Assessing soil erosion in a semiarid ecosystem in Central Argentina using 137Cs and 7Be measurements.

Argentina is a Latin American country which encounters soil degradation problems. The most productive regions have implemented conservative land practices (no-till). However, agricultural frontier has been displaced to marginal lands with arid and semiarid climates, with the consequent disappearance in many areas of native forest and land degradation. In this work, the fallout of gamma-emitting radionuclides, 137Cs and 7Be, was jointly used to assess changes in soil erosion in a recently converted semiarid ecosystem into agricultural land. 137Cs was utilized to estimate the erosion over the past 60 years, whereas 7Be was employed to estimate the erosion after the conversion of the area to cultivated land and soil tillage. For 137Cs the Proportional Model (PM), the Mass Balance Model II (MBMII) and the MODERN model were used, for 7Be the Profile Distribution Model (PDM) and the MODERN model were used. 137Cs indicates mean erosional rates of 8.2, 10.5 and 6.5 Mg ha-1 a-1, using MBMII, PM and MODERN, respectively, and that a soil layer between 0.5 and 0.8 mm was annually lost by erosion. By applying a 7Be tracer, we measured erosion rates of 2.4 and 3.3 Mg ha-1 (with PDM and Modern, respectively), indicating the loss of the upper 0.2 mm of soil. This erosion can be attributed to a few heavy rainfalls that occurred within the past 90 days. The results suggest that current land management practices have led to an increase in soil erosion. This could be attributed to the fact that the soil remains bare after crop harvest, which may compromise its conservation and future productivity.

Major drivers of soil acidification over 30 years differ in paddy and upland soils in China.

Elevated nitrogen (N) fertilization has largely increased crop production in China, but also increased acidification risks, thereby threatening crop yields. However, natural soil acidification due to bicarbonate (HCO3) leaching and base cation (BC) removal by crop harvest also affect soil acidity whereas the input of HCO3 and BC via fertilizers and manure counteract soil acidification. Insights in rates and drivers of soil acidification in different land use types is too limited to support crop- and site-specific mitigation strategies. In this study, we assessed the historical changes in cropland acidification rates and their drivers for the period 1985-2019 at 151 sites in a typical Chinese county with the combined nutrient and soil acidification model VSD+. VSD+ could well reproduce long-term changes in pH and in the BC concentrations of calcium, magnesium and potassium between 1985 and 2019 in non-calcareous soils. In paddy soils, the acidity production rate decreased from 1985 onwards, mainly driven by a pH-induced reduction in HCO3 leaching and N transformations. In upland soils, however, acidity production was mainly driven by N transformations and hardly changed over time. Crop BC removal by harvesting played a minor role in both paddy and upland soils, but its relative importance increased in paddy soils. The acidity input was partly neutralized by HCO3 input from fertilizers and manure, which decreased over time due to a change from ammonia bicarbonate to urea. Soil buffering by both BC and aluminium release decreased in paddy soils due to a reduction in net acidity production, while it stayed relatively constant in upland soils. We conclude that acidification management in paddy soils requires a focus on avoiding high HCO3 leaching whereas the management in upland soils should focus on balancing N with recycling organic manure and crop residues.

Effect of agricultural management practices on rice yield and greenhouse gas emissions in the rice-wheat rotation system in China.

Agricultural management practices (AMPs) have the potential to significantly enhance crop yield, albeit with the possible side effect of escalating greenhouse gas emissions. Few studies have undertaken a comprehensive quantification of the impact of AMPs on crop production and soil GHG, particularly in identifying the optimal AMPs for rice cultivation within rice-wheat rotation system. Here, we combined data analysis and keyword search methods on 1433 individual experimental observations from 172 studies on diverse soil types in the subtropical monsoon climate zone of China to assess the impact of AMPs on rice yield, CH4 and N2O emissions, total greenhouse gas emissions (TGHGE). We focused on four key AMPs: mineral N fertilizer management (including ordinary N fertilizer and slow-/controlled-release fertilizer (SCRF)), organic material management (incorporating organic fertilizer, biochar amendment, and straw return), water-saving irrigation, and no-tillage. Our result showed the rice yield ranged from 2525 to 31,196 kg ha-1, and mineral N fertilizer and organic material management boosted rice yield by 2.84-16.19 % and 2.47-8.52 %, respectively. In terms of N2O emissions, biochar amendment resulted in a decrease of 13.05 %, while ordinary N fertilizer, organic fertilizer, and water-saving irrigation led to increases of 63.16 %, 136.66 %, and 37.41 %, respectively. The implementation of SCRF, water-saving irrigation, and no-tillage significantly curtailed CH4 (6.83 %-35.91 %) and TGHGE (6.22 %-20.59 %). Conversely, organic fertilizer and straw return significantly escalated CH4 emissions by 102.20 % and 33.64 % and TGHGE by 85.03 % and 32.40 %. Rice yield and GHG emissions are mainly influenced by variables such as soil bulk density, pH, soil organic carbon, soil texture, mean annual temperature, and total nitrogen. Our study demonstrates that the application of SCRF, water-saving irrigation, and no-tillage can effectively reduce GHG without compromising yield. These practices are particularly effective under climatic and soil conditions of rice-wheat rotation systems in China, thereby contributing to the sustainable rice farming.

Net greenhouse gas balance in U.S. croplands: How can soils be part of the climate solution?

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2 ) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2 O) and methane (CH4 ). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2 O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 ± 1.16 $$ 13.2\pm 1.16 $$ Tg CO2 -C year-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 ± 0.02 $$ 0.39\pm 0.02 $$ Tg N2 O-N year-1 and 0.21 ± 0.01 $$ 0.21\pm 0.01 $$ Tg CH4 -C year-1 , respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 ± 11.46 $$ 122.3\pm 11.46 $$ Tg CO2 -eq year-1 , with the largest contribution from N2 O emissions. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2 O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

The effect of environmental regulation and green subsidies on agricultural low-carbon production behavior: A survey of new agricultural management entities in Guangdong Province.

Agricultural low-carbon production emerges as a pivotal function for achieving sustainable green development. However, there remains insufficient empirical evidence regarding the effect of environmental regulations and green subsidies upon the low-carbon production behavior of new agricultural entities. In this study, a questionnaire survey was administered to 268 respondents representing new agricultural entities in Guangdong Province, P.R.C. Subsequently, a structural equation model had been employed for validation analysis. This study's findings demonstrate that in general, environmental regulations positively and significantly affect the behavior of agricultural low-carbon production. Conversely, the influence of green subsidies is not statistically significant. In addition, differences are observed across different sectors, with environmental regulations significantly affecting low-carbon production behavior in the plantation sector, but not in the livestock sector. Conversely, green subsidies significantly impact low-carbon production behavior in the livestock sector, but not in the plantation sector. These findings highlight the promotional role of government-enforced environmental regulations and green subsidies in fostering low-carbon agricultural practices. Therefore, new agricultural entities should strive to augment green production technology capacities to realize sustainable green development.

A spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination in sub-watersheds.

Best management practices (BMPs) have been extensively employed in effective watershed management for non-point source pollution. The weights of objective functions and the restrictive conditions of combined BMPs are the vital requirements for BMPs allocation. Therefore, it is more beneficial to explore that a spatial optimal allocation method considering multi-attribute decision making and multiple BMPs random combination. Here is the novel framework based on Soil and Water Assessment Tool (SWAT) and the Non-dominated Sorting Genetic Algorithm II (NSGA-Ⅱ), which considers multiple objectives in deriving watershed-scale pollution control practices by considering BMPs cost and combined reduction rates of total nitrogen (TN) and total phosphorus (TP). The framework also integrates combined Entropy Weight method (EWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve the weights of TN and TP, and considers the attributes of the sub-basin itself, which is more local suitability. Four categories of BMPs, tillage management, nutrient management, vegetative filter strips, and landscape management, were evaluated in the Jing River Basin (JRB) and resulted in reduction rates of 9.77%, 10.53%, 16.40%, and 14.27% averagely, respectively. BMP allocation schemes, derived from multi-objective optimization, are stratified into three financial scenarios. Low-cost scenario, costing up to 2 billion RMB, primarily targets the grain for green program in 28.81% of sub-basins. Medium-cost scenario, between 2 and 6 billion RMB, predominantly utilizes the grain for green in areas with a slope greater than 15°, accounting for 20.00% of sub-basins. High-cost scenario exceeds 6 billion RMB, mainly due to the implementation of multiple combination measures. The three configuration scenarios can provide decision-makers with a trade-off between measure costs and reduction efficiency. Overall, the innovative framework not only facilitates cost-effective implementation but provides a beneficial methodology for selecting cost-effective conservation practices in other regions.

Modeling the Impact of Agricultural Mitigation Measures on the Spread of Sharka Disease in Sweet Cherry Orchards.

Sharka is a disease affecting stone fruit trees. It is caused by the Plum pox virus (PPV), with Myzus persicae being one of the most efficient aphid species in transmitting it within and among Prunus orchards. Other agricultural management strategies are also responsible for the spread of disease among trees, such as grafting and pruning. We present a mathematical model of impulsive differential equations to represent the dynamics of Sharka disease in the tree and vector population. We consider three transmission routes: grafting, pruning, and through aphid vectors. Grafting, pruning, and vector control occur as pulses at specific instants. Within the model, human risk perception towards disease influences these agricultural management strategies. Model results show that grafting with infected biological material has a significant impact on the spread of the disease. In addition, detecting infectious symptomatic and asymptomatic trees in the short term is critical to reduce disease spread. Furthermore, vector control to prevent aphid movement between trees is crucial for disease mitigation, as well as implementing awareness campaigns for Sharka disease in agricultural communities that provide a long-term impact on responsible pruning, grafting, and vector control.

Carabid Beetles (Coleoptera) as Indicators of Sustainability in Agroecosystems: A Systematic Review.

The sustainability of agroecosystems is at risk owing to continuous anthropogenic disturbance. As such, there is a need to evaluate indicator taxa that may be used to monitor the health of agricultural management systems. Carabid beetles are ubiquitous and functionally crucial in agroecosystems while at the same time are sensitive to the changes caused by management practices. Their quick response to anthropogenic disturbances has been proposed as a practical and realistic tool for monitoring the sustainability of agricultural practices. However, there is still disagreement about carabids as possible indicators of agroecosystem sustainability. We conducted a systematic review of the responses of carabid beetles to agricultural systems in different biogeographical areas. We examined whether these beetles could serve as potential indicators of agroecosystem sustainability. The ISI Web of Science, Google Scholar, and Scopus were used to search for papers published from 2000-2019. In total, we included 69 studies indicating the use of carabids to monitor the impact of management practices in agroecosystems. Most studies were conducted in European countries (n = 37), while Southern Africa and East Asia countries were significantly under-represented (n = 10). Carabid beetle response to agroecosystems varied between management practices, with biodiversity indices (n = 41: positive 60%, negative 19%, and neutral 19%) being the most measured response variable, followed by functional diversity (n = 28: positive 67%, negative 25%, and neutral 7%). Overall, our findings highlight the need for more research in underdeveloped countries, to investigate the potential of overlooked carabids and include response variables measuring functional diversity in assessing the sustainability of agricultural management. This will assist policy makers and land managers in making active and informed decisions about agroecological disturbances and management.

Effects of conservation tillage on soil enzyme activities of global cultivated land: A meta-analysis.

The negative impacts of conventional agriculture and the imperative to adopt conservation tillage garnered significant attention. However, the effects of conservation tillage on soil enzyme activities still lack comprehensive cognition. Here, we collected 14,308 pairwise observations from 369 publications worldwide to systematically evaluate the effects of different conservation tillage practices (reduced tillage (T), reduced tillage with straw return (TS), reduced tillage with straw mulch return (TSO), no-tillage (NT), no-tillage with straw return (NTS), and no-tillage with straw mulch return (NTSO)) on the activities of 35 enzymes in soil. The results showed that: (1) the effect of conservation tillage on soil enzyme activity varied by enzyme type, except for peroxidase (-12.34%), which showed an overall significant positive effect (10.28-89.76%); (2) the NTS and TS demonstrated strong potential to improve soil enzyme activities by increasing a wide variety of soil enzyme activities (12-15) and efficacy (9.76-75.56%) than other conservation tillage (8.60-68.68%); (3) in addition, the effect of conservation tillage on soil enzyme activity was regulated by soil depth, crop type, years of conservation tillage, climate (mean annual precipitation and temperature), and soil physicochemical properties (e.g., pH, bulk density, electrical conductivity, organic matter, ammonium nitrogen, total phosphorus, available phosphorus, total potassium, available potassium, etc.). Overall, our quantitative analysis clearly suggests that conservation tillage is an effective measure for improving soil enzyme activity on global croplands, where combination of reduced tillage or no-till with straw return are considered to have great potential and promise. The results contribute to better comprehend the effects of conservation tillage on soil activity and provide a valuable insight for agricultural management.

Improving model capability in simulating spatiotemporal variations and flow contributions of nitrate export in tile-drained catchments.

It is essential to identify the dominant flow paths, hot spots and hot periods of hydrological nitrate-nitrogen (NO3-N) losses for developing nitrogen loads reduction strategies in agricultural watersheds. Coupled biogeochemical transformations and hydrological connectivity regulate the spatiotemporal dynamics of water and NO3-N export along surface and subsurface flows. However, modeling performance is usually limited by the oversimplification of natural and human-managed processes and insufficient representation of spatiotemporally varied hydrological and biogeochemical cycles in agricultural watersheds. In this study, we improved a spatially distributed process-based hydro-ecological model (DLEM-catchment) and applied the model to four tile-drained catchments with mixed agricultural management and diverse landscape in Iowa, Midwestern US. The quantitative statistics show that the improved model well reproduced the daily and monthly water discharge, NO3-N concentration and loading measured from 2015 to 2019 in all four catchments. The model estimation shows that subsurface flow (tile flow + lateral flow) dominates the discharge (70-75%) and NO3-N loading (77-82%) over the years. However, the contributions of tile drainage and lateral flow vary remarkably among catchments due to different tile-drained area percentages and the presence of farmed potholes (former depressional wetlands that have been drained for agricultural production). Furthermore, we found that agricultural management (e.g. tillage and fertilizer management) and catchment characteristics (e.g. soil properties, farmed potholes, and tile drainage) play important roles in predicting the spatial distributions of NO3-N leaching and loading. The simulated results reveal that the model improvements in representing water retention capacity (snow processes, soil roughness, and farmed potholes) and tile drainage improved model performance in estimating discharge and NO3-N export at a daily time step, while improvement of agricultural management mainly impacts NO3-N export prediction. This study underlines the necessity of characterizing catchment properties, agricultural management practices, flow-specific NO3-N movement, and spatial heterogeneity of NO3-N fluxes for accurately simulating water quality dynamics and predicting the impacts of agricultural conservation nutrient reduction strategies.

Soil Carbon Stocks and Greenhouse Gas Mitigation of Agriculture in the Brazilian Cerrado-A Review.

New agricultural practices and land-use intensification in the Cerrado biome have affected the soil carbon stocks. A major part of the native vegetation of the Brazilian Cerrado, a tropical savanna-like ecoregion, has been replaced by crops, which has caused changes in the soil carbon (C) stocks. To ensure the sustainability of this intensified agricultural production, actions have been taken to increase soil C stocks and mitigate greenhouse gas emissions. In the last two decades, new agricultural practices have been adopted in the Cerrado region, and their impact on C stocks needs to be better understood. This subject has been addressed in a systematic review of the existing data in the literature, consisting of 63 articles from the Scopus database. Our review showed that the replacement of Cerrado vegetation by crop species decreased the original soil C stocks (depth 0-30 cm) by 73%, with a peak loss of 61.14 Mg ha-1. However, when analyzing the 0-100 cm layer, 52.4% of the C stock data were higher under cultivated areas than in native Cerrado soils, with a peak gain of 93.6 Mg ha-1. The agricultural practices implemented in the Brazilian Cerrado make low-carbon agriculture in this biome possible.

Validating Farmland Biodiversity Life Cycle Assessment at the Landscape Scale.

Life cycle assessment (LCA) aims at providing standardized evaluations of processes involving resource use, human health, and environmental consequences. Currently, spatial dependencies are most often neglected, though they are essential for impact categories like biodiversity. The "Swiss Agricultural Life Cycle Assessment for Biodiversity (SALCA-BD)" evaluates the impact of agricultural field management on 11 indicator species groups. We tested if its performance can be improved by accounting for the spatial context of the individual fields. We used high-resolution bird/butterfly point observations in two agricultural regions in Switzerland and built linear mixed models to compare SALCA-BD scores to the observed species richness at the field/landscape scale. We calculated a set of landscape metrics, tested their relationship with the landscape-model prediction errors, and then added all significant metrics as additional predictors to the landscape models. Our results show that field-scale SALCA-BD scores were significantly related to the observed field-scale richness for both indicator groups. However, the performance decreased when aggregated to the landscape scale, with high variability between regions. Adding specific landscape metrics improved the landscape model for birds but not for butterflies. Integrating the spatial context to LCA biodiversity assessments could provide moderate benefits, while its usefulness depends on the conditions of the respective assessment.

Magnitude and efficiency of straw return in building up soil organic carbon: A global synthesis integrating the impacts of agricultural managements and environmental conditions.

Enhancing soil organic carbon (SOC) through straw return (SR) has been widely recommended as a promising practice of climate-smart agriculture. Many studies have investigated the relative effect of straw return on SOC content, while the magnitude and efficiency of straw return in building up SOC stock remain uncertain. Here, we present an integrative synthesis of the magnitude and efficiency of SR-induced SOC changes, using a database comprising 327 observations at 115 sites globally. Straw return increased SOC by 3.68 ± 0.69 (95 % Confidence Interval, CI) Mg C ha-1, with a corresponding C efficiency of 20.51 ± 9.58 % (95 % CI), of which <30 % was contributed directly by straw-C input. The magnitude of SR-induced SOC changes increased (P < 0.05) with increasing straw-C input and experiment duration. However, the C efficiency decreased significantly (P < 0.01) with these two explanatory factors. No-tillage and crop rotation were found to enhance the SR-induced SOC increase, in both magnitude and efficiency. Straw return sequestrated larger amount of C in acidic and organic-rich soils than in alkaline and organic-poor soils. A machine learning random forest (RF) algorithm showed that the amount of straw-C input was the most important single factor governing the magnitude and efficiency of straw return. However, local agricultural managements and environmental conditions were together the dominant explanatory factors determining the spatial differences in SR-induced SOC stock changes. This entails that by optimizing agricultural managements in regions with favorable environmental conditions the farmer can accumulate more C with minor negative impacts. By clarifying the significance and relative importance of multiple local factors, our findings may aid the development of tailored region-specific straw return policies integrating the SOC increment and its environmental side costs.

The abundance, characteristics and distribution of microplastics (MPs) in farmland soil-Based on research in China.

Microplastics (MPs) in farmland soil deteriorate soil environment and increase food toxicity, thereby threatening the agricultural production environment and human safety. However, a systematic understanding of MPs pollution in farmland soil is lacking in China. Therefore, the relevant literature was comprehensively discussed to discuss the abundance, characteristics, distribution and influencing factors of MPs in farmland soil. The conclusions are as follows: (1) The highest and lowest MPs abundance were in marginal tropical humid and plateau temperate semi-arid regions, accounting for 7579 n/kg and 48 n/kg, respectively. (2) The main shapes of MPs in farmland soil are fragment/flake and fiber, accounting for 44.0 % and 34.4 %, respectively. The MPs are mostly transparent (21.8 %) and black (21.5 %). Among the MPs types, polyethylene (PE) and polypropylene (PP) are dominant, accounting for 26.2 % and 19.0 %, respectively. The main size of MPs in farmland soil is 0.1-0.5 mm, with average proportions was 51.4 %. (3) Compared with non-fertilizing and non-mulching, the MPs abundance in the fertilizing and mulching farmland soils increased by 170 % and 232 %, respectively. (4) In the farmland soil, the MPs abundance was significantly positive with temperature, sunshine hour, and altitude. (5) In farmland soil of China, the most commonly used MPs dispersion treatment was H2O2 solution digestion, the extracting solution commonly used for density flotation was NaCl solution, and microscopic and spectroscopic measurements were typically used measurements. The results could provide a basis for monitoring the MP abundances in farmland soil and preventing the transfer of MPs pollution in soil.

Evaluating the impacts of sustainable land management practices on water quality in an agricultural catchment in Lower Austria using SWAT.

Managing agricultural watersheds in an environmentally friendly manner necessitate the strategic implementation of well-targeted sustainable land management (SLM) practices that limit soil and nonpoint source pollution losses and translocation. Watershed-scale SLM-scenario modeling has the potential to identify efficient and effective management strategies from the field to the integrated landscape level. In a case study targeting a 66-hectare watershed in Petzenkirchen, Lower Austria, the Soil and Water Assessment Tool (SWAT) was utilized to evaluate a variety of locally adoptable SLM practices. SWAT was calibrated and validated (monthly) at the catchment outlet for flow, sediment, nitrate-nitrogen (NO3-N), ammonium nitrogen (NH4-N), and mineralized phosphorus (PO4-P) using SWATplusR. Considering the locally existing agricultural practices and socioeconomic and environmental factors of the research area, four conservation practices were evaluated: baseline scenario, contour farming (CF), winter cover crops (CC), and a combination of no-till and cover crops (NT + CC). The NT + CC SLM practice was found to be the most effective soil conservation practice in reducing soil loss by around 80%, whereas CF obtained the best results for decreasing the nutrient loads of NO3-N and PO4-P by 11% and 35%, respectively. The findings of this study imply that the setup SWAT model can serve the context-specific performance assessment and eventual promotion of SLM interventions that mitigate on-site land degradation and the consequential off-site environmental pollution resulting from agricultural nonpoint sources.

Nitrogen management to minimize yield-scaled ammonia emission from paddy rice in the Middle and Lower Yangtze River Basin: A meta-analysis.

Paddy fields in China contributed to one third of the global cropland ammonia (NH3) emission inventory, while rice accounted for half of cereal consumption, necessitating exhaustive considerations of the balance between NH3 emissions abatement and food demand. The concept of yield-scaled emission intensity (emissions per unit crop production) has the potential to guide sustainable intensification strategies, yet its application to NH3 emissions remains poorly understood. Here, by constructing novel crop-specific models for single rice production and NH3 emissions in the Middle and Lower Yangtze River Basin (LYRB) as a case study, the relationships between fertilizer N application and yield-scaled NH3 were estimated. Contrary to our hypothesis of a tipping point, our results showed that yield-scaled NH3 curves could not directly identify optimal nitrogen (N) rates. However, the benefit of lower N fertilizer rate on NH3 abatement consistently outweighed the risk of yield loss. The exponential relationships between yield-scaled NH3 and N surplus allowed us to estimate the N surplus criterion as 15.6 kg N ha-1 (or 190 kg N ha-1 fertilizer N rate) for the LYRB. Under the N surplus criterion, NH3 emissions can be reduced by 23-27% without severely impacting rice yield, compared to the N rate required for the highest yield. Moreover, five major controlling factors for yield-scaled NH3 were estimated by random forest models, ranked in order of importance as N rate, total N, K rate, mean annual precipitation, and soil organic carbon. Among the agricultural practices (irrigation, tillage, and fertilizer management), deep placement was the most effective measure to reduce yield-scaled NH3, showing 48% reduction potential, followed by proper N splitting frequency (43%). Overall, this study highlights the efficacy of N application optimization and targeted farm management in mitigating NH3 emission while maintaining crop productivity.

Optimizing cultivars and agricultural management practices can enhance soybean yield in Northeast China.

Soybean is an important oil crop in China, and the national focus of soybean production is Northeast China. Crop yield is affected by climate, cultivars and agricultural management practices. Optimizing the composite impacts of these factors on soybean yield and yield gaps is crucial for the local agricultural community. In this study, we used the DSSAT-CROPGRO-Soybean model (validated based on longer-than-20-years agro-meteorological experiments data) to simulate the potential yield (Yp), attainable yield (Ya), and potential farmer's yield (Ypf) of soybean for 56 counties from 1981 to 2017 in Northeast China. Combined with actual farmer's yield (Yf), we computed different types of yield gaps. Furthermore, we optimized cultivars, agricultural management practices, and those interactions on soybean yield and yield gaps. On county-level, the Yp, Ya, Ypf and Yf averaged 5528.9, 4762.9, 3786.8 and 1918.8 kg ha-1, respectively. The total yield gap between Yf and Yp was 63.8 % of Yp. The yield gap between Ya and Yp was 12.8 %, which caused by uncontrollable factors; the yield gap between Ypf and Ya was 17.6 %, which caused by agronomic factors; and the yield gap between Yf and Ypf was 33.5 %, which caused by socioeconomic factors. During 1981-2017, climate, cultivar, sowing date and plant density change affected Ypf by -7.5, 4.5, -3.0 and - 2.0 %, respectively. By optimizing cultivar, sowing date and plant density, Ypf would increase by 13.1, 7.9 and 3.1 % and yield gap would close by 9.2, 5.6 and 2.1 %, respectively. By comprehensively optimizing cultivar, sowing date and plant density, Ypf would increase by 19.4 % and yield gap would close by 13.7 %. This work has practical significance for understanding climate, cultivar and agricultural management impacts on soybean yield, and demonstrates an effective approach, by optimizing cultivars and agricultural management practices to address climate change, increase yield and close yield gaps.

Microbial transformation of soil organic matter under varying agricultural management systems in Ukraine.

Introduction: This paper presents comparative studies on the content and structure of organic matter (OM) and the activity of microbiological cellulose destruction in three types of Ukrainian soils intensively used in agricultural production. Methods: The highest content of humus in the arable layer (4.9%), OM (410 t ha-1), and total carbon (30.9 mg C g-1 soil) was determined in chernic phaeozems, which is 2.2-2.5 times higher than in albic retisols. The soil of natural ecosystems is characterised by a high content of microbial carbon (Cmic) in the carbon fraction of organic soil compounds. Results and discussion: In arable soils, the content and reserves of humus and soil organic matter (SOM) have decreased by an average of 1.5-2 times. The most considerable loss of humus reserves in the soil profile was identified in albic retisols (1.96-1.44 times) and the smallest in chernic phaeozems (1.27-1.81 times). During the long-term systematic application of mineral fertilisers, the Corg content decreased by 8-21% in chernic phaeozems, 12-33% in greyzemic phaeozems, and 6-38% in albic retisols. A significant difference of 2.1-8.0 times was determined regarding the number of aerobic cellulolytic microorganisms and 1.3-3.3 times in the potential cellulolytic activity of the studied soils. The high number of cellulose-destroying microorganisms is characteristic of chernic phaeozems with a high content of OM in the soil; the advantage over other types of studied soils was 1.4 times and 7.8 times for greyzemic phaeozems and albic retisols, respectively. Among the studied soil types, high values of CO2 emissions were identified in chernic phaeozems. Intensive agricultural practices in Ukrainian soils have significantly altered the content and composition of organic matter, leading to reduced humus and soil organic matter reserves. The study also underscores the importance of considering the abundance of cellulose-destroying microorganisms and their potential activity in assessing soil health and sustainability.

Soil quality and microbial communities in subtropical slope lands under different agricultural management practices.

Land degradation is a major threat to ecosystem. Long-term conventional farming practices can lead to severe soil degradation and a decline in crop productivity, which are challenging for both local and global communities. This study was conducted to clarify the responses on soil physicochemical properties and microbial communities to changes in farming practices. Slope land orchards under three agricultural management practices-conventional farming (CF), organic farming (OF), and ecofriendly farming (EFF)-were included in this study. We found that soil carbon stock increased by 3.6 and 5.1 times in surface soils (0-30 cm) under EFF and OF treatments, respectively. EFF and OF significantly increased the contents of total nitrogen by 0.33-0.46 g/kg, ammonia-N by 3.0-7.3 g/kg, and microbial biomass carbon by 0.56-1.04 g/kg but reduced those of pH by 0.6 units at least, and available phosphorous by 104-114 mg/kg. The application of phosphorous-containing herbicides and chemical fertilizers might increase the contents of phosphorous and nitrate in CF soil. High abundances of Acidobacteria and Actinobacteria were observed in EFF and OF soils, likely because of phosphorous deficiency in these soils. The abundance of fungi in OF soil indicated that plants' demand for available soil phosphorous induced the fungus-mediated mineralization of organic phosphorous. High abundances of Gammaproteobacteria, Planctomycetes, Firmicutes, and Nitrospirae were observed in CF soil, possibly because of the regular use of herbicides containing phosphorous and chemical fertilizers containing high total nitrogen contents.

Drivers of Farmers' Intention to Use the Digital Agricultural Management System: Integrating Theory of Planned Behavior and Behavioral Economics.

China's fishery industry has national and international relevance whose aquaculture production accounts for more than 60 percent of the world's total aquaculture production. But the average amount of pesticides used per hectare in China is roughly five times of the world average. The abuse of chemical fertilizers and drugs has brought chronic, long-term, and cumulative harm to both human beings and environment. The digital agricultural management system should be adopted to reduce non-negligible environment pollution and the quality and safety risks of aquatic products. So, it is essential to understand the factors that may influence the adopting intention of this digital management approaches. The present study aimed to examine the adopting intention of farmers toward the digital agricultural management system using two theories-the theory of planned behavior (TPB) and the behavioral economics-as the research framework. The population was composed of farmers in the provinces of Guangdong province in south China of whom 219 farmers were sampled with stratified random sampling technique. Structural equation modeling was used to analyze the data, and it was revealed that this research framework could potentially predict intention. And we observed that the two biased belief of availability bias and loss aversion bias can be the main predictive influence factors of responsible behaviors in adopting the digital agriculture management system, which highlights the importance of framing recommendations in terms of losses rather than gain may be more effective to increase farmers' intention to adopt the digital system on their farms.