Effects of Major Grassland Conservation Programs Implemented in Inner Mongolia since 2000 on Vegetation Restoration and Natural and Anthropogenic Disturbances to Their Success

Shao, Liqun; Chen, Haibin; Zhang, Chen; Huo, Xuexi

doi:10.3390/su9030466

Cited by 19 publications

(11 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, grassland has experienced obvious restoration in IM, and these ecological policies and programs have also contributed significantly to land-use change activities (with lower TPs in this study). This is in accordance with many previous studies [22,42,92,95]. However, land degradation is still the major ecological issue in IM [4].…”

Section: Yearssupporting

confidence: 93%

“…Many previous studies have evaluated and monitored grassland degradation and restoration based on a long-time-scale vegetation index [39,41]. The merits of this method include the accessibility of assessing and monitoring data sources and the flexibility for processes within a specified time scale [42]. However, this method cannot provide details on grassland degradation and restoration during a specified range; for example, it does not show how degraded or restored grassland is converted or transformed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015

Nacun

2018

Sustainability

View full text Add to dashboard Cite

Land-use and land-cover changes have important effects on ecology, human systems, the environment, and policy at both global and regional scales. Thus, they are closely related to human activities. The extraction of more details about land-use change and grassland degradation is necessary to achieve future sustainable development in Inner Mongolia. The current study presents the patterns and processes of land-use changes over space and time, while also analyzing grassland degradation that is based on an analysis of land-use changes using a transition matrix, the Markov chain model and Moran’s I index, and a combination of long-time-scale remote sensing data as the data source. The major results indicate the following. (1) In 1990–2015, 13% (123,445 km2) of the total study area, including eight land-use types, changed. Woodland increased the most and moderate grassland decreased the most. (2) Grassland degradation, which occupied 2.8% of the total area of Inner Mongolia, was the major land-use conversion process before 2000, while, after 2000, 8.7% of the total area was restored; however, grassland degradation may still be the major ecological issue in Inner Mongolia. (3) Environmental protection policies show a close relationship with land-use conversion.

show abstract

Section: Yearssupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015

Nacun

2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Land-use change includes various land-use processes, such as urbanisation, land degradation, water body shrinkage, and surface mining, and has significant effects on ecosystem services and functions (Sohl and Benjamin, 2012). Grassland is the major land-use type on the Mongolian Plateau; its degradation was first witnessed in the 1960s.…”

Section: Introductionmentioning

confidence: 99%

Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

Batunacun¹,

Wieland

Lakes

et al. 2021

Geosci. Model Dev.

View full text Add to dashboard Cite

Abstract. Machine learning (ML) and data-driven approaches are increasingly used in many research areas. Extreme gradient boosting (XGBoost) is a tree boosting method that has evolved into a state-of-the-art approach for many ML challenges. However, it has rarely been used in simulations of land use change so far. Xilingol, a typical region for research on serious grassland degradation and its drivers, was selected as a case study to test whether XGBoost can provide alternative insights that conventional land-use models are unable to generate. A set of 20 drivers was analysed using XGBoost, involving four alternative sampling strategies, and SHAP (Shapley additive explanations) to interpret the results of the purely data-driven approach. The results indicated that, with three of the sampling strategies (over-balanced, balanced, and imbalanced), XGBoost achieved similar and robust simulation results. SHAP values were useful for analysing the complex relationship between the different drivers of grassland degradation. Four drivers accounted for 99 % of the grassland degradation dynamics in Xilingol. These four drivers were spatially allocated, and a risk map of further degradation was produced. The limitations of using XGBoost to predict future land-use change are discussed.

show abstract

“…The grassland ecosystems in Inner Mongolia represent an important ecological barrier in the north of the Country and play an important role in the social economy (Ouyang et al, 2018; Xiao, Xiao, Luo, Song, & Bi, 2019). Due to the influence of climate warming, along with prolonged droughts and overgrazing, the grassland in Inner Mongolia has suffered serious degradation, and approximately 90% have been degraded over a few decades (Akiyama & Kawamura, 2010; Shao, Chen, Zhang, & Huo, 2017), which led to myriads of environmental and economic problems, such as deterioration of biodiversity and ecosystem function and services and the aggravation of sandstorms, desertification, and poverty (Han et al, 2018a; Qi, Chen, Wan, & Ai, 2012; Shao & Dong, 2006). To mitigate grassland degradation and to promote the restoration of grassland ecosystems, a series of national grassland protection projects have been implemented in Inner Mongolia since 2000 (Jixia, Qibin, Jing, Depeng, & Quansheng, 2018; Li & Qin, 2014), for example, the Beijing–Tianjin Wind/Sand Source Control Program (BTWSSC), the Grazing Withdrawal Program, the Ecological Subsidy and Award System (ESAS), and the Natural Forest Protection Project (NFPP) (Dang, Li, Li, & Dou, 2018; Deng, Zhang, Cheng, Hu, & Chen, 2019; Feng, Tian, Yu, Yin, & Cao, 2019; Hua, Huang, & Li, 2019; Wang, Zhao, Fu, & Wei, 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessing the degradation of grassland ecosystems based on the advanced local net production scaling method—The case of Inner Mongolia, China

2020

View full text Add to dashboard Cite

The gradual degradation of grasslands on a global scale goes hand‐in‐hand with significant challenges for agriculture and animal husbandry development. Numerous relevant policies and projects have been implemented to protect and restore Chinese ecosystems, but it is still unclear to what degree grassland ecosystems can be recovered. In view of this, we constructed an advanced local net production scaling (ALNS) method by replacing the classification method by self‐organizing feature maps (SOFM) and tailoring the ideal state evaluation method in the LNS method. The ALNS method is used to analyze differences within grassland ecosystems, explore the ideal state of grassland ecosystems, and define degradation as the degree to which the actual state deviates from the ideal state, representing the degree to which grassland ecosystems can be recovered. It thereby quantifies and assesses the overall degradation of such systems in Inner Mongolia. Based on the results, more than 98.5% of the total grassland area failed to reach the ideal state, with the highest levels in the northeast with DN (degraded net primary productivity) values exceeding 200 gc/(m2·yr), followed by the midlands with DN values from 50 to 200 gc/(m2·yr) and the southwest with DN values between 0 and 150 gc/(m2·yr). The ALNS method can efficiently assess grassland ecosystem degradation and can be used to indicate the deviation degrees from ideal states, facilitating the development of protection and restoration programs for grassland ecosystems.

show abstract

Effects of Major Grassland Conservation Programs Implemented in Inner Mongolia since 2000 on Vegetation Restoration and Natural and Anthropogenic Disturbances to Their Success

Cited by 19 publications

References 40 publications

An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015

An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015

Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

Assessing the degradation of grassland ecosystems based on the advanced local net production scaling method—The case of Inner Mongolia, China

Contact Info

Product

Resources

About