Effects of climatic data low-pass filtering on the ICBM temperature- and moisture-based soil biological activity factors in a cool and humid climate

The air temperature (T_air), total precipitation (TP) and potential evapotranspiration (PET) are standard input data for soil carbon dynamic models, i.e., for calculating temperature and moisture effects on soil biological activity. The resolution needed depends on objectives, the complexity of models and inbuilt pedotransfer functions. The Introductory Carbon Balance Model (ICBM) soil climate front end model calculates a multiplicative soil-temperature (r_{e_temp}) and -moisture (r_{e_wat}) factor with a daily time-step to estimate soil biological activity, i.e., r_{e_crop} = r_{e_temp} × r_{e_wat}. Our objective was to determine how much r_{e_temp}, r_{e_wat} and r_{e_crop} are affected by low-pass filtering of the climatic input data for a cool, humid temperate region. To achieve this we conducted spectral analysis on T_air, TP, PET and r_{e_crop} in the frequency domain. Thereafter we applied Fourier low-pass filters of 5, 15, 30, 60 and 180 days on T_air, TP, PET and tracked their effects through the soil climate model's state variables and outputs. This was done using a sandy and a heavy clay soil and an 89-year daily time-series from a meteorological station in Quebec (Canada). The Fourier spectra showed that the variance for T_air, PET and r_{e_crop} was dominated by an annual cycle, as could be expected. There was no yearly cycle for TP. The variation in r_{e_temp} explained most of the variance in r_{e_crop}. The soil climate module outputs were not sensitive to low-pass filtering of PET. A daily time-step was needed to avoid overestimating r_{e_crop} for the sandy soil. Using a weekly time-step for TP and T_air allowed us to explain about 80% of the variance in r_{e_crop} for the heavy clay soil. This study also indicates that the standard leaf (and green) area index functions for calculating transpiration should receive more attention, since they have significant effects on the state and output variables.     

Alternative soil quality indices for evaluating the effect of intensive cropping, fertilisation and manuring for 31 years in the semi-arid soils of India

Soil quality assessment provides a tool for evaluating the sustainability of alternative soil management practices. Our objective was to develop the most sensitive soil quality index for evaluating fertilizer, farm yard manure (FYM), and crop management practices on a semiarid Inceptisol in India. Soil indicators and crop yield data from a long-term (31 years) fertilizer, manure, and crop rotation (maize, wheat, cowpea, pearl millet) study at the Indian Agricultural Research Institute (IARI) near New Delhi were used. Plots receiving optimum NPK, super optimum NPK and optimum NPK + FYM had better values for all the parameters analyzed. Biological, chemical, and physical soil quality indicator data were transformed into scores (0 to 1) using both linear and non-linear scoring functions, and combined into soil quality indices using unscreened transformations, regression equation, or principal component analysis (PCA). Long-term application of optimum inorganic fertilizers (NPK) resulted in higher soil quality ratings for all methods, although the highest values were obtained for treatment, which included FYM. Correlations between wheat (Triticum aestivum L.) yield and the various soil quality indices showed the best relationship (highest r) between yield and a PCA-derived SQI. Differences in SQI values suggest that the control (no NPK, no manure) and N only treatments were degrading, while soils receiving animal manure (FYM) or super optimum NPK fertilizer had the best soil quality, respectively. Lower ratings associated with the N only and NP treatments suggest that one of the most common soil management practices in India may not be sustainable. A framework for soil quality assessment is proposed.     

Snow-cover environmental monitoring and assessment in Northeast China using passive microwave emission models

In this study, we present the application of the passive microwave emission models to snow-cover environment monitoring and assessment in Northeast China. The study employs the radiative transfer function and strong fluctuation theory to develop the models. We used the exponential form of a spherical symmetric correlation function to describe random permittivity fluctuations. From strong fluctuation, we then obtained the phase matrix and extinction coefficients of snow-packs for the spherical symmetric correlation function. We also used the vector radiative transfer formula for the layer of a random medium by solving Gaussian quadrature and eigen analysis. By comparing the brightness temperatures at 5, 10.7, 18, and 37 GHz, the modelling results agreed with experimental data of dry-snow physical parameters as measured in the fieldwork.     

艾比湖流域核心区景观生态功能区划及生态调控措施研究

在探讨了景观生态功能区划的概念、原则及区划方法的基础上,以新疆艾比湖流域核心区为对象,采用叠置法并利用“3S”技术对研究区进行了自下而上的景观生态功能区的划分,共划分出4个景观生态功能区和9个景观生态功能亚区。分析了各景观功能区的主导生态功能、保护目标,并有针对性地提出了景观生态调控的工程措施和管理措施,为恢复和重建艾比湖流域景观生态安全格局提供科学的参考依据。     

水功能区与水环境功能区划分归一研究

水功能区划分和水环境功能区划分最终目标都是为了水资源的可持续利用,同时使水环境得到有效的保护.但由于两种划分的立足点不同,划分的侧重点、分类体系、功能区名称存在一定的差异,各自划分容易由于使用和管理的不统一造成混乱.通过浙江省水功能区和水环境功能区的舍二为一划分,合理确定了全省各流域水系水体的水质保护目标和使用功能,以保证水资源开发利用发挥最佳经济、社会、环境效益.     

基于VEGETATION数据的区域生态系统质量评价之二——生产能力指数评价

区域生态系统生产能力指数是评价其生态功能的重要指标之一.文章构建了区域生态系统生产能力指数评价模型,并对中国1998～2004年间区域生态系统生产能力进行评价,发现中国各区域生态系统的生产能力在时空发布上差异巨大,在空间上呈现从西北往东南逐级变好的趋势,西北最差.在时间分异上,区域生态系统生产能力呈现明显的季节性发布,尤以北方地区最为明显.     

柴窝堡湖的生态功能价值及其保护

柴窝堡湖湿地是乌鲁木齐市的门户,南郊的最佳水上旅游景点和渔业基地,是候鸟迁飞的重要歇息地,是乌鲁木齐地区古人类文明的发源地和生存的摇篮,还是我国批准的第100个湿地公园。但是,作为乌鲁木齐市第二水源地过度抽水,使生态环境急剧恶化,面临干涸。保护柴窝堡湖生态环境,特别是保持适当的水面积,势在必行!     

Brassinosteroids protect photosynthetic machinery against the cadmium induced oxidative stress in two tomato cultivars

The present study was conducted with an aim to gain better insight of brassinosteroid generated response on the effects of cadmium on photosynthetic machinery and active oxygen metabolism in two tomato cultivars (K-25 and Sarvodya). These tomato cultivars were subjected to graded cadmium levels in soil (0, 3, 6, 9 or 12 mg kg⁻¹ soil) with their foliage being sprayed with 0 or 10⁻⁸ M of 28-homobrassinolide/24-epibrassinolide (HBL/EBL) at 59 d stage. The results suggested that photosynthetic parameters, leaf water potential and activity of several enzymes (nitrate reductase and carbonic anhydrase) decreased significantly in both the cultivars, to a lesser extent in K-25 than Sarvodya with the increasing levels of cadmium in the soil. However, the activity of antioxidant enzymes and proline content increased in response to metal treatment as well as the application of brassinosteroids (HBL/EBL). Overall, exogenous application of brassinosteroids improved the activity of photosynthetic machinery and that of antioxidant defense system in both the cultivars, and also nullified the damaging effect of metal on these parameters.     

Transfer functions for solid-solution partitioning of cadmium for Australian soils

To assess transport and ecotoxicological risks of metals, such as cadmium (Cd) in soils, models are needed for partitioning and speciation. We derived regression-based “partition-relations” based on adsorption and desorption experiments for main Australian soil types. First, batch adsorption experiments were carried out over a realistic range of dissolved Cd concentrations in agricultural soils in Australia. Results showed linear sorption relationships, implying the adequacy of using Kd values to describe partitioning. Desorption measurements were then carried out to assess in-situ Kd values and relate these to soil properties The best transfer functions for solid-solution partitioning were found for Kd values relating total dissolved Cd concentration to total soil Cd concentrations, accounting for the variation in pH, SOM contents and DOC concentrations. Model predictions compared well with measurements of an independent data set, but there was a tendency to underestimate dissolved Cd concentrations of highly polluted soils.     

Optimization of co-digestion of various industrial sludges for biogas production and sludge treatment: Methane production potential experiments and modeling

Optimal biogas production and sludge treatment were studied by co-digestion experiments and modeling using five different wastewater sludges generated from paper, chemical, petrochemical, automobile, and food processing industries situated in Ulsan Industrial Complex, Ulsan, South Korea. The biomethane production potential test was conducted in simplex-centroid mixture design, fitted to regression equation, and some optimal co-digestion scenarios were given by combined desirability function based multi-objective optimization technique for both methane yield and the quantity of sludge digested. The co-digestion model incorporating main and interaction effects among sludges were utilized to predict the maximum possible methane yield. The optimization routine for methane production with different industrial sludges in batches were repeated with the left-over sludge of earlier cycle, till all sludges have been completely treated. Among the possible scenarios, a maximum methane yield of 1161.53 m³ is anticipated in three batches followed by 1130.33 m³ and 1045.65 m³ in five and two batches, respectively. This study shows a scientific approach to find a practical solution to utilize diverse industrial sludges in both treatment and biogas production perspectives.