Modeling denitrification nitrogen losses in China's rice fields based on multiscale field-experiment constraints

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, N2 O, 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.

Multitask Deep Learning Enabling a Synergy for Cadmium and Methane Mitigation with Biochar Amendments in Paddy Soils

Biochar has demonstrated significant promise in addressing heavy metal contamination and methane (CH4) emissions in paddy soils; however, achieving a synergy between these two goals is challenging due to various variables, including the characteristics of biochar and soil properties that influence biochar's performance. Here, we successfully developed an interpretable multitask deep learning (MTDL) model by employing a tensor tracking paradigm to facilitate parameter sharing between two separate data sets, enabling a synergy between Cd and CH4 mitigation with biochar amendments. The characteristics of biochar contribute similar weightings of 67.9% and 62.5% to Cd and CH4 mitigation, respectively, but their relative importance in determining biochar's performance varies significantly. Notably, this MTDL model excels in custom-tailoring biochar to synergistically mitigate Cd and CH4 in paddy soils across a wide geographic range, surpassing traditional machine learning models. Our findings deepen our understanding of the interactive effects of Cd and CH4 mitigation with biochar amendments in paddy soils, and they also potentially extend the application of artificial intelligence in sustainable environmental remediation, especially when dealing with multiple objectives.

Improved gross primary production estimation in rice fields through integrated multi-scale methodologies

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 (Vc_uptake), 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 Vc_uptake 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 Vc_uptake 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 Vc_uptake agreed with R ² 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.

The Alien Plant Species Impact in Rice Crops in Northwestern Italy

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.

Soil nematode abundances drive agroecosystem multifunctionality under short-term elevated CO2 and O3

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.

Macroaggregates Serve as Micro-Hotspots Enriched With Functional and Networked Microbial Communities and Enhanced Under Organic/Inorganic Fertilization in a Paddy Topsoil From Southeastern China

Microbial communities of soil aggregate-size fractions were explored with molecular and networking assays for topsoil samples from a clayey rice paddy under long-term fertilization treatments. The treatments included no fertilizer (NF) as control, chemical fertilizer only (CF), chemical fertilizer with swine manure (CFM), and chemical fertilizer with rice straw return (CFS). Following a wet-sieving protocol, water-stable aggregates were separated into size fractions of large macroaggregates (L-MacA, >2,000 μm), macroaggregates (MacA, 2,000-250 μm), microaggregates (MicA, 250-53 μm), fine microaggregates (F-MicA, 53-2 μm), and fine clay (F-Clay, <2 μm). Mass proportion was 32.3-38.2% for F-MicA, 23.0-31.5% for MacA, 19.0-23.1% for MicA, 9.1-12.0% for L-MacA, and 4.9-7.5% for F-Clay, respectively. The proportion of MacA was increased, but F-Clay was reduced by fertilization, whereas the mean weight diameter was increased by 8.0-16.2% from 534.8 μm under NF to 621.5 μm under CFM. Fertilization affected bacterial 16S rRNA and fungal 18S rRNA gene abundance in F-MicA and F-Clay but not in aggregates in size larger than 53 μm. However, bacterial and fungal community α-diversities and community structures were quite more divergent among the fertilization treatments in all size fractions. Organic carbon and gene abundance of bacteria and fungi were enriched in both L-MacA and MacA but depleted in F-Clay, whereas microbial Shannon diversity was rarely changed by fraction size under the four treatments. L-MacA and MacA contained more bacteria of r-strategists and copiotrophs, whereas F-MicA and F-Clay were demonstrated with a higher abundance of K-strategists and oligotrophs. Guilds of parasitic and litter saprotrophic fungi were enriched in F-MicA but depleted in L-MacA. Furthermore, most of bacterial and fungal operational taxonomic units were strongly interacted in L-MacA and MacA rather than in MicA and F-Clay. Thus, MacA acted as micro-hotspots enriched with functional and networked microbial communities, which were enhanced with organic/inorganic fertilization in the rice paddy.

Contribution of periphytic biofilm of paddy soils to carbon dioxide fixation and methane emissions

Rice paddies are major contributors to anthropogenic greenhouse gas emissions via methane (CH₄) flux. The accurate quantification of CH₄ emissions from rice paddies remains problematic, in part due to uncertainties and omissions in the contribution of microbial aggregates on the soil surface to carbon fluxes. Herein, we comprehensively evaluated the contribution of one form of microbial aggregates, periphytic biofilm (PB), to carbon dioxide (CO₂) and CH₄ emissions from paddies distributed across three climatic zones, and quantified the pathways that drive net CH₄ production as well as CO₂ fixation. We found that PB accounted for 7.1%-38.5% of CH₄ emissions and 7.2%-12.7% of CO₂ fixation in the rice paddies. During their growth phase, PB fixed CO₂ and increased the redox potential, which promoted aerobic CH₄ oxidation. During the decay phase, PB degradation reduced redox potential and increased soil organic carbon availability, which promoted methanogenic microbial community growth and metabolism and increased CH₄ emissions. Overall, PB acted as a biotic converter of atmospheric CO₂ to CH₄, and aggravated carbon emissions by up to 2,318 kg CO₂ equiv ha^-1 season^-1. Our results provide proof-of-concept evidence for the discrimination of the contributions of surface microbial aggregates (i.e., PB) from soil microbes, and a profound foundation for the estimation and simulation of carbon fluxes in a potential novel approach to the mitigation of CH₄ emissions by manipulating PB growth.

Straw Incorporation with Nitrogen Amendment Shapes Bacterial Community Structure in an Iron-Rich Paddy Soil by Altering Nitrogen Reserves

Incorporation of crop straw into the soil along with inorganic fertilization is a widespread agricultural practice and is essential in nutrient-scarce soils, such as iron-rich (ferruginous) paddy soils. The responses of soil bacterial communities to straw incorporation under different nitrogen inputs in iron-rich soils remain unclear. Therefore, 6000 kg ha⁻¹ dry wheat (Triticum aestivum L. cv. Zhengmai 12) straw was applied to a rice paddy with and without nitrogen amendment (0, 80, 300, and 450 kg ha⁻¹ N as urea), to investigate its effects on soil fertility and bacterial community structure. Organic matter, total nitrogen, and water contents tended to decrease in straw-incorporated soils with different nitrogen inputs. Proteobacteria was the dominant bacterial phylum across all treatments (26.3–32.5% of total sequences), followed by Chloroflexi, Acidobacteria, and Nitrospirae. Up to 18.0% of all the taxa in the bacterial communities were associated with iron cycling. Straw incorporation with nitrogen amendment increased the relative abundance of iron oxidizers, Gallionellaceae, while decreasing the relative abundance of iron reducers, Geobacteraceae. Bacterial community composition shifted in different treatments, with total nitrogen, water, and Fe(III) contents being the key drivers. Straw incorporation supplemented by 300 kg ha⁻¹ N increased bacterial richness and enhanced all the predicted bacterial functions, so that it is recommended as the optimal nitrogen dosage in practice.

Elevated Atmospheric CO2 and Nitrogen Fertilization Affect the Abundance and Community Structure of Rice Root-Associated Nitrogen-Fixing Bacteria

Elevated atmospheric CO2 (eCO2) results in plant growth and N limitation, yet how root-associated nitrogen-fixing bacterial communities respond to increasing atmospheric CO2 and nitrogen fertilization (eN) during the growth stages of rice is unclear. Using the nifH gene as a molecular marker, we studied the combined effect of eCO2 and eN on the diazotrophic community and abundance at two growth stages in rice (tillering, TI and heading, HI). Quantitative polymerase chain reaction (qPCR) showed that eN had no obvious effect on nifH abundance in rice roots under either ambient CO2 (aCO2) or eCO2 treatment at the TI stage; in contrast, at the HI, nifH copy numbers were increased under eCO2 and decreased under aCO2. For rhizosphere soils, eN significantly reduced the abundance of nifH under both aCO2 and eCO2 treatment at the HI stage. Elevated CO2 significantly increased the nifH abundance in rice roots and rhizosphere soils with nitrogen fertilization, but had no obvious effect without N addition at the HI stage. There was a significant interaction [CO2 × N fertilization] effect on nifH abundance in root zone at the HI stage. In addition, the nifH copy numbers in rice roots were significantly higher at the HI stage than at the TI stage. Sequencing analysis indicated that the root-associated diazotrophic community structure tended to cluster according to the nitrogen fertilization treatment and that Rhizobiales were the dominant diazotrophs in all root samples at the HI stage. Additionally, nitrogen fertilization significantly increased the relative abundance of Methylosinus (Methylocystaceae) under eCO2 treatment, but significantly decreased the relative abundance of Rhizobium (Rhizobiaceae) under aCO2 treatment. Overall, the combined effect of eN and eCO2 stimulates root-associated diazotrophic methane-oxidizing bacteria while inhibits heterotrophic diazotrophs.

Methanogenesis Is an Important Process in Controlling MeHg Concentration in Rice Paddy Soils Affected by Mining Activities

Rice paddies are agricultural sites of special concern because the potent toxin methylmercury (MeHg), produced in rice paddy soils, accumulates in rice grains. MeHg cycling is mostly controlled by microbes but their importance in MeHg production and degradation in paddy soils and across a Hg concentration gradient remains unclear. Here we used surface and rhizosphere soil samples in a series of incubation experiments in combination with stable isotope tracers to investigate the relative importance of different microbial groups on MeHg production and degradation across a Hg contamination gradient. We showed that sulfate reduction was the main driver of MeHg formation and concentration at control sites, and that methanogenesis had an important and complex role in MeHg cycling as Hg concentrations increased. The inhibition of methanogenesis at the mining sites led to an increase in MeHg production up to 16.6-fold and a decrease in MeHg degradation by up to 77%, suggesting that methanogenesis is associated with MeHg degradation as Hg concentrations increased. This study broadens our understanding of the roles of microbes in MeHg cycling and highlights methanogenesis as a key control of MeHg concentrations in rice paddies, offering the potential for mitigation of Hg contamination and for the safe production of rice in Hg-contaminated areas.

Silicate Fertilizer Amendment Alters Fungal Communities and Accelerates Soil Organic Matter Decomposition

Soil microorganisms play a crucial role in organic matter decomposition and nutrient cycling in cropping systems. Compared to bacteria, fungal community composition and the role of fungi in organic matter decomposition and nutrient cycling in agro-systems are, however, elusive. Silicon (Si) fertilization is essential to improve agronomic performance of rice. The effects of the Si fertilizer application on the soil fungal community composition and their contribution in soil organic matter (SOM) decomposition are not yet studied. We investigated the short-term (120 days) slag silicate fertilizer (SSF) amendment impacts on plant photosynthesis and soil biochemical changes, soil fungal communities (assessed by ITS amplicon illumina sequencing), hydrolytic and oxidase enzyme activities, CO₂ emissions, and bacterial and fungal respiration in diverse eco-geographic races of rice (Oryza sativa L.), i.e., Japonica rice (O. sativa japonica) and Indica rice (O. sativa indica). The short-term SSF amendment significantly increased the relative abundance of saprotrophic fungi and accelerated organic matter decomposition. The increase in saprotrophic fungi was mostly attributed to greater labile C availability and Si availability. Higher organic matter decomposition was accompanied by an increase in both hydrolytic and oxidative enzyme activities in response to the SSF amendment. The stimulation of oxidative enzyme activities was explained by an increase in root oxidase activities and iron redox cycling, whereas stimulation of hydrolytic enzyme activities was explained by the greater labile C availability under SSF fertilization. We conclude that the short-term SSF amendment increases saprotrophic fungal communities and soil hydrolytic and oxidative enzyme activities, which in turn stimulates SOM mineralization and thus could have negative feedback impacts on soil C storage in submerged rice paddies.

Improvement and application of the PCPF-1@SWAT2012 model for predicting pesticide transport: a case study of the Sakura River watershed

BACKGROUND

The Soil and Water Assessment Tool combined with Pesticide Concentration in Paddy Field (PCPF-1@SWAT) model was previously developed to simulate the fate and transport of rice pesticides in watersheds. However, the current model is deficient in characterizing the rice paddy area and is incompatible with the ArcSWAT2012 program. In this study, we modified the original PCPF-1@SWAT model to develop a new PCPF-1@SWAT2012 model to address the deficiency in the rice paddy area and utilizing the ArcSWAT2012 program. Next, the new model was applied to the Sakura River watershed, Ibaraki, Japan in order to simulate the transport of four herbicides: mefenacet, pretilachlor, bensulfuron-methyl and imazosulfuron.

RESULTS

The results showed that the water flow rate simulated by PCPF1@SWAT2012 was similar with the observed data. The calculated Nash-Sutcliffe efficiency coefficient (NSE) (0.73) and percent bias (PBIAS) (-20.38) suggested satisfactory performance of the model. In addition, the concentrations of herbicides simulated by the PCPF-1@SWAT2012 model were in good agreement with the observed data. The statistical indices NSE and root mean square error (RMSE) estimated for mefenacet (0.69 and 0.18, respectively), pretilachlor (0.86 and 0.18, respectively), bensulfuronmethyl (0.46 and 0.21, respectively) and imazosulfuron (0.64 and 0.28, respectively) indicated satisfactory predictions.

CONCLUSION

The PCPF-1@SWAT2012 model is capable of simulating well the water flow rate and transport of herbicides in this watershed, comprising different land use types, including a rice paddy area. © 2018 Society of Chemical Industry.

[Diversity of the Microbial Community in Rice Paddy Soil with Biogas Slurry Irrigation Analyzed by Illumina Sequencing Technology]

In order to explore the variation in soil microbial community diversity in paddy fields with different irrigation periods, we collected in situ rice field soils during different biogas irrigation periods and analyzed the microbial community structures of these soils by high-throughput sequencing. The results showed that as the biogas irrigation period increased, the soil pH decreased gradually, while organic matter, nitrate nitrogen, phosphate, and other nutrients were accumulated. Years of continued biogas irrigation was not conducive to improving rice yields. The results showed that as the biogas irrigation period increased, the richness in microbial species in paddy soils decreased gradually, and the diversity in the microbial communities was also reduced. Proteobacteria accounts for the largest proportion in rice paddy soil with biogas slurry irrigation. With the increase of biogas irrigation years, the proportion of β-Proteobacteria, Bacteroidia, Bacteroidales, Burkholderiales, Bacteroides, and Thiobacillus increased, while the proportion of Gemmatimonadetes and α-Proteobacteria decreased gradually. Dissolved organic carbon (F=2.67, P=0.09) had the greatest effect on microbial community structures in the studied paddy soils.

Diversity of microbial communities potentially involved in mercury methylation in rice paddies surrounding typical mercury mining areas in China

Mercury can be a serious hazard to human health, especially in paddy soils surrounding mining areas. In this study, mercury (Hg)‐methylating microbes with the potential biomarker gene hgcA were obtained from 45 paddy soil samples in mercury mining areas in Fenghuang, Wanshan, and Xunyang. In different areas, the abundance of the hgcA gene was affected by different environmental factors, including organic matter, pH, total carbon content, total nitrogen content, and total mercury content. Phylogenetic analysis showed that hgcA microbes in paddy soils were potentially members of the phyla Proteobacteria, Euryarchaeota, Chloroflexi, and two unnamed groups. Canonical correspondence analysis showed that pH and organic matter impacted the hgcA gene diversity and the microbial community structures in paddy soils. The identification of Hg‐methylating microbes may be crucial for understanding mercury methylation/demethylation processes, which would be helpful in assessing the risk of methylmercury contamination in the food chain.

Simulating the fate and transport of nursery-box-applied pesticide in rice paddy fields

BACKGROUND

The Pesticide Concentration in a Paddy Field model (PCPF-1) was modified by adding a root zone compartment to simulate nursery-box-applied (NB-applied) pesticide. The PCPF-NB model was validated for predicting the concentrations of NB-applied fipronil and imidacloprid in rice paddy fields using two treatment methods: before transplanting (BT) and at sowing (AS). Uncertainty and sensitivity analyses were used to evaluate the robustness of the concentrations predicted by the model.

RESULTS

The hourly predicted concentrations of imidacloprid and fipronil were accurate in both paddy water and 1 cm deep paddy soil. The coefficient of determination and Nash-Sutcliffe model efficiency were greater than 0.87 and 0.60 respectively. The 95th percentiles of the predicted concentrations of fipronil and imidacloprid indicated that the influence of input uncertainty was minor in paddy water but important in paddy soil. The pesticide deposition rate and the desorption rate from the root zone were identified to be the major contributors to the variation in the predicted concentrations in paddy water and soil.

CONCLUSION

The PCPF-NB model was validated for predicting the fate and transport of NB-applied fipronil and imidacloprid using the BT and AS treatment methods. © 2015 Society of Chemical Industry.

Mitigating global warming potentials of methane and nitrous oxide gases from rice paddies under different irrigation regimes

A field experiment was conducted in Bangladesh Agricultural University Farm to investigate the mitigating effects of soil amendments such as calcium carbide, calcium silicate, phosphogypsum, and biochar with urea fertilizer on global warming potentials (GWPs) of methane (CH4) and nitrous oxide (N2O) gases during rice cultivation under continuous and intermittent irrigations. Among the amendments phosphogypsum and silicate fertilizer, being potential source of electron acceptors, decreased maximum level of seasonal CH4 flux by 25-27 % and 32-38 % in continuous and intermittent irrigations, respectively. Biochar and calcium carbide amendments, acting as nitrification inhibitors, decreased N2O emissions by 36-40 % and 26-30 % under continuous and intermittent irrigations, respectively. The total GWP of CH4 and N2O gases were decreased by 7-27 % and 6-34 % with calcium carbide, phosphogypsum, and silicate fertilizer amendments under continuous and intermittent irrigations, respectively. However, biochar amendments increased overall GWP of CH4 and N2O gases.

Sulfate-reducing microorganisms in wetlands - fameless actors in carbon cycling and climate change

Freshwater wetlands are a major source of the greenhouse gas methane but at the same time can function as carbon sink. Their response to global warming and environmental pollution is one of the largest unknowns in the upcoming decades to centuries. In this review, we highlight the role of sulfate-reducing microorganisms (SRM) in the intertwined element cycles of wetlands. Although regarded primarily as methanogenic environments, biogeochemical studies have revealed a previously hidden sulfur cycle in wetlands that can sustain rapid renewal of the small standing pools of sulfate. Thus, dissimilatory sulfate reduction, which frequently occurs at rates comparable to marine surface sediments, can contribute up to 36–50% to anaerobic carbon mineralization in these ecosystems. Since sulfate reduction is thermodynamically favored relative to fermentative processes and methanogenesis, it effectively decreases gross methane production thereby mitigating the flux of methane to the atmosphere. However, very little is known about wetland SRM. Molecular analyses using dsrAB [encoding subunit A and B of the dissimilatory (bi)sulfite reductase] as marker genes demonstrated that members of novel phylogenetic lineages, which are unrelated to recognized SRM, dominate dsrAB richness and, if tested, are also abundant among the dsrAB-containing wetland microbiota. These discoveries point toward the existence of so far unknown SRM that are an important part of the autochthonous wetland microbiota. In addition to these numerically dominant microorganisms, a recent stable isotope probing study of SRM in a German peatland indicated that rare biosphere members might be highly active in situ and have a considerable stake in wetland sulfate reduction. The hidden sulfur cycle in wetlands and the fact that wetland SRM are not well represented by described SRM species explains their so far neglected role as important actors in carbon cycling and climate change.