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
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
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
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.
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。
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.
