摘要：
Biochar and organic fertilizer are widely supported to maintain crop production and sustainable development of agroecosystems. However, it is unclear how biochar and organic fertilizer alone or in combination regulate soil functional microbiomes and their relationships to ecosystem multifunctionality (EMF). Herein, a long-term (started in 2013) field experiment, containing five fertilization treatments, was employed to explore the effects of biochar and organic fertilizer applications on the EMF (based on 18 functional indicators of crop productivity, soil nutrient supply, element cycling, and microbial biomass) and the functional microbiomes of bulk soil and rhizosphere soil [normalizing the abundances of 64 genes related to carbon (C), nitrogen (N), phosphorus (P), and sulphur (S) cycles]. Compared with single-chemical fertilization, biochar and organic fertilizer inputs significantly enhanced most ecosystem-single functions and, in particular, the EMF significantly increased by 18.7-30.1%; biochar and organic fertilizer applications significantly increased the abundances of soil microbial functional taxa related to C-N-P-S cycles to varying degree. The combined application of biochar and organic fertilizer showed a better improvement in these indicators compared to using them individually. Most functional microbial populations in the soil, especially the taxa involved in C degradation, nitrification, nitrate-reduction, organic P mineralization, and S cycling showed significantly positive associations with the EMF at different threshold levels, which ultimately was regulated by soil pH and nutrient availability. These results highlight the strong links between soil microbiomes and agroecosystem functions, as well as providing scientific support for inclusion of biochar in agricultural production and services with organic amendments. 8-year field evidence revealed impacts of biochar and pig manure on soil functional microbiome and ecosystem functions.Biochar and pig manure inputs notably enhanced most ecosystem-single functions and the EMF increased by 18.7-30.1%.Biochar and pig manure inputs notably enriched soil functional microbes related to C-N-P-S cycles to varying degree.Increase in EMF was related to microbe-driven soil processes such as C degradation, nitrification, and Po mineralization.Inclusion of biochar in crop production with organic amendments could enhance agro-ecosystem functions and services.
期刊：
Global Change Biology,2024年30(2):e17158- ISSN：1354-1013
通讯作者：
Wang, JJ
作者机构：
[Wang, Jianjun; Wen, Shuailong; Jiang, Shuyu; Han, Lei; Hu, Ang; Zhong, Jicheng] Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Lake & Watershed Sci Water Secur, Nanjing, Peoples R China.;[Jiang, Shuyu] Nanjing Normal Univ, Coll Life Sci, Nanjing, Peoples R China.;[Han, Lei] Hunan Agr Univ, Coll Resources & Environm, Changsha, Peoples R China.;[Jang, Kyoung-Soon] Korea Basic Sci Inst, Biochem Anal Team, Cheongju, South Korea.;[Tanentzap, Andrew J.] Univ Cambridge, Dept Plant Sci, Cambridge, England.
通讯机构：
[Wang, JJ ] C;Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Lake & Watershed Sci Water Secur, Nanjing, Peoples R China.
关键词：
carbon quality temperature hypothesis;carbon-climate feedback;chemodiversity;functional traits;geography;global warming;greenhouse gas;lake ecosystems
摘要：
The mean value of temperature sensitivity of organic carbon decomposition in lake sediments is 1.78 ± 0.62. The quantity of sediment organic carbon determines the absolute rate of decomposition, while the quality of organic carbon determines the sensitivity of decomposition to warming. At both molecular and compositional levels, functional traits of DOM revealed the positive correlation between Q10 and biochemical recalcitrance, thus supporting the carbon quality temperature hypothesis. Abstract Organic carbon decomposition in lake sediments contributes substantially to the global carbon cycle and is strongly affected by temperature. However, the magnitude of temperature sensitivity (Q10) of decomposition and the underlying factors remain unclear at the continental scale. Carbon quality temperature (CQT) hypothesis asserts that less reactive and more recalcitrant molecules tend to have higher temperature sensitivities, but its support is challenged by complex composition of organic matter and environmental constraints. Here, we quantified Q10 of the sediments across 50 freshwater ecosystems along a 3500 km north–south transect, and characterized the quality of sediment dissolved organic carbon with chemodiversity reflected in molecular richness, functional traits (i.e., molecular weight, bioavailability, etc.) and composition. We further included classic environmental variables, such as climatic, physicochemical and microbial factors, to explore how Q10 is constrained by these factors or carbon quality. We found that Q10 varied greatly across lakes, with the mean value of 1.78 ± 0.62, but showed nonsignificant latitudinal pattern. Q10 was primarily predicted by chemodiversity and showed an increasing trend with the biochemical recalcitrance indicated by traits such as aromaticity and standard Gibb's Free Energy at both molecular and compositional levels. This suggests that carbon quality is the crucial determinant of Q10 in lakes, supporting the CQT hypothesis. Moreover, Q10 decreased linearly with the increase of molecular richness, implying that the resistance of decomposition to warming is associated with higher molecular diversity. Compared with the structural equation model containing only environmental variables, inclusion of chemodiversity increased 32.8% of the explained variation in Q10, and chemodiversity was the only driver showing direct effects. Collectively, this study illustrates the importance of chemodiversity in shaping the pattern of Q10, and has significant implications for accurately predicting the carbon turnover in lake ecosystems in the context of global warming.
关键词：
Soil organic matter;Spatial prediction;Digital soil mapping;Sampling density optimization;Random forest
摘要：
Purpose Spatial prediction of soil organic matter (SOM) in cultivated land is crucial for evaluating soil productivity and its role in terrestrial carbon cycling. Cultivated soils in mountainous regions are commonly scattered on the footslope whereas those in the plain regions are continuously planar distributed; hence, they are quite different in the degree of variation in soil-forming factors and thereby the soil properties including SOM. Materials and methods In this study, we used the digital soil mapping approach (DSM) to predict SOM (0-20 cm) in cultivated soils in a hill-mountain region, Longshan County (LS), and a plain-platform region, Nanxian County (NX), which are both located at the same latitude in Southern China. By using 6746 and 9571 soil sampling points for LS and NX, respectively, together with 33 environmental covariates, the optimal spatial interpolation models and the reasonable sample strategy were carefully discussed. Results and discussion Descriptive statistical results showed that SOM in LS and NX were both moderate variations (coefficient variation, 0.34) and were approximately normal distribution. SOM in NX was strongly spatially dependent while SOM in LS was a moderate spatial dependence. The conditional Latin hypercube sampling (cLHS) was more appropriate compared with the Simple Random Sampling (SRS) as the sampling strategy. The optimal model for predicting cultivated land SOM was the Random Forest (RF) model for both LS and NX. The prediction accuracy was positively correlated with the sampling density. Specifically, to obtain a high prediction accuracy, the reasonable sampling density for SOM in LS should be controlled at >= 4.0 per km(2), higher than that in NX (>= 2.0 per km(2)). Conclusions The combination of cLHS and the RF model probably is the best choice for cultivated land SOM spatial prediction in different terrains. Therefore, our results provide a basis for future DSM of SOM in similar regions and help optimize soil sampling density.
摘要：
Hydrochar serves not only as a fuel source but also as a versatile carbon material that has found extensive application across various domains. The application performance of hydrochar, e.g., energy recovery and carbon stability, is substantially influenced by its mass yield, higher heating value (HHV), and compositions (C, H, O, N, S, and ash), so the prediction and engineering of these properties is promising. In this study, two machine learning algorithms, namely gradient boosting regression (GBR) and random forest (RF), were used to predict the hydrochar properties mentioned above. The GBR models (with test regression coefficient (R2) values of 0.87-0.98 for single-target prediction and average test R2 of 0.93 for multi-target prediction) exhibited superior predictive capabilities to the RF models (with test R2 of 0.78-0.97 for single-target and average test R2 of 0.90 for multi-target prediction). The interpretation of ML models revealed the importance ranking of features for all targets. Then, engineering hydrochar was carried out through three different optimizations to the as-built multi target prediction model: i) optimizations of HTC conditions for given biomass samples; ii) optimization of biomass mixture recipes; iii) simultaneous optimization of both biomass mixing recipes and HTC conditions.
摘要：
Biological nitrogen fixation and nitrification inhibitor applications contribute to improving soil nitrogen (N) availability, however, free-living N fixation affected by nitrification inhibitors has not been effectively evaluated in soils under different weed management methods. In this study, the effects of the nitrification inhibitors dicyandiamide (DCD) and 3, 4-dimethylpyrazole phosphate (DMPP) on the nitrogenase, nifH gene，and diazotrophic communities in soils under different weed management methods (AMB, weeds growth without mowing or glyphosate spraying; GS, glyphosate spraying; MSG, mowing and removing weeds and glyphosate spraying; and WM, mowing aboveground weeds) were investigated. Compared to the control counterparts, the DCD application decreased soil nitrogenase activity and nifH gene abundance by 4.5% and 37.9%, respectively, under the GS management method, and the DMPP application reduced soil nitrogenase activity by 20.4% and reduced the nifH gene abundance by 83.4% under the MSG management method. The application of nitrification inhibitors significantly elevated soil NH(4)(+)-N contents but decreased NO(3)(-)-N contents, which had adverse impacts on soil nifH gene abundance and nitrogenase activity. The nifH gene abundances were also negatively impacted by dissolved organic N and Geobacter but were positively affected by available phosphorus and diazotrophic community structures. Nitrification inhibitors significantly inhibited Methylocella but stimulated Rhizobiales and affected soil diazotrophic communities. The nitrification inhibitors DCD and DMPP significantly altered soil diazotrophic community structures, but weed management outweighed nitrification inhibitors in reshaping soil diazotrophic community structures. The non-targeted effects of the nitrification inhibitors DMPP and DCD on soil free-living N fixation were substantially influenced by the weed management methods.
作者机构：
[Xia, Yongqiu; Han, Haojie; Li, Xiaohan; Yan, Xiaoyuan; Yan, Xing] Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Changshu Natl Agroecosyst Observat & Res Stn, Nanjing 210008, Peoples R China.;[Han, Haojie; Li, Xiaohan; Yan, Xing] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.;[Wen, Jiong] Yueyang Agr Res Acad, Yueyang 414215, Peoples R China.;[Rong, Xiangmin] Hunan Agr Univ, Coll Resources & Environm, Changsha 410128, Peoples R China.
通讯机构：
[Xia, YQ ] C;Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Changshu Natl Agroecosyst Observat & Res Stn, Nanjing 210008, Peoples R China.
关键词：
N removal kinetics;Small water bodies;Dissolved organic carbon;Intensive agricultural areas
摘要：
Small water bodies are extensively distributed and play critical roles in nitrogen (N) removal, primarily through sediment denitrification. However, our comprehension understanding of the N removal rate constant in these systems, particularly within the first-order kinetics model, remains limited. To address this gap, a one-year field study was conducted to investigate the N removal rate and N removal rate constant in various small water bodies within a typical intensive agricultural area. We observed a decrease in N removal rates in the downstream direction, from ditches to downstream ponds and streams, potentially due to upstream water bodies receiving higher nutrient inputs. Moreover, our findings revealed that the N removal process in small water bodies generally follows a first-order kinetics reaction model, with the N removal rate constant varying from 0.22 d-1 in streams and 0.48 d-1 in vegetated ditches. Both water dissolved organic carbon (DOC) and dissolved oxygen (DO) concentrations collectively influenced the N removal rate constants. By leveraging the relationship between the N removal rate constant and these environmental factors, we further estimated that, on average, small water bodies remove 68% of the N loading in the Dongting Lake Basin. We recommend implementing artificial management measures, such as vegetation, to enhance the N removal capacity of water bodies. However, the caution must be exercised in measures like concrete linings in ditches, as they can hinder N removal. These findings not only offer methods for estimating N removal in small water bodies, but also provide an insight into enhancing the N removal capacity of these systems to effectively mitigate non-point N pollution.
摘要：
Arsenic is a ubiquitous environmental pollutant. Microbe-mediated arsenic biotransformations significantly influence arsenic mobility and toxicity. Arsenic transformations by soil and aquatic organisms have been well documented, while little is known regarding effects due to endophytic bacteria. An endophyte Pseudomonas putida ARS1 was isolated from rice grown in arsenic contaminated soil. P. putida ARS1 shows high tolerance to arsenite (As(III)) and arsenate (As(V)), and exhibits efficient As(V) reduction and As(III) efflux activities. When exposed to 0.6 mg/L As(V), As(V) in the medium was completely converted to As(III) by P. putida ARS1 within 4 hr. Genome sequencing showed that P. putida ARS1 has two chromosomal arsenic resistance gene clusters ( arsRCBH ) that contribute to efficient As(V) reduction and As(III) efflux, and result in high resistance to arsenicals. Wolffia globosa is a strong arsenic accumulator with high potential for arsenic phytoremediation, which takes up As(III) more efficiently than As(V). Co-culture of P. putida ARS1 and W. globosa enhanced arsenic accumulation in W. globosa by 69%, and resulted in 91% removal of arsenic (at initial concentration of 0.6 mg/L As(V)) from water within 3 days. This study provides a promising strategy for in situ arsenic phytoremediation through the cooperation of plant and endophytic bacterium. (c) 2023 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
通讯机构：
[Liang, T ; Yan, XL] C;Chinese Acad Sci, Key Lab Land Surface Pattern & Simulat, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.;Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China.
关键词：
Back propagation neural network algorithm;Hydrogeological features;Industrial site contamination;Integrated modeling;Three-dimensional spatial analysis
摘要：
Intensive industrial activities cause soil contamination with wide variations and even perturb groundwater safety. Precision delineation of soil contamination is the foundation and precondition for soil quality assurance in the practical environmental management process. However, spatial non-stationarity phenomenon of soil contamination and heterogeneous sampling are two key issues that affect the accuracy of contamination delineation model. Taking a typical industrial park in North China as the research object, we constructed a random forest (RF) model for finely characterizing the distribution of soil contaminants using sparse-biased drilling data. Results showed that the R2 values of arsenic and 1,2-dichloroethane predicted by RF (0.8896 and 0.8973) were greatly higher than those of inverse distance weighted model (0.2848 and 0.2908), indicating that RF was more adaptable to actual non-stationarity sites. The back propagation neural network algorithm was utilized to establish a three-dimensional visualization of the contamination parcel of subsoil-groundwater system. Multiple sources of environmental data, including hydrogeological conditions, geochemical characteristics and anthropogenic industrial activities were integrated into the model to optimize the prediction accuracy. The feature importance analysis revealed that soil particle size was dominant for the migration of arsenic, while the migration of 1,2-dichloroethane highly depended on vertical permeability coefficients of the soil. Contaminants migrated downwards with soil water under gravity-driven conditions and penetrated through the subsoil to reach the saturated aquifer, forming a contamination plume with groundwater flow. Our findings afford a new idea for spatial analysis of soil-groundwater contamination at industrial sites, which will provide valuable technical support for maintaining sustainable industry.
关键词：
Intercropping;Soil C pool;Carbon use efficiency;Microbial growth;Microbial diversity;Core microbiota
摘要：
Intercropping is a powerful practice to alter the allocation of photosynthetic carbon (C) to belowground ecosystems via promotion of diversified plant communities. The feedback of soil C stability to intercropping is controlled by microbial C use efficiency (CUE). Despite its significance, there is currently insufficient evidence to decipher how soil microbial CUE reacts to intercropping. By combining a 10-year-long intercropping experiment with a substrate-independent 18O-H2O labelling approach and high-throughput sequencing, we elucidated the performance of intercropping on soil C pool and microbial metabolic traits as well as their relationships with soil microbial communities. Compared with monoculture, maize intercropping with peanut and soybean significantly increased soil C storage, soil mineral-associated organic C (MAOC), soil dissolved organic (DOC), and soil microbial biomass (MBC) contents at maize four growth stages. Soil microbial CUE increased significantly, especially at maize flowering and mature stages, as a consequence of enhanced microbial growth and biomass turnover rate after maize intercropping with peanut and soybean. Soil C storage and accessibility indicators (e.g., MAOC, DOC, and MBC contents) could significantly predict the changes of soil microbial diversity and core taxa. Meanwhile, the beta-diversity (community composition) of soil bacteria, fungi, saprotroph and protists, as well as rare fungal taxa were positively correlated with soil microbial CUE, and these indicators showed a high prediction of the microbial CUE. Soil C storage and accessibility indicators directly and indirectly influenced soil microbial CUE by regulating microbial diversity and key taxa. Soil microbial diversity and core taxa directly and indirectly influenced microbial CUE by mediating microbial respiration, growth, biomass, and enzyme activity, which mediated by soil C storage and accessibility. These findings provide an evidence for the associations between microbial diversity, CUE, and soil C stability, highlighting the importance of intercropping-driven soil microbiome to enhance soil microbial CUE.
摘要：
Understanding how phytoplankton interacts with local and regional drivers as well as their feedbacks is a great challenge, and quantitative analyses of the regulating role of human activities and climate changes on these feedback loops are also limited. By using monthly monitoring dataset (2000-2017) from Lake Taihu and empirical dynamic modelling to construct causal networks, we quantified the strengths of causal feedbacks among phytoplankton, local environments, zooplankton, meteorology as well as global climate oscillation. Prevalent bidirectional causal linkages between phytoplankton biomass (chlorophyll a) and the tested drivers were found, providing holistic and quantitative evidence of the ubiquitous feedback loops. Phytoplankton biomass exhibited the highest feedbacks with total inorganic nitrogen and ammonia and the lowest with nitrate. The feedbacks between phytoplankton biomass and environmental factors from 2000 to 2017 could be classified into two groups: the local environments (e.g., nutrients, pH, transparency, zooplankton biomass)-driven enhancement loops promoting the response of the phytoplankton biomass, and the climate (e.g., wind speed)-driven regulatory loops suppressing it. The two counterbalanced groups modified the emergent macroecological patterns. Our findings revealed that the causal feedback networks loosened significantly after 2007 following nutrient loading reduction and unsuccessful biomanipulation restoration attempts by stocking carp. The strength of enhancement loops underwent marked decreases leading to reduced phytoplankton responses to the tested drivers, while the climate (decreasing wind speed, warming winter)-driven regulatory loops increased- like a tug-of-war. To counteract the self-amplifying feedback loops, the present eutrophication mitigation efforts, especially nutrient reduction, should be continued, and introduction of alternative measures to indirectly regulate the critical components (e.g., pH, Secchi depth, zooplankton biomass) of the loops would be beneficial.
通讯机构：
[Yang, Y ; Wu, HZ ] H;Hunan Prov Inst Prod & Goods Qual Inspect, Changsha 410007, Peoples R China.;Hunan Agr Univ, Coll Resources & Environm, Changsha 410128, Hunan, Peoples R China.
摘要：
The emerging sample pretreatment technique of magnetic solid-phase extraction (MSPE) has drawn the attention of researchers owing to its advantages of less reagent consumption, fast separation/enrichment process, high adsorption capacity, and simple operation. This paper presents a review of synthesis techniques, classification, and analysis procedures for MSPE in the detection of heavy metals in food. Magnetic adsorbents derived from silica, metal oxides, carbon, polymers, etc., are applied for the detection of heavy metals in food. Then, the recent development of the technology of MSPE for the analysis of heavy metal extraction in food is summarized in detail. Finally, the future outlook for the improvement of MSPE is also discussed. The emerging sample pretreatment technique of magnetic solid-phase extraction (MSPE).
期刊：
Journal of Energy Storage,2024年83:110629 ISSN：2352-152X
通讯作者：
Qiang Wang
作者机构：
[Ying-Rong Wang; Yu-Lin Nie; Qian Wang; Shan Liu] College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, Hunan, PR China;State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, PR China;[Yuan Yang] International Joint Laboratory of Hunan Agricultural Typical Pollution Restoration and Water Resources Safety Utilization, College of Resources and Environment, Hunan Agricultural University, No. 1 Nongda Road, Furong District, Changsha, 410128, PR China;[Qiang Wang] College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, Hunan, PR China<&wdkj&>State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, PR China
通讯机构：
[Qiang Wang] C;College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, Hunan, PR China<&wdkj&>State Environmental Protection Key Laboratory of Monitoring for Heavy Metal Pollutants, PR China
摘要：
Iron-based sulfate (Na2Fe(SO4)2) is receiving increasing attention because of its heat resistance, moisture resistance as well as low cost. Herein, Na2Fe(SO4)2 (NFS/bc + s), which is modified by sucrose and carbon black, was synthesized by the method of environment-friendly and economic liquid phase without waste water and with ~100 % utilization of raw materials. NFS/bc + s has a special structure with broken, open, porous, hollow cuboid, which provide an excellent specific capacity of 90.64 mAh/g at 0.1C, additionally, NFS/bc + s also shows good stability in charge-discharge cycles (its discharge capacity remain 71 % of initial capacity after 100 cycles at 1C between the high voltage range from 2.75 to 4.5 V). The excellent electrochemical performance is due to the large number of electrochemical active sites provided by the broken hollow structure. Therefore, the prepared electrode material has a potential practical application prospect in the sodium ion battery system.
摘要：
Cadmium (Cd) is a highly toxic heavy metal that causes serious damage to plant and human health. Phytolacca acinosa Roxb. has a large amount of aboveground biomass and a rapid growth rate, and it has been identified as a novel type of Cd hyperaccumulator that can be harnessed for phytoremediation. However, the molecular mechanisms underlying the response of P. acinosa to Cd2+ stress remain largely unclear. In this study, the phenotype, biochemical, and physiological traits of P. acinosa seeds and seedlings were analyzed under different concentrations of Cd2+ treatments. The results showed higher Cd2+ tolerance of P. acinosa compared to common plants. Meanwhile, the Cd2+ content in shoots reached 449 mg/kg under 10 mg/L Cd2+ treatment, which was obviously higher than the threshold for Cd hyperaccumulators. To investigate the molecular mechanism underlying the adaptability of P. acinosa to Cd stress, RNA-Seq was used to examine transcriptional responses of P. acinosa to Cd stress. Transcriptome analysis found that 61 genes encoding TFs, 48 cell wall-related genes, 35 secondary metabolism-related genes, 133 membrane proteins and ion transporters, and 96 defense system-related genes were differentially expressed under Cd2+ stress, indicating that a series of genes were involved in Cd2+ stress, forming a complex signaling regulatory mechanism. These results provide new scientific evidence for elucidating the regulatory mechanisms of P. acinosa response to Cd2+ stress and new clues for the molecular breeding of heavy metal phytoremediation.
摘要：
Abstract Soil protease plays a fundamental role in soil nitrogen (N) transformations. Soil N and phosphorus (P) management significantly influence soil protease activity. However, the impacts of N and P combined modification on soil protease remain unclear. A better understanding of the activity and dynamic of soil protease could provide new insights into soil N cycling and available N supply. This study aimed to quantify the influences of combined effects of N and P managements on soil protease activities and decipher the potential mechanism from the perspectives of soil chemical properties, functional microbes, and functional genes. The nitrification inhibitor 3, 4‐dimethylpyrazole phosphate (DMPP) application or phosphate‐solubilizing bacteria (PSB) Klebsiella inoculation significantly increased soil protease activity (23.39% and 70.99%, respectively) and ammonium N (NH4+–N) contents, relative to the blank control. However, compared with the DMPP or PSB alone application, the combined applications of DMPP and PSB significantly decreased protease activity, implying that an antagonistic effect on soil protease activity was generated. The abundances of genus Klebsiella were stimulated by the DMPP or PSB but significantly inhibited by the combined additions of DMPP and PSB. The DMPP and PSB applications also significantly changed soil microbial communities and led to more complicated soil microbial co‐occurrence networks. Soil protease activity had a significantly positive correlation with the normalized abundances of tri and clpX genes. Our findings suggested that the combined additions of DMPP and PSB generated an antagonistic effect on soil protease activity and that the antagonistic effect was directly associated with soil NH4+–N and NO3−–N contents, P fractions, and functional gene abundances.
期刊：
Biology and Fertility of Soils,2024年60(2):253-253 ISSN：0178-2762
通讯作者：
Xiangbi Chen
作者机构：
[Shaohong Deng; Chong Ma; Hang Qiao; Wei Gao; Jinshui Wu; Yirong Su; Xiangbi Chen] Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, The Chinese Academy of Sciences, Changsha, People’s Republic of China;Department of Ecological and Resources Engineering, Fujian Key Laboratory of Eco-industrial Green Technology, Wuyi University, Wuyishan, People’s Republic of China;College of Resources and Environmental Sciences, Hunan Agricultural University, Changsha, People’s Republic of China;[Jun Zhao] Fort Lauderdale Research and Education Center, Department of Microbiology and Cell Science, University of Florida, Davie, USA;[Qiang Tu; Youming Zhang] State Key Laboratory of Microbial Technology, Shandong University, Qingdao, People’s Republic of China
通讯机构：
[Xiangbi Chen] K;Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, The Chinese Academy of Sciences, Changsha, People’s Republic of China
关键词：
Controlled-release nitrogen fertilizer;Double-cropping rice;Nitrogen losses;Nitrogen uptake;Productivity;Soil nitrogen pool
摘要：
Considerable literature has demonstrated the advantage of controlled-release nitrogen (CRN) fertilizer in improving crop productivity. However, few researches have explored the long-term impacts of using CRN fertilizers as alternative to common urea on production and N utilization in double-cropping paddy. To address this gap, our study utilized a database derived from a 10-year field experiment from 2013 to 2022. During early and late rice seasons, compared to common urea (early rice, 150kg hm(-2); late rice, 180kg hm(-2)), CRN fertilizer (150kg hm(-2); 180kg hm(-2)) input significantly increased yield by 7.4%, and 11.7%, as well as N use efficiency (NUE) from 23.0% and 24.6% to 33.0% and 37.5%, respectively. CRN application significantly reduced N losses, evidenced by decrease in runoff (23.1% and 19.4%), leaching (12.7% and 12.1%), ammonia volatilization (28.9% and 30.2%), and N(2)O emissions (10.4% and 16.1%). A reduction of 10% in CRN fertilizer input maintained yield. Compared with normal amount, reducing 10, 20, and 30% CRN input increased NUE by 7.0-7.6%, 7.3-7.4%, and 11.6-12.6%; reduced runoff loss by 16.1-17.9%, 27.9-30.7%, and 35.0-37.2%; decreased leaching loss by 7.6-12.8%, 18.1-22.6%, and 26.5-31.4%; decreased ammonia volatilization by 9.9-12.3%, 16.3-22.7%, and 23.2-29.3%, and decreased N(2)O loss by 7.8-13.3%, 12.8-32.8%, and 20.3-36.9%, respectively. Soils with CRN input showed higher total and inorganic N contents than the soils with common urea, and the content increased in parallel with CRN fertilizer input. Soil N content and N runoff loss were significantly related to yield and N uptake, and N runoff and leaching losses were significantly related to NUE. These results support the sustainable use of CRN fertilizers as a viable alternative to common urea, indicating that application rate of 135 and 162kgN hm(-2) of early and late rice, respectively, maintain yield and enhance N utilization in double-season paddy of southern China.
摘要：
High crop diversity can potentially enhance farmland productivity and ecosystem services, through direct or indirect effects, particularly belowground. Intercropping is a powerful technique to increase crop diversity and belowground biodiversity. It has attracted long-term global attention. However, little is known about the impacts of belowground microbiota on intercropping-driven increases in crop productivity. This study was an 8 -year experiment involving five maize planting patterns, which aimed to distinguish the contributions of rare and abundant microbiota (bacteria, fungi, and eukaryotes) in rhizosphere soil to support maize production. The results indicated that the richness and phylogenetic diversity of rare microbial taxa were significantly higher than those of abundant taxa across all soil samples. Maize and soybean intercropping increased the diversity of rare taxa rather than abundant taxa. Plant growth stages significantly altered the community composition of both rare and abundant microbial taxa. The assembly of the rare and abundant communities is mainly driven by deterministic processes and, in particular, the abundant taxa rather than the rare taxa mainly contributed to maize productivity gain. The changes in maize productivity were significantly associated with many core species in the abundant microbial communities mainly belonging to bacterial Actinomycetales and Rhodocyclaceae, fungal Tausonia and Curvularia, and eukaryotic Leptophyryidae and Ochromonadaceae. The network complexity of abundant fungi and eukaryotic communities also exerted notable effects on maize productivity. Overall, these findings underscored the importance of the core taxa and network stability of abundant microbiota in intercropping systems. This suggests the potential of intercropping to improve crop production by regulating belowground microbial effects in intensive agroecosystems.
作者：
Lijian Leng;Xinni Lei;Naif Abdullah Al-Dhabi;Zhibin Wu;Zequn Yang;...
期刊：
Chemical Engineering Journal,2024年485:149862 ISSN：1385-8947
通讯作者：
Ting Xiong<&wdkj&>Hailong Li
作者机构：
[Xinni Lei; Zequn Yang; Tanghao Li; Weijin Zhang; Hao Zhan; Haoyi Peng; Hailong Li] School of Energy Science and Engineering, Central South University, Changsha 410083, China;Xiangjiang Laboratory, Changsha 410205, China;[Ting Xiong] School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China;[Naif Abdullah Al-Dhabi] Department of Botany and Microbiology, College of Science, King Saud University, P. O. Box 2455, Riyadh 11451, Saudi Arabia;[Zhibin Wu] College of Resources and Environment, Hunan Agricultural University, Changsha, Hunan 410128, China
通讯机构：
[Ting Xiong; Hailong Li] S;School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha 410205, China<&wdkj&>School of Energy Science and Engineering, Central South University, Changsha 410083, China
摘要：
Biochar, derived through biomass pyrolysis, is an emerging carbonaceous material with significant potential in various applications. The performance of biochar in applications depends heavily on its surface characteristics, including its content of N-containing functional groups. In this study, machine learning (ML) was used for the prediction and engineering of biochar N-containing functional groups, specifically amine-N (N-A), pyrrolic-N (N-5), and pyridinic-N (N-6). The single-target random forest model accurately predicted N recovery in biochar (char-N yield) and N-A, N-5, and N-6 contents, achieving test R2 of 0.91–0.97. Model interpretations revealed that pyrolysis temperature was the most influential factor in predicting char-N yield, N-A, N-5, and N-6. The multi-target random forest model achieved an average test R2 of 0.93, and it was used to optimize pyrolysis parameters for designing biochar N-functional groups. This process was followed by experimental verification. Relative errors for the three N-containing functional groups were mostly within 15% (18.4% on average). The favorable results obtained from experimental verification demonstrate the significant potential of ML in biochar engineering.
摘要：
Utilizing an acid-resistant biological soil crust (BSC) species that we discovered, we developed a device capable of efficiently removing cadmium (Cd) from mine wastewater with varying levels of acidity. Our research has demonstrated that this particular BSC species adapts to acidic environments by regulating the balance of fatty acids and acid-resistant enzymes. At a Cd concentration of 5 mg/L, the BSC grew well. When the initial Cd concentration was 2 mg/L, and the flow rate was set at 1 mL/min (at pH levels of 3, 4, and 5), BSC had a high removal rate of Cd, and the removal rate increased with the increase of pH (from 90% to 97%). Chemisorption is the primary removal mechanism in the initial stage, where the functional groups and minerals on the surface of the BSC play a significant role. In addition, BSC also adapts to Cd stress by changing bacterial community structure. It was discovered through infrared spectroscopy and two-dimensional correlation analysis that hydrophilic groups, specifically phosphate and carboxyl groups, exhibited the highest reactivity during the Cd binding process. Protein secondary structure analysis confirmed that as the pH increased, the adsorption capacity of the BSC increased; making biofilm formation easier. This study presents a novel approach for the treatment of acidic wastewater.
