Preserving the soil quality of the siltated back area in the lower reaches of the Yellow River Basin is the key to the sustainable ecological development of the Yellow River Basin.Soil quality has gradually become an ...Preserving the soil quality of the siltated back area in the lower reaches of the Yellow River Basin is the key to the sustainable ecological development of the Yellow River Basin.Soil quality has gradually become an important part of the ecological landscape construction,so the evaluation of soil quality in the lower reaches of the Yellow River is helpful for the rational utilization of soil resources,and can effectively guide the actual development and construction of the silt back area.After collecting the siltated soil under three different utilization modes in the Gaoqing County section of the lower reaches of the Yellow River Basin,16 soil physical and chemical properties were used as evaluation indexes.The principal component analysis method was used to combine the correlations between the indexes,and the suitable soil indexes were selected to establish a minimum data set for comprehensively evaluating the soil quality of the silt back soil.The results show three key aspects of this system.(1)The minimum dataset for the quality evaluation of siltated soil in the siltation area of the lower reaches of the Yellow River comprised six indexes:capillary water holding capacity,available phosphorus,water content,water-stable macroaggregate content,available potassium and alkaline hydrolyzable nitrogen.The soil quality index SQi-MDS was 0.421,the overall soil quality level was low,and the soil nutrient content was generally"nitrogen deficiency and potassium deficiency".(2)The linear fiting R^(2)=0.82737 between the full dataset and the minimum dataset indicated a positive correlation,so the minimum dataset can accurately evaluate the quality of the soil in the silt back area.(3)The soil quality index values of bare land,forest land and cultivated land were 0.321,0.581 and 0.360,respectively,with the highest soil quality in forest land and the lowest soil quality in bare land.The findings of this paper can provide a theoretical basis and reference for the rational utilization and sustainable development of sedimentary soil in the lower reaches of the Yellow River.展开更多
The paper aims to discuss three interesting issues of statistical inferences for a common risk ratio (RR) in sparse meta-analysis data. Firstly, the conventional log-risk ratio estimator encounters a number of problem...The paper aims to discuss three interesting issues of statistical inferences for a common risk ratio (RR) in sparse meta-analysis data. Firstly, the conventional log-risk ratio estimator encounters a number of problems when the number of events in the experimental or control group is zero in sparse data of a 2 × 2 table. The adjusted log-risk ratio estimator with the continuity correction points based upon the minimum Bayes risk with respect to the uniform prior density over (0, 1) and the Euclidean loss function is proposed. Secondly, the interest is to find the optimal weights of the pooled estimate that minimize the mean square error (MSE) of subject to the constraint on where , , . Finally, the performance of this minimum MSE weighted estimator adjusted with various values of points is investigated to compare with other popular estimators, such as the Mantel-Haenszel (MH) estimator and the weighted least squares (WLS) estimator (also equivalently known as the inverse-variance weighted estimator) in senses of point estimation and hypothesis testing via simulation studies. The results of estimation illustrate that regardless of the true values of RR, the MH estimator achieves the best performance with the smallest MSE when the study size is rather large and the sample sizes within each study are small. The MSE of WLS estimator and the proposed-weight estimator adjusted by , or , or are close together and they are the best when the sample sizes are moderate to large (and) while the study size is rather small.展开更多
【目的】开展土壤健康评价,不仅可以了解甜瓜田土壤健康状况,还可以精准识别土壤障碍因子,为甜瓜田健康土壤培育提供理论支撑。本研究通过建立土壤健康评价数据库并构建最小数据集(minimum data set,MDS),系统评价吐鲁番市甜瓜田的土壤...【目的】开展土壤健康评价,不仅可以了解甜瓜田土壤健康状况,还可以精准识别土壤障碍因子,为甜瓜田健康土壤培育提供理论支撑。本研究通过建立土壤健康评价数据库并构建最小数据集(minimum data set,MDS),系统评价吐鲁番市甜瓜田的土壤健康状况。【方法】在新疆吐鲁番市吐峪沟乡、亚尔镇、三堡乡的甜瓜田中,选择种植年限平均为5年的72个甜瓜地块,采集0—20 cm土层土壤样品,测定了28项土壤物理、化学和生物学指标,建立土壤健康评价数据库。利用主成分分析构建最小数据集,运用线性和非线性评分函数进行土壤健康评价,并通过全数据集(total data set,TDS)对最小数据集的评价结果进行验证。【结果】用主成分分析法筛选出容重、电导率、有效磷、有机碳、交换性钙、土壤呼吸和β-木糖苷酶7个指标,建立了土壤健康评价最小数据集。采用线性评分函数法,基于全数据集和最小数据集计算的土壤健康指数分别为0.44和0.49,变异系数分别为22.5%和18.7%;采用非线性评分函数法,得到的土壤健康指数平均值分别为0.46和0.47,变异系数分别为25.8%和24.3%。基于全数据集和最小数据集计算的土壤健康指数间均呈显著正相关(P<0.01),斜率接近0.9。整体上,吐峪沟乡和亚尔镇甜瓜田土壤健康指数均高于三堡乡。【结论】最小数据集可以代替全数据集用于甜瓜田土壤健康评价,非线性评分函数计算的土壤健康指数变异系数大,说明非线性评分函数更加敏感,建议选择非线性评分函数用于甜瓜田土壤健康评价。新疆吐鲁番市甜瓜田土壤pH为碱性,土壤养分含量处于丰富水平,但有机碳和活性碳含量较低。经最小数据集评价,吐鲁番甜瓜田土壤健康指数在0.5以下,处于中等水平。展开更多
The mathematical modeling for evaluation of the sphericity error is proposed with minimum radial separation center. To obtain the minimum sphericity error from the form data, a geometric approximation technique was de...The mathematical modeling for evaluation of the sphericity error is proposed with minimum radial separation center. To obtain the minimum sphericity error from the form data, a geometric approximation technique was devised. The technique regarded the least square sphere center as the initial center of the concentric spheres containing all measurement points, and then the center was moved gradually to reduce the radial separation till the minimum radial separation center was got where the constructed concentric spheres conformed to the minimum zone condition. The method was modeled firstly, then the geometric approximation process was analyzed, and finally,the software for data processing was programmed. As evaluation example, five steel balls were measured and the measurement data were processed with the developed program. The average iteration times of the approximation technique is 4.2, and on average the obtained sphericity error is 0. 529μm smaller than the least square solution,with accuracy increased by 7. 696%.展开更多
The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusion...The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer（ASTER） data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared（VNIR） and short wave infrared（SWIR） data were transformed using band ratios and minimum noise fraction（MNF）, while the thermal infrared（TIR） data were processed using mafic index（MI） and principal components analysis（PCA）. ASTER band ratios（6/8, 5/4, 2/1） in RGB image and MNF（1, 2, 4） in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.展开更多
Evaluating soil quality(SQ)is crucial for ensuring the long-term stability of restored slope ecosystems,yet selecting efficient assessment methods remains challenging.The aim of this study was to develop a targeted SQ...Evaluating soil quality(SQ)is crucial for ensuring the long-term stability of restored slope ecosystems,yet selecting efficient assessment methods remains challenging.The aim of this study was to develop a targeted SQ evaluation system to compare the differences in the effectiveness of ecological restoration methods for slopes.We analysed the characteristics of 18 soil physicochemical and biological indices within a total data set(TDS)for five restored slopes with distinct ecological restoration techniques and three untreated slopes(as the control)in Yichang,China.Principal component analysis,entropy weight method,and Norm were employed to identify a minimum data set(MDS)and four soil quality index(SQI)models,linear unweighted(SQI_(L-A)),linear weighted(SQI_(L-W)),nonlinear unweighted(SQI_(NL-A)),and nonlinear weighted(SQI_(NL-W)),were used to comprehensively evaluate the MDS-based SQ.The results revealed that(1)MDS,consisting of microbial biomass carbon(MBC),microbial biomass phosphorus(MBP),microbial biomass quotient(qMBC),catalase(CAT),and bulk density(BD),effectively characterized the SQ of the ecological restoration slopes;(2)the SQI_(NL-W)model demonstrated superior discrimination among different ecological restoration slopes,with a significantly greater coefficient of determination(R^(2)=0.881,P<0.01)than other SQI models;and(3)all five ecological restoration techniques effectively improved SQ of slope to varying degrees,elevating it from low to high levels,with the vegetative cement-soil eco-restoration&vegetation concrete eco-restoration technique demonstrating the best effect(SQI_(NL-W)=0.627).Our study developed a practical SQ evaluation system based on the validated MDS and the most suitable SQI model(SQI_(NL-W)).This system enables reliable assessment on the effectiveness of restoration techniques.展开更多
本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science...本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。展开更多
基金The Project of China Coal Geology Group Co.,Ltd.(2023HXFWSBXY005)。
文摘Preserving the soil quality of the siltated back area in the lower reaches of the Yellow River Basin is the key to the sustainable ecological development of the Yellow River Basin.Soil quality has gradually become an important part of the ecological landscape construction,so the evaluation of soil quality in the lower reaches of the Yellow River is helpful for the rational utilization of soil resources,and can effectively guide the actual development and construction of the silt back area.After collecting the siltated soil under three different utilization modes in the Gaoqing County section of the lower reaches of the Yellow River Basin,16 soil physical and chemical properties were used as evaluation indexes.The principal component analysis method was used to combine the correlations between the indexes,and the suitable soil indexes were selected to establish a minimum data set for comprehensively evaluating the soil quality of the silt back soil.The results show three key aspects of this system.(1)The minimum dataset for the quality evaluation of siltated soil in the siltation area of the lower reaches of the Yellow River comprised six indexes:capillary water holding capacity,available phosphorus,water content,water-stable macroaggregate content,available potassium and alkaline hydrolyzable nitrogen.The soil quality index SQi-MDS was 0.421,the overall soil quality level was low,and the soil nutrient content was generally"nitrogen deficiency and potassium deficiency".(2)The linear fiting R^(2)=0.82737 between the full dataset and the minimum dataset indicated a positive correlation,so the minimum dataset can accurately evaluate the quality of the soil in the silt back area.(3)The soil quality index values of bare land,forest land and cultivated land were 0.321,0.581 and 0.360,respectively,with the highest soil quality in forest land and the lowest soil quality in bare land.The findings of this paper can provide a theoretical basis and reference for the rational utilization and sustainable development of sedimentary soil in the lower reaches of the Yellow River.
文摘The paper aims to discuss three interesting issues of statistical inferences for a common risk ratio (RR) in sparse meta-analysis data. Firstly, the conventional log-risk ratio estimator encounters a number of problems when the number of events in the experimental or control group is zero in sparse data of a 2 × 2 table. The adjusted log-risk ratio estimator with the continuity correction points based upon the minimum Bayes risk with respect to the uniform prior density over (0, 1) and the Euclidean loss function is proposed. Secondly, the interest is to find the optimal weights of the pooled estimate that minimize the mean square error (MSE) of subject to the constraint on where , , . Finally, the performance of this minimum MSE weighted estimator adjusted with various values of points is investigated to compare with other popular estimators, such as the Mantel-Haenszel (MH) estimator and the weighted least squares (WLS) estimator (also equivalently known as the inverse-variance weighted estimator) in senses of point estimation and hypothesis testing via simulation studies. The results of estimation illustrate that regardless of the true values of RR, the MH estimator achieves the best performance with the smallest MSE when the study size is rather large and the sample sizes within each study are small. The MSE of WLS estimator and the proposed-weight estimator adjusted by , or , or are close together and they are the best when the sample sizes are moderate to large (and) while the study size is rather small.
文摘【目的】开展土壤健康评价,不仅可以了解甜瓜田土壤健康状况,还可以精准识别土壤障碍因子,为甜瓜田健康土壤培育提供理论支撑。本研究通过建立土壤健康评价数据库并构建最小数据集(minimum data set,MDS),系统评价吐鲁番市甜瓜田的土壤健康状况。【方法】在新疆吐鲁番市吐峪沟乡、亚尔镇、三堡乡的甜瓜田中,选择种植年限平均为5年的72个甜瓜地块,采集0—20 cm土层土壤样品,测定了28项土壤物理、化学和生物学指标,建立土壤健康评价数据库。利用主成分分析构建最小数据集,运用线性和非线性评分函数进行土壤健康评价,并通过全数据集(total data set,TDS)对最小数据集的评价结果进行验证。【结果】用主成分分析法筛选出容重、电导率、有效磷、有机碳、交换性钙、土壤呼吸和β-木糖苷酶7个指标,建立了土壤健康评价最小数据集。采用线性评分函数法,基于全数据集和最小数据集计算的土壤健康指数分别为0.44和0.49,变异系数分别为22.5%和18.7%;采用非线性评分函数法,得到的土壤健康指数平均值分别为0.46和0.47,变异系数分别为25.8%和24.3%。基于全数据集和最小数据集计算的土壤健康指数间均呈显著正相关(P<0.01),斜率接近0.9。整体上,吐峪沟乡和亚尔镇甜瓜田土壤健康指数均高于三堡乡。【结论】最小数据集可以代替全数据集用于甜瓜田土壤健康评价,非线性评分函数计算的土壤健康指数变异系数大,说明非线性评分函数更加敏感,建议选择非线性评分函数用于甜瓜田土壤健康评价。新疆吐鲁番市甜瓜田土壤pH为碱性,土壤养分含量处于丰富水平,但有机碳和活性碳含量较低。经最小数据集评价,吐鲁番甜瓜田土壤健康指数在0.5以下,处于中等水平。
基金Supported by National Natural Science Foundation of China(No.50175081) andTianjin Municipal Science and Technology Commission (No.0431835116).
文摘The mathematical modeling for evaluation of the sphericity error is proposed with minimum radial separation center. To obtain the minimum sphericity error from the form data, a geometric approximation technique was devised. The technique regarded the least square sphere center as the initial center of the concentric spheres containing all measurement points, and then the center was moved gradually to reduce the radial separation till the minimum radial separation center was got where the constructed concentric spheres conformed to the minimum zone condition. The method was modeled firstly, then the geometric approximation process was analyzed, and finally,the software for data processing was programmed. As evaluation example, five steel balls were measured and the measurement data were processed with the developed program. The average iteration times of the approximation technique is 4.2, and on average the obtained sphericity error is 0. 529μm smaller than the least square solution,with accuracy increased by 7. 696%.
基金supported by the Special Fund for Basic Scientific Research of Central Colleges (Nos. 2014G1271060, 2013G1271103)Chang’an University, China and the High Resolution Earth Observation Systems of National Science and Technology Major Projects
文摘The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer（ASTER） data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared（VNIR） and short wave infrared（SWIR） data were transformed using band ratios and minimum noise fraction（MNF）, while the thermal infrared（TIR） data were processed using mafic index（MI） and principal components analysis（PCA）. ASTER band ratios（6/8, 5/4, 2/1） in RGB image and MNF（1, 2, 4） in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China.
基金supported by the fund project of the Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University),Hubei Province,China(Grant No.2023KDZ12)Hubei Provincial Engineering Research Center of Slope Habitat Construction Technique Using Cement-based Materials(China Three Gorges University),Hubei Province,China(Grant No.2022SNJ04).
文摘Evaluating soil quality(SQ)is crucial for ensuring the long-term stability of restored slope ecosystems,yet selecting efficient assessment methods remains challenging.The aim of this study was to develop a targeted SQ evaluation system to compare the differences in the effectiveness of ecological restoration methods for slopes.We analysed the characteristics of 18 soil physicochemical and biological indices within a total data set(TDS)for five restored slopes with distinct ecological restoration techniques and three untreated slopes(as the control)in Yichang,China.Principal component analysis,entropy weight method,and Norm were employed to identify a minimum data set(MDS)and four soil quality index(SQI)models,linear unweighted(SQI_(L-A)),linear weighted(SQI_(L-W)),nonlinear unweighted(SQI_(NL-A)),and nonlinear weighted(SQI_(NL-W)),were used to comprehensively evaluate the MDS-based SQ.The results revealed that(1)MDS,consisting of microbial biomass carbon(MBC),microbial biomass phosphorus(MBP),microbial biomass quotient(qMBC),catalase(CAT),and bulk density(BD),effectively characterized the SQ of the ecological restoration slopes;(2)the SQI_(NL-W)model demonstrated superior discrimination among different ecological restoration slopes,with a significantly greater coefficient of determination(R^(2)=0.881,P<0.01)than other SQI models;and(3)all five ecological restoration techniques effectively improved SQ of slope to varying degrees,elevating it from low to high levels,with the vegetative cement-soil eco-restoration&vegetation concrete eco-restoration technique demonstrating the best effect(SQI_(NL-W)=0.627).Our study developed a practical SQ evaluation system based on the validated MDS and the most suitable SQI model(SQI_(NL-W)).This system enables reliable assessment on the effectiveness of restoration techniques.
文摘本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。
