Linking soil structure and microbial communities to predict CO2 emissions from drained arable peatlands

Understanding the interactions between soil structure, microbial communities, and greenhouse gas dynamics is critical for predicting carbon losses from drained peatlands under agricultural use. This study investigates CO₂ emissions across winter wheat, sugar beet, and bare soil treatments on a productive UK peat farm, integrating high-resolution X-ray Computed Tomography (XCT), microbial community profiling, and in situ gas and soil measurements. Soil structure differed between treatments, with bare soil exhibiting the highest pore connectivity and gas diffusivity. These structural conditions aligned with higher in situ CO₂ concentrations, despite reduced root inputs and microbial diversity. In contrast, cropped soils supported more diverse microbial communities, especially fungi, but exhibited lower gas diffusivity and CO₂ concentrations—likely reflecting restricted oxygen availability and plant–microbe competition. Relative gas diffusivity (Dp/D₀) was strongly regulated by soil moisture across all treatments, with a consistent inverse relationship (R² > 0.93). A machine learning model (XGBoost) accurately predicted CO₂ concentrations (R² = 0.83) using microbial and physical soil properties, identifying microbial taxa potentially linked to carbon cycling. These findings demonstrate that subtle differences in pore architecture can shape microbial function and carbon loss, even in the absence of statistically significant structural differences. This highlights the need to integrate microbial ecology and soil physics in greenhouse gas modelling for sustainable management of agricultural peatlands

Using artificial mixtures to test the impacts of tracer combinations and model selection on the performance of sediment source fingerprinting in a burned area

Sediment source fingerprinting can be an effective method for identifying sediment sources in wildfire-impacted areas, but the effects of tracer and model selection on robustness remain poorly understood. In this study, soil samples were collected from three potential sources (burned surface, unburned surface, and channel banks) in a wildfire-affected area, and artificial mixtures with known source proportions were created. Three types of tracers (fallout radionuclides, magnetic susceptibilities, and soil colour parameters) were tested for their sensitivity to wildfire. Ten composite fingerprints, generated through the traditional three-step procedure (TSP) as well as consensus ranking and the conservativeness index (CM) were used to assess the accuracy of two un-mixing models. These comprised one frequentist (FingerPro) and one Bayesian (MixSIAR) model. The results indicated that wildfire had substantial effects on most tracer properties, with the median concentration and variance increased by up to 104% and 374%, respectively. Among the ten composite fingerprints, the CM selection method performed best, with the average and standard deviation of the corresponding MAE being 7% and 1%, respectively. While the TSP method could achieve a near-global optimum in some cases, it was the least stable among the ten tracer sets, generating a standard deviation for the MAE of 9%. Compared to FingerPro, MixSIAR solutions calculated using composite fingerprints excluding TSP returned lower MAE values (reduced by an average of 28%). The standard deviations of MAE for MixSIAR solutions employing tracer sets, except for CM, were lower (decreased by an average of 37%), suggesting that MixSIAR delivered higher accuracy and precision for our case study. These findings offer valuable insights for future fingerprinting research in wildfire impacted areas, which can support soil conservation and catchment restoration efforts in burned regions

Short-term effects of overwintering on porosity of the compacted topsoil due to harvest traffic in Northeast China

The multi-hydrothermal processes in agricultural soils during overwintering modify compacted soil structure in cold winter regions. The depth-dependent changes in the topsoil pore-network within field-based compacted zones caused by harvest traffic, before and after winter, remain poorly understood. In this study, we aimed to investigate the short-term effects of overwintering on topsoil porosity of a clay loam soil in the harvest traffic zone in Northeast China using X-ray CT. Undisturbed soil cores were collected in the 0–10 cm layer of the non-traffic and traffic zones before and after winter. After harvest, both total porosity (εtotal) and porosity of > 0.04 mm (εX-ray) significantly decreased by 0.04 and 0.07 cm3 cm−3 due to the machinery traffic, respectively. Following winter, the εtotal of the traffic zone significantly increased by 0.08 cm3 cm−3 and was greater than that of non-traffic zone porosity before winter. The loosening effects of overwintering on compacted soil in the traffic zone diminished with increasing soil depth, and marked alterations limited to the uppermost 3.5 cm. The increase in εX-ray was primarily resulted from the changes in 0.04–1.0 mm pores. Therefore, it is indicated that overwintering can alleviate soil compaction of traffic zone only in the uppermost layer

Erioglossum rubiginosum, a new alternative host of rubber tree powdery mildew Erysiphe quercicola

Erioglossum rubiginosum (synonym as Lepisanthes rubiginosa), is a shrub-like plant belonging to the family Sapindaceae. This species is a common undergrowth plant species in rubber tree plantations, which provide more than 90% of the total natural rubber production. Powdery mildew was found to occur seriously on E. rubiginosum during an investigation on powdery mildew of rubber tree caused by Erysiphe quercicola. In this study, leaves of E. rubiginosum with powdery mildew symptoms were collected and the pathogen was identified using morphological and molecular analyses using the internal transcribed spacer (ITS) and 28 S rDNA regions. The results indicated that E. quercicola was the causal agent of E. rubiginosum powdery mildew. Based on cross-pathogenicity analysis, E. quercicola from E. rubiginosum and rubber tree could cause typical symptoms on each other, which confirmed that E. rubiginosum is an alternative host of rubber tree powdery mildew. To our knowledge, this is the first report of E. quercicola causing powdery mildew on E. rubiginosum. Whether E. rubiginosum can be one of the primary sources of the rubber tree powdery mildew epidemics needs future studies

Crop rotation phase has a greater impact on soil biology than crop rotation diversity

The effect of plant diversity on the belowground soil food web remains poorly understood. In this study the soil microbial community structure and biomass, and the abundance of microfauna, mesofauna, and macrofauna were assessed at three levels of crop rotation diversity: A Simple rotation (2 plant species), a Moderate rotation (4 plant species), and a Diverse rotation (10 plant species). Soils subjected to more diverse crop rotations did not differ in their microbial community structure, were lower in soil total C, and exhibited a smaller microbial biomass, but a higher crop yield. The mean abundance of Collembola and mites exhibited a trend of Simple > Moderate > Diverse. These observations may be associated with higher levels of disturbance in soils of more diverse rotations due to more frequent tillage operations to establish a greater diversity of crops. The lack of a significant positive effect of crop rotation diversity on soil biology was observed despite the field experiment being established three to four years prior to these measurements. We did observe effects due to the phase of the crop rotation. Within the Simple rotation, we found a significant effect of crop rotation phase on collembolan and mite abundances, and within the Diverse rotation on earthworm biomass. These observations suggest that the crop rotation phase, and perhaps the identity of the individual plants used in a crop rotation, affect soil biology more than the diversity of the crop rotation per se

An improved approach for estimating root elongation rate from penetrometer resistance and macropore porosity on a silty clay loam soil

The role of macropores is often ignored in classical models for predicting root elongation using soil penetrometer resistance (PR). In this study, we propose an empirical model that includes the effects of macropores and PR on maize (Zea mays L.) root elongation rate (RER) and compare its performance with three previous models. Undisturbed soil cores were collected from an 11-yr tillage experiment (including no-tillage and conventional tillage systems) in Northeast China. For each soil core, soil bulk density (BD), penetrometer resistance (PR), air-filled porosity (AFP), and pore size distribution from water release characteristics, and RER of maize seedlings at a matric potential of \u100000 20 kPa were determined. Results showed that RER negatively correlated with BD, PR, and the volume of ε60 (the volume of pores greater than 60 μm) (P 60 μm), performed better in predicting RER than the previous models, with a root mean square error (RMSE) of 0.36. The new model is useful in simulating maize root distribution under field conditions

Starship giant transposable elements cluster by host taxonomy using k-mer-based phylogenetics

Starships are a recently established superfamily of giant cargo-mobilising transposable elements in the fungal subphylum Pezizomyotina (phylum Ascomycota). To date, Starship elements have been identified up to ∼700 Kbp in length and carrying hundreds of accessory genes, which can confer both beneficial and deleterious traits to the host genome. Classification of Starship elements has been centred on the tyrosine recombinase gene that mobilises the element, termed the captain. We contribute a new perspective to Starship classification by using an alignment-free kmer-based phylogenetic tree building method, which can infer relationships between elements in their entirety, including both active and degraded elements and irrespective of high variability in element length and cargo content. In doing so we found that relationships between entire Starships differed from those inferred from captain genes and revealed patterns of element relatedness corresponding to host taxonomy. Using Starships from Gaeumannomyces species as a case study, we found that kmer-based relationships correspond with similarity of cargo gene content. Our results suggest that Starship-mediated horizontal transfer events are frequent between species within the same genus but are less prevalent across larger host evolutionary distances. This novel application of a kmer-based phylogenetics approach overcomes the issue of how to represent and compare highly variable Starships elements as a whole, and in effect shifts the perspective from a captain to a cargo-centred concept of Starship identity. SUMMARY We applied a kmer-based phylogenetic classification approach to giant Starship cargo-mobilising elements from species across the Pezizomycotina (Ascomycota, Fungi). We found Starship elements to frequently cluster according to host taxonomy, suggesting horizontal transfer of elements is less common across larger evolutionary distances. Kmer-based phylogenetics approaches show promise for both element classification and to inform our understanding of the evolution of Starships and other giant cargo-mobilising elements

Socio-economic factors constrain climate change adaptation in a tropical export crop

Climate change will alter the geographical locations most suited for crop production, but adaptation to these new conditions may be constrained by edaphic and socio-economic factors. Here we investigate climate change adaptation constraints in banana, a major export crop of Latin America and the Caribbean. We derived optimal climatic, edaphic and socio-economic conditions from the distribution of intensive banana production across Latin America and the Caribbean, identifed using remote sensing imagery. We found that intensive banana production is constrained to low-lying, warm aseasonal regions with slightly acidic soils, but is less constrained by precipitation, as irrigation facilitates production in drier regions. Production is limited to areas close to shipping ports and with high human population density. Rising temperatures, coupled with requirements for labour and export infrastructure, will result in a 60% reduction in the area suitable for export banana production, along with yield declines in most current banana producing areas

Biomes Affect Baking Properties and Quality Parameters of Different Wheat Genotypes

Wheat (Triticum aestivum L.) is predominantly cultivated in the Atlantic Forest biome. However, the recent expansion of agricultural frontiers in Brazil has led to its introduction into the Savannah biome. The commercial and technological quality parameters of wheat are determined by the interaction between genotype and growing environment. In this context, the objective of this study was to evaluate the effects of six wheat genotypes cultivated in five distinct environments, three located in the Atlantic Forest biome and two in the Savannah biome. The results demonstrated that environmental conditions significantly influenced protein and starch contents, which in turn affected hectoliter weight and falling number. On the other hand, genotypic variation had a marked effect on thousand-grain weight, colorimetric parameters (L* and b*), water and sodium retention capacities, dough tenacity and extensibility, as well as gluten strength. Wheat genotypes cultivated in the Savannah biome exhibited superior baking performance and technological quality, characterized by elevated starch content, enhanced gluten strength (with the exception of the genotype Feroz), and greater dough tenacity (except for the genotype Guardião), when compared to those cultivated in the Atlantic Forest biome. These results highlight the potential for identifying more sustainable cultivation environments, considering the different biomes, for the production of wheat with superior nutritional and technological quality, promoting the efficient use of natural and economic resources throughout the production cycle

Active navigation and meteorological selectivity drive insect migration patterns through the Levant

Insect migration is crucial to many natural processes and human activities, yet large-scale patterns remain poorly understood. On the Mediterranean’s eastern shores lies a 70 km-wide stretch of hospitable habitat between the sea and the Arabian Desert, which we term the Levantine Corridor, extending ~400 km south from Turkey to the edge of the Sahara. We deployed 7 biological radars over 8 years, recording 6.3 million individual large insects (>10 mg) and revealing an important migration route at the nexus of three continents, with over 700 million large insects estimated to cross annually. However, a comparison with European insect migration flows suggests that Levantine insect fluxes are lower than at higher latitudes, challenging the conjecture that the Levantine Corridor acts as a funnel for insect migration as reported for birds. Insects showed strong migratory directionality differing from prevailing wind direction in spring and autumn, with mass migrations separated by periods of weaker movements. Migration intensity strongly depended on the weather, with insects preferentially migrating in seasonally beneficial tailwinds when possible and in warmer temperatures. The study reveals an unexplored insect migration route with implications for food webs, pollination, disease transmission, pest outbreaks and species invasions across West Asia, East Europe and Northeast Africa