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In rice paddies, which exhibit higher ammonia (NH₃) emission factors than upland soils, identifying key drivers of NH₃ flux intensity is crucial. Contrary to the commonly held view that NH₃ flux is primarily governed by soil ammonium (NH₄⁺) concentrations, we found no significant relationship between NH₃ flux and NH₄⁺ levels in the soil during rice cultivation. To pinpoint a primary factor influencing NH₃ flux intensity under conventional rice cropping practices, we conducted a 2-year field study applying four nitrogen (N) fertilization rates (0, 45, 90, and 180 kg N ha⁻¹) using urea [(NH₂)₂CO], the most common N fertilizer. NH₃ emissions were tracked using the ventilation method. Following N application, NH₃ flux sharply increased but rapidly returned to baseline. Half of the N applied as a basal fertilizer was incorporated within the soil, contributing only 10% of total NH₃ emissions. In contrast, top-dressed applications—20% of total N at the tillering stage and 30% at panicle initiation—accounted for approximately 90% of NH₃ loss. Seasonal NH₃ flux increased quadratically with rising N application rates, correlating strongly with NH₄⁺ concentrations in floodwater rather than soil. Grain yield responded quadratically to N levels, peaking at 120 kg N ha⁻¹ with a 37% increase over control yields. NH₃ flux intensity, defined as seasonal NH₃ flux per unit of grain yield, showed a quadratic response to N fertilization, decreasing with initial fertilizer additions (up to 38 kg N ha⁻¹) but then sharply increased with further N fertilization increase. Hence, reducing NH₄⁺ concentrations in floodwater through moderated N application and deeper fertilizer placement could be essential for minimizing NH₃ volatilization in rice systems. [ABSTRACT FROM AUTHOR]

In order to achieve reasonable yield while keeping environmental risks low, nitrogen fertilizer reduction has been adopted for in rice cultivation. The response of the soil microbial community structure to this management is not fully understood. In this study, the treatments comprising conventional farming practices (330 kg ha−1), reduced N application (270 kg ha−1 and 300 kg ha−1, respectively), and a control without N application were set up in order to reveal the effects of N application rate on the soil microbial community composition in rice paddies. It was discovered that Proteobacteria, Acidobacteria, Actinobacteria, and Chloroflexi represented the most abundant bacterial phyla in all samples. The assembly of the soil bacterial community differed among the treatments, with NH4+-N, available phosphorus (AP), and organic matter (OM) as key drivers. The reduction of N application by 20% decreased soil NO3− up to 32% and increased the abundance of the total functional pathways, especially those associated with carbon fixation, N, S, and CH4 metabolism, whereas N reduction by 10% increase soil N accumulation and soil bacterial richness. In summary, a reduction of N fertilizer by up to 20% compared to the amount used in traditional practices could most effectively regulate the soil bacterial community composition and increase the predicted functional groups associated with N transformation, while maintaining lower soil nitrogen contents. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) paddies are increasingly threatened by cadmium (Cd) pollution, and potentially serve as CH4 emitters to the atmosphere. Remediation agents widely mitigate Cd pollution in paddy soil, however, we know little about their regulations on CH4 emission. Here, via adding biochar (B), sulfhydryl-modified palygorskite (SMP), and selenium foliar fertilizer (SFF), we conducted a pot experiment to investigate soil and rice Cd contents together with in-situ CH4 fluxes. Compared to CK, the addition of SMP, SFF, and B-SMP reduced Cd in brown rice by 25% to 50%, 25%, and 50% to 75%, respectively. Agents 7% B, 7% B-0.01% SMP, and SFF reduced CH4 emissions by 8.46%, 5.30%, and 4.11%, respectively. CH4 emission increased gradually along the growing season, with the cumulative CH4 fluxes ranging between 338.82 and 619.13 kg hm−2. Our results highlight that mixed 7% B-0.01% SMP and SFF showed collaborative effects on Cd remediation and CH4 emission. This study reveals the feasibility of reducing Cd pollution and CH4 emission in karst rice paddies, which hopes to supplement the knowledge of collaborative controls on soil remediation and carbon emission. [ABSTRACT FROM AUTHOR]

Unreasonable soil tillage measures have caused a sharp decline in the soil carbon (C) pool capacity of rice (Oryza sativa L.) paddy fields, have reduced soil fertility, and have threatened the safe production of rice. Based on long-term position–location experiments started in 2005, this paper systematically studied the effects of different soil tillage treatments (CT: no return of plowing straw to the field as control; CTS: return of plowing straw to the field; NTS: return of no-tillage straw to the field; RTS: return of rotary plowing straw to the field) on soil physical and chemical properties and soil organic carbon (SOC) accumulation characteristics in rice paddy fields, in order to clarify the impact of different long-term soil tillage measures on soil carbon cycle microecology in double-cropped rice paddy fields and provide a theoretical basis for soil SOC sequestration and the sustainable utilization of rice paddy fields in double-cropped rice paddy fields in southern China. The results were as follows: A total of 30.7–40.7% of the SOC stored in rice paddy fields was residue C derived from microorganisms, and 45.7–54.2% of SOC accumulation came from plant residue-derived C. Straw return treatments (CTS, RTS, and NTS) significantly increased soil lignin phenol content and promoted the accumulation of plant-derived SOC. Soil lignin phenol content in the RTS treatment was significantly higher than that in the CTS treatment (p < 0.05). Amino sugar content in rhizosphere soil was higher than that in non-rhizosphere soil. The measure of returning straw to the field increased amino sugar content in the rhizosphere and non-rhizosphere. C derived from plants was greater than that from microbial residues in double-cropped rice paddy fields in southern China. Hence, no-till/rotary tillage and straw return can improve the sequestration of soil SOC, which is of great significance for achieving "C neutrality" and alleviating the pressure on food security. [ABSTRACT FROM AUTHOR]

Fine classification and phenological information of rice paddy are of great significance for precision agricultural management. General compact polarimetric (CP) synthetic aperture radar (SAR) offers the advantage of providing rich polarimetric information, making it an important means of monitoring rice growth. Therefore, in response to the current challenges of difficulty in rice type classification and the small differences in phenological polarimetric characteristics, a novel strategy for fine classification and phenological analysis of rice paddy is proposed. This strategy thoroughly explores the polarimetric information of general CP SAR data and the target scattering characterization capabilities under different imaging modes. Firstly, the general CP SAR data is formalized using the standard CP descriptors, followed by the extraction of general CP features through the ΔαB/αB target decomposition method. optimal CP features are generated to achieve fine classification of rice paddy. Finally, 6 phenological stages of rice are analyzed based on the general CP features. The experiment results of rice classification show that the classification accuracy based on this strategy exceeds 90%, with a Kappa coefficient above 0.88. The highest classification accuracies were observed for transplanting hybrid rice paddy (T-H) and direct-sown japonica rice paddy (D-J), at 80.9% and 89.9%, respectively. The phenological evolution rule of the two rice types indicate that from early June (seedling stage) to late July (elongation stage), the CP feature variation trends of T-H and D-J are generally consistent. However, from October (mature stage) to November (harvest stage), the variation trends of the CP features for T-H and D-J are significantly different. The study found that from the booting-heading stage to the harvest stage, the linear π/4 mode outperforms circular and elliptical polarimetric modes in distinguishing different types of rice. Throughout the entire phenological period of rice growth, CP SAR of linear π/4 mode is surpasses that of other linear modes in discriminating different type of rice. The proposed strategy enables highprecision fine classification rice paddy, and the extracted general CP αB parameter effectively reflects the phenological change trends in rice growth. [ABSTRACT FROM AUTHOR]

Jarosite, a prominent mineral in oxidised acid sulfate soil, is known to sorb and incorporate a variety of elements, including Al. However, to understand the role that jarosite plays in regulating element cycles, it is crucial to understand the stability and transformation pathways of jarosite in an acid sulfate soil under dynamic biogeochemical conditions. In this study, we observed the transformation of unsubstituted jarosite and Al-substituted jarosite, collectively referred to as 'jarosite', in an acid-sulfate rice paddy topsoil and subsoil from Thailand. Jarosite was incubated in flooded paddy topsoils and subsoils for up to sixteen weeks, both in laboratory mesocosms and in the field, using bags made of polyethylene terephthalate mesh. One set of mesh bags contained jarosite that was not mixed with any other minerals, and referred to as 'pure mineral' incubations. Mineral transformations occurred under the influence of the soil porewater only and were primarily followed by X-ray diffraction analysis. A parallel set of mesh bags contained soil with 57Fe-labelled jarosite enrichment (Fe enriched in soil by a factor of 1.3 but 57Fe enrichment factor of 12.5–13.6), which allowed jarosite transformation to occur in close association with the soil matrix. Mineral transformations in 57Fe-jarosite-enriched soil were followed using 57Fe Mössbauer spectroscopy. In laboratory mesocosms and in the field, jarosite transformed most quickly in topsoil, whereas jarosite underwent limited transformation in subsoils, especially in laboratory mesocosms where Fe reduction was slow. The chemical environment around the jarosite affected the outcome of the transformation processes. Crystalline Fe oxyhydroxides, such as goethite, dominated the products in mesh bags where jarosite was not mixed with soil, whereas short-range-ordered or non-mineral Fe phases, such as Fe(II) sorbed to mineral surfaces or complexed with organic ligands, were dominant transformation products of jarosite when mixed in soil. Furthermore, Al substitution in jarosite caused contrasting effects in mesh bags containing pure minerals or mineral-enriched soil. Aluminium substitution slowed the transformation of jarosite in pure mineral mesh bags, but Al-substituted and unsubstituted jarosite showed similar transformation rates and pathways when incubated as a mixture with soil. The contrasting rate of transformation in topsoil and subsoil, the contrasting products of transformation in pure mineral mesh bags and 57Fe-jarosite-enriched soil, and the contrasting effect of Al substitution in pure mesh bags or jarosite-enriched soil, all demonstrate that the rate and products of jarosite transformation are defined by a balance between competitive transformation pathways that affect the transforming minerals. [ABSTRACT FROM AUTHOR]

The chemodiversity and thermodynamic stability of dissolvable organic matter (DOM) in paddy soil under different crop residue managements remain unclear. Using Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) analysis, we explored the molecular composition of DOM in paddy soil 4 years following incorporation of maize residue in different forms (air‐dried straw, manure and biochar). Compared to the control without amendments, manure increased the pool size of DOM but reduced its chemodiversity, while the straw and biochar amendments reduced the pool size but increased the chemodiversity of DOM by 0.22 and 0.05, respectively. Though approximately 60% of the compounds were shared among the treatments, those distinct among the treatments were shaped by residue‐derived lignin‐like compounds. Moreover, the nominal oxidation state of carbon (NOSC), which corresponds to the energy content in organic carbon, decreased with the maize residue amendments, regardless of the forms. Thus, crop residue amendments could lead to higher DOM persistence in the short‐term, potentially slowing carbon turnover in paddy soil. [ABSTRACT FROM AUTHOR]

This study aimed for a better understanding of the niche specification of bacteria carrying the tfd-genes for aerobic 2,4-dichlorphenoxyacetic acid (2,4-D) degradation in the rice paddy ecosystem. To achieve this, a dedicated microcosm experiment was set up to mimic the rice paddy system, with and without 2,4-D addition, allowing spatial sampling of the different rice paddy compartments and niches, i.e., the main anaerobic bulk soil and the aerobic surface water, surface soil, root surface and rhizosphere compartments. No effect of 2,4-D on the growth and morphology of the rice plant was noted. 2,4-D removal was faster in the upper soil layers compared to the deeper layers and was more rapid after the second 2,4-D addition compared to the first. Moreover, higher relative abundances of the 2,4-D catabolic gene tfdA and of the mobile genetic elements IncP-1 and IS1071 reported to carry the tfd-genes, were observed in surface water and surface soil when 2,4-D was added. tfdA was also detected in the root surface and rhizosphere compartment but without response to 2,4-D addition. While analysis of the bacterial community composition using high-throughput 16S rRNA gene amplicon sequencing did not reveal expected tfd-carrying taxa, subtle community changes linked with 2,4-D treatment and the presence of the plant were observed. These findings suggest (i) that the surface soil and surface water are the primary and most favorable compartements/niches for tfdmediated aerobic 2,4-D biodegradation and (ii) that the community structure in the 2,4-D treated rice paddy ecosystem is determined by a niche-dependent complex interplay between the effects of the plant and of 2,4-D. [ABSTRACT FROM AUTHOR]

Italy is the leading rice producer in Europe and the second in the Mediterranean basin (after Egypt), with most of the production concentrated in a large paddy area between the Lombardy and Piedmont regions (northern Italy). In this area, irrigation of rice was traditionally carried out by wet seeding and continuous flooding; in the last fifteen years, this technique has been gradually replaced by dry seeding followed by a delayed flooding (DFL) or by an alternation of flooding and dry periods (FTI), which are economically more advantageous. This study presents the results of an extensive monitoring campaign designed and carried out in 2021 in a representative paddy district of the Lomellina area (Pavia, northern Italy) to assess the impact of the actual rice cropping strategies on surface water and groundwater quality, with particular attention to two widely used herbicides (MCPA and clomazone) and to nutrient losses (e.g., N, P, K). Results show that MCPA and clomazone concentrations detected in surface water and groundwater are always below the RAC (Regulatory Acceptable Concentration) values. As to nutrients, they do not show significant trends along the season in surface water and groundwater: this may be due to the fact that nutrient sources are many. Concerning the concentrations, nitrates may pose a problem for the area, especially for groundwater. However, further studies would be needed to understand to which extent rice cropping can be considered the major source of contamination for water resources. [ABSTRACT FROM AUTHOR]

Biochar is widely recognized as an effective amendment for soils contaminated with cadmium (Cd). However, the properties and elemental compositions of biochar derived from different feedstocks may significantly impact the transfer of Cd in the soil-rice system. This study conducted a two-year field trial in Cd-contaminated paddy soil. Rapeseed straw biochar (REB), rice husk biochar (RHB), and bone char (BOC) were applied once at rates of 0 t ha−1 (CK) and 15 t ha−1, respectively. The results indicated that biochar significantly decreased grain Cd concentrations by on average of 60.1 % and 22.9 % in 2021 and 2022, respectively. BOC significantly decreased CaCl2-Cd concentration by on average of 52.1 % and 64.7 % during two rice growing seasons, which was higher than that of crop biochar (22.7 % and 17.8 %). Soil exchangeable Ca and dissolved P in BOC treatment were higher, and had significantly negatively correlated with CaCl2-Cd (r = -0.50; r = -0.724). REB with higher S content efficiently increased the proportion of organics and sulfides bounding Cd. Except for BOC, REB and RHB significantly enhanced Cd fixation in IP by 44.4 %-92.0 % and 42.8 %-59.5 % in two years, in which IP-bound Fe and IP-bound Cd in REB were by 10.9 % and by 9.11 %-27.4 % higher than those of RHB respectively. The electron donating capacity of REB was 2.21-folds higher than that of RHB, which could promote IP formation by enhancing Fe(Ⅲ) reduction. RHB decreased Cd transformation from roots to shoots by 20.6 %-30.3 % compared to REB and BOC. Higher Si content in rice root in RHB treatment may promote complexation and deposition of Si hemicellulose-bound Cd in the root cell walls. This study reveals the important role of biochar's elemental composition and properties in soil Cd immobilization and the mitigation of rice Cd uptake.

In rice paddies, which exhibit higher ammonia (NH₃) emission factors than upland soils, identifying key drivers of NH₃ flux intensity is crucial. Contrary to the commonly held view that NH₃ flux is primarily governed by soil ammonium (NH₄⁺) concentrations, we found no significant relationship between NH₃ flux and NH₄⁺ levels in the soil during rice cultivation. To pinpoint a primary factor influencing NH₃ flux intensity under conventional rice cropping practices, we conducted a 2-year field study applying four nitrogen (N) fertilization rates (0, 45, 90, and 180 kg N ha⁻¹) using urea [(NH₂)₂CO], the most common N fertilizer. NH₃ emissions were tracked using the ventilation method. Following N application, NH₃ flux sharply increased but rapidly returned to baseline. Half of the N applied as a basal fertilizer was incorporated within the soil, contributing only 10% of total NH₃ emissions. In contrast, top-dressed applications—20% of total N at the tillering stage and 30% at panicle initiation—accounted for approximately 90% of NH₃ loss. Seasonal NH₃ flux increased quadratically with rising N application rates, correlating strongly with NH₄⁺ concentrations in floodwater rather than soil. Grain yield responded quadratically to N levels, peaking at 120 kg N ha⁻¹ with a 37% increase over control yields. NH₃ flux intensity, defined as seasonal NH₃ flux per unit of grain yield, showed a quadratic response to N fertilization, decreasing with initial fertilizer additions (up to 38 kg N ha⁻¹) but then sharply increased with further N fertilization increase. Hence, reducing NH₄⁺ concentrations in floodwater through moderated N application and deeper fertilizer placement could be essential for minimizing NH₃ volatilization in rice systems.

Purpose: It is unclear whether a higher biochar (BC) application rate enhances rice (Oryza sativa L.) yield and reduces CH4 emissions. This study investigated changes in rice yield and CH4 emissions with varying BC application rates. Methods: Data on rice yield and CH4 emission from paddies amended with or without BC were collected from the literature, and the biochar effects were analyzed using the data set. Results: Across the biochar application rate from 2 to 48 t ha-1, the rice yield increased (by 10.8%) while the area-scaled (by 14.4%) and yield-scaled CH4 emission (by 22.2%) decreased. However, the correlation of BC application rates with rice yield and CH4 mitigation was not significant, implying that a higher BC application rate did not enhance rice yield and CH4 reduction. Interestingly, for a data set showing increased rice yield and decreased CH4 emission by BC, the magnitude of change in the rice yield and CH4 mitigation per unit weight of BC (1 t ha-1) decreased with an increase in the BC application rate. These results suggest that BC effects on rice yield and CH4 mitigation are not additive, probably because of the decreases in the inherent capacity of unit weight of BC to enhance rice yield and reduce CH4 emission, which might be caused by the adverse effects of toxic compounds contained in BC, losses of BC, and a higher degree of nutrient immobilization by BC. Conclusions: Annual BC application at a low rate (e.g., 2 t ha-1) rather than a luxury application may be an effective and economical strategy for long-term rice yield enhancement and CH4 mitigation using BC. [ABSTRACT FROM AUTHOR]

The global efforts on reducing methane (CH4) emissions was emphasized in COP 28 and the potential for improved estimation became feasible through bottom-up data acquisition with advanced remote sensing technology. The objectives of this study were to extract summer rice and winter crop cultivation areas based on satellite images and to incorporate into estimating CH4 emissions in South Korea for the year 2020. Satellite images of Sentinel-1 and Sentinel-2 were acquired from European Space Agency. Rice paddy was classified with backscattering coefficient from Sentinel-1 images, while the normalized difference vegetation index from Sentinel-2 images was used to identify winter cropping field. The equation of IPCC guidelines was used to estimate CH4 emissions by incorporating the areas of rice paddy and winter crop extracted with the respective satellite image. National farming statistics were used to determine the scaling factors for paddy organic matter and water management practices. The estimated areas for rice paddy and winter crop cultivation were 712,237 ha and 117,840 ha, respectively. The rice paddy areas were primarily concentrated in the western regions of the Korean peninsula, whereas winter crop cultivation was predominantly found in southern part of the country. The total amount of CH4 emissions was 6272 Gg CO2 eq./yr when considering rice straw and winter cropping practices into estimation (modified Tier 2 method). This represents a 7% increase compared to the method that considered solely the rice straw incorporation (current Tier 2 method). The CH4 emissions per unit area were also 8.82 tons CO2 eq./ha/yr with the modified Tier 2 method, indicating a 10% greater compared to the current Tier 2 method. Substantial CH4 emissions were primarily concentrated in western regions where extensive rice paddy cultivation occurs, while greater CH4 emissions per unit area were predominantly found in southern regions with substantial winter crop cultivation. The study findings hold importance for improving the accuracy of CH4 emissions estimation by employing bottom-up approach that utilizes satellite imagery to assess rice paddy and winter cropping areas. Further study would be needed to incorporate field-based data on rice crop management practices, such as rice straw and water management, to further refine CH4 emission estimation method. [ABSTRACT FROM AUTHOR]

Methane emissions from flooded rice paddies are a major source of atmospheric methane and represent a significant greenhouse gas with high climate-forcing potential due to anthropogenic activities globally. For sustainable agriculture, it is necessary to find effective methods for mitigating greenhouse gas emissions without reducing crop productivity. We investigated mechanisms to reduce methane emissions during rice cultivation by applying rice straw, rice husk biochar, humic acid, and a humic acid–iron complex, assessing greenhouse gases and rice yield over a single season. The results demonstrated that the treatment plots with rice straw and the humic acid–iron complex significantly reduced methane emissions (563 ± 113.9 kg ha−1) by 34.4% compared to plots treated with rice straw alone (859 ± 126.4 kg ha−1). Rice yield was not compromised compared to the control group treated with only NPK fertilizer, and growth in terms of plant height and tiller number was enhanced in the plots treated with rice straw and the humic acid–iron complex. Conversely, the plots treated solely with rice husk biochar and humic acid did not show a methane reduction effect when compared to the NPK treatment. The humic acid–iron complex has demonstrated potential as a methane mitigation agent with practical applicability in the field, warranting further long-term studies to validate its effectiveness. [ABSTRACT FROM AUTHOR]

Monitoring and conserving bird biodiversity in rice landscapes is a global challenge. Although environmental DNA (eDNA) metabarcoding can potentially provide a sensitive and comprehensive assessment of bird biodiversity in farmlands, there is a lack of research on the usefulness of eDNA samples from paddy water as sources of information on the species richness and abundance of birds. Hence, in this study, we conducted eDNA metabarcoding during the breeding seasons of birds in 2021 and 2022 in central Japan and evaluated its accuracy and comprehensiveness by comparing its performance with that of the conventional line-transect survey. More bird species (18) were detected by conducting the line-transect survey than by performing eDNA metabarcoding (8 bird species). Twelve bird species were detected only by the line-transect survey; meanwhile, two aquatic bird species, including nocturnal species, were detected by performing eDNA metabarcoding alone. The frequency of occurrence of each species among the water sample replicates was positively associated with species biomass. In addition, the frequency of occurrence was higher in aquatic birds than in terrestrial birds probably because aquatic birds intensively breed and forage in flooded rice fields, resulting in higher amounts of DNA deposition. Overall, our results suggest that although conventional bird surveys are superior to eDNA metabarcoding using paddy water samples for monitoring terrestrial bird diversity, eDNA metabarcoding plays a complementary role in assessing aquatic bird diversity.

This study aimed for a better understanding of the niche specification of bacteria carrying the tfd-genes for aerobic 2,4-dichlorphenoxyacetic acid (2,4-D) degradation in the rice paddy ecosystem. To achieve this, a dedicated microcosm experiment was set up to mimic the rice paddy system, with and without 2,4-D addition, allowing spatial sampling of the different rice paddy compartments and niches, i.e., the main anaerobic bulk soil and the aerobic surface water, surface soil, root surface and rhizosphere compartments. No effect of 2,4-D on the growth and morphology of the rice plant was noted. 2,4-D removal was faster in the upper soil layers compared to the deeper layers and was more rapid after the second 2,4-D addition compared to the first. Moreover, higher relative abundances of the 2,4-D catabolic gene tfdA and of the mobile genetic elements IncP-1 and IS1071 reported to carry the tfd-genes, were observed in surface water and surface soil when 2,4-D was added. tfdA was also detected in the root surface and rhizosphere compartment but without response to 2,4-D addition. While analysis of the bacterial community composition using high-throughput 16S rRNA gene amplicon sequencing did not reveal expected tfd-carrying taxa, subtle community changes linked with 2,4-D treatment and the presence of the plant were observed. These findings suggest (i) that the surface soil and surface water are the primary and most favorable compartements/niches for tfd-mediated aerobic 2,4-D biodegradation and (ii) that the community structure in the 2,4-D treated rice paddy ecosystem is determined by a niche-dependent complex interplay between the effects of the plant and of 2,4-D.

Rice is an important food crop for human beings. Accurately distinguishing different varieties and sowing methods of rice on a large scale can provide more accurate information for rice growth monitoring, yield estimation, and phenological monitoring, which has significance for the development of modern agriculture. Compact polarimetric (CP) synthetic aperture radar (SAR) provides multichannel information and shows great potential for rice monitoring and mapping. Currently, the use of machine learning methods to build classification models is a controversial topic. In this paper, the advantages of CP SAR data, the powerful learning ability of machine learning, and the important factors of the rice growth cycle were taken into account to achieve high-precision and fine classification of rice paddies. First, CP SAR data were simulated by using the seven temporal RADARSAT-2 C-band data sets. Second, 20-two CP SAR parameters were extracted from each of the seven temporal CP SAR data sets. In addition, we fully considered the change degree of CP SAR parameters on a time scale (ΔCPDoY). Six machine learning methods were employed to carry out the fine classification of rice paddies. The results show that the classification methods of machine learning based on multitemporal CP SAR data can obtain better results in the fine classification of rice paddies by considering the parameters of ΔCPDoY. The overall accuracy is greater than 95.05%, and the Kappa coefficient is greater than 0.937. Among them, the random forest (RF) and support vector machine (SVM) achieve the best results, with an overall accuracy reaching 97.32% and 97.37%, respectively, and Kappa coefficient values reaching 0.965 and 0.966, respectively. For the two types of rice paddies, the average accuracy of the transplant hybrid (T-H) rice paddy is greater than 90.64%, and the highest accuracy is 95.95%. The average accuracy of direct-sown japonica (D-J) rice paddy is greater than 92.57%, and the highest accuracy is 96.13%. [ABSTRACT FROM AUTHOR]

Rice cultivation serves as a significant anthropogenic source of methane (CH4) and nitrous oxide (N2O). Although N2O emissions remain relatively small compared to CH4 emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. While numerous studies have investigated nitrous oxide emissions in response to nitrogen fertilization, existing research assessing nitrous oxide emissions based on nitrogen fertilizer levels has often been limited to cultivation periods. Therefore, there is a need for comprehensive analyses covering the entire year, including the dry periods, to address nitrous oxide emissions as an important source throughout the entire agricultural cycle. In this case study, we investigated the characteristics of N2O emissions in a central region of South Korea, where a single rice-cropping cycle occurs annually over a span of three whole years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N2O emissions during rice cultivation and fallow periods. In this context, we attempted to discover the complex dynamics of N2O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We discovered that the greater contribution of cumulative N2O emissions during the fallow period made a much greater contribution (up to approximately 90%) to the whole-year N2O emissions than those during the rice cultivation period. During the fallow period from rice harvest to rice planting in the following year, variations in N2O emissions were associated with high-flux events after rainy periods on dry soils. This highlights the considerable influence of soil moisture content and weather conditions on N2O emissions during the fallow period. This affects high emission events, which in turn significantly impact the cumulative emissions over the entire period. We underscore that assessing N2O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N2O emissions, periodic gas collection throughout a year covering both rice cultivation and fallow phases is required in alignment with the monitoring of different temperature and soil moisture conditions. We captured statistical differences in cumulative N2O emissions due to nitrogen fertilization treatments across the three years. However, no significant difference was observed in the three-year average emissions among the different (one, one-and-a-half, and double) nitrogen fertilization treatments, with the exception of the control treatment (no fertilization). Based on the findings, we recommend at least three whole-year evaluations to ensure the estimation accuracy of N2O emissions under different nitrogen fertilization conditions. The findings from this study could help prepare the further revision or refinement of N2O emission factors from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC). [ABSTRACT FROM AUTHOR]

Denitrification plays a critical role in soil nitrogen (N) cycling, affecting N availability in agroecosystems. However, the challenges in direct measurement of denitrification products (NO, N2O, and N2) hinder our understanding of denitrification N losses patterns across the spatial scale. To address this gap, we constructed a data‐model fusion method to map the county‐scale denitrification N losses from China's rice fields over the past decade. The estimated denitrification N losses as a percentage of N application from 2009 to 2018 were 11.8 ± 4.0% for single rice, 12.4 ± 3.7% for early rice, and 11.6 ± 3.1% for late rice. The model results showed that the spatial heterogeneity of denitrification N losses is primarily driven by edaphic and climatic factors rather than by management practices. In particular, diffusion and production rates emerged as key contributors to the variation of denitrification N losses. These findings humanize a 38.9 ± 4.8 kg N ha−1 N loss by denitrification and challenge the common hypothesis that substrate availability drives the pattern of N losses by denitrification in rice fields. [ABSTRACT FROM AUTHOR]

To understand how certain types of agroecosystem management provide resources for biodiversity and conservation opportunities beyond protected areas, it is necessary to consider the cumulative effects on a local scale. Our study focuses on a rice-Pantanal wetland agricultural system within Brazil, where our goals were: i) to quantify the impact of rice paddies on taxonomic, functional, and phylogenetic diversity metrics of small mammals as biodiversity indicators, ii) to compare diversity indices based on incidence and abundance data. We carried out a thorough assessment to sample small mammal species in both the rice paddy and the adjacent legal reserve by employing a multiple diversity metrics approach. We captured the small mammals until reaching saturation on the species accumulation curve over 12,774 trap nights, resulting in 447 individuals, 10 species, including seven rodents and three marsupial species. Abundance-based beta-diversity between rice-paddy and forest reserve were higher (0.95) than incidence-based estimate (0.33). The species composition differed between the legal reserve (8 spp.) and the rice paddy (7 spp.), with the reserve exhibiting higher taxonomic diversity values compared to the rice paddy. In terms of functional and phylogenetic diversity, overall, the rice paddy exhibited higher values for the incidence-based metrics and the abundance-based metrics indicated that the reserve was more diverse. We conclude that Neotropical Pantanal rice fields retain substantial functional and phylogenetic diversities, providing suitable habitats for species thriving in open and semi-aquatic environments. Simultaneously, the legal reserve retains an essential aspect of functional diversity, when considering abundance, needed to maintain ecosystem resilience and stability. Proper abundance estimation is thus a key parameter for accurately evaluating the role of agricultural landscapes as biodiversity conservation opportunities beyond protected areas. Abundance-based indices should be used to correctly evaluate the contribution of each habitat to agroecosystem sustainability, especially in seasonal or extreme event-prone environments.

Rice paddy is one of the key crops of Korean agriculture and it has long been regarded as an important crop. Due to the high self-sufficiency of rice in Korea, the need to establish systematic rice paddy field data is increasing, and rice paddy research using remote sensing is being conducted several times in Korea. The optical satellite remote sensing method faces difficulties in data acquisition due to the abundance of clouds caused by the summer monsoon season, a characteristic of the domestic climate. However, the drone remote sensing method equipped with an optical sensor has the advantage of being able to freely acquire data, avoiding periods with high cloud cover. In this study, a drone equipped with a multispectral optical sensor was utilized to measure the height of rice paddy. Compared to satellites, drones provide the advantage of flexible timing for observations, allowing for the acquisition of high-frequency time-series data according to specific preferences. In this study, we seek to obtain values related to rice growth rates by analyzing optical data acquired through drone remote sensing. The DJI MAVIC 2 PRO drone was employed, and the Metashape program was utilized to generate a highresolution digital elevation model (DEM) from optical data. After the harvest period, rice-free rice paddy data were assumed to be digital terrain model (DTM), the height of the rice paddies. During the rice growth period, a digital surface model (DSM) was generated from drone imagery, and by calculating the difference between DSM and DTM, the height and growth of the rice plants were observed. Using network GPS measurement data, we validated monthly DEM models. This allowed us to anticipate the acquisition of precise rice growth data throughout the year, from planting to harvest.

Abstract Large river deltas are usually ecologically important wetland habitats, but also fertile agricultural exploitation areas, creating a conflict of long‐running substantial interest between agricultural expansion and wetland conservation. Over the past several years, large‐scale cultivation of water‐consuming rice has been growing rapidly in the semi‐arid climate of the Yellow River Delta (YRD). Timely monitoring of rice cultivation dynamics is of great significance for sustainable ecological conservation of the delta, which has insufficient freshwater resources. This study proposed a stratified metrics‐based method that integrates statistical spectral indices and phenological metrics at different growing stages to improve the accuracy of rice paddy classification in areas where rice and wetlands coexist. We applied the method to time‐series Sentinel‐1/2 images to produce annual rice paddy maps of the YRD from 2016 to 2021. Together with rice paddy data from 2011 to 2015 from Statistical Yearbooks of Dongying Bureau of Statistics, we investigated the expansion dynamics over the past decade and in this paper discuss the advantages and disadvantages of rice cultivation expansion over wetland ecosystem conservation. Rapid expansion of rice cultivation intensifies water conflicts, and adversely affects wetland restoration in the YRD. Considering the important ecological services of rice paddies as alternative habitats, we argue for maintaining a reasonable scale of rice paddies and optimizing their distribution as a potential solution to achieving the overall sustainable conservation of the YRD in the context of water scarcity.

Given the extensive rice paddy fields in South Korea, accurate simulation of hydrological behavior in these fields is critical due to their considerable water resource usage. The soil and water assessment tool (SWAT) is commonly used to simulate watershed water flows and quality, including those in rice paddy fields. However, it lacks comprehensive consideration of submerging water conditions typical to South Korean rice paddies. Therefore, this study introduced a modification to the SWAT model to better simulate these conditions and assessed its feasibility in two distinct watersheds. The first application evaluated the impact of submerging water conditions on surface, subsurface, and base flows. The second assessed the impact of combined submerging water and fertilization conditions on the flow and water quality within the watershed. The findings indicated that submerging water conditions significantly affected runoff, and that water quality was responsive to different fertilization scenarios. [ABSTRACT FROM AUTHOR]

To discriminate rice paddies in the Sefidroud Irrigation Network with minimal training data, we developed a Rule-based Rice Discriminate Algorithm (RRDA) and applied it to Sentinel-2 images from 2018. We compared the results with three alternative classification approaches: unsupervised classification (USV), random forests (RF), and support vector machine (SVM), as well as local data from the latest version of the Guilan cadastral map. Our findings reveal that while RF and SVM perform similarly in terms of overall accuracy and Kappa coefficients, RF excels in discriminating rice paddies, and SVM accurately identifies water bodies. The USV method, with an overall accuracy of 75% and a Kappa of 0.636, demonstrates less desirable accuracy for rice paddy discrimination. Although RRDA's accuracy assessment was slightly lower than SVM, it indicates better discrimination of rice paddies and higher compliance with the cadastral map. Using RRDA, we estimated the area of rice paddies in the Sefidroud Irrigation and Drainage Network to be 156,170 ha, significantly different from the latest statistical data reported by the Guilan Regional Water Authority (186,722.96 ha). [ABSTRACT FROM AUTHOR]

Veterinary antibiotics (VAs) have been indiscriminately used in animal feed for the past five decades to increase and ensure profits with negligible environmental considerations. The VAs amoxicillin (AMX), chlortetracycline (CTC), and oxytetracycline (OTC), which can be unintentionally introduced by irrigation water during rice cultivation, were evaluated for their phytotoxic effects, absorption–translocation into plants, and soil residues using a randomized complete block design. It was found that exposure to VAs can severely affect the photosynthetic pathway of rice plants. The uptake and translocation of VAs by rice plants varied significantly. CTC and OTC translocated more easily than AMX, a member of the β-lactam class, which accumulated at the lowest concentration compared to CTC and OTC across all treatments. Rice yield was about 4.3–5.7% lower in the experimental plots that received fifty-fold the background levels of VAs compared to the control. The findings indicate that these widely used veterinary antibiotics can hamper crop production, leave residues in the soil, and constitute a risk to human health if introduced into the agro-ecosystem unintentionally. [ABSTRACT FROM AUTHOR]

Biochar is an efficacious amendment for mitigating nitrous oxide (N2O) emissions in soils. Nevertheless, the underlying mechanisms responsible for reduced N2O emissions by biochar in paddy soils remain inadequately elucidated. Here, using two typical paddy soils with contrasting pH values (5.40 and 7.56), the N2 and N2O fluxes and the associated functional genes were investigated in soil amended with varying amounts of biochar (0%, 0.5%, and 5%, weight/weight) via soil slurry incubation integrated with the N2/Ar technique and qPCR analysis. The results showed that N2O fluxes were significantly (p < 0.05) reduced by 0.65–3.64 times following biochar amendment, concomitant with a significant (p < 0.05) increase in N2 fluxes (5.47–46.14%) in both acidic and alkaline paddy soils. As a result, the N2O/(N2O + N2) ratios were significantly (p < 0.05) reduced by 1.53–4.65 fold in both soil types. In acidic paddy soils, the enhanced denitrification rates and the decreased N2O/(N2O + N2) ratios exhibited a strong correlation with increased pH values. In alkaline paddy soil, these changes were ascribed to the enhanced nosZ Clade I gene abundance and nosZ/(nirS + nirK) ratio. Our findings reveal that biochar primarily mitigates N2O emissions in paddy soils by promoting its reduction to N2. [ABSTRACT FROM AUTHOR]

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Abstract Understanding productivity in agricultural ecosystems is important, as it plays a significant role in modifying regional carbon balances and capturing carbon in the form of agricultural yield. This study in particular combines information from flux determinations using the eddy covariance (EC) methodology, process‐based modeling of carbon gain, remotely (satellite) sensed vegetation indices (VIs), and field surveys to assess the gross primary production (GPP) of rice, which is a primary food crop worldwide. This study relates two major variables determining GPP. The first is leaf area index (LAI) and carboxylation capacity of the rice canopy (Vcuptake), and the second being MODIS remotely sensed vegetation indices (VIs). Success in applying such derived relationships has allowed GPP to be remotely determined over the seasonal course of rice development. The relationship to VIs of both LAI and Vcuptake was analyzed first by using the regression approaches commonly applied in remote sensing studies. However, the resultant GPP estimations derived from these generic models were not consistently accurate and led to a large proportion of underestimations. The new, alternative approach developed to estimate LAI and Vcuptake uses consistent development curves for rice (i.e., relies on consistent biological regulations of plant development). The modeled GPP based on this consistent development curve for both LAI and Vcuptake agreed with R2 from 0.76 to 0.92 (within the 95% confidence interval). The results of this study demonstrate that improved linkages between ground‐based survey data, eddy flux measurements, process‐based models, and remote sensing data can be constructed to estimate GPP in rice paddies. This study suggests further that the conceptual application of the consistent development curve, such as the combining of different scale measurements, has the potential to predict GPP better than the common practice of utilizing simple linear models, when seeking to estimate the critical parameters that influence carbon gain and agricultural yields.

Abstract The application of novel bioorganic fertilizer (BIO) has been established as a weed biocontrol strategy, and reduce herbicides pollution and negatively effects on agricultural ecosystems. However, its long-term influences on soil bacterial communities are unknown. Here, 16 S rRNA sequencing to identify the changes that occur in soil bacterial community and enzyme under BIO treatments after five years in a field experiment. BIO application effectively controlled weeds, however no obvious differences between treatments were observed under BIO-50, BIO-100, BIO-200 and BIO-400 treatment. Anaeromyxobacter and Clostridium_ sensu_ stricto_1 were the two dominant genera among BIO-treated soil samples. The BIO-800 treatment had a slight influence on the species diversity index, which was more remarkable after five years. The seven significantly-different genera between BIO-800 treatment and untreated soils included C._sensu_stricto_1, Syntrophorhabdus, Candidatus_Koribacter, Rhodanobacter, Bryobacter, Haliangium, Anaeromyxobacter. In addition, BIO application had different effects on soil enzymatic activities and chemical properties. The extractable P and pH saliency correlated with Haliangium and C._Koribacter, and C._sensu_stricto_1 observably correlated with exchangeable K, hydrolytic N and organic matter. Taken together, our data suggest that BIO application effectively controlled weeds and a slight influence on soil bacterial communities and enzymes. These findings expand our knowledge of the application of BIO as widely used as a sustainable weed control in rice paddy.

Carbon dioxide (CO2) and methane (CH4) are the most important two greenhouse gases in the atmosphere which were closely coupled between terrestrial ecosystems and the atmosphere. However, the relationship between CO2 and CH4 fluxes of rice paddy at different temporal scales is still unclear. Based on 6 years of eddy covariance measurements on a flooded rice paddy field in Eastern China, the relationship between gross primary productivity (GPP) and CH4 fluxes and the effects of biophysical and environmental factors on daily CH4/GPP were investigated. CH4 fluxes and GPP were tightly linked at diurnal and seasonal scales. On average, half‐hourly CH4 fluxes lagged GPP by 1.5 hr while daily GPP lagged CH4 fluxes by 19 days over the growing season. Leaf area index, water table depth (WTD), air temperature, vapor pressure deficit, and canopy conductance significantly affect daily CH4/GPP. A semi‐empirical multiplicative model was able to capture 77% and 84% seasonal variability of daily CH4/GPP for the training data set and testing data set, respectively. WTD is a crucial input affecting the performance of the model. Without WTD included, the agreement between estimated and observed daily CH4/GPP was weakened. Under the condition without WTD data available, separate calibration of the semi‐empirical multiplicative model before and after panicle initiation could improve the estimation of daily CH4/GPP to some extent. The findings in this study enhance our understanding regarding the complex interactions between CH4 fluxes and GPP in the rice paddy and are helpful for better estimation of CH4 fluxes from GPP. Plain Language Summary: This study investigated the relationship between CH4 fluxes and gross primary productivity (GPP) during the growing seasons on a rice paddy field. Results showed CH4 fluxes and GPP were tightly linked at diurnal and seasonal scales. Half‐hourly CH4 fluxes lagged GPP by 1.5 hr while daily GPP lagged CH4 fluxes by 19 days over the growing season. The long time lag of daily GPP relative to daily CH4 fluxes was mainly caused by the water management‐induced fast decline of CH4 fluxes after rice ripened. Due to the significant effects of biophysical and environmental factors on daily CH4/GPP, a semi‐empirical multiplicative model with the above factors as inputs was able to capture 77% and 84% seasonal variability of daily CH4/GPP for the training data set and testing data set, respectively. Without WTD included in the model, the agreement between estimated and observed daily CH4/GPP was weakened. Therefore, it is a very useful finding to promote our understanding of the complex interactions between CH4 fluxes and GPP in the rice paddy for better estimation of CH4 fluxes from GPP. Key Points: The positive relationship between CH4 fluxes and gross primary productivity (GPP) was observed at diurnal and seasonal scales during the rice paddy growing seasonOn average, half‐hourly CH4 fluxes lagged GPP by 1.5 hr while daily GPP lagged CH4 fluxes by 19 days over the growing seasonA semi‐empirical multiplicative model was able to capture the seasonal variability of daily CH4/GPP well [ABSTRACT FROM AUTHOR]

Large river deltas are usually ecologically important wetland habitats, but also fertile agricultural exploitation areas, creating a conflict of long‐running substantial interest between agricultural expansion and wetland conservation. Over the past several years, large‐scale cultivation of water‐consuming rice has been growing rapidly in the semi‐arid climate of the Yellow River Delta (YRD). Timely monitoring of rice cultivation dynamics is of great significance for sustainable ecological conservation of the delta, which has insufficient freshwater resources. This study proposed a stratified metrics‐based method that integrates statistical spectral indices and phenological metrics at different growing stages to improve the accuracy of rice paddy classification in areas where rice and wetlands coexist. We applied the method to time‐series Sentinel‐1/2 images to produce annual rice paddy maps of the YRD from 2016 to 2021. Together with rice paddy data from 2011 to 2015 from Statistical Yearbooks of Dongying Bureau of Statistics, we investigated the expansion dynamics over the past decade and in this paper discuss the advantages and disadvantages of rice cultivation expansion over wetland ecosystem conservation. Rapid expansion of rice cultivation intensifies water conflicts, and adversely affects wetland restoration in the YRD. Considering the important ecological services of rice paddies as alternative habitats, we argue for maintaining a reasonable scale of rice paddies and optimizing their distribution as a potential solution to achieving the overall sustainable conservation of the YRD in the context of water scarcity. [ABSTRACT FROM AUTHOR]

This study investigated, using the closed chamber method, the impact of (1) vegetation community type (Typha latifolia, Cyperus papyrus and Phragmites mauritianus) in a natural tropical freshwater marsh wetland (marsh) and (2) conversion of a natural tropical freshwater marsh into a rice paddy wetland (rice paddy), on nitrous oxide (N2O) emission. Both the marsh and the rice paddy were continuously flooded, while the rice paddy was unfertilized. Average N2O emission from the marsh did not vary significantly (p > 0.05) among the vegetation communities, ranging from 0.5 to 0.6 μg m−2 h−1. Similarly, these N2O emission rates were not significantly different (p > 0.05) from those recorded in the rice paddy (0.7 ± 2.8 [SE] μg m−2 h−1). There was no significant correlation (p > 0.05) between environmental parameters and N2O emission. We concluded that vegetation community type does not affect N2O emission from natural tropical freshwater marshes under continuous flooding. Further, converting natural tropical freshwater marshes into continuously flooded and unfertilized rice paddies does not affect N2O emission but instead enhances carbon emission, as was depicted by the significantly lower (p > 0.05) soil organic carbon content in the rice paddy. In view of climate change mitigation, therefore, wetland management should give priority to the conservation/protection of natural wetlands. HIGHLIGHTS Vegetation community type does not affect N2O emission from continuously flooded natural tropical wetlands.; Continuously flooded and unfertilized rice paddies are not N2O emission hotspots but are significant carbon sources.; N2O emission from continuously flooded tropical wetlands is not affected by seasonal changes.; Conserving natural wetlands, rather than converting them into rice paddies, enhances climate change mitigation.;

In order to improve transplanter performance and mat characteristics in mat-type paddy tray nurseries in paddy cultivation and to increase the paddy seedling quality and yield, a soil mix fertilizer with vermicompost and farmyard manure was optimized in different proportions. The investigation provides valuable insights for optimizing paddy cultivation practices, with emphasis on the potential of a specific treatment TC7, composed of 50% vermicompost, 30% farmyard manure, and 20% soil, to contribute to more robust and productive paddy cultivation systems. The TC7 treatment showed notable results, including highest average paddy seed germination (93.00 ​± ​2.24%), significant paddy seedling height (16.85 ​± ​1.72 ​cm), balanced root-to-shoot ratio (0.72 ​± ​0.013), robust seedling vigour index (1567.05 ​± ​121.45), substantial biomass production (0.481 ​± ​0.0010 ​g), and significant dry matter production (0.0422 ​± ​0.0029 ​g). The highest mat thickness of 28.10 ​± ​0.05 ​mm and the lowest mat weight per m2 area of 22.30 ​± ​1.56 ​kg/m2 was recorded in TC4 treatment containing 44% vermicompost, 44% farmyard manure, and 12% soil. The highest rolling quality of the mat with a rolling score of 10.00 ​± ​0.027 in TC8 treatment containing 30% vermicompost, 50% farmyard manure, and 20% soil, and the maximum mat strength of 54.90 ​± ​3.82 ​kg/m2 in TC10 treatment (soil alone). Mechanical transplanter performance exhibited superiority maximum planted hills per meter run (7 ​± ​1), optimum seedlings per hill (3), minimum occurrences of missing hills (1), and a maximum plant population per m2 (116 ​± ​5) utilizing seedling mats prepared with TC7 treatment. The highest grain yield of 4180 ​± ​449 ​kg/ha and grain straw ratio of 0.88 ​± ​0.0317 was recorded in the TC7 treatment. Thus, this study recommends fine-tuning and adopting the TC7 treatment combination to facilitate sustainable smart farming practices in India. Farmers are encouraged to consider implementing TC7 treatment combinations to elevate the quality and productivity of paddy cultivation.

Rice feeds about half of the world's population. The intensification of rice farming has threatened biodiversity and ecosystem services, such as pest control. A growing body of evidence suggests that Environmentally or wildlife‐friendly farming (EFF) can be effective in biodiversity conservation. However, its dependence on spatial and temporal scales of EFF implementation and surrounding semi‐natural habitats has remained largely unknown.We evaluated the effects of three types of EFF (organic farming, winter flooding and integrated pest management [IPM]) against conventional farming on plants, spiders and waterbirds in Japan. Through systematic surveys of 254 rice fields across rice production areas, we monitored EFF implementation at field and landscape scales, considering the time since transition to EFF and the surrounding semi‐natural areas.EFF implementation at the field scale, such as organic farming, was found to have positive effects on plant richness and spider abundance, whereas the percent area of EFF fields within a 200‐m radius positively affected Ardeidae abundance. However, as the percent area of surrounding semi‐natural habitats increased, the difference in the plant richness between organic and other fields decreased.Prolonged implementation periods of IPM or winter flooding, together with a reduction of more than 50% in synthetic fertilisers and pesticides from conventional agriculture, led to an increase in the spider abundance. Conversely, no clear positive effect of longer implementation periods of organic farming resulted in similar spider abundance in the three EFF types after 20 years.Synthesis and applications: This suggests that the benefits of EFF depend on their spatial and temporal scales and the surrounding semi‐natural areas. We propose that such a context dependency should be considered in future policy. Our findings also provide a starting point for future research to test the mixed biodiversity benefits of EFF across cropland types and around the world. [ABSTRACT FROM AUTHOR]

The application of novel bioorganic fertilizer (BIO) has been established as a weed biocontrol strategy, and reduce herbicides pollution and negatively effects on agricultural ecosystems. However, its long-term influences on soil bacterial communities are unknown. Here, 16 S rRNA sequencing to identify the changes that occur in soil bacterial community and enzyme under BIO treatments after five years in a field experiment. BIO application effectively controlled weeds, however no obvious differences between treatments were observed under BIO-50, BIO-100, BIO-200 and BIO-400 treatment. Anaeromyxobacter and Clostridium_ sensu_ stricto_1 were the two dominant genera among BIO-treated soil samples. The BIO-800 treatment had a slight influence on the species diversity index, which was more remarkable after five years. The seven significantly-different genera between BIO-800 treatment and untreated soils included C._sensu_stricto_1, Syntrophorhabdus, Candidatus_Koribacter, Rhodanobacter, Bryobacter, Haliangium, Anaeromyxobacter. In addition, BIO application had different effects on soil enzymatic activities and chemical properties. The extractable P and pH saliency correlated with Haliangium and C._Koribacter, and C._sensu_stricto_1 observably correlated with exchangeable K, hydrolytic N and organic matter. Taken together, our data suggest that BIO application effectively controlled weeds and a slight influence on soil bacterial communities and enzymes. These findings expand our knowledge of the application of BIO as widely used as a sustainable weed control in rice paddy. [ABSTRACT FROM AUTHOR]

Crop straw retention in the rice-based rotation cropland has been widely accepted as an effective method to improve soil quality in China. Rice–wheat rotation cropland is one the most prevalent rice-based rotation patterns, where it only exploits a small proportion of the total agricultural land yet feeds the majority of the Chinese population. Previous studies indicated that the incorporation of fore-rotating crop straw can effectively facilitate soil carbon sequestration in rice paddy fields. However, the application of crop straw may increase methane (CH4) emissions from rice paddies due to the anaerobic soil condition. To mitigate CH4 emissions from rice paddies while still preserving their soil carbon sequestration ability, a field experiment was conducted in the 2012–2016 rice growing seasons to determine the optimal low-carbon crop straw retention strategy. Five treatments with different wheat straw retention strategies were employed in this study, including non-fertilization and non-straw (Control), conventional fertilization without straw incorporation (CF), conventional fertilization with wheat straw incorporation (FS), slow-release fertilizer combined with wheat straw (SFS), and conventional fertilization with wheat-straw-derived biochar (FB). The results indicated that FS, SFS, and FB treatments significantly increased soil carbon sequestration in comparison with CF treatment. However, the increment of soil carbon sequestration was offset by raw wheat straw induced excess CH4 emissions under FS and SFS treatments. In contrast, the application of wheat-straw-derived biochar significantly promoted soil carbon sequestration, but showed no significant effect on CH4 emissions. Collectively, to the farmers, who aim to achieve agricultural carbon neutrality, the application of straw-derived biochar is worthy of consideration in rice cultivation processes. [ABSTRACT FROM AUTHOR]

Understanding productivity in agricultural ecosystems is important, as it plays a significant role in modifying regional carbon balances and capturing carbon in the form of agricultural yield. This study in particular combines information from flux determinations using the eddy covariance (EC) methodology, process‐based modeling of carbon gain, remotely (satellite) sensed vegetation indices (VIs), and field surveys to assess the gross primary production (GPP) of rice, which is a primary food crop worldwide. This study relates two major variables determining GPP. The first is leaf area index (LAI) and carboxylation capacity of the rice canopy (Vcuptake), and the second being MODIS remotely sensed vegetation indices (VIs). Success in applying such derived relationships has allowed GPP to be remotely determined over the seasonal course of rice development. The relationship to VIs of both LAI and Vcuptake was analyzed first by using the regression approaches commonly applied in remote sensing studies. However, the resultant GPP estimations derived from these generic models were not consistently accurate and led to a large proportion of underestimations. The new, alternative approach developed to estimate LAI and Vcuptake uses consistent development curves for rice (i.e., relies on consistent biological regulations of plant development). The modeled GPP based on this consistent development curve for both LAI and Vcuptake agreed with R2 from 0.76 to 0.92 (within the 95% confidence interval). The results of this study demonstrate that improved linkages between ground‐based survey data, eddy flux measurements, process‐based models, and remote sensing data can be constructed to estimate GPP in rice paddies. This study suggests further that the conceptual application of the consistent development curve, such as the combining of different scale measurements, has the potential to predict GPP better than the common practice of utilizing simple linear models, when seeking to estimate the critical parameters that influence carbon gain and agricultural yields. [ABSTRACT FROM AUTHOR]

Alien species represent one of the causes of biodiversity loss, both in natural and anthropic environments. This study contributes to the assessment of alien species impact on Western Po Plain rice field cultivations, referring to different agricultural management practices and ecological traits. Flora and vegetation were studied (the latter through the phytosociological method), and α-biodiversity was estimated through Shannon and Simpson Indices. Results highlighted a significant floristic contingent depletion and increase in therophyte and alien components, compared to pre-existing studies (1950s); higher α-biodiversity levels in organic farms, compared to conventional farms, but also a higher invasive alien species percentage. The high deterioration of the territorial–landscape context appears to play a major role in shaping these patterns. Some of these alien species are particularly aggressive (e.g., Murdannia keisak), as confirmed by two experimental rice field plots which were left unharvested, continuously flooded, making it possible to assess the competitiveness between weed species. The detected weed vegetation is attributed to the Oryzo sativae-Echinochloetum cruris-galli association, already described for Southern Europe, with two different ecological and floristic variants. Future studies, by including other sites and framing their territorial–landscape context, may further complement this overview on the alien species distribution and behavior in rice fields, hence facilitating their strategic management. [ABSTRACT FROM AUTHOR]

The Denitrification-Decomposition (DNDC)-Rice is a mechanistic model which is widely used for the simulation and estimation of greenhouse gas emissions [nitrous oxide (N2O)] from soils under rice cultivation. N2O emissions from paddy fields in South Korea are of high importance for their cumulative effect on climate. The objective of this study was to estimate the N2O emissions and biogeochemical factors involved in N2O emissions such as ammonium (NH4+) and nitrate (NO3−) using the DNDC model in the rice-growing regions of South Korea. N2O emission was observed at every application of fertilizer and during end-season drainage at different rice-growing regions in South Korea. Maximum NH4+ and NO3− were observed at 0–10 cm depth of soil. NH4+ increased at each fertilizer application and no change in NO3− was observed during flooding. NH4+ decreased and NO3− increased simultaneously at end-season drainage. Minimum and maximum cumulative N2O emissions were observed at Chungcheongbuk-do and Jeju-do regions of South Korea, respectively. The simulated average cumulative N2O emission in rice paddies of South Korea was 1.37 kg N2O-N ha−1 season−1. This study will help in calculating the total nitrogen emissions from agriculture land of South Korea and the World. HIGHLIGHTS We successfully simulated N2O emission from rice paddy fields of South Korea.; DNDC model was used to estimate N2O emission in South Korea.; Biogeochemical factors of soil such as NH4+ and NO3− concentration were also focused upon.; Simulated N2O emission in this study was strongly correlated as R2 =0.88–0.90.; Results may help to estimate the nitrogen budget of South Korea as well as the world.;

Agricultural lands have been increasingly reported to be contaminated by metals and metalloids, leading to exposure to these toxins for humans and wildlife. Previous studies on metal/metalloid contamination have reported biomagnification of total elemental Hg (THg) and, less consistently, of Cd, in both aquatic and terrestrial ecosystems. Whether other metals or metalloids can biomagnify in food webs, especially those that produce food for humans, is uncertain. We aimed to compare metal/metalloid contamination and their biomagnification patterns between rice paddy and sugarcane agroecosystems. We collected samples at an inactive Pb-Zn mine site, and two reference sites in southwestern Guangxi, southern China. Samples were widely distributed across the food web, including soil, rice grain and leaves, sugarcane leaves, crickets, grasshoppers, spiders, and frogs. We found that Cr, Cd, Pb, THg, and Zn were the metals associated with mining activities, while As and Cu were higher at the reference sites. In soil, and in the majority of species for which there were significant differences between agroecosystems, concentrations of Cd, Cr, Cu, Pb, THg, and Zn were higher in rice, suggesting that the rice paddy ecosystem is particularly sensitive to metal contamination. When quantitatively rating the patterns of biomagnification using post-hoc multiple comparisons among species’ bioaccumulation factors (BAFs), rice paddies had stronger patterns of biomagnification (3 strong relationships [e.g., all insectivores had higher or as high BAFs compared to all other species], 7 medium relationships [e.g., one of the insectivores had the highest BAFs, but another had an intermediary value, similar to an herbivore], 6 weak [e.g., one insectivore had the highest BAFs, but the other was as low as a primary producer], and 3 no relationships [e.g., no significant differences among species in BAFs]) than sugarcane ecosystems (1 strong, 2 medium, 8 weak, and 9 no relationships; Repeated measures t-test, P-value = 0.0023) across 6 metals (Cr, Cd, Cu, Hg, Pb, Zn). The strongest biomagnification was evident for THg and Zn, whereas an intermediary level of biomagnification was found for Cd, Cr, Cu, and Pb; biodilution was observed for As and Mn. Therefore, focusing on metal/metalloid apportionment to better understand the sources of the metals at our study sites would be of utility to lower the exposure of wildlife and people. Most importantly, the local authorities should check metal concentrations in any farming product from the mining area and even the close reference site to safeguard human health.

Farmlands fertilized with livestock manure-derived amendments have become a hot topic in the dissemination of antibiotic resistance genes (ARGs). Field ponding water connects rice paddies with surrounding water bodies, such as reservoirs, rivers, and lakes. However, there is a knowledge gap in understanding whether and how manure-borne ARGs can be transferred from paddy soil into field ponding water. Our studies suggest that the manure-derived ARGs aadA1, bla1, catA1, cmlA1-01, cmx(A), ermB, mepA and tetPB-01 can easily be transferred into field ponding water from paddy soil. The bacterial phyla Crenarchaeota, Verrucomicrobia, Cyanobacteria, Choloroflexi, Acidobacteria, Firmicutes, Bacteroidetes, and Actinobacteria are potential hosts of ARGs. Opportunistic pathogens detected in both paddy soil and field ponding water showed robust correlations with ARGs. Network co-occurrence analysis showed that mobile genetic elements (MGEs) were strongly correlated with ARGs. Our findings highlight that manure-borne ARGs and antibiotic-resistant bacteria in paddy fields can conveniently disseminate to the surrounding waterbodies through field ponding water, posing a threat to public health. This study provides a new perspective for comprehensively assessing the risk posed by ARGs in paddy ecosystems. [ABSTRACT FROM AUTHOR]

Rice is a globally significant staple food crop. Therefore, it is crucial to have adequate tools for monitoring changes in the extent of rice paddy cultivation. Such a system would require a sustainable and operational workflow that employs open-source medium to high spatial and temporal resolution satellite imagery and efficient classification techniques. This study used similar phenological data from Sentinel-2 (S2) optical and Sentinel-1 (S1) Synthetic Aperture Radar (SAR) satellite imagery to identify paddy rice distribution with deep learning (DL) techniques. Using Google Earth Engine (GEE) and U-Net Convolutional Neural Networks (CNN) segmentation, a workflow that accurately delineates smallholder paddy rice fields using multi-temporal S1 SAR and S2 optical imagery was investigated. The study′s accuracy assessment results showed that the optimal dataset for paddy rice mapping was a fusion of S2 multispectral bands (visible and near infra-red (VNIR), red edge (RE) and short-wave infrared (SWIR)), and S1-SAR dual polarization bands (VH and VV) captured within the crop growing season (i.e., vegetative, reproductive, and ripening). Compared to the random forest (RF) classification, the DL model (i.e., ResU-Net) had an overall accuracy of 94% (three percent higher than the RF prediction). The ResU-Net paddy rice prediction had an F1-Score of 0.92 compared to 0.84 for the RF classification generated using 500 trees in the model. Using the optimal U-Net classified paddy rice maps for the dates analyzed (i.e., 2016–2020), a change detection analysis over two epochs (2016 to 2018 and 2018 to 2020) provided a better understanding of the spatial–temporal dynamics of paddy rice agriculture in the study area. The results indicated that 377,895 and 8551 hectares of paddy rice fields were converted to other land-use over the first (2016–2018) and second (2018–2020) epochs. These statistics provided valuable insight into the paddy rice field distribution changes across the selected districts analyzed. The proposed DL framework has the potential to be upscaled and transferred to other regions. The results indicated that the approach could accurately identify paddy rice fields locally, improve decision making, and support food security in the region. [ABSTRACT FROM AUTHOR]

The response of soil biotas to climate change has the potential to regulate multiple ecosystem functions. However, it is still challenging to accurately predict how multiple climate change factors will affect multiple ecosystem functions. Here, we assessed the short‐term responses of agroecosystem multifunctionality to a factorial combination of elevated CO2 (+200 ppm) and O3 (+40 ppb) and identified the key soil biotas (i.e., bacteria, fungi, protists, and nematodes) concerning the changes in the multiple ecosystem functions for two rice varieties (Japonica, Nanjing 5055 vs. Wuyujing 3). We provided strong evidence that combined treatment rather than individual treatments of short‐term elevated CO2 and O3 significantly increased the agroecosystem multifunctionality index by 32.3% in the Wuyujing 3 variety, but not in the Nanjing 5055 variety. Soil biotas exhibited an important role in regulating multifunctionality under short‐term elevated CO2 and O3, with soil nematode abundances better explaining the changes in ecosystem multifunctionality than soil biota diversity. Furthermore, the higher trophic groups of nematodes, omnivores‐predators served as the principal predictor of agroecosystem multifunctionality. These results provide unprecedented new evidence that short‐term elevated CO2 and O3 can potentially affect agroecosystem multifunctionality through soil nematode abundances, especially omnivores‐predators. Our study demonstrates that high trophic groups were specifically beneficial for regulating multiple ecosystem functions and highlights the importance of soil nematode communities for the maintenance of agroecosystem functions and health under climate change in the future. [ABSTRACT FROM AUTHOR]

The response of soil biotas to climate change has the potential to regulate multiple ecosystem functions. However, it is still challenging to accurately predict how multiple climate change factors will affect multiple ecosystem functions. Here, we assessed the short‐term responses of agroecosystem multifunctionality to a factorial combination of elevated CO2 (+200 ppm) and O3 (+40 ppb) and identified the key soil biotas (i.e., bacteria, fungi, protists, and nematodes) concerning the changes in the multiple ecosystem functions for two rice varieties (Japonica, Nanjing 5055 vs. Wuyujing 3). We provided strong evidence that combined treatment rather than individual treatments of short‐term elevated CO2 and O3 significantly increased the agroecosystem multifunctionality index by 32.3% in the Wuyujing 3 variety, but not in the Nanjing 5055 variety. Soil biotas exhibited an important role in regulating multifunctionality under short‐term elevated CO2 and O3, with soil nematode abundances better explaining the changes in ecosystem multifunctionality than soil biota diversity. Furthermore, the higher trophic groups of nematodes, omnivores‐predators served as the principal predictor of agroecosystem multifunctionality. These results provide unprecedented new evidence that short‐term elevated CO2 and O3 can potentially affect agroecosystem multifunctionality through soil nematode abundances, especially omnivores‐predators. Our study demonstrates that high trophic groups were specifically beneficial for regulating multiple ecosystem functions and highlights the importance of soil nematode communities for the maintenance of agroecosystem functions and health under climate change in the future. [ABSTRACT FROM AUTHOR]

The global cultivation area of rice is equivalent to 4% of the world's forest area and may be an important sink and source of trace gases. To produce a precise terpenoid emission inventory, it is essential to obtain reliable data of terpenoid emission from rice plants. In the present study, terpenoid emissions from various rice species were measured using flow-through chamber and tower flux measurement methods. In the flow-through chamber measurement, linalool was emitted from the above-ground parts of the three rice cultivars "Koshihikari", "Nipponbare" and "IR72". The emission rates gradually decreased (<0.1 µg gDW−1 h−1) within two days during the measurement periods. As the touching stimulus might have enhanced linalool emission, a non-contact measurement method, i.e., the tower flux measurement method, was applied to a "Koshihikari" paddy. Linalool was not detected, but α-pinene was detected in the atmosphere above the rice paddy. The α-pinene flux (mean ± 95% confidence interval) was 0.006 ± 0.004 nmol m−2 s−1 on a land-area basis. The flux was 1/200 of the previously reported monoterpene emission rate of the rice plants measured in a commercial chamber, but was not largely different from three other reports. We provide terpenoid flux data above a rice paddy for the first time, which is more reliable because the tower flux measurement method can avoid stimuli to rice leaves and stems. Although the obtained terpenoid emission rate is very low, the obtained values can contribute to the establishment of a precise BVOC inventory in Asia. [ABSTRACT FROM AUTHOR]