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In this paper, we analyze the use of qualitative, quantitative, and mixed methods in the field of rural studies by means of a content analysis of the leading journals. We begin with a short discussion of the pros and cons of mixed methods research in rural studies. We then move on to the empirical portion. We use a classification of published articles for the years 2000, 2004, 2008, 2012, and 2016 in the leading journals in the field: Sociologia Ruralis, Rural Sociology, and Journal of Rural Studies. We found striking differences in the publication policy of the three journals regarding methods applied. Sociologia Ruralis primarily accepts articles of a qualitative nature, and this has scarcely changed over the years. Rural Sociology, on the other hand, accepts mostly quantitative articles, and this has also been quite stable over time. The Journal of Rural Studies has traditionally been oriented towards qualitative research, but, in recent years, mixed method approaches play a visible role (around 20% in 2016). JRS is also the only journal that shows a sharp increase in papers of non-Western origin, with an emphasis on quantitative methods but not on mixed methods. The overall conclusion is that the rural research context offers considerable scope for a broader and increased application of mixed methods, and this merits greater attention among rural journals. • The use of mixed methods research in rural studies is increasing. • There are striking differences in the publication policy of the main journals of rural studies regarding methods applied. • The share of non-Western countries in the published articles is still very limited. • JRS is the only journal that shows a sharp increase in papers of non-Western origin, mainly from China. • The rural research context offers considerable scope for a broader and increased application of mixed methods. [ABSTRACT FROM AUTHOR]

Increasing domestic rapeseed production is an important national goal in China. Researchers often use tools such as crop models to determine optimum management practices for new varieties to increased production. The CROPGRO-Canola model has not been used to simulate rapeseed in China. The overall goal of this work was to identify key inputs to the CROPGRO-Canola model for calibration with limited datasets in the Yangtze River basin. First, we conducted a global sensitivity analysis to identify key genetic and soil inputs that have a large effect on simulated days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index. The extended Fourier amplitude test method (EFAST) sensitivity analysis was performed for a single year at 8 locations in the Yangtze River basin (spatial analysis) and for seven years at a location in Wuhan, China (temporal analysis). The EFAST software was run for 4520 combinations of input parameters for each site and year, resulting in a sensitivity index for each input parameter. Parameters were ranked using the top-down concordance method to determine relative sensitivity. Results indicated that the model outputs of days to flowering, days to maturity, yield, above-ground biomass, and maximum leaf area index were most sensitive to parameters that affect the duration of critical growth periods, such as emergence to flowering, and temperature response to these stages, as well as parameters that affect total biomass at harvest. The five model outputs were also sensitive to several soil parameters, including drained upper and lower limit (SDUL and SLLL) and drainage rate (SLDR). The sensitivity of parameters was generally spatially and temporally stable. The results of the sensitivity analysis were used to calibrate and evaluate the model for a single rapeseed experiment in Wuhan, China. The model was calibrated using two seasons and evaluated using three seasons of data. Excellent nRMSE values were obtained for days to flowering (≤1.71%), days to maturity (≤ 1.48%), yield (≤ 9.96%), and above-ground biomass (≤ 9.63%). The results of this work can be used to guide researchers on model calibration and evaluation across the Yangtze River basin in China. [ABSTRACT FROM AUTHOR]

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The study was conducted at three sites during 2008 and 2009 in the North-East China Plain (NECP). Field experiments consisted of five or six nitrogen (N) fertilization rates (0–350 kg N ha−1). Shoot biomass and N concentration (Nc) of spring maize (Zea mays L.) were determined on six sampling dates during the growing season. Nitrogen application rate had a significant effect on aerial biomass accumulation and Nc. As expected, shoot Nc declined during the growing period. A critical N dilution curve (Nc = 36.5 W −0.48) was determined in China, which was a little different from those reported for maize in France and Germany. Besides, the N nutrition index (NNI) calculated from this critical N dilution curve was significantly related to relative grain yield, which can be expressed by a linear with plateau model (R2 = 0.66; P < 0.001). NNI can be used as a reliable indicator of the level of N deficiency during the growing season of maize. [ABSTRACT FROM AUTHOR]

Observations from 550 surface stations in China during 1961-2000 are used to evaluate the skill of seven global coupled climate models in simulating extreme temperature and precipitation indices. It is found that the models have certain abilities to simulate both the spatial distributions of extreme climate indices and their trends in the observed period. The models' abilities are higher overall for extreme temperature indices than for extreme precipitation indices. The well-simulated temperature indices are frost days (Fd), heat wave duration index (HWDI) and annual extreme temperature range (ETR). The well-simulated precipitation indices are the fraction of annual precipitation total due to events exceeding the 95th percentile (R95T) and simple daily intensity index (SDII). In a general manner, the multi-model ensemble has the best skill. For the projections of the extreme temperature indices, trends over the twenty-first century and changes at the end of the twenty-first century go into the same direction. Both frost days and annual extreme temperature range show decreasing trends, while growing season length, heat wave duration and warm nights show increasing trends. The increases are especially manifested in the Tibetan Plateau and in Southwest China. For extreme precipitation indices, the end of the twenty-first century is expected to have more frequent and more intense extreme precipitation. This is particularly visible in the middle and lower reaches of the Yangtze River, in the Southeast coastal region, in the west part of Northwest China, and in the Tibetan Plateau. In the meanwhile, accompanying the decrease in the maximum number of consecutive dry days in Northeast and Northwest, drought situation will reduce in these regions. [ABSTRACT FROM AUTHOR]

Modelling of the carbon dynamics in arable soils is complex and the accuracy of the predictions is unknown before the model is applied to each specific site. Objectives were (i) to test the accuracy of predictions of the carbon dynamics using the Rothamsted Carbon (RothC) Model in a field trial in Quzhou, North China Plain, using different methods for initialization and estimation of carbon input into the soil and (ii) to test the applicability of the RothC model for plots with either conventional tillage (CT) or no-tillage (NT) systems. A field trial was conducted with applications of differing amounts of N (0, 112 or 187 kg N ha−1 year−1), P (0, 75 or 150 kg P2O5 ha−1 year−1) and wheat straw (0, 2.25 or 4.5 t DM ha−1 year−1) in differing combinations with either CT or NT for 18 years. CT and NT affected stocks of soil organic carbon (SOC) similarly. Carbon inputs from crops were either estimated from published regression functions that relate C inputs to crop yield including rhizodeposition (models 1 and 2) or published root:aboveground biomass ratios (model 3). Model 1, which was not calibrated to the site conditions, was successful in predicting the carbon dynamics in seven out of nine treatments (model efficiencies EF ranged from 0.28 to 0.87), whereas for two treatments, EF (−0.35 and−2.3) indicated an unsuccessful prediction. The prediction of the C dynamics in NT experiments using model 1 was generally successful, but this may have been due to the fact that NT did not have a specific effect on SOC stocks for this trial. Model 2, which was the same as model 1 except for an optimization of the stock of inert organic matter using one treatment, predicted SOC stocks in the remaining eight treatments overall better than model 1. Model 3 was less successful than models 1 and 2 in all treatments (−19 ≤ EF ≤ 0.56). The results indicate that the RothC model may successfully predict C dynamics—for the site studied even without prior calibration as in model 1—, but care should be taken in choosing an appropriate approach for estimating C inputs into the soil. [ABSTRACT FROM AUTHOR]

The ecological and environmental impacts of the Sanmenxia Hydropower Station on the lower reach of the Yellow River were examined based on the monitoring data, since the 1970s, of the Sanmenxia Hydropower Station's normal operation. Different operation modes of the reservoir were considered in addition to the effects of tributaries downstream of Sanmenxia. The environmental consequences were evaluated in terms of the total ion content (TIC), since it is regarded as the most important index reflecting the status of natural water quality in the Yellow River. However, the ecological consequence was assessed according to the severity level of the no-flow events, which has become the major concern of the Yellow River Authorities in recent years. The TIC monitored at the hydrological stations along the lower Yellow River was closely related to the reservoir's operation mode and the inflow from the tributaries between Sanmenxia and Huayuankou. Also, the variation of the severity level of the no-flow events is primarily controlled by the operation modes. The present study is of fundamental importance to determine the relative optimal operation mode of the hydropower station, so as to harmonize various purposes and constraints such as a decrease of the TIC and the severity level of the no-flow events, an increase in power generation, irrigation, and flood prevention. [ABSTRACT FROM AUTHOR]