Donghao Ma

Soil viruses are crucial for microbial life, biogeochemical cycles of carbon and nutrients, and for microbial necromass formation. We hypothesized that the effects of viruses on these processes depend on organic matter and nutrient availability in soils. Here, we combined a 34‐year long‐term fertilization trial, 150 sequenced soil metagenomes, and microcosm experiments to explore how viruses modulate carbon and nutrient dynamics depending on resource availability. We uncovered 2789 viral populations (vOTUs) grouping into 301 viral clusters, 91% of which were previously unknown. Organically fertilized soils harbored most lytic viruses carrying diverse element cycling‐related auxiliary viral genes (AVGs) acquired through co‐evolution and horizontal gene transfer. Synthesis and heterologous expression assays further indicated that four AVGs (i.e., cbhA , pel , wbpD , GT2 ) had higher transcript levels in Escherichia coli under nutrient rich than nutrient poor conditions. Addition of virus particles to soils raised microbial carbon use efficiency (CUE; biomass production relative to carbon uptake) and accelerated microbial turnover leading to boosted microbial necromass formation by 14%. Conversely, in soils without organic fertilizers, viruses facilitate bacterial adaptation to stress (e.g., defense system and interference competition) and accelerate microbial decomposition of organic matter. 35 days after virus addition, CO ₂ and N ₂ O emissions increased by 41% and 52%, respectively. Finally, we propose the Viral Entombing‐Priming (VEP) framework to describe the contrasting roles of viruses in carbon and nutrient dynamics depending on soil fertility. This work reveals the viral “Matthew effect” ( the rich get richer and the poor get poorer ) in resource‐rich and resource‐poor soils and could unlock nature‐based pathways to raise carbon and nutrient retention for sustainable agriculture.

Increasing soil sodicity represents a critical threat to global agroecosystem health, but how exchangeable sodium percentage (ESP) modulates relationships between biodiversity and ecosystem multifunctionality (BEF) is unresolved. We surveyed 378 soil samples from 189 paired saline–sodic lands and adjacent farmlands across four major saline–sodic regions of China spanning ~2000 km. Random forest models demonstrated that ESP emerged as the primary abiotic predictor of soil multifunctionality, defining sharp thresholds ~13% for cropped systems and ~44% for natural saline–sodic habitats beyond which BEF relationships undergo fundamental reorganization. These breaks coincide with significant shifts toward fungal dominance within microbial communities. Notably, under hyper‐sodic conditions, fungal diversity emerges as essential for sustaining ecosystem functions. Metagenomic and trait‐based analyses further characterized three functional dimensions of microbial trait‐based strategies—environmental responsiveness, metabolic capacity, and nutrient recycling. We then mechanistically linked microbial life‐history strategies to soil multifunctionality. Our results showed that in farmland soils, nutrient recycling was positively associated with multifunctionality, whereas metabolic capacity was negatively correlated with multifunctionality, and in saline–sodic soils metabolic capacity exhibited a positive association with multifunctionality. Collectively, this study establishes ESP as a key regulator of BEF relationships and microbial eco‐evolutionary adaptations, providing mechanistic insights for managing saline–sodic soils under escalating climate change.

To apply AquaCrop to the study of agricultural soil moisture in the North China Plain, a water-treatment experiment on summer maize was carried out at the Fengqiu experimental station of the Chinese Academy of Sciences from 2017 to 2018. A water treatment was used to achieve field water capacities of 20 (W1), 40 (W2), and 60 (W3) cm soil layers under irrigation, and a rain-fed treatment (W0) was added. The model parameters were calibrated using the measured data in 2017. Then, they were applied to 2018 to verify the ability of the model to simulate water stress. The results showed that the variation trends for crop yield, canopy coverage, total soil water content, and the curve in the growth cycle simulated via AquaCrop were consistent with the actual observations; the results of a discrete analysis showed that the values of b (regression coefficient), R² (determination coefficient), and EF (efficiency) were close to 1, and the values of the RMSE (root mean square error) were close to 0, which proved that the model could simulate dynamic changes in summer maize yield, canopy coverage, and total soil water content well. AquaCrop had good applicability in the North China Plain and could be applied to the study of agricultural water consumption and water-use efficiency in this area. The simulated values obtained can serve as an easily obtainable source of long-term experimental data in areas with frequent non-extreme weather events.

Ponding at the soil surface exerts profound impacts on infiltration. However, the effects of ponding depth on infiltration, especially the development of a saturated zone below the soil surface, have yet to be considered in present infiltration models. A new general Green‐Ampt model solution (GAMS) was derived for a one‐dimensional vertical infiltration problem under a uniform initial moisture distribution with ponding on its surface. An expression was included in the new solution for simulating the saturated layer developed below the soil surface as long as the pressure head at the surface is sufficiently high to saturate the soil. The GAMS simulates the infiltration processes closer to the numerical solution by HYDRUS‐1D than the traditional and the recently improved Green‐Ampt model. Moreover, an inversion method to improve the estimates of soil hydraulic parameters from one‐dimensional vertical infiltration experiments that is based on the GAMS was suggested. The effect of ponding depth (h_p), initial soil moisture content, soil texture, and hydraulic soil properties (saturated hydraulic conductivity K_s, water‐entry suction h_d and shape coefficient n of soil water retention curve) in the saturated zone was also evaluated. The results indicate that the saturated zone length increased at a comparable rate with the unsaturated wetted zone length during infiltration. Generally, a larger saturated zone was found for soils with higher initial soil moisture contents, coarser texture, higher K_s values, greater n, and lower −h_d. Our findings reveal that including the saturated zone in the infiltration model yields a better estimate of the soil hydraulic parameters. The proposed GAMS model can improve irrigation design and rainfall‐runoff simulations.

Ponding at the soil surface exerts profound impacts on infiltration. However, the effects of ponding depth on infiltration, especially the development of a saturated zone below the soil surface, have not been considered in present infiltration models. A new general Green-Ampt model solution (GAMS) was derived for a one-dimensional vertical infiltration into soils under a uniform initial moisture distribution with ponding on its surface. An expression was included in the new solution for simulating the saturated layer developed below the soil surface as long as the pressure head at the surface is greater than the water-entry suction. The GAMS simulates the infiltration processes closer to the numerical solution by HYDRUS-1D than the traditional and a recently improved Green-Ampt model. Moreover, an inversion method to improve the estimates of soil hydraulic parameters from one-dimensional vertical infiltration experiments that is based on the GAMS was suggested. The effect of ponding depth (hp), initial soil moisture content, soil texture, and hydraulic soil properties (Ks, hd and n) in the saturated zone was also evaluated. The results indicate that the saturated zone developed at a much faster rate than the unsaturated zone during infiltration. Generally, a larger saturated zone was found for soils with higher initial soil moisture content, coarser texture, higher Ks values and lower hd and n. Our findings reveal that including the saturated zone in the infiltration model yields a better estimate for the soil hydraulic parameters. The proposed GAMS model can improve irrigation design and rainfall-runoff simulations.