PR | IFPRI3; ISI; CRP3.2; 4 Transforming Agricultural and Rural Economies | Development Strategies and Governance (DSG); Transformation Strategies | CGIAR Research Program on Maize (MAIZE)

Conservation of soil health and crop productivity is the central theme for sustainable agriculture practices. It is unrealistic to expect that the burgeoning crop production demands will be met by a soil ecosystem that is increasingly unhealthy and constrained. Therefore, the present review is focused on soil amendment techniques, using biochar in combination with arbuscular mycorrhizal fungi (AMF), which is an indispensable biotic component that maintains plant-soil continuum. Globally significant progress has been made in elucidating the physical and chemical properties of biochar; along with its role in carbon sequestration. Similarly, research advances on AMF include its evolutionary background, functions, and vital roles in the soil ecosystem. The present review deliberates on the premise that biochar and AMF have the potential to become cardinal to management of agro-ecosystems. The wider perspectives of various agronomical and environmental backgrounds are discussed. The present state of knowledge, different aspects and limitations of combined biochar and AMF applications (BC + AMF), mechanisms of interaction between biochar and AMF, effects on plant growth, challenges and future opportunities of BC + AMF applications are critically reviewed. Given the severely constrained nature of soil health, the roles of BC + AMF in agriculture, bioremediation and ecology have also been examined. In spite of the potential benefits, the functionality and dynamics of BC + AMF in soil are far from being fully elucidated.

Uncertainty assessment of parameters associated with non-point source pollution mechanism modeling are crucial for improving the effectiveness of pollution controlling. In this study, an approach based on Bayesian inference and integrated Markov chain Monte Carlo and multilevel factorial analysis has been developed, and it can not only apply straightforward Bayesian inference to assess parameter uncertainties, but also quantitatively investigate the main and interactive effects of multiple parameters on the model response variables by measuring the specific variations of model outputs. Its applicability and advantages are presented through the application of the Soil and Water Assessment Tool to Shitoukoumen Reservoir Catchment in northeast China. This study investigated the uncertainties of a set of sensitive parameters and their multilevel effects on model response variables, including average annual runoff (AAR), average annual sediment (AAS) and average annual total nitrogen (AAN). Results revealed that (i) soil conservation service runoff curve number for moisture condition II (CN2) had a positive effect on all response variables; (ii) available water capacity of the soil layer (SOL_AWC) had a negative effect on all response variables; (iii) the universal soil loss equation support practice (USLE_P) had a positive effect on AAS and AAN, and little effect on AAR; while the nitrate percolation coefficient (NPERCO) had a positive effect on AAN, and little effect on AAS and AAR; and (iv) the interactions amongst parameters had obvious interdependent effects on the model response variables, for example, the interaction between CN2 and SOL_AWC had a major impact on AAR. The above findings can improve the simulating and predicting capabilities of non-point source pollution mechanism model. Overall, this study highlights that the proposed approach represents a promising solution for uncertainty assessment of model parameters in non-point source pollution mechanism modeling.

Polyacrylamide (PAM) use in irrigation for erosion control has increased water infiltration and reduced soil erosion. This has improved runoff water quality via lower concentrations of nitrogen, phosphorous, and pesticides, and decreased biological oxygen demand. Since non-toxic high molecular weight anionic PAMs removed clay size sediment particles in flowing water, it was hypothesized that PAM would effectively remove or immobilize microorganisms in flowing water. In an agricultural field at the USDA Agricultural Research Service, Idaho, USA, the efficacy of PAM-treatment of furrow irrigation water to remove several categories of microorganisms in the inflow and runoff was determined. Treatments were: (1) PAM application and a control; (2) three flow rates; (3) two distances from the inflow point; and (4) three times during each irrigation. After water travelled 1 m at 7.5 and 15.5/min, PAM-treatment reduced total bacterial and microbial biomass and total fungal biomass relative to the control treatment. After water travelled 40 m at 7.5, 15.5, and 22.5/min, PAM-treatment reduced algae, the numbers active and total bacteria, active and total fungal length, and total bacterial biomass, total fungal and microbial biomass relative to the control treatment. Although specific organisms were not identified or monitored in this study, the results clearly have implications for controlling the spread of soil-borne plant pathogens and other classes of harmful organisms within and among fields via irrigation water and in re-utilized return flows. Beyond furrow-irrigated agriculture, new methods to manage overland transmission of harmful microorganisms could potentially help control transport of pathogens from animal waste in runoff and groundwater.

We investigated artificial radionuclides (²³⁹⁺²⁴⁰Pu and ¹³⁷Cs) in surface sediments and sediment cores collected from the Bohai Bay and the tidal flat of the Liaodong Bay, China. Increasing trends for ²³⁹⁺²⁴⁰Pu activities and ²⁴⁰Pu/²³⁹Pu atom ratios (˃0.18) were observed from land to sea and from north to south in the Bohai Bay. This spatial pattern implied that the scavenging process between riverine sediments and Pacific Proving Ground (PPG) source Pu transported by the currents such as Yellow Sea Warm Current had occurred in the Bohai Bay. In contrast, relatively lower ²⁴⁰Pu/²³⁹Pu atom ratios in the tidal flat of Liaodong Bay were due to the mixing process between more global out and less PPG source Pu. The riverine Pu contributions to the total global fallout Pu in the Haihe River (32.8%) were much lower than those in the Yangtze River estuary (77%–80%), indicating better soil conservation in the Haihe River Catchment.

Understanding the factors driving ecosystem service (ES) change is essential for maintaining ES functions and achieving sustainable development. Although research on the spatial variations in the effects of driving forces on ESs provides guidance for regional ecological management, the responses of driving forces to environmental conditions have not been adequately investigated, especially in regions with high spatial heterogeneity. By using remote sensing images and socioeconomic data, this paper aims to fill this gap by estimating the spatial distribution characteristics of the effects of driving forces on ESs and their responses to different environmental conditions in Sichuan Province, China. First, the biophysical values of soil conservation (SC) and water yield (WY) were evaluated using ecological simulation models. Second, the spatial distribution of the effects of four driving forces on two services was explored using the geographically weighted regression (GWR) model. Finally, the responses of driving forces to environmental conditions were quantified by using scatter plots. The results revealed that the spatial patterns of SC and WY showed spatial heterogeneity. The effects of driving forces on ESs varied with space. Both positive and negative effects of driving forces were observed in Sichuan Province. Under different biophysical and socioeconomic conditions, the effects of driving forces on ESs showed different change trends, characterized by fluctuating trends and obvious thresholds. In our study area, urban sprawl, impervious surfaces, agricultural expansion, intensive human activities, and complex topographic features contributed to the variations in the effects of driving forces. Our results suggest that the responses of driving forces to different land-use coverage, topographical, NDVI, and socioeconomic conditions should be considered in ecological decision-making. Such research results are expected to manage the driving forces of ESs and serve as a practical reference for local management in order to maintain the functions of ESs and attain sustainable development.

The phenomenon of “equifinality for different parameters” limits the link between parameters and catchment characteristics; however, solving the equifinality problem is a major challenge in the development, generalization, and application of a model. This study focused on the Yanhe River Watershed to investigate the time-varying characteristics of sensitivity and identifiability of SWAT (Soil and Water Assessment Tool) runoff and sediment parameters based on the Sobol’ and generalized likelihood uncertainty estimation methods. The results indicate that (i) the nondominated sorting genetic algorithm-II has good adaptability and reliability in parameter calibration of the SWAT model in the Yanhe River Watershed. The evaluation indicators (Nash–Sutcliffe efficiency, R², and percent bias) of monthly runoff and sediment in the Ganguyi hydrological station were all satisfactory per the SWAT model during the calibration and validation periods. (ii) The interaction between runoff and sediment parameters is a crucial reason for parameter sensitivity, which has obvious time-varying characteristics and is largely dependent on precipitation in the Yanhe River Watershed. Temporal and spatial variability of precipitation should be considered in the detailed analysis of parameter identifiability, and watershed managers should not ignore changes in the runoff process when regulating sediment. (iii) Only a relatively small number of parameters can be identified in the runoff and sediment simulation process of the Yanhe River Watershed, such as CN2 (initial soil conservation service runoff curve number for moisture condition II), CH_K2 (effective hydraulic conductivity in main channel alluvium), ALPHA_BF (baseflow alpha factor), USLE_C (cover and management factor), USLE_P (support practice factor), and USLE_K (soil erodibility factor), due to high surface runoff, reduced lag time, reduced low flows, increased peak flows, and channel erosion, respectively. More importantly, there is a strong positive correlation between parameter identifiability and parameter sensitivity. Both are effective methods of parameter diagnosis, but the identifiability of parameters is not equivalent to its sensitivity. Our results strongly suggest that a detailed parameter sensitivity and identifiability analysis is a critical step in improving hydrological model performance to reduce the risk of “equifinality for different parameters” while articulating all relevant hydrological processes.