Assessing biogeochemical effects and best management practice for a wheat–maize cropping system using the DNDC model

Contemporary agriculture is shifting from a single-goal to a multi-goal strategy, which in turn requires choosing best management practice (BMP) based on an assessment of the biogeochemical effects of management alternatives. The bottleneck is the capacity of predicting the simultaneous effects of different management practice scenarios on multiple goals and choosing BMP among scenarios. The denitrification–decomposition (DNDC) model may provide an opportunity to solve this problem. We validated the DNDC model (version 95) using the observations of soil moisture and temperature, crop yields, aboveground biomass and fluxes of net ecosystem exchange of carbon dioxide, methane, nitrous oxide (N2O), nitric oxide (NO) and ammonia (NH3) from a wheat–maize cropping site in northern China. The model performed well for these variables. Then we used this model to simulate the effects of management practices on the goal variables of crop yields, NO emission, nitrate leaching, NH3 volatilization and net emission of greenhouse gases in the ecosystem (NEGE). Results showed that no-till and straw-incorporated practices had beneficial effects on crop yields and NEGE. Use of nitrification inhibitors decreased nitrate leaching and N2O and NO emissions, but they significantly increased NH3 volatilization. Irrigation based on crop demand significantly increased crop yield and decreased nitrate leaching and NH3 volatilization. Crop yields were hardly decreased if nitrogen dose was reduced by 15% or irrigation water amount was reduced by 25%. Two methods were used to identify BMP and resulted in the same BMP, which adopted the current crop cultivar, field operation schedules and full straw incorporation and applied nitrogen and irrigation water at 15 and 25% lower rates, respectively, than the current use. Our study indicates that the DNDC model can be used as a tool to assess biogeochemical effects of management alternatives and identify BMP

Modeling nitrogen loadings from agricultural soils in southwest China with modified DNDC

Degradation of water quality has been widely observed in China, and loadings of nitrogen (N) and other nutrients from agricultural systems play a key role in the water contamination. Process‐based biogeochemical models have been applied to quantify nutrient loading from nonpoint sources at the watershed scale. However, this effort is often hindered by the fact that few existing biogeochemical models of nutrient cycling are able to simulate the two‐dimensional soil hydrology. To overcome this challenge, we launched a new attempt to incorporate two fundamental hydrologic features, the Soil Conservation Service curve and the Modified Universal Soil Loss Equation functions, into a biogeochemistry model, Denitrification‐Decomposition (DNDC). These two features have been widely utilized to quantify surface runoff and soil erosion in a suite of hydrologic models. We incorporated these features in the DNDC model to allow the biogeochemical and hydrologic processes to exchange data at a daily time step. By including the new features, DNDC gained the additional ability to simulate both horizontal and vertical movements of water and nutrients. The revised DNDC was tested against data sets observed in a small watershed dominated by farmlands in a mountainous area of southwest China. The modeled surface runoff flow, subsurface drainage flow, sediment yield, and N loading were in agreement with observations. To further observe the behaviors of the new model, we conducted a sensitivity test with varied climate, soil, and management conditions. The results indicated that precipitation was the most sensitive factor determining the rate of N loading from the tested site. A Monte Carlo test was conducted to quantify the potential uncertainty derived by variations in four selected input parameters. This study demonstrates that it is feasible and effective to use enhanced biogeochemical models such as DNDC for quantifying N loadings by incorporating basic hydrological features into the model framework

Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

Complementary and alternative medicine use and absenteeism among individuals with chronic disease

Background It is estimated that over half of the adult U.S. population currently has one or more chronic conditions, resulting in up to an estimated $1,600 in productivity loss annually for each employee with chronic disease. Previous studies have suggested that integrating alternative or complementary health approaches with conventional medicine may be beneficial for managing the symptoms, lifestyle changes, treatment, physical and psychosocial consequences that result from chronic illness. Methods Using the 2012 National Health Interview Survey Data, we examined the associations between self-reported use of various forms of complementary and alternative medicine (CAM) therapies (dietary supplements, mind-body practices) and the number of days missed from job or business in the past 12 months due to illness or injury. Multivariable Poisson regression was used to determine the association between CAM use and absence from work among individuals with one or more chronic disease (n = 10,196). Results Over half (54 %) of the study population reported having one chronic disease, while 19 % had three or more conditions. The three most common chronic diseases were high cholesterol (48 %), arthritis (35 %) and hypertension (31 %). More participants used dietary supplements (72 %) while fewer individuals reported using mind-body practices (17 %) in the past twelve months. Over half of individuals reported missing any number of days from job or business due to illness or injury (53 %). Of those who had missed any days from work, 42 % missed one or two days, 36 % missed three to five days, and 23 % missed six days or more. The rate of missing days from job or business due to injury or illness increased among those who reported use of mind-body practices (Incidence Rate Ratio (IRR) = 1.55, 95 % CI: 1.09, 2.21). There was no association between use of dietary supplements and absenteeism (IRR = 1.13, 95 % CI: 0.85, 1.51). Conclusions In a population of individuals with chronic disease, individuals who reported use of mind-body practices had higher rate of absenteeism due to injury or illness. Future studies should examine the effects CAM on symptoms associated with chronic disease and whether managing these symptoms can reduce absence from work, school, and other responsibilities. Keywords Dietary supplements Mind-body practices Complementary and alternative medicine Employee health Absenteeism Chronic diseas

Characteristics of multiple‐year nitrous oxide emissions from conventional vegetable fields in southeastern China

The annual and interannual characteristics of nitrous oxide (N2O) emissions from conventional vegetable fields are poorly understood. We carried out 4 year measurements of N2O fluxes from a conventional vegetable cultivation area in the Yangtze River delta. Under fertilized conditions subject to farming practices, approximately 86% of the annual total N2O release occurred following fertilization events. The direct emission factors (EFd) of the 12 individual vegetable seasons investigated ranged from 0.06 to 14.20%, with a mean of 3.09% and a coefficient of variation (CV) of 142%. The annual EFd varied from 0.59 to 4.98%, with a mean of 2.88% and an interannual CV of 74%. The mean value is much larger than the latest default value (1.00%) of the Intergovernmental Panel on Climate Change. Occasional application of lagoon‐stored manure slurry coupled with other nitrogen fertilizers, or basal nitrogen addition immediately followed by heavy rainfall, accounted for a substantial portion of the large EFds observed in warm seasons. The large CVs suggest that the emission factors obtained from short‐term observations that poorly represent seasonality and/or interannual variability will inevitably yield large uncertainties in inventory estimation. The results of this study indicate that conventional vegetable fields associated with intensive nitrogen addition, as well as occasional applications of manure slurry, may substantially account for regional N2O emissions. However, this conclusion needs to be further confirmed through studies at multiple field sites. Moreover, further experimental studies are needed to test the mitigation options suggested by this study for N2O emissions from open vegetable fields

Identifying distinct trajectories of health behaviors after a breast cancer diagnosis

Breast cancer (BC) survivors are at increased risk of cancer recurrence, a second cancer, and non-cancer comorbidities. Previous studies suggest that many women adopt a spontaneous change in lifestyle after a BC diagnosis in hope of achieving a better survival outcome. While this observation has led to the suggestion that a BC diagnosis is a “teachable moment” for improving health behaviors, other conflicting studies report that BC survivors do not make positive changes in health behaviors following a breast cancer diagnosis. Although previous studies suggest that receipt of cancer chemotherapy and hormonal therapy is associated with weight loss or weight gain, the association between post-diagnosis weight change with changes in lifestyle has not been studied in detail. The majority of prior studies of post-diagnosis changes in behavior and weight have examined the mean change between two time points, and therefore may over simplify the trajectory of change over time due to lack of more granular data. New methods are needed to examine the distribution and correlates of behavior/weight trajectories following the BC diagnosis. In my dissertation, a systematic literature review was conducted to evaluate the evidence regarding the frequency, magnitude and pattern of post-diagnosis changes in diet [fruit/vegetable (F/V), dietary fat], physical activity [moderate to vigorous physical activity (MVPA) and sedentary behaviors], alcohol intake, and body weight among BC survivors. A total of 66 studies were included in the systematic review. These studies suggest that after a breast cancer diagnosis, women are less likely to engage in MVPA and more likely to reduce alcohol intake. Previous studies suggested that women may experience weight change after a BC diagnosis, although there were strong evidence showing both weight gain and weight loss were common. The reports of changes in diet and sedentary behavior following a BC diagnosis are limited and inconclusive about the direction of change. The results of the review suggested that there is wide variation in post-diagnosis lifestyle changes among BC survivors. However, very few studies have investigated the variability in multiple behavior trajectories following a BC diagnosis. In this dissertation, I made use of a population of 4,505 women newly diagnosed with a BC and enrolled in the Kaiser Permanente Northern California Pathways Study. I used a combination of statistical methods, including a semi-parametric, group-based trajectory modeling and a non-parametric K-means for longitudinal data analysis, to identify latent trajectories groups that are unobserved clusters of individuals following similar trajectories of a behavior. These analyses tested the hypotheses that in the 24 months following a breast cancer diagnosis, women follow a mixture of lifestyle (F/V, dietary fat, MVPA, sedentary behavior, alcohol) and body mass index (BMI) trajectories, which can be stable, temporarily increase or temporarily decrease. My analysis identified multiple distinct trajectories of lifestyle behaviors and BMI during the first 24 months after a BC diagnosis. The trajectory analysis results suggest that the large majority of women maintained their lifestyles following a BC diagnosis. Socioeconomic status, dispositional optimism, perceived social support, and the severity of CIPN during active treatment were associated with the post-diagnosis trajectories of. Furthermore, the BMI trajectories were stable over the first 24 months following a BC diagnosis. The BMI trajectories were associated with trajectories of F/V, dietary fat intake, MVPA, sedentary behavior and alcohol intake over the same period, independent of demographic characteristics, tumor characteristics and cancer treatment received. In summary, previous studies suggest that women may spent fewer time on MVPA and drink less alcohol after a BC diagnosis, while both weight gain and loss are common post diagnosis. In a trajectory analysis of 4505 BC survivors enrolled in the Pathways Study, I did not observe any latent trajectory of meaningful change in health behavior or BMI in the first 24 months after a BC diagnosis in the Pathways Study. Instead, my analysis suggests that most women maintained their body weight following a BC diagnosis. The BMI trajectories were strongly associated with trajectory of F/V, dietary fat intake, MVPA, sedentary behavior, and alcohol intake over the same period, independent of demographic characteristics, tumor characteristics and receipt of cancer therapies. These results suggest that there is an absence of spontaneous changes in lifestyle behaviors after BC diagnosis and the importance of maintaining a healthy lifestyle in weight management after a BC diagnosis. Future studies should examine the associations of these health behaviors and BMI trajectories and BC prognosis to better understand the effect of post-diagnosis changes in lifestyle and weight on BC-specific and all-cause mortality