Image-based quantification of soil microbial dead zones induced by nitrogen fertilization

Different effects of taproot and fibrous root crops on pore structure and microbial network in reclaimed soil

Understanding the effects of plant roots on the pore structure and microbial community of soil is crucial to recovery and improve soil productivity in mining areas. This study aims to assess the impact of taproot (TR) and fibrous root (FR) crops on the physicochemical properties, pore structure, and microbial communities and networks in reclaimed mine soil. Results showed that reclamation positively influenced pore structure and microbial diversity. Tillage with TR and FR crops significantly increased porosity, total pore volume, and area of mining soil (p < 0.05). Compared with TR, FR produced more macropores, mesopores, and micropores. In addition, the module group, average degree, density, and connectivity of microbial network in FR cultivated soil were higher than those in TR cultivated soil. The microbial network map showed that FR had more keystone taxa than TR, and mainly consisted of Acidobacteria and Proteobacteria. In the FR microbial network, Rhizobiales, Betaproteobacteria, and Acidobacteria_Gp11 play critical roles as module hubs and Noviherbaspirillum and Zavarzinella as connectors. Furthermore, most of the key microbes were significantly correlated (p < 0.05) with the total pore area and probably tended to live in pores >75 μm and 0.1-5 μm in size. Therefore, FR crops were more effective than TR crops in improving pore structure and enhancing the development of microbial network in reclaimed soil.

Statistical Effective Diffusivity Estimation in Porous Media Using an Integrated On-site Imaging Workflow for Synchrotron Users

Transport in porous media plays an essential role for many physical, engineering, biological and environmental processes. Novel synchrotron imaging techniques and image-based models have enabled more robust quantification of geometric structures that influence transport through the pore space. However, image-based modelling is computationally expensive, and end users often require, while conducting imaging campaign, fast and agile bulk-scale effective parameter estimates that account for the pore-scale details. In this manuscript we enhance a pre-existing image-based model solver known as OpenImpala to estimate bulk-scale effective transport parameters. In particular, the boundary conditions and equations in OpenImpala were modified in order to estimate the effective diffusivity in an imaged system/geometry via a formal multi-scale homogenisation expansion. Estimates of effective pore space diffusivity were generated for a range of elementary volume sizes to estimate when the effective diffusivity values begin to converge to a single value. Results from OpenImpala were validated against a commercial finite element method package COMSOL Multiphysics (abbreviated as COMSOL). Results showed that the effective diffusivity values determined with OpenImpala were similar to those estimated by COMSOL. Tests on larger domains comparing a full image-based model to a homogenised (geometrically uniform) domain that used the effective diffusivity parameters showed differences below 2 % error, thus verifying the accuracy of the effective diffusivity estimates. Finally, we compared OpenImpala's parallel computing speeds to COMSOL. OpenImpala consistently ran simulations within fractions of minutes, which was two orders of magnitude faster than COMSOL providing identical supercomputing specifications. In conclusion, we demonstrated OpenImpala's utility as part of an on-site tomography processing pipeline allowing for fast and agile assessment of porous media processes and to guide imaging campaigns while they are happening at synchrotron beamlines.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11242-023-01993-7.

Utility of Plant Growth-Promoting Rhizobacteria for Sustainable Production of Bermudagrass Forage

A two-year study was conducted in bermudagrass hay fields in central Alabama to estimate the potential of plant growth-promoting rhizobacteria (PGPR) as a tool for sustainable agriculture in forage management. This study compared the effects of two treatments of PGPR, applied with and without lowered rates of nitrogen, to a full rate of nitrogen fertilizer in a hay production system. The PGPR treatments included a single-strain treatment of Paenibacillus riograndensis (DH44), and a blend including two Bacillus pumilus strains (AP7 and AP18) and a strain of Bacillus sphaericus (AP282). Data collection included estimates of forage biomass, forage quality, insect populations, soil mesofauna populations, and soil microbial respiration. Applications of PGPR with a half rate of fertilizer yielded similar forage biomass and quality results as that of a full rate of nitrogen. All PGPR treatments increased soil microbial respiration over time. Additionally, treatments containing Paenibacillus riograndensis positively influenced soil mesofauna populations. The results of this study indicated promising potential for PGPR applied with lowered nitrogen rates to reduce chemical inputs while maintaining yield and quality of forage.

The successional trajectory of bacterial and fungal communities in soil are fabricated by yaks’ excrement contamination in plateau, China

The soil microbiome is crucial in determining contemporary realistic conditions for future terrestrial ecological and evolutionary development. However, the precise mechanism between the fecal deposition in livestock grazing and changes in the soil microbiome remains unknown. This is the first in-depth study of bacterial and fungal taxonomic changes of excrement contaminated soils in the plateau (&gt;3,500 m). This suggests the functional shifts towards a harmful-dominated soil microbiome. According to our findings, excrement contamination significantly reduced the soil bacterial and fungal diversity and richness. Furthermore, a continuous decrease in the relative abundance of microorganisms was associated with nutrient cycling, soil pollution purification, and root-soil stability with the increasing degree of excrement contamination. In comparison, soil pathogens were found to have the opposite trend in the scenario, further deteriorating normal soil function and system resilience. Such colonization and succession of the microbiome might provide an important potential theoretical instruction for microbiome-based soil health protection measures in the plateau of China.

A 3D image-based modelling approach for understanding spatiotemporal processes in phosphorus fertiliser dissolution, soil buffering and uptake by plant roots

Phosphorus (P) is a key yield-limiting nutrient for crops, but the main source of P fertiliser is finite. Therefore, efficient fertilisation is crucial. Optimal P application requires understanding of the dynamic processes affecting P availability to plants, including fertiliser dissolution rate and soil buffer power. However, standard soil testing methods sample at fixed time points, preventing a mechanistic understanding of P uptake variability. We used image-based modelling to investigate the effects of fertiliser dissolution rate and soil buffer power on P uptake by wheat roots imaged using X-ray CT. We modelled uptake based on 1-day, 1-week, and 14-week dissolution of a fixed quantity of total P for two common soil buffer powers. We found rapid fertiliser dissolution increased short-term root uptake, but total uptake from 1-week matched 1-day dissolution. We quantified the large effects root system architecture had on P uptake, finding that there were trade-offs between total P uptake and uptake per unit root length, representing a carbon investment/phosphorus uptake balance. These results provide a starting point for predictive modelling of uptake from different P fertilisers in different soils. With the addition of further X-ray CT image datasets and a wider range of conditions, our simulation approach could be developed further for rapid trialling of fertiliser-soil combinations to inform field-scale trials or management.

Response of cbbL-harboring microorganisms to precipitation changes in a naturally-restored grassland

The impact of the long-term uneven precipitation distribution model on the diversity and community composition of soil C-fixing microorganisms in arid and semiarid grasslands remains unclear. In 2015, we randomly set up five experimental plots with precipitation gradients on the natural restoration grassland of the Loess Plateau (natural precipitation, NP; ± 40% natural precipitation: decreased precipitation (DP), DP40; increased precipitation (IP), IP40; ± 80% natural precipitation: DP80; IP80). In the third and fifth years after the experimental layout (spanned two years), we explored the cbbL-genes, which are functional genes in the Calvin cycle, harboring microbial diversity and community composition under different precipitation treatments. The results showed that the increase in mean annual precipitation significantly changed the cbbL-harboring microbial alpha diversity, especially when controlling for 40% natural precipitation. The response of the dominant microbial communities to interannual increased precipitation variation shifted from Gammaproteobacteria (Bradyrhizobium) to Betaproteobacteria (Variovorax). The structural equation model showed that precipitation directly affected the cbbL-harboring microbial diversity and community composition and indirectly by affecting soil NO₃^- (mg N kg ^-1), soil organic matter, dissolved organic N content, and above- and underground biomass. In conclusion, studying how cbbL-harboring microbial diversity and community composition respond to uneven precipitation variability provides new insights into the ecological processes of C-fixing microbes in semi-arid naturally-restored grasslands dominated by the Calvin cycle.

Precipitation-optimised targeting of nitrogen fertilisers in a model maize cropping system

Typically, half of the nitrogen (N) fertiliser applied to agricultural fields is lost to the wider environment. This inefficiency is driven by soil processes such as denitrification, volatilisation, surface run-off and leaching. Rainfall plays an important role in regulating these processes, ultimately governing when and where N fertiliser moves in soil and its susceptibility to gaseous loss. The interaction between rainfall, plant N uptake and N losses, however, remains poorly understood. In this study we use numerical modelling to predict the optimal N fertilisation strategy with respect to rainfall patterns and offer mechanistic explanations to the resultant differences in optimal times of fertiliser application. We developed a modelling framework that describes water and N transport in soil over a growing season and assesses nitrogen use efficiency (NUE) of split fertilisations within the context of different rainfall patterns. We used ninety rainfall patterns to determine their impact on optimal N fertilisation times. We considered the effects of root growth, root N uptake, microbial transformation of N and the effect of soil water saturation and flow on N movement in the soil profile. On average, we show that weather-optimised fertilisation strategies could improve crop N uptake by 20% compared to the mean uptake. In drier years, weather-optimising N applications improved the efficiency of crop N recovery by 35%. Further analysis shows that maximum plant N uptake is greatest under drier conditions due to reduced leaching, but it is harder to find the maximum due to low N mobility. The model could capture contrasting trends in NUE seen in previous arable cropping field trials. Furthermore, the model predicted that the variability in NUE seen in the field could be associated with precipitation-driven differences in N leaching and mobility. In conclusion, our results show that NUE in cropping systems could be significantly enhanced by synchronising fertiliser timings with both crop N demand and local weather patterns.

Space and time-resolved monitoring of phosphorus release from a fertilizer pellet and its mobility in soil using microdialysis and X-ray computed tomography

Phosphorus is an essential nutrient for crops. Precise spatiotemporal application of P fertilizer can improve plant P acquisition and reduce run-off losses of P. Optimizing application would benefit from understanding the dynamics of P release from a fertilizer pellet into bulk soil, which requires space- and time-resolved measurements of P concentration in soil solutions. In this study, we combined microdialysis and X-ray computed tomography to investigate P transport in soil. Microdialysis probes enabled repeated solute sampling from one location with minimal physical disturbance, and their small dimensions permitted spatially resolved monitoring. We observed a rapid initial release of P from the source, producing high dissolved P concentrations within the first 24 h, followed by a decrease in dissolved P over time compatible with adsorption onto soil particles. Soils with greater bulk density (i.e., reduced soil porosity) impeded the P pulse movement, which resulted in a less homogeneous distribution of total P in the soil column at the end of the experiment. The model fit to the data showed that the observed phenomena can be explained by diffusion and adsorption. The results showed that compared with conventional measurement techniques (e.g., suction cups), microdialysis measurements present a less invasive alternative. The time-resolved measurements ultimately highlighted rapid P dynamics that require more attention for improving P use efficiency.