Dataset Information

Quantitative correlations between soil and plants in reclaimed mining dumps using a coupling coordination degree model.

ABSTRACT: It is generally accepted that coevolution between soil and plant has great significance for the sustainable development of mining dumps in fragile eco-environment. However, this was not very clear in opencast mine area located in Western China. Based on comprehensive index systems and a combination of subjective and objective weighting method, a coupling coordination degree model, including comprehensive evaluation function, coupling degree and coupling coordination degree, was established to find the 'short plank' of different reclamation patterns and to quantify the status quo of coevolution between soil and plant systems in mined plots. The results indicated that only the plot with Pinus tabuliformis was under synchronous development, a mixed model of Robinia pseudoacacia-Pi. tabuliformis and R. pseudoacacia monoculture were developed with vegetation lagging, while plots R. pseudoacacia-Ulmus pumila-Ailanthus altissima and original landform were soil lagged. All plots were in the state of primary and intermediate coordination. Thus, some effective measures should be taken for the further development in different patterns.

SUBMITTER: Guo A

PROVIDER: S-EPMC6170530 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Quantitative correlations between soil and plants in reclaimed mining dumps using a coupling coordination degree model.

Guo Anning A Zhao Zhongqiu Z Yuan Ye Y Wang Yangyang Y Li Xuezhen X Xu Ruicong R

Royal Society open science 20180919 9

It is generally accepted that coevolution between soil and plant has great significance for the sustainable development of mining dumps in fragile eco-environment. However, this was not very clear in opencast mine area located in Western China. Based on comprehensive index systems and a combination of subjective and objective weighting method, a coupling coordination degree model, including comprehensive evaluation function, coupling degree and coupling coordination degree, was established to fi ...[more]

PMID: 30839684

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Project description:BackgroundPrimary medical and health care facilities are the first lines of defense for the health of population. This study aims to evaluate the current state and trend of equity and coupling coordination degree (CCD) of staff in primary medical and health care institutions (SPMHCI) based on the quantity and living standards of citizens in China 2013-2019. The research findings are expected to serve as a guideline for the allocation of SPMHCI.MethodsThe data used in this study including the quantity and living standards of citizens, as well as the number of SPMHCI in 31 provincial administrative regions of China, were obtained from the China Statistical Yearbook and the China Health Statistics Yearbook. The equity and CCD for SPMHCI were analyzed by using the Gini coefficient and the CCD model, and the Grey forecasting model GM (1, 1) (GM) was used to predict the equity and CCD from 2020 to 2022.ResultsBetween 2013 and 2019, the number of SPMHCI increased from 3.17 million to 3.50 million, and the population-based Gini coefficient declined from 0.0704 to 0.0513. In urban and rural areas, the Gini coefficients decreased from 0.1185 and 0.0737 to 0.1025 and 0.0611, respectively. The CCD between SPMHCI and citizens' living standards (CLS) changed from 0.5691, 0.5813, 0.5818 to 0.5650, 0.5634, 0.6088 at national, urban, and rural levels, respectively. The forecasting results of GM revealed that at the national, urban and rural levels from 2020 to 2022, the Gini coefficient would rise at a rate of - 13.53, - 5.77%, and - 6.10%, respectively, while the CCD would grow at a rate of - 0.89, 1.06, and 0.87%, respectively.ConclusionsIn China, the number of SPMHCI has increased significantly, with an equitable allocation based on the population. The interaction between SPMHCI and CLS is sufficient, but the degree of mutual promotion is moderate. The government could optimize SPMHCI and improve the chronic disease management services to improve CLS and to ensure the continued operation of primary medical and health care institutions in urban areas.

Project description:Grazing exclusion is an effective management practice to restore grassland ecosystem functioning. However, little is known about the role of soil microbial communities in regulating grassland ecosystem functioning during long-term ecosystem restorations. We evaluated the recovery of a degraded semiarid grassland ecosystem in northern China by investigating plant and soil characteristics and the role of soil microbial communities in ecosystem functioning after 22 years of grazing exclusion. Grazing exclusion significantly increased the alpha diversity and changed the community structure of bacteria, but did not significantly affect the alpha diversity or community structure of fungi. The higher abundance of copiotrophic Proteobacteria and Bacteroidetes with grazing exclusion was due to the higher carbon and nutrient concentrations in the soil, whereas the high abundance of Acidobacteria in overgrazed soils was likely an adaptation to the poor environmental conditions. Bacteria of the Sphingomonadaceae family were associated with C cycling under grazing exclusion. Bacteria of the Nitrospiraceae family, and especially of the Nitrospira genus, played an important role in changes to the N cycle under long-term exclusion of grazing. Quantitative PCR further revealed that grazing exclusion significantly increased the abundance of nitrogen fixing bacteria (nifH), ammonia oxidizers (AOA and AOB), and denitrifying bacteria (nirK and nosZ1). Denitrifying enzyme activity (DEA) was positively correlated with abundance of denitrifying bacteria. The increase in DEA under grazing exclusion suggests that the dependence of DEA on the availability of NO3 - produced is due to the combined activity of ammonia oxidizers and denitrifiers. Our findings indicate that decades-long grazing exclusion can trigger changes in the soil bacterial diversity and composition, thus modulating the restoration of grassland ecosystem functions, carbon sequestration and soil fertility.

Dataset Information

Quantitative correlations between soil and plants in reclaimed mining dumps using a coupling coordination degree model.

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Quantitative correlations between soil and plants in reclaimed mining dumps using a coupling coordination degree model.

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