for phosphorus can shift predator-prey interactions from a (+, -) type to an unusual (-, -) class. This leads to complex dynamics with multiple positive equilibria, where bistability and deterministic extinction of the grazer are possible. We derive simple graphical tests for the local stability of all equilibria and show that system dynamics are confined to a bounded region. Numerical simulations supported by qualitative analysis reveal that Rosenzweig's paradox of enrichment holds only in the part of the phase plane where the grazer is energy limited; a new phenomenon, the paradox of energy enrichment, arises in the other part, where the grazer is phosphorus limited. A bifurcation diagram shows that energy enrichment of producer-grazer systems differs radically from nutrient enrichment. Hence, expressing producer-grazer interactions in stoichiometrically realistic terms reveals qualitatively new dynamical behavior.