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Biochar-based controlled release nitrogen fertilizers (BCRNFs) have received increasing attention due to their ability to improve nitrogen-use efficiency (NUE) and increase crop yields. We previously developed a novel BCRNF, but its effects on soil microbes, NUE, and crop yields have not been reported. Therefore, we designed a pot experiment with five randomised treatments: CK (without urea and biochar), B (addition biochar without urea), B + U (biochar mixed urea), Urea (addition urea without biochar), and BCRNF (addition BCRNF), to investigate the effects of BCRNF on nitrifiers and denitrifiers, and how these impact nitrogen supply and NUE. Results of high-throughput sequencing revealed bacterial community groups with higher nutrient metabolic cycling ability under BCRNF treatment during harvest stage. Compared to Urea treatment, BCRNF treatment stimulated nitrification by increasing the copy number of the bacterial amoA gene and reducing nitrous oxide emission by limiting the abundance of nirS and nirK . Eventually, BCRNF successfully enhanced the yield (~ 16.6%) and NUE (~ 58.79%) of rape by slowly releasing N and modulating the abundance of functional microbes through increased soil nitrification and reduced denitrification, as compared with Urea treatment. BCRNF significantly improved soil NO 3 − , leading to an increase in N uptake by rape and NUE, thereby promoting rape growth and increasing grain yield.

Irrigated agriculture has important implications for achieving the United Nations Sustainable Development Goals. However, there is a lack of systematic and quantitative analyses of its impacts on food–energy–water–CO 2 nexus. Here we studied impacts of irrigated agriculture on food–energy–water–CO 2 nexus across food sending systems (the North China Plain (NCP)), food receiving systems (the rest of China) and spillover systems (Hubei Province, affected by interactions between sending and receiving systems), using life cycle assessment, model scenarios, and the framework of metacoupling (socioeconomic-environmental interactions within and across borders). Results indicated that food supply from the NCP promoted food sustainability in the rest of China, but the NCP consumed over four times more water than its total annual renewable water, with large variations in food–energy–water–CO 2 nexus across counties. Although Hubei Province was seldom directly involved in the food trade, it experienced substantial losses in water and land due to the construction of the South-to-North Water Transfer Project which aims to alleviate water shortages in the NCP. This study suggests the need to understand impacts of agriculture on food–energy–water–CO 2 nexus in other parts of the world to achieve global sustainability. Local human activities can lead to cross-border environmental impacts through the food–energy–water–CO 2 nexus. Here, the authors report wide variations in environmental impacts of irrigated agriculture across counties within the North China Plain under different environmental and socioeconomic scenarios.

Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development. The paper reveals areas of common and differentiated SDG priority at the national and subnational levels in China considering synergy and trade-off. The findings suggest that provincial governments should formulate more targeted policy aligning with national priority to achieve SDGs.

Research results on the effects of land cover change on water resources vary greatly and the topic remains controversial. Here we use published data worldwide to examine the validity of Fuh’s equation, which relates annual water yield ( R ) to a wetness index (precipitation/potential evapotranspiration; P / PET ) and watershed characteristics ( m ). We identify two critical values at P / PET =1 and m =2. m plays a more important role than P / PET when m <2, and a lesser role when m >2. When P / PET <1, the relative water yield ( R / P ) is more responsive to changes in m than it is when P / PET >1, suggesting that any land cover changes in non-humid regions ( P / PET <1) or in watersheds of low water retention capacity ( m <2) can lead to greater hydrological responses. m significantly correlates with forest coverage, watershed slope and watershed area. This global pattern has far-reaching significance in studying and managing hydrological responses to land cover and climate changes. The effects of forests on water yield are uncertain, with some studies indicating that increased evapotranspiration reduces water yield and other showing that forests increase it. Here, the authors analyse published data to settle this debate, finding that afforestation has a positive effect on water yield.

The 2015/16 El Niño brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ. γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data—RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ (γ ≥ 0.3) appear to have a stronger capacity to recover than low-γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.

Human economic activities drive the production and consumption of goods and services, contribute to the achievement of the United Nations Sustainable Development Goals (SDGs). However, the extent of economic growth’s influence on the SDGs remains unclear. To fill this knowledge gap, here, we quantified the environmental effects of economic activities and explored correlations between environmental effect and achieving SDGs. We developed six Environmental Footprint Indices, with a higher score indicating better efficiency or lower burden. Here we show that the various Environmental Footprint Indices had synergistic and trade-off effects on most SDG targets indices, but the synergistic effects prevailed. As income increased, the correlation between Environmental Footprint Indices and SDG target indices gradually strengthened. improved production efficiency and consumption changes notably advance SDGs, especially in low-income group countries. Our work provides scientific insights into the impact and prospects of environmental regulation required for achieving the SDGs by 2030. Economic development and its interactions with the SDGs is an important focus for sustainable future growth. This paper develops six environmental footprint indices highlighting the synergies with human production and the SDG targets.

Global agricultural trade creates multiple telecoupled flows of nitrogen (N) and phosphorus (P). The flows of physical and virtual nutrients along with trade have discrepant effects on natural resources in different countries. However, existing literature has not quantified or analyzed such effects yet. Here we quantified the physical and virtual N and P flows embedded in the global agricultural trade networks from 1997 to 2016 and elaborated components of the telecoupling framework. The N and P flows both increased continuously and more than 25% of global consumption of nutrients in agricultural products were related to physical nutrient flows, while virtual nutrient flows were equivalent to one-third of the nutrients inputs into global agricultural system. These flows have positive telecoupling effects on saving N and P resources at the global scale. Reducing inefficient trade flows will enhance resource conservation, environmental sustainability in the hyper-globalized world. This study identifies the flows of physical and virtual nutrients (N and P) within the global agricultural trade network by trade tracing, and explores strategies to improve global nutrient use efficiency using the telecoupling framework.

Carbon and water fluxes are key properties of ecosystem processes and functions. A better understanding of their temporal dynamics and coupling mechanism between these fluxes will help us improve ecosystem management for mitigation as well as adaption to future climatic change. From 2003 to 2009, carbon and water flux data were obtained by the eddy covariance method over an old-growth forest in the lower subtropical China. The 7 years of observational data indicated that the water-use efficiency (WUE) of the old-growth forest exhibited weak inter-annual variability. The mean annual WUE ranged from 1.70 to 1.98 g C kg −1 H 2 O. An analysis of the effects of environmental variables on the monthly gross primary productivity (GPP) and evapotranspiration (ET) indicated that solar radiation, air temperature, precipitation and vapor pressure deficit (VPD) produced similar effects on the monthly GPP and ET, which suggests that photosynthesis and ET were similarly driven by the climatic variables. At the monthly scale, the WUE decreased significantly as the precipitation and soil moisture content increased. However, a significant correlation was not detected between the WUE and the VPD at the monthly scale. Moisture conditions tend to be major drivers of the ecosystem WUE.

As vegetation plays a critical role in terrestrial ecosystems, understanding its status and variation is vital for preserving the stability of an ecosystem. Central Asia serves as a representative example of an arid and semi-arid region characterized by sparse vegetation and poor soils, making its vegetation particularly fragile and sensitive. To investigate the vegetation condition in the region, this study examined the spatial and temporal characteristics of vegetation variation from 2001 to 2020, utilizing the normalized difference vegetation index (NDVI) as an indicator. Meanwhile, trend analysis, Mann–Kendall abrupt change point test, geodetector, and correlation analysis were used to quantitatively analyze the natural and anthropogenic drivers of these variations over the past two decades. The results suggest that vegetation coverage in Central Asia was relatively low, with an annual average NDVI of 0.16 over the past 20 years. Moreover, the spatial distribution of NDVI in Central Asia exhibited significant spatial heterogeneity, with vegetation coverage declining from north to south and from east to west. Furthermore, the NDVI exhibited a slightly increasing trend during the period of 2001 to 2020 with an increased rate of 0.00025/yr. However, we detected an abrupt change point in vegetation dynamics in Central Asia around 2010, which indicated a significant shift in vegetation variation in the region. Land-use type has a great influence on the spatial heterogeneity of NDVI in Central Asia, which can explain 46% of the vegetation distribution in this region. Moisture factors such as precipitation and soil water content followed with 35% and 32% contributions, respectively. Regarding the temporal variation of NDVI, it is mainly driven by the fluctuation in precipitation, with the degree of influence of precipitation on NDVI varying for different regions in various geographical conditions. This study offers a more comprehensive insight into the spatial and temporal dynamics of NDVI in Central Asia and indicates that precipitation plays a significant role in driving the spatial heterogeneity and temporal variation of NDVI. These findings are essential for predicting vegetation changes in arid regions under future environmental conditions and formulating effective strategies to prevent and alleviate vegetation degradation.