Climate change unequally affects nitrogen use and losses in global croplands

Limited improvement of crop nitrogen management sustainability through optimal crop distributions in drylands

Efficient nitrogen (N) management is essential for sustainable global food production. Although optimal crop distributions are recognized as potential adaptive strategies to offset the adverse effects of climate change, their effectiveness in improving regional crop N management sustainability is still uncertain. Here, we quantified spatiotemporal trends of the sustainable N management index (SNMI) for optimal crop distributions (determined by maximum crop suitability per grid) in the Hexi Corridor drylands in Northwest China since the 1960s, using crop yields and N use efficiency (NUE) simulated by a process-based regional crop model (pDSSAT). We also reduced the uncertainties of model parameters and climate scenarios in yield simulations through field water-nitrogen experiments for six crops (maize, wheat, potato, rapeseed, cotton, and alfalfa) and emergent-constraint approach, respectively. Analysis of SNMI shows an upward trend over the past 60 years, but future 20 years find a significant decline. Our findings indicate a 4-29% reduction in uncertainty using constrained crop yields versus regional average yields, which improve the sustainability of crop N management in optimal crop distributions with a lower SNMI. Future climate scenarios would further intensify crop yield loss, but optimal crop distributions will decline regional crop yield by 2%, increase NUE by 10%, and decrease SNMI by 13% compared to the 2011-2020. These results demonstrate a limited improvement of optimal crop distributions on historical SNMI, whereas their effectiveness is supported in future climate conditions-a result of a noticeable enhancement in NUE that compensates the detrimental impacts of yield reduction. Therefore, we recommend revisiting more adaptive strategies alongside optimal crop distributions for consistently improve the sustainability of crop N management.

Adaptive Mitigation of Warming-Induced Food Crisis and Nitrogen Pollution

Feeding the world's population in the face of global warming is a challenging task. Warming poses a dual threat to both global food security and nitrogen pollution in croplands. However, a consensus remains elusive regarding the precise impact of warming on the nitrogen cycle in global croplands. Our study revealed that warming alone could reduce grain yields by 21% (with a 95% confidence interval of 15-27%) while increasing nitrogen losses to the environment by 54-169%. Under the 2050 warming scenario, the annual global nitrogen harvest is projected to decrease by 16 million tonnes (Tg), accompanied by an increase in nitrogen surplus (nitrogen lost to the environment) of 29 Tg relative to the baseline. Implementation of timely and robust adaptive mitigation strategies, including optimization of planting dates, cultivars, irrigation, and fertilization practices, could mitigate the warming-induced food crisis and nitrogen pollution, averting potential losses of US$ 530 billion at an estimated cost of US$ 73 billion.

Influence of precipitation and temperature variability on anthropogenic nutrient inputs in a river watershed: Implications for environmental management

Since the Industrial Revolution, anthropogenic activities have substantially increased the input of nitrogen (N) and phosphorus (P) into river watersheds, exacerbated by uncertainties stemming from climate change. This study provided a detailed analysis of N and P inputs within the Dawen River Watershed in China from 2000 to 2021. The Net Anthropogenic Nitrogen Input (NANI) and Net Anthropogenic Phosphorus Input (NAPI) methods were used in study, which aimed to investigate how they respond to various climate change factors. Our findings reveal a generally decreasing trend in NANI, with an average of 17,882.34 kg/km2/yr. NAPI showed an initially increasing and then decreasing trend, with an average value of 5151.79 kg/km2/yr. Fertilizer usage emerged as the primary sources of nutrient inputs, accounting for approximately 63.42% of N and 61.88% of P inputs. Precipitation positively impacted the NANI and NAPI while temperature exerted more influential but opposing effects. Lag effects were evident as demonstrated by the stronger impacts of temperature in preceding year on NANI and NAPI. Moreover, climate not only influenced the quantity of NANI and NAPI but also impacted their changes, as well as the inputs of their components. Through quantitative analyses, we unveiled key thresholds in the correlation between nutrient inputs and climate variables, with cutoffs of 14.1 °C in temperature and 820 mm in precipitation. Our study highlights the complex relationships between anthropogenic nutrient inputs and climate change, and identifies critical climate thresholds that underscore the importance of sustainable management practices in the Dawen River Watershed to mitigate negative environmental impacts.

Integrated irrigation and nitrogen optimization is a resource-efficient adaptation strategy for US maize and soybean production

Climate change poses substantial challenges to agriculture and crop production, but the combined role of nitrogen and water inputs in adaptation has been largely overlooked. Here, by developing regression models using US county-level data (2008-2020), we demonstrate that integrated optimization of irrigation and nitrogen inputs represents the most resource-efficient strategy to offset the climate-related yield losses. Under the 1.5 °C (3 °C) warming scenario, this approach involves increasing irrigation water withdrawals for maize by 62% (67%) and reducing it for soybean by 65% (58%), while increasing nitrogen inputs for maize by 4% (13%) and for soybean by 10% (130%) annually. This strategy reduces unsustainable irrigation water withdrawals by 73% (56%) for maize and 26% (28%) for soybean, enhancing water sustainability. Cost-benefit analysis indicates this optimization is cost-effective for over 80% of US maize and soybean productions, underscoring its critical role for climate change adaptation.

Warm growing season activates microbial nutrient cycling to promote fertilizer nitrogen uptake by maize

The influence of nitrogen (N) inputs on soil microbial communities and N uptake by plants is well-documented. Seasonal variations further impact these microbial communities and their nutrient-cycling functions, particularly within multiple cropping systems. Nevertheless, the combined effects of N fertilization and growing seasons on soil microbial communities and plant N uptake remain ambiguous, thereby constraining our comprehension of the optimal growing season for maximizing crop production. In this study, we employed 15N isotope labeling, high-throughput sequencing, and quantitative polymerase chain reaction (qPCR) techniques to investigate the effects of two distinct growing seasons on microbial communities and maize 15N uptake ratios (15NUR). Our results showed that the warm growing season (26.6 °C) increased microbial diversity, reduced network complexity but enhanced stability, decreased microbial associations, and increased modularization compared to the cool growing season (23.1 °C). Additionally, the warm growing season favored oligotrophic species and increased the abundance of microbial guilds and functional genes related to N, phosphorus, and sulfur cycling. Furthermore, alterations in the characteristics of soil microbial keystone taxa were closely linked to variations in maize 15NUR. Overall, our findings demonstrate significant seasonal variations in soil microbial diversity and functioning, with maize exhibiting higher 15NUR during the warm growing season of the double cropping system.

Electrocatalytic nitrate reduction using iron single atoms for sustainable ammonium supplies to increase rice yield

Increasing food production and ensuring drinking water safety have always been a focus of attention, especially for people in underdeveloped regions of the world. Traditional excessive fertilizer applications have increased crop yield but also caused groundwater nitrate pollution. Agricultural irrigating water is an important reservoir for nitrogen (N) (e.g., nitrate) accumulation after fertilization. Ammonium (NH4+-N) is a more readily absorbed N form by rice than nitrate (NO3--N). In this study, we proposed a strategy using iron single-atom catalysts (Fe-SAC) to selectively reduce NO3--N to NH4+-N from the real paddy field irrigating water to provide sustainable NH4+-N supplies for rice uptakes, thereby highlighting decreasing N fertilizer applications and mitigating NO3--N pollution. Then, we constructed a solar-energy-driven electrochemical reactor for NO3--N reduction, with the Fe single atom as the core catalyst, and achieved an average NH4+-N selectivity of 80.2 ± 2.6% with no additional energy input. Sustainable NH4+-N supplies resulted in a 30.4 % increase in the 100-grain weight of the cultivated rice and a 50% decrease of fertilizer application than those of the fertilization group in the pot experiment, which were one of the best values ever reported. Furthermore, the 15N isotope tracing results indicated a N use efficiency (NUE) from 15NO3--N of 71.2 ± 3.2%. Sustainable NH4+-N supplies played a key role in promoting rice root development which contributed to the high NUE. Our study shares unique insights in increasing grain yield, reducing fertilizer applications, and preventing nitrate leaching into groundwater.

Sustainable food systems under environmental footprints: The delicate balance from farm to table

In today's world, agriculture is not only about food production but also a critical factor in global environmental change, economic stability, and human health, among other aspects. With population growth and increasingly scarce resources, exploring sustainable development of food systems has become crucial. Achieving this goal requires striking a delicate balance among food security, economic development, ecological environment, and human health. Traditional approaches to sustainable agricultural development research often focus solely on singular domains, overlooking the inherent connections and interactions among environmental, socioeconomic, and health dimensions. This perspective limits our comprehensive understanding of food systems. Environmental footprint assessments can be integrated with economic, systemic, and decision models to analyze environmental, socioeconomic, and health issues within food systems. This integration accurately captures the diversity, overlap, accumulation, and heterogeneity of environmental pressures resulting from human and natural factors. Therefore, we propose an innovative conceptual framework that considers environmental, socioeconomic, and health dimensions as crucial components, with the environmental footprint indicators at its core, to link various stages from farm to table. This framework constructs an evidence gap map, integrating dispersed data and perspectives from existing literature, thus showing knowledge gaps across these domains. Such an interdisciplinary approach not only provides a more comprehensive perspective on the multidimensional complexity of sustainable food systems but also reveals potential synergies and conflicts among environmental, socioeconomic, and health domains, thereby guiding more comprehensive and cautious policy-making. Importantly, it provides direction for future research to achieve the sustainable development of food systems, emphasizing the necessity of a comprehensive, integrated research perspective, particularly in strengthening studies on composited footprints, viewing the entire farm-to-table continuum holistically. Stakeholders must collaborate and coordinate environmental, socioeconomic, and health objectives to drive the sustainable development of food systems.

The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

Exploring soil nitrogen and sulfur dynamics: implications for greenhouse gas emissions on the Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau is particularly vulnerable to the effects of climate change and disturbances caused by human activity. To better understand the interactions between soil nitrogen and sulfur cycles and human activities on the plateau, the distribution characteristics of soil nitrogen and sulfur density and their influencing factors for three soil layers in Machin County at depths of 0-20 cm, 0-100 cm, and 0-180 cm are discussed in this paper. The results indicated that at depths of 0-180 cm, soil nitrogen density in Machin County varied between 1.36 and 16.85 kg/m2, while sulfur density ranged from 0.37 to 4.61 kg/m2. The effects of three factors-geological background, land use status, and soil type-on soil nitrogen and sulfur density were all highly significant (p < 0.01). Specifically, natural factors such as soil type and geological background, along with anthropogenic factors including land use practices and grazing intensity, were identified as decisive in causing spatial variations in soil nitrogen and sulfur density. Machin County on the Tibetan Plateau exhibits natural nitrogen and sulfur sinks; However, it is crucial to monitor the emissions of N2O and SO2 into the atmosphere from areas with high external nitrogen and sulfur inputs and low fertility retention capacities, such as bare land. On this basis, changes in the spatial and temporal scales of the nitrogen and sulfur cycles in soils and their source-sink relationships remain the focus of future research.

Fertilizer response to climate change: Evidence from corn production in China

Corn is the third most cultivated food crop in the world, and climate change has important effects on corn production and food security. China is the top user of chemical fertilizer in the world, and analyzing how to effectively manage fertilizer application in such a developing country with resource constraints is crucial. We present empirical evidence from China to demonstrate the nonlinear impact of temperature on fertilizer usage in corn production based on a panel dataset that shows 2297 corn-growing counties during 1998-2016. Our findings indicate that fertilizer usage barely changes with increasing temperatures that are below 28 °C; however, exposure to temperatures above 28 °C leads to a sharp increase in fertilizer use. The increase in temperatures in the sample period implies that fertilizer usage per hectare for corn increased by 1.5 kg. Summer corn fertilizer application in the Yellow-Huai River Valley is more sensitive to warming than in the North region. Moreover, nitrogen, phosphorus, and potassium fertilizers have different temperature thresholds of 32 °C, 20 °C, and 20 °C, respectively, that cause significant changes.

Nitrogen fertilization practices alter microbial communities driven by clonal integration in Moso bamboo

Nitrogen (N) fertilization is crucial for maintaining plant productivity. Clonal plants can share resources between connected ramets through clonal integration influencing microbial communities and regulating soil biogeochemical cycling, especially in the rhizosphere. However, the effect of various N fertilization practices on microbial communities in the rhizosphere of clonal ramets remain unknown. In this study, clonal fragments of Moso bamboo (Phyllostachys edulis), consisting of a parent ramet, an offspring ramet, and an interconnecting rhizome, were established in the field. NH4NO3 solution was applied to the parent, offspring ramets or rhizomes to investigate the effect of fertilization practices on the structure and function of rhizosphere microbial communities. The differences in N availability, microbial biomass and community composition, and abundance of nitrifying genes among rhizosphere soils of ramets gradually decreased during the rapid growth of Moso bamboo, irrespective of fertilization practice. The soil N availability variation, particularly in NO3-, caused by fertilization practices altered the rhizosphere microbial community. Soil N availability and stable microbial biomass N in parent fertilization were the highest, being 9.0 % and 18.7 %, as well as 60.8 % and 90.4 % higher than rhizome and offspring fertilizations, respectively. The microbial network nodes and links in rhizome fertilization were 1.8 and 7.5 times higher than in parent and offspring fertilization, respectively. However, the diversity of bacterial community and abundance of nitrifying and denitrifying genes were the highest in offspring fertilization among three practices, which may be associated with increased N loss. Collectively, the rhizosphere microbial community characteristics depended on fertilization practices by altering the clonal integration of N in Moso bamboo. Parent and rhizome fertilization were favorable for N retention in plant-soil system and resulted in more stable microbial functions than offspring fertilization. Our findings provide new insights into precision fertilization for the sustainable Moso bamboo forest management.

High resolution spatiotemporal modeling of long term anthropogenic nutrient discharge in China

High-resolution integration of large-scale and long-term anthropogenic nutrient discharge data is crucial for understanding the spatiotemporal evolution of pollution and identifying intervention points for pollution mitigation. Here, we establish the MEANS-ST1.0 dataset, which has a high spatiotemporal resolution and encompasses anthropogenic nutrient discharge data collected in China from 1980 to 2020. The dataset includes five components, namely, urban residential, rural residential, industrial, crop farming, and livestock farming, with a spatial resolution of 1 km and a temporal resolution of monthly. The data are available in three formats, namely, GeoTIFF, NetCDF and Excel, catering to GIS users, researchers and policymakers in various application scenarios, such as visualization and modelling. Additionally, rigorous quality control was performed on the dataset, and its reliability was confirmed through cross-scale validation and literature comparisons at the national and regional levels. These data offer valuable insights for further modelling the interactions between humans and the environment and the construction of a digital Earth.

Managing fragmented croplands for environmental and economic benefits in China

Cropland fragmentation contributes to low productivity and high abandonment risk. Using spatial statistics on a detailed land use map, we show that 10% of Chinese croplands have no potential to be consolidated for large-scale farming (>10 ha) owing to spatial constraints. These fragmented croplands contribute only 8% of total crop production while using 15% of nitrogen fertilizers, leading to 12% of fertilizer loss in China. Optimizing the cropping structure of fragmented croplands to meet animal food demand in China can increase animal food supply by 19%, equivalent to increasing cropland proportionally. This crop-switching approach would lead to a 10% and 101% reduction in nitrogen and greenhouse gas emissions, respectively, resulting in a net benefit of US$ 7 billion yr-1. If these fragmented croplands were relocated to generate large-scale farming units, livestock, vegetable and fruit production would be increased by 8%, 3% and 14%, respectively, and reactive nitrogen and greenhouse gas emissions would be reduced by 16% and 5%, respectively, resulting in a net benefit of US$ 44 billion yr-1. Both solutions could be used to achieve synergies between food security, economic benefits and environmental protection through increased agricultural productivity, without expanding the overall cropland area.

Temporal rich club phenomenon and its formation mechanisms

The temporal rich club (TRC) phenomenon is widespread in real systems, forming a tight and continuous collection of the prominent nodes that control the system. However, there is still a lack of sufficient understanding of the mechanisms of TRC formation. Here we use the international N-nutrient trade network as an example of an in-depth identification, analysis, and modeling of its TRC phenomenon. The system exhibits a statistically significant TRC phenomenon, with eight economies forming the cornerstone club. Our analysis reveals that node degree is the most influential factor in TRC formation compared to other variables. The mathematical evolution models we constructed propose that the TRC in the N-nutrient trade network arises from the coexistence of degree-homophily and path-dependence mechanisms. By comprehending these mechanisms, we introduce a different perspective on TRC formation. Although our analysis is limited to the international trade system, the methodology can be extended to analyze the mechanisms underlying TRC emergence in other systems.