Comparing the long‐term effects of artificial and natural vegetation restoration strategies: A case‐study of Wuqi and its adjacent counties in northern China

Xu, Xin; Zhang, Daojun

doi:10.1002/ldr.4018

Cited by 19 publications

(7 citation statements)

References 86 publications

(133 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As GGP is a top-down ecological policy, the annual task of GGP is transmitted stepwise from the provincial government and the final strategy always depends on the local government (Xu and Zhang, 2021a). The government should fully consider the local natural conditions and socio-economic development before planning scientific strategies.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the driving effects of socio-economic development on soil erosion from the perspective of prefecture-level

Wang

Zeng²,

Li³

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

Soil erosion is affected by nature and human activities. Compared with biophysical factors, the effects of socio-economic factors on soil erosion have not been well investigated. Here, taking two prefectures (Yan’an and Qingyang) with different socio-economic conditions and ecological restoration intensity on the Chinese Loess Plateau (CLP) as a case, we combined the Revised Universal Soil Loss Equation (RUSLE), partial least squares structural equation modeling (PLS-SEM), and gray relation analysis to explore the response of soil erosion to socio-economic development. Our results showed that Grain for Green Program (GGP) has effectively controlled soil erosion and increased the vegetation coverage of the study area. For Yan’an, the vegetation coverage was increased by 6.2% and erosion modulus was decreased by 33.9% in 2015 compared with that in 1995. The differences in industrial structure and agricultural input led to different responses of soil erosion to socio-economic development. Economic development and agricultural input accelerated soil erosion in Qingyang but inhibited soil erosion in Yan’an due to different development strategies. Moreover, the increase of the gray relation grade between socio-economic factors and soil erosion in Yan’an indicates that soil erosion is easier to be controlled by the development of the socio-economy. The results indicate that the triple-win situation of economic development, vegetation restoration, and soil conservation can be realized by adjusting the economic structure, strengthening ecological restoration, and agricultural investment. This research emphasizes the important effect of socio-economic development on soil erosion and provides a reference for soil erosion control and ecological restoration for regions suffering from severe soil erosion.

show abstract

Section: Discussionmentioning

confidence: 99%

Evaluation of the driving effects of socio-economic development on soil erosion from the perspective of prefecture-level

Wang

Zeng²,

Li³

et al. 2022

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…In this study, a plant community succession model was developed to detect the long-term effects of mining-induced ground deformation. This model has a wide application potential in research related to spontaneous succession, such as natural based solutions for ecosystems (Xu & Zhang, 2021); however, there are still some limitations in this current model. During the simulation of the mining and non-mining scenarios with initial plant communities, a rapid decrease in the shrub coverages in the early stage of the succession occurred in both scenarios, which did not correspond to the actual changes in the shrub communities.…”

Section: Limitations Of the Plant Community Succession Model And Futu...mentioning

confidence: 99%

Detecting long-term effects of mining-induced ground deformation on plant patterns in semi-arid areas using a cellular automata model

Zhang

Hou

et al. 2022

Preprint

View full text Add to dashboard Cite

Contexts Mining-induced ground deformation has various effects on different plant communities. However, little is known about the effects of ground deformation on plant patterns after spontaneous succession, and there is currently no quantitative approach to the detection of these long-term effects. Objectives A plant community succession model (PCSM) based on cellular automate was developed, and the 30-year plant succession within a subsidence area in the Yungang mining area in China under mining and non-mining scenarios, as well as under two sets of initial conditions (plant-covered and bare), were simulated and compared. Methods The normalized mean square error (NMSE) was applied to test the accuracy of the PCSM and to reveal the effects of ground deformation at the patch scale, which was 0.06–0.59 for simulated and observed plant patterns. Six landscape indicators (contagion index (CONTAG), patch cohesion index (COHESION), landscape division (DIVISION), Shannon’s diversity index (SHDI), Shannon’s evenness index (SHEI), and aggregation index (AI)) were calculated for the mining and non-mining scenarios and compared to reveal the effects at the landscape scale. Results The results show that the DIVISION, SHDI, and SHEI were significantly higher in the mining scenario than in the non-mining scenario under plant-covered conditions; while the DIVISION was greater for the mining scenario than for the non-mining scenario, indicating that the ground deformation resulted in a loose, separated, and mixed plant pattern. The dynamics of the plant coverages and patterns in the two scenarios reflect the negative and positive effects of ground deformation on the tree and shrub communities, respectively. In terms of the shrub and tree communities, the NMSEs fluctuated at a high level under bare conditions, especially at the patch scale of 10 × 10 m, for which it was maintained at >0.5. Conclusion Overall, the mining-induced ground deformation chronically influenced the plant succession by limiting tree communities and promoting shrub communities, and it led to a heterogenous plant pattern. The results of this research provide a reference for detecting the long-term effects of mining-induced ground deformation on plant patterns, and they also provide insights into the effects of underground mining on different plant communities.

show abstract

“…However, there is an ongoing discussion among scholars regarding the extent to which human activities contribute to vegetation greening on the Loess Plateau [38][39][40]. Most research has focused on vegetation greenness at the regional [38,[41][42][43][44][45] or watershed scale [46][47][48][49][50], with limited studies conducted at the county scale. Additionally, the analysis of driving factors behind spatiotemporal changes in vegetation greenness has mainly focused on natural factors [51][52][53], with limited consideration of socioeconomic factors.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Driving Forces of Vegetation Greening on the Loess Plateau at the County Scale

Kong,

Huang,

et al. 2024

Forests

View full text Add to dashboard Cite

China has implemented several ecological projects in the Loess Plateau region to address severe land degradation and soil erosion. Accurately assessing ecological restoration and its driving factors remains challenging. Previous studies in this area concentrated on driving factors have mainly focused on natural factors at the regional or watershed scale, with limited consideration of socioeconomic factors at the county scale. In this study conducted in Huanglong County on the Loess Plateau, the focus was to fill the gaps in previous research and provide insights into the socioeconomic driving forces behind vegetation greening. Remote sensing image data (NDVI) from 1999 to 2019 were used to analyze vegetation greenness dynamics in the region. Five socioeconomic variables were considered, including afforestation intensity, deforestation intensity, agricultural intensity, village intensity, and road intensity layers, to characterize the impact of afforestation, agriculture, and urbanization policies. The RESTREND (residual trends) method was employed to assess the relative importance of climate and human activities on vegetation dynamics. This study found that temperature–NDVI relationships are more suitable for building RESTREND models than precipitation–NDVI relationships. Human activity was the main driver of vegetation dynamics, contributing 62% compared to 38% from climate change. Agricultural practices and afforestation were found to have a positive impact on ecological restoration, while deforestation and urbanization had no significant impact. These findings highlight a conceptual framework for understanding the intricate relationship between ecological restoration, climatic factors, and human activity on the Loess Plateau. This study suggests that significant progress has been made in ecological restoration through human efforts in combating land degradation. However, it emphasizes the need to strengthen natural conservation efforts and gradually transition toward restoration processes driven by natural forces for sustainable socioeconomic development. The methodology used in this study can be applied to explore the driving forces of ecological restoration in other regions facing human-driven land degradation.

show abstract

Comparing the long‐term effects of artificial and natural vegetation restoration strategies: A case‐study of Wuqi and its adjacent counties in northern China

Cited by 19 publications

References 86 publications

Evaluation of the driving effects of socio-economic development on soil erosion from the perspective of prefecture-level

Evaluation of the driving effects of socio-economic development on soil erosion from the perspective of prefecture-level

Detecting long-term effects of mining-induced ground deformation on plant patterns in semi-arid areas using a cellular automata model

Exploring the Driving Forces of Vegetation Greening on the Loess Plateau at the County Scale

Contact Info

Product

Resources

About