Land degradation and management of red beds in China: Two case studies

Yan, Lei; Kašanin‐Grubin, Milica

doi:10.1007/s11629-019-5560-2

Cited by 17 publications

(7 citation statements)

References 57 publications

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“…Although the domestic management theory analysis model has been developed for several years, there are still some deficiencies in the establishment, operation, and upgrading of the sports data mining model compared with some more developed countries [ 5 ]. Wei et al optimized the data analysis process according to the management principle of three-dimensional space.…”

Section: Related Workmentioning

confidence: 99%

Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0

Hou

2022

Computational Intelligence and Neuroscience

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The digital age of artificial intelligence marks the rapid development of tourism engineering and the gradual improvement of intelligent management theory. This study aims to solve the problems of low efficiency of dynamic relationship analysis and low data utilization in traditional intelligent management methods of tourism engineering. This work studies the dynamic optimization model of tourism engineering management theory based on the artificial intelligence data analysis model and designs the dynamic analysis model of tourism engineering management data based on the convolution neural network. The model can collect dynamic data information of tourism management from many aspects and can also be used to study and analyze human behavior patterns based on the convolutional neural network algorithm. According to the human behavior data analysis model and convolution neural network algorithm, this study formulates the real-time management data scheme of tourism engineering and better extracts the characteristic information of the dynamic data of tourism engineering management. The results show that the topology optimization model of tourism intelligent management based on the convolutional neural network achieves high feasibility, high data accuracy, and high response speed. It can improve the collaborative coupling relationship between management efficiency and dynamic data in tourism engineering management based on big data analysis technology. It realizes the effective combination of tourism management, digital management, and artificial intelligence algorithm.

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Section: Related Workmentioning

confidence: 99%

Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0

Hou

2022

Computational Intelligence and Neuroscience

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“…The China Danxia refers to a red terrestrial landscape of sedimentary origin formed by endogenous (crustal uplift) and exogenous (weathering and water erosion) forces, covering an area of about 822 km 2 (UNESCO, 2010). The China Danxia is a particularly ecologically fragile region in South China because of its prolonged exposure to exogenous forces, which resulted in its soils losing ions and nutrient elements and becoming acidic to strongly acidic, with a loose physical structure, thin soil layers, and exposed parent material (Peng et al, 2011;Yan and Kasanin-Grubin, 2019). Consequently, the Grain for Green Program has been implemented widely in South China due to land degradation in the China Danxia (Yan and Kasanin-Grubin, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The China Danxia is a particularly ecologically fragile region in South China because of its prolonged exposure to exogenous forces, which resulted in its soils losing ions and nutrient elements and becoming acidic to strongly acidic, with a loose physical structure, thin soil layers, and exposed parent material (Peng et al, 2011;Yan and Kasanin-Grubin, 2019). Consequently, the Grain for Green Program has been implemented widely in South China due to land degradation in the China Danxia (Yan and Kasanin-Grubin, 2019). Vegetation restoration has been shown to be an effective practice in reverse the declining trend of land productivity by improving a variety of ecosystem services and functions (Yang et al, 2020;Resch et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Vegetation restoration of abandoned cropland improves soil ecosystem multifunctionality through alleviating nitrogen-limitation in the China Danxia

Wang

Yang²,

Zhang³

et al. 2023

Front. Plant Sci.

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The microbial requirement for nutrient resources can be estimated by soil extracellular enzyme stoichiometry (EES) and their stoichiometries. Implementing the Grain for Green Program has significantly impacted land use and soil nutrient management in the China Danxia. However, drivers of soil microbial nutrient limitation changes in abandoned cropland (AC) remained unclear after vegetation restoration. Here, according to vector analysis, we evaluated microbial nutrient limitation by studying soil EES across vegetation restoration types (naturally restored secondary forests (NF) and artificially planted forests (AF)) with AC as a control. Results showed both NF and AF soils averaged higher C- and P- acquiring enzyme, indicating rapid C and P turnover rates after vegetation restoration. However, vegetation restoration resulted in higher C requirement for microorganisms with higher enzyme C:N and vector length. In addition, microorganisms shifted from N- (< 45°) to P-limited (> 45°) conditions with enzyme N:P less than 1 after vegetation restoration, and NF exacerbated microbial P limitation compared to AF. Decreased N limitation following vegetation restoration could be contributed to improving soil ecosystem multifunctionality. The greater variation of EES was explained by the interaction of pH, soil nutrient, and microbial biomass than by any one of these factors alone, suggesting that both abiotic and biotic factors regulate microbial nutrient limitation and microbial process. Overall, our results revealed vegetation restoration could alleviate N limitation in the China Danxia, and thus enhance soil ecosystem by regulating lower microbial N limitation, which provide insight into nutrient management strategies under ecological restoration of degraded areas.

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“…The red beds area covers 9.16 × 10 5 km 2 , accounting for 9.5% of the total land area of China [1], which exceeds the loess area (6.3 × 10 4 km 2 ) [2] and is close to the total area of bare carbonate rock (9.1 × 10 4 km 2 ) [3]. Furthermore, there are 144 million people depending on agriculture or tourism in red bed regions for their livelihoods [4]. Under the influence of temperature difference, moisture, and heavy metals, the red bed soft rock disintegrates easily [5,6] because it is a rock series of coarse and hard red continental clastic accumulation mainly composed of conglomerate, sandstone, mudstone, etc.…”

Section: Introductionmentioning

confidence: 99%

Effects of Forest Vegetation Restoration on Soil Organic Carbon and Its Labile Fractions in the Danxia Landform of China

et al. 2022

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The Danxia landform is a unique red bed landform in China. The effects of vegetation restoration on soil organic carbon (SOC) components are still poorly understood in the Danxia landform region of southwest China. In this study, soil samples were collected from selected five different vegetation restoration types (shrub (SH), mixed conifer–broadleaf forest (MCBF), evergreen broad-leaved forest (EBF), Chinese fir forest (CFF), and bamboo forest (BF)) at 0–30 cm depth to discuss the concentrations and stocks of SOC and its labile organic carbon (LOC) fractions ((dissolved organic C (DOC), microbial biomass C (MBC), and easily oxidized organic C (EOC)) and their relationship with soil physicochemical properties and enzyme activities. The results indicated that the contents of SOC and LOC fractions as well as SOC stocks declined with increasing soil depth in five vegetation restoration types. At 0–30 cm depth, BF and CFF showed higher the average concentrations and total stocks of SOC and EOC compared with SH, EBF, and MCBF. The highest average DOC content was in BF, but no significant differences was observed in the total DOC stocks among five vegetation restoration types. BF and EBF showed significantly greater average MBC concentrations and total MBC stocks than other vegetation restoration types. SOC and its LOC fractions were positively correlated with soil moisture and three enzyme activities in different degrees under the five vegetation restoration types and closely related with total nitrogen (TN) and total phosphorus (TP) except for TP of CFF and BF and negatively affected by pH (except for CFF and the DOC and MBC of MCBF) and BD. Generally, soil TN, TP, and invertase were found to be the main driver factors for soil carbon accumulation. However, the overall levels of SOC and its labile fractions indicate that BF had the strongest carbon storage capacity, followed by CFF and EBF. This study can provide a good reference for ecosystem management and the selection of appropriate restoration strategies in Danxia landform regions.

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Land degradation and management of red beds in China: Two case studies

Cited by 17 publications

References 57 publications

Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0

Research on Management Efficiency and Dynamic Relationship in Intelligent Management of Tourism Engineering Based on Industry 4.0

Vegetation restoration of abandoned cropland improves soil ecosystem multifunctionality through alleviating nitrogen-limitation in the China Danxia

Effects of Forest Vegetation Restoration on Soil Organic Carbon and Its Labile Fractions in the Danxia Landform of China

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