Determining optimal range of reduction rates for nitrogen fertilization based on responses of vegetable yield and nitrogen losses to reduced nitrogen fertilizer application.

Vegetable production is commonly accompanied by high nitrogen fertilizer rates but low nitrogen use efficiency in China. Reduced fertilization has been frequently recommended in existing studies as an efficient measurement to avoid large amount of nutrient loss and subsequent nonpoint source pollution. However, the reported responses of vegetable yield and nitrogen losses to reduced fertilization rates varied in a large range, which has resulted into large uncertainties in the potential benefits of those recommended reduction rates. Thus, we constructed the relationship between responses of nitrogen losses and vegetable yield to reduced nitrogen fertilization rates to determine the optimal range of reduction rates for nitrogen fertilization in a proportional form based on data reported in literatures across China's mainland, and evaluated the roles of greenhouse, managing options, and vegetable species on the responses. The relationships were constructed separately for 4 subregions: Northern arid and semiarid, loess plateau regions (NSL), Temperate monsoon zone (TMZ), Southeast monsoon zone (SMZ), Southwest zone (SWZ). The optimal nitrogen fertilizer reduction range for the TMZ, SMZ and SWZ were 51 % to 67 %, 40 % to 66 % and 54 % to 80 %, respectively and no reduction for NSL. Vegetable yields were not be sacrificed when fertilizations were reduced within the optimal ranges. Greenhouse and managing options showed no significant effect on the responses of both vegetable yield and nitrogen losses by the optimal reduction range but vegetable species played a relatively important role on the responses of vegetable yield. This indicated that the optimal reduction rates can be effective on reducing nitrogen loss in both open-field and greenhouse conditions across China's mainland without extra managing options. Therefore, the optimal reduction rates can still serve as a good starting point for making regional plans of nitrogen reduction that help balancing the chasing of high vegetable yield and low nitrogen loss.

N-glycosylation of the SARS-CoV-2 spike protein at Asn331 and Asn343 is involved in spike-ACE2 binding, virus entry, and regulation of IL-6.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global public health crisis. The causative agent, the SARS-CoV-2 virus, enters host cells via molecular interactions between the viral spike protein and the host cell ACE2 surface protein. The SARS-CoV-2 spike protein is extensively decorated with up to 66 N-linked glycans. Glycosylation of viral proteins is known to function in immune evasion strategies but may also function in the molecular events of viral entry into host cells. Here, we show that N-glycosylation at Asn331 and Asn343 of SARS-CoV-2 spike protein is required for it to bind to ACE2 and for the entry of pseudovirus harboring the SARS-CoV-2 spike protein into cells. Interestingly, high-content glycan binding screening data have shown that N-glycosylation of Asn331 and Asn343 of the RBD is important for binding to the specific glycan molecule G4GN (Galß-1,4 GlcNAc), which is critical for spike-RBD-ACE2 binding. Furthermore, IL-6 was identified through antibody array analysis of conditioned media of the corresponding pseudovirus assay. Mutation of N-glycosylation of Asn331 and Asn343 sites of the spike receptor-binding domain (RBD) significantly reduced the transcriptional upregulation of pro-inflammatory signaling molecule IL-6. In addition, IL-6 levels correlated with spike protein levels in COVID-19 patients' serum. These findings establish the importance of RBD glycosylation in SARS-CoV-2 pathogenesis, which can be exploited for the development of novel therapeutics for COVID-19.

Taking full advantage of 'low-quality' datasets in watershed modeling and management: From a perspective of parameter calibration.

The quality of calibration datasets is critical for establishing well-calibrated models for reliable decision-making support. However, the analysis of the influence of calibration dataset quality and the discussion on how to use flawed and/or incomplete datasets are still far from sufficient. An evaluation framework for the impact of model calibration data on parameter identifiability, sensitivity, and uncertainty (ISU) was established. Three quantitative and normalized indicators were designed to describe the magnitude of ISU. With the case study of the upper Daqing River watershed, China and the model SWAT (Soil and Water Assessment Tool), one ideal dataset without quality flaws and 79 datasets with different types of flaws including observation error, low monitoring frequency, short data duration and low data resolution were evaluated. The result showed that 4 of 13 parameters that control canopy, groundwater and channel processes have higher ISU values, indicating the high identifiability, high sensitivity, and low uncertainty. The largest gap of parameter ISU between dataset with quality flaw and ideal dataset was 0.61 due to short data duration, while the smallest gap was -0.28 due to low monitoring data frequency. Although some defective datasets caused unacceptable calibration results and model output, some defective datasets can still be valuable for model calibration which depends on the hydrological processes of interest when applying the model. Equivalent calibration results were yielded by the datasets with similar statistical properties. When using datasets with traditional defective issues for calibration, a new step checking the consistency among decision goal, representative system process, determinative parameters and calibration datasets is suggested. Practices including process-related data selection, dataset regrouping and risk self-reporting when using low-quality datasets are encouraged to increase the reliability of model-based watershed management.

Urbanization and land use regulate soil vulnerability to antibiotic contamination in urban green spaces.

The presence of antibiotics in environment is an emerging concern because of their ubiquitous occurrence, adverse eco-toxicological effects, and promotion of widespread antibiotic resistance. Urban soil, which plays a noticeable role in human health, may be a reservoir of antibiotics because of intensive human disturbance. However, little is understood about the vulnerability of soil to antibiotic contamination in urban areas and the spatial-temporal characteristics of anthropogenic and environmental pressures. In this study, we developed a framework for the dynamic assessment of soil vulnerability to antibiotic contamination in urban green spaces, combining antibiotic release, exposure, and consequence layers. According to the results, soil vulnerability risks shown obvious spatial-temporal variation in urban areas. Areas at a high risk of antibiotic contamination were usually found in urban centers with high population densities and in seasons with low temperature and vegetation coverage. Quinolones (e.g., ofloxacin and norfloxacin) were priority antibiotics that posed the highest vulnerability risks, followed by tetracyclines. We also confirmed the effectiveness of the vulnerability assessment by correlating soil vulnerability indexes and antibiotic residues in urban soils. Furthermore, urbanization- and land use-related parameters were shown to be critical in regulating soil vulnerability to antibiotic contamination based on sensitivity analysis. These findings have important implications for the prediction and mitigation of urban soil contamination with antibiotics and strategies to improve human health.

Reducing risks of antibiotics to crop production requires land system intensification within thresholds.

Land system intensification has substantially enhanced crop production; however, it has also created soil antibiotic pollution, undermining crop production. Here, we projected soil antibiotic pollution risks to crop production at multiple geographical scales in China and linked them to land system intensification (including arable land expansion and input increase). Our projections suggest that crop production will substantially decrease when the soil antibiotic pollution risk quotient exceeds 8.30-9.98. Land systems explain most of the variability in antibiotic pollution risks (21-66%) across spatial scales. The convex nonlinearities in tradeoffs between antibiotic pollution risk and crop production indicate that vegetable and wheat production have higher thresholds of land system intensification at which the risk-yield tradeoffs will peak than do maize and rice production. Our study suggests that land system intensification below the minimum thresholds at multiple scales is required for acceptable antibiotic pollution risks related to crop yield reduction.

Occurrence, spatial distribution and ecological risks of antibiotics in soil in urban agglomeration.

Antibiotics in soil environment are regarded as emerging pollutants and have introduced increasing risks to soil ecosystem and human health in rapid urbanization areas. Identifying the occurrence and spatial variability of antibiotics in soils is an urgent issue in sustaining soil security. In this study, antibiotics in soils were investigated and analyzed in Beijing-Tianjin-Hebei urban agglomeration. The occurrence, spatial distribution, and related affecting factors of antibiotics in soils were identified and ecological risks of antibiotics in soil environment were assessed. Results showed that (1) The mean concentration of soil antibiotics in Beijing-Tianjin-Hebei urban agglomeration was 21.79 µg/kg. Land use substantially affected the occurrence and concentration of antibiotics in soils. Concentrations of antibiotics in cropland and orchard soils were 2-3 times higher than the other land use types. (2) The concentrations of antibiotics in soils in Beijing-Tianjin-Hebei urban agglomeration presented a spatial pattern of high values in southeast, and low values in northwest. Spatial variability of antibiotics in soils was closely related to the application of organic fertilizer and wastewater irrigation as well as topographical features. Furthermore, soil properties and land management policy had substantial influences on soil antibiotics, and soil heavy metals may aggravate the accumulation of antibiotics in soils. (3) Ecological risks assessment of antibiotics in soils demonstrated that erythromycin (ERY), sulfamethoxazole (SMX), and doxycycline (DOX) may introduce high risks to soil ecosystem health, and more attention should be paid to the areas with intensive human activities that had potential high risk to soil ecosystem health. This study suggests that scientific land and soil management should be considered to prevent soil antibiotic pollution and sustain soil security in urban agglomeration.

Can agricultural land use alter the responses of soil biota to antibiotic contamination?

Antibiotics accumulate in soils via various agricultural activities, endangering soil biota that play fundamental roles in maintaining agroecosystem function. However, the effects of land-use heterogeneity on soil biota tolerance to antibiotic stresses are not well understood. In this study, we explored the relationships between antibiotic residues, bacterial communities, and earthworm populations in areas with different land-use types (forest, maize, and peanut fields). The results showed that antibiotic levels were generally higher in maize and peanut fields than in forests. Furthermore, land use modulated the effects of antibiotics on soil bacterial communities and earthworm populations. Cumulative antibiotic concentrations in peanut fields were negatively correlated with bacterial diversity and earthworm abundance, whereas no significant correlations were detected in maize fields. In contrast, antibiotics improved bacterial diversity and richness in forest soils. Generally, earthworm populations showed stronger tolerance to antibiotics than did soil bacterial communities. Agricultural land use differentially modified the responses of the soil bacterial community and earthworm population to antibiotic contamination, and earthworms might provide an alternative for controlling antibiotic contamination.

A Case-Control Study of Follicular Fluid Cytokine Profiles in Women with Diminished Ovarian Reserve.

Ovarian reserve is an important determinant of a woman's reproductive potential, and women with diminished ovarian reserve (DOR) often seek in vitro fertilization (IVF). The underlying etiology of DOR is unknown, but follicular fluid cytokine concentrations likely play a role in follicular development and maturation. The present study seeks to investigate the expression of cytokines in follicular fluid (FF) of women with DOR undergoing IVF and explore correlated functional pathways. One hundred ninety-four women undergoing ovarian stimulation were recruited at the time of oocyte retrieval. Women were classified as having DOR if they met one or more of the following criteria: AMH < 1 ng/ml, FSH > 10 mIU/ml, and/or AFC < 10. Controls included women undergoing IVF for male factor, tubal factor due to tubal ligation, or planned oocyte cryopreservation (non-oncologic). The concentrations of 480 cytokines and related growth factors in follicular fluid were determined using a multiplex immunoassay. Fifty-nine cytokines had significantly different concentrations (53 higher and 6 lower) in the DOR relative to the control group after adjusting for age and body mass index (BMI) (false discovery rate; FDR < 0.1). Using the most informative 44 biomarkers as indicated by a random forest (RF) model, an area under the curve (AUC) of 0.78 was obtained. Thus, follicular microenvironment differs between women with DOR and normal ovarian reserve. The differentially expressed cytokines belong to diverse processes that are primarily involved in follicular maturation and ovulation. These changes may play an important role in treatment outcomes in women with DOR.

Organophosphate esters in surface soils from a heavily urbanized region of Eastern China: Occurrence, distribution, and ecological risk assessment.

Organophosphate esters (OPEs) pose increasing concerns for their widespread distribution in soil environments and potential threat to human health. In this study, we investigated the occurrence and associated risks of seven OPEs in surface soils and the potential influence of human activities on soil OPE contamination in a heavily urbanized region of the Yangtze River Delta in Eastern China. All target OPEs were detected in the soil samples (100% of samples) reflecting their widespread distribution in the study region. The total OPE concentration (the sum of the seven OPEs) ranged from 162.7 to 986.0 ng/g on a dry weight basis, with a mean value of 469.3 ± 178.6 ng/g. Tris (2-butoxyethyl) phosphate was the main compound, accounting for 67-78% of the total OPE concentration. Ecological risk assessment showed that tris(2-chloroisopropyl) phosphate, tris(2,3-dichloropropyl) phosphate, tris(2-butoxyethyl) phosphate, and tris(2-ethylhexyl) phosphate posed a medium potential risk to terrestrial biota (0.1 < risk quotient <1). The human exposure estimation showed insignificant risks to local population. Redundancy analysis revealed that the individual and total OPE contaminations were positively correlated with human activity parameters. The total OPE concentrations were positively correlated to population density (R2 = 0.38, P < 0.001), and urban land use percentage (R2 = 0.39, P < 0.001), while negatively correlated to forest land use percentage (R2 = 0.59, P < 0.001), suggesting a significant contribution of human disturbance to OPE pollution. These results can facilitate OPE contamination control and promote sustainable soil management in urbanized and industrialized regions.

Assessment of extrinsic and intrinsic influences on water quality variation in subtropical agricultural multipond systems.

Understanding wetland water quality dynamics and associated influencing factors is important to assess the numerous ecosystem services they provide. We present a combined self-organizing map (SOM) and linear mixed-effects model (LMEM) to relate water quality variation of multipond systems (MPSs, a common type of non-floodplain wetlands in agricultural regions of southern China) to their extrinsic and intrinsic influences for the first time. Across the 6 test MPSs with environmental gradients, ammonium nitrogen (NH4+-N), total nitrogen (TN), and total phosphate (TP) almost always exceeded the surface water quality standard (2.0, 2.0, and 0.4 mg/L, respectively) in the up- and midstream ponds, while chlorophyll-a (Chl-a) exhibited hypertrophic state (≥28 µg/L) in the midstream ponds during the wet season. Synergistic influences explained 69±12% and 73±10% of the water quality variations in the wet and dry season, respectively. The adverse, extrinsic influences were generally 1.4, 6.9, 3.2, and 4.3 times of the beneficial, intrinsic influences for NH4+-N, nitrate nitrogen (NO3--N), TP, and potassium permanganate index (CODMn), respectively, although the influencing direction and degree of forest and water area proportion were spatiotemporally unstable. While CODMn was primarily linked with rural residential areas in the midstream, higher TN and TP concentrations in the up- and midstream were associated with agricultural land, and NH4+-N reflected a small but non-negligible source of free-range poultry feeding. Pond surface sediments exhibited consistent, adverse effects with amplifications during rainfall, while macrophyte biomass can reflect the biological uptake of CODMn and Chl-a, especially in the mid- and downstream during the wet season. Our study advances nonpoint source pollution (NPSP) research for small water bodies, explores nutrient "source-sink" dynamics, and provides a timely guide for rural planning and pond management. The modelling procedures and analytical results can inform refined assessment of similar NFWs elsewhere, where restoration efforts are required.

Deposition- and transport-dominated erosion regime effects on the loss of dissolved and sediment-bound organic carbon: Evaluation in a cultivated soil with laboratory rainfall simulations.

Erosion-induced soil carbon loss has been identified as a critical process in the global carbon (C) cycle. Surface coverage substantially alters the soil erosion process and the effects of net loss or deposition on soil organic C (SOC). However, information on SOC loss induced by soil erosion at the process level is limited. The aim of this study was to investigate how runoff and erosion regimes affect dissolved and sediment-bound organic C (DOC and SBOC) loss. Thus, six simulated rainfall events were conducted on two laboratory plots (9.75 m × 1.83 m) with different surface coverages (17-83%) and coverage distributions (upslope vs. downslope) using polypropylene geotextiles. The results showed that the variability in the process of runoff and sediment yield existed as a result of altered surface coverage over the erosion zone (SSerosion zone) and covered zone (SScovered zone) on the slope. Thus, the erosion regimes can be identified as deposition- and transport-dominated processes, which were the main soil erosion subprocesses. The surface coverage located downslope (SCtop-bottom slope) can more efficiently reduce runoff (21.9-85.7%) and sediment (67.6-98.3%) than the SCbottom-top slope (runoff: 20.1-83.0%; sediment: 35.0-93.3%), which has the surface coverage located upslope. DOC (8.0-11.3 mg L-1) and SBOC (0.3-0.5 mg g-1) in the deposition-dominated process on the SCtop-bottom slope were higher than in the transport-dominated process on the SCbottom-top slope (DOC: 6.8-10.2 mg L-1; SBOC: 0.2-0.3 mg g-1). The loading of DOC and SBOC was largely dependent on runoff and sediment yield, and DOC load contributed 83.9-89.7% of the SOC loss. Overall, laboratory results highlighted the soil C loss at different hydrological and erosion regimes (deposition- vs. transport-dominated process). This study provides important information that can be used to facilitate further implementations such as watershed modeling of soil C dynamics and the corresponding decision-making processes.

Projecting the effects of agricultural conservation practices on stream fish communities in a changing climate.

How anticipated climate change might affect long-term outcomes of present-day agricultural conservation practices remains a key uncertainty that could benefit water quality and biodiversity conservation planning. To explore this issue, we forecasted how the stream fish communities in the Western Lake Erie Basin (WLEB) would respond to increasing amounts of agricultural conservation practice (ACP) implementation under two IPCC future greenhouse gas emission scenarios (RCP4.5: moderate reductions; RCP8.5: business-as-usual conditions) during 2020-2065. We used output from 19 General Circulation Models to drive linked agricultural land use (APEX), watershed hydrology (SWAT), and stream fish distribution (boosted regression tree) models, subsequently analyzing how projected changes in habitat would influence fish community composition and functional trait diversity. Our models predicted both positive and negative effects of climate change and ACP implementation on WLEB stream fishes. For most species, climate and ACPs influenced species in the same direction, with climate effects outweighing those of ACP implementation. Functional trait analysis helped clarify the varied responses among species, indicating that more extreme climate change would reduce available habitat for large-bodied, cool-water species with equilibrium life-histories, many of which also are of importance to recreational fishing (e.g., northern pike, smallmouth bass). By contrast, available habitat for warm-water, benthic species with more periodic or opportunistic life-histories (e.g., northern hogsucker, greater redhorse, greenside darter) was predicted to increase. Further, ACP implementation was projected to hasten these shifts, suggesting that efforts to improve water quality could come with costs to other ecosystem services (e.g., recreational fishing opportunities). Collectively, our findings demonstrate the need to consider biological outcomes when developing strategies to mitigate water quality impairment and highlight the value of physical-biological modeling approaches to agricultural and biological conservation planning in a changing climate.

Exploring the multiscale hydrologic regulation of multipond systems in a humid agricultural catchment.

Assessing the hydrologic processes over scales ranging from single wetland to regional is critical to understand the hydrologically-driven ecosystem services especially nutrient buffering of wetlands. Here, we present a novel approach to quantify the multiscale hydrologic regulation of multipond systems (MPSs), a common type of small, scattered wetland in humid agricultural regions, because previous studies have stopped in commending the catchment scale flood and drought resilience of these waters, and contemporary models do not adequately represent the corresponding intra-catchment fill-spill relationships. A new version of Soil and Water Assessment Tool (SWAT) was developed to incorporate improved representation of: (1) perennial or intermittent spillage connections of pond-to-pond and pond-to-stream, and (2) bidirectional exchange between pond surface water and shallow groundwater. We present SWAT-MPS, which adopts rule-based artificial intelligence to model the possibilities of different spillage directions and GA-based parameter optimization over the two simulation years (June 2017 to May 2019), with successfully replicated streamflow and pond water-level variations in a 4.8 km2 test catchment, southern China. Water balance analysis and scenario simulations were then executed to assess the hydrologic regulation at single pond, single MPS, and entire catchment scales. Results revealed (1) the presence of 9 series- or series-parallel connected MPSs, in which pond overflow accounted for as much as 59% of the catchment water yield; (2) seasonally- and MPS-independent baseflow support and quickflow attenuation, with ranked level of pond water storage for baseflow support across different landuse types: forest > farm > village, and inversed correlation of pond spillage to baseflow and quickflow variations in the farmland; and (3) MPS-aggregated catchment flood peak reduction (>20%) and baseflow increment (26%) in the following dry days. Meteorological data analysis and simulated average daily values indicated these hydrologic patterns are credible even if extending to a 5-year period. As a first modelling attempt to explore the intra-catchment details of MPSs, our study underscores the water storage and connectivity in their hydrologic regulation, and suggests inventories, long-term field monitoring, and several research directions of the new model for integrated pond management in watersheds and river basins. These findings can inform refined assessment of similar small, scattered wetlands elsewhere, where restoration efforts are required.

CN-China: Revised runoff curve number by using rainfall-runoff events data in China.

The curve number (CN) method developed by the United States Department of Agriculture (USDA) in 1954 is the most common adopted method to estimate surface runoff. For years, applicability of the CN method is a conundrum when implementing to other countries. Specifically, countries with more complex natural environment may require more dedicated adjustments. Therefore, the current CN look-up table provided by USDA might not be appropriate and could be questionable to be applied directly to regions elsewhere. Some studies have been conducted to modify CN values according to specified natural characteristics in scattered regions of mainland China. However, an integral and representative work is still not available to address potential concerns in general matters. In this study, a large set of rainfall-runoff monitoring data were collected to adjust CN values in 55 study sites across China. The results showed that the revised CN values are largely different from CN look-up table provided by USDA, which would lead to huge errors in runoff estimation. In this study, the revised CN (dubbed CN-China) provides better reference guidelines that are suitable for most natural conditions in China. In addition, scientists and engineers from other parts of the world can take advantage of the proposed work to enhance the quality of future programs related to surface runoff estimation.

Is the correlation between hydro-environmental variables consistent with their own time variability degrees in a large-scale loessial watershed?

Temporal scale is an important keyword in environmental hydrology but little information is available in the relationship between correlation and time variability degree of hydro-environmental variables at a watershed scale, which makes it difficult to design effective real-time management strategies. Here we take the Yanhe River Watershed as a study case to simulate and inventory the fractal characteristics of correlation and time variability degree of runoff, rainfall, and NH4+-N at different time scales, focusing on the long-term series of 1984-2012. (i) The coupled modeling framework based on SWAT (Soil and Water Assessment Tool), statistics and fractal theory is a time series analysis method that is particularly suitable for the evaluation of long-range correlation of non-linear time series. The Nash-Sutcliffe Efficiency coefficient (NSE), R2 and PBIAS during the calibration and verification period proved the reliability and acceptability of the established SWAT model in modeling multi-time scale runoff and NH4+-N load in the upstream catchment of Ganguyi hydrological station. (ii) Runoffs at all time scales showed positive correlations with rainfall although the significant level had a certain time scale differences. More interestingly, the correlation between NH4+-N loss and runoff at different time scales was significantly higher than that of rainfall. (iii) Each hydro-environmental variable has different fractal and time variation characteristics at different time scales, and the correlation levels between different hydrological variables are not completely consistent with their own time variability degrees at different time scales. These findings point to a fundamental challenge in managing regions with leading infiltration-excess runoff and uneven nutrient loading because the meteorological and hydrological variables in these regions exhibit the strongest temporal variability, which will affect the effective allocation and implementation in management practices.

Multimedia mass balance approach to characterizing the transport potential of antibiotics in soil-plant systems following manure application.

Antibiotics are ubiquitous in agro-ecosystems worldwide, which can pose remarkable risks to ecological security and human health. However, comprehensive evaluation on the multimedia fate and transport potential of antibiotics in soil-plant systems is still lacking. A mass balance approach was performed to gain insights into the transport and fate of antibiotics in soil-plant systems following manure application. Our results showed that more than 99 % of antibiotics were released from applied manure fertilizer into the soil-plant system. Antibiotic concentrations in soil and plant compartments increased over 120 days. Most of the antibiotics persisted in soil (about 65 %), while less than 0.1 % accumulated in the plants. Rainfall-induced runoff, subsurface interflow and soil water infiltration were alternative transport pathways for antibiotics in soil-plant systems although their contributions were limited. Dissipation was the main removal pathway for antibiotics accounting for about 33 % of total input mass. Tetracyclines had higher mass proportion in soil following by quinolones, whereas most of sulfonamides and macrolides were dissipated. Mass balance approach based on tracking environmental fates of antibiotics can facilitate the understandings in the source comparisons and mitigation strategies, and therefore provide insights to inform modeling and limiting the transport of manure-borne antibiotics to neighboring environmental compartments.

Impact of human activities on phosphorus flows on an early eutrophic plateau: A case study in Southwest China.

The net anthropogenic phosphorus inputs (NAPI) model has been used extensively to assess changes in phosphorus (P) inputs and cycling in the environment. However, temporary populations have generally been unconsidered in these assessments. In this study, the NAPI model was used to estimate P loads from the 16 towns and villages in the Erhai Lake Basin (ELB), Southwest China and to evaluate the potential impact from temporary residents (tourism). The results showed that the average value P inputs in the basin (estimated at 2384 kg P km-2 year-1) were 5 times the national average level, and that temporary residents contributed 1%. Agriculture accounted for most of the net P, with chemical fertilizers (55% of the inputs) as the main source, followed by food and animal feed. Only 9.54% of the P inputs to the basin were exported. River water quality and NAPI were significantly correlated (P < 0.01). Tourism industry contributes significantly to regional economic growth and prosperity, but its beneficial effects on the economy does not equate with the adverse impact on environment. This study illustrates what is happening in Southwest China and provides scientific evidence that shows we need to find novel ways to reduce nutrients.

An innovative modeling approach of linking land use patterns with soil antibiotic contamination in peri-urban areas.

Due to the intensive use and continuous release, high and persistent concentrations of antibiotics are found in soils worldwide. This severe contamination elevates the risks associated with antibiotic exposure and resistance for soil ecosystems and human health. Estimating antibiotic concentrations in soils is a complex and important challenge because the limited information is available on antibiotic use and emission and the high exposure risk to human health occurred in peri-urban areas. In this study, soil antibiotic contamination was linked with land use patterns in a data-scarce peri-urban area in four different seasons, and we established a modeling framework based on land use to estimate spatially explicit distribution of antibiotics in soils. The soil antibiotic concentration was found to be substantially affected by surrounding land use patterns in buffer zones with a radius of 350 m. Agricultural land was the main source of antibiotics entering the soil. Notably, road networks also had considerable impacts on antibiotic residues in soils. Then, a statistical model was developed in describing the linkage between land use patterns and soil antibiotic concentration. Model evaluation suggested that the proposed model successfully simulated the variation of antibiotics in soil with good statistical performance (R2 > 0.7). Finally, the model was extrapolated to investigate detailed distribution of antibiotics in soils. Clear spatial and seasonal dynamics can be found in soil antibiotic concentration. To our knowledge, this was the first attempt to adopt a model focusing on land use pattern to estimate the spatially explicit distribution of antibiotics in soils. Despite of some uncertainties, the research provides a land-use-based modeling approach as a reference for preventing and controlling soil antibiotic contamination in the future.

Investigation of watershed nutrient export affected by extreme events and the corresponding sampling frequency.

Although the real-time monitoring technique has been widely applied due to the improvement of sensors, development of traditional sampling methods is still worth of being discussed due to the economically feasibility. Currently, extreme events (e.g. extreme rainfall caused by climate change) play a relatively important role in nutrient export. However, impacts of extreme events on the optimization of sampling strategy is still not well addressed despite the uncertainty of different frequency sampling programs has been sufficiently discussed in previous studies. Therefore, the corresponding impact of extreme events impact on the optimization of sampling strategy was investigated by examining temporal (i.e., inter-annual and seasonal) variations of available data. Uncertainty of nutrient flux estimates under different sampling frequencies was explored by subsampling daily monitoring data. Results showed that uncertainty in flux estimates differed between nitrogen and phosphorus. The relative error (RE) in annual TN flux estimates ranged from -4.2% to 2.4% (once per three-day) to -21.4-31.1% (monthly sampling), while the RE in annual TP flux estimates varied from -14.1% to 8.2% (once per three-day) to -65.9%-163.4% (monthly sampling). Biweekly and weekly sampling routines are considered the optimal sampling program for total nitrogen (TN) and for total phosphorus (TP) when the extreme events impact were not been considered. The uncertainty of flux estimates with different sampling frequencies increased with the increasing extreme events. High level of uncertainty occurred in years with the most extreme events in 2012 (RE: 21.4-69.0% for TN, 33.3-96.6% for TP), while the lowest can be found in 2011 (RE: 0-20.7% for TN, 0-48.3% for TP) (with the fewest extreme events). In addition, uncertainty in TN and TP flux estimates was generally greater during summer season than during other seasons. These results highlighted the important role of extreme events in nutrient export. Approximately half of the annual TN and TP flux occurred in some extreme days that only accounted for less than 20% in the same year. The onset of these extremes of nutrient export was likely due to the stormflow with addition of external fertilizer and the direct discharge of surface ponding water from paddy fields during special periods of time. These results would be helpful for the optimization of sampling strategy.

A review of pesticide fate and transport simulation at watershed level using SWAT: Current status and research concerns.

The application of pesticides in agriculture is a widely-used way to alleviate pest stresses. However, it also introduces various environmental concerns due to the offsite movement of pesticide residues towards receiving water bodies. While the application of process-based modeling approaches can provide quantitative information on pesticide exposure, there are nonetheless growing requirements for model development and improvement to better represent various hydrological and physico-chemical conditions at watershed scale, and for better model integration to address environmental, ecological and economic concerns. The Soil and Water Assessment Tool (SWAT) is an ecohydrological model used in over 3000 published studies, including about 50 for simulating pesticide fate and transport at the watershed scale. To better understand its strengths and limitations, we conducted a rigorous review of published studies that have used SWAT for pesticide modeling. This review provides recommendations for improving the interior algorithms (fate simulation, pathway representation, transport/pollution control, and other hydrological related improvement) to better represent natural conditions, and for further extension of pesticide exposure modeling using SWAT by linking it with other models or management tools to effectively address the various concerns of environmental researchers and local decision makers. Going beyond past studies, we also recommend future improvement to fill research gaps in developing modularized field level simulation, improved BMPs, new in-pond and in-stream modules, and the incorporation of soft data. Our review pointed out a new insight of pesticide fate and transport modeling at watershed level, which should be seen as steps leading to the direction for model development, as well as better addressing management concerns of local stakeholders for model implementation.