Eco-engineering controls vegetation trends in southwest China karst

Zhang, Xuemei; Yue, Yuemin; Tong, Xiaowei; Wang, Kelin; Qi, Xiangkun; Deng, Chuxiong; Brandt, Martin

doi:10.1016/j.scitotenv.2021.145160

Cited by 77 publications

(55 citation statements)

References 77 publications

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“…In addition, the urban heat island effect increases the temperature cities, which promotes increasing vegetation NPP [21]. Since 1978, China has implemented large-scale ecological engineering, which led to many areas of vegetation greening [118]. We found that ecological engineering led to not only vegetation NPP increase but also more vegetation NPP increase from decreasing trends, which is similar to the existing research results [119][120][121].…”

Section: Effects Of Vegetation Type Dynamics On the Nonlinear Trend O...supporting

confidence: 86%

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

et al. 2021

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Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

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Section: Effects Of Vegetation Type Dynamics On the Nonlinear Trend O...supporting

confidence: 86%

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

et al. 2021

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“…Understanding the influences of landforms (karst and non-karst) on forest restoration at different research scales can provide decision-makers with a reference base to develop and implement ecological restoration measures. The forest restoration probability on the grid scale generally decreases with increased proportion of karst area in the grid; however, the differences in forest restoration probability corresponding to the proportion of karst areas in different states are small, probably due to the close relationship with the input of ecological engineering [9]. Since 2000, the GOC has invested more than 130 billion yuan into ecological environmental governance in karst regions [8].…”

Section: Assessing the Potential Forest Restoration Probabilitymentioning

confidence: 99%

“…The effect of landform types on forest restoration is mainly reflected in the forest restoration probability and differences between karst and non-karst regions. This is mainly because it is more difficult to restore vegetation in vulnerable environments, which are characterized by poor soil formation and high permeability of carbonates [9]. In the future, additional capital investment is required for ecological restoration in karst regions.…”

Section: Implications and Future Directionsmentioning

confidence: 99%

“…The karst ecosystem in China is one of the largest exposed carbonate rock areas in the world, with an area larger than 540,000 km 2 and a living population of 220 million [8]. Recently, issues such as the increased vulnerability of local ecosystems, special hydrogeological structures, and stony desertification have attracted significant research attention [9]. To improve the ecological conditions in karst regions, the Government of China (GOC) has implemented a series of ecological measures, including afforestation and stony desertification.…”

Section: Introductionmentioning

confidence: 99%

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Mapping Forest Restoration Probability and Driving Archetypes Using a Bayesian Belief Network and SOM: Towards Karst Ecological Restoration in Guizhou, China

Zhou

Chen

2022

Remote Sensing

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To address ecological threats such as land degradation in the karst regions, several ecological restoration projects have been implemented for improved vegetation coverage. Forests are the most important types of vegetation. However, the evaluation of forest restoration is often uncertain, primarily owing to the complexity of the underlying factors and lack of information related to changes in forest coverage in the future. To address this issue, a systematic case study based on the Guizhou Province, China, was carried out. First, three archetypes of driving factors were recognized through the self-organizing maps (SOM) algorithm: the high-strength ecological archetype, marginal archetype, and high-strength archetype dominated by human influence. Then, the probability of forest restoration in the context of ecological restoration was predicted using Bayesian belief networks in an effort to decrease the uncertainty of evaluation. Results show that the overall probability of forest restoration in the study area ranged from 22.27 to 99.29%, which is quite high. The findings from regions with different landforms suggest that the forest restoration probabilities of karst regions in the grid and the regional scales were lower than in non-karst regions. However, this difference was insignificant mainly because the ecological restoration in the karst regions accelerated local forest restoration and decreased the ecological impact. The proposed method of driving-factor clustering based on restoration as well as the method of predicting restoration probability have a certain reference value for forest management and the layout of ecological restoration projects in the mid-latitude ecotone.

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“…Researchers proposed different agricultural development models to coordinate the human-earth areal system in the ecologically vulnerable karst areas and realize sustainable development up to a point. They argued that the primary task in karst areas is to restore regional surface vegetation while addressing ecological poverty caused by the fragile ecological environment [21][22][23]. Focusing on the farmers' livelihood, policymakers have combined ecological engineering projects to form five development models with rocky desertification management as the core in Guizhou and Guangxi provinces.…”

Section: Introductionmentioning

confidence: 99%

Sustainable Agricultural Development Models of the Ecologically Vulnerable Karst Areas in Southeast Yunnan from the Perspective of Human–Earth Areal System

Xiao-qing

Wang

et al. 2022

Land

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Rocky desertification in ecologically-fragile karst areas limit regional socio-economic development in the face of significant human–earth conflict. Coordination of ecological restoration and agricultural development is critical for sustainable development in karst areas. From the perspective of the human–earth areal system, the framework of sustainable agricultural development was proposed in typically karst areas. We integrated principles of ecological vulnerability, resource and environmental carrying capacity, agricultural foundation, suitability of agricultural land, and the farmers’ willingness. In this study, we found the ecological vulnerability of Guangnan County was slight, but the proportion of moderate and severe vulnerability areas was high, with significant differences between the two sides of the line “Zhe (Zhetu)-Lian (Liancheng)-Yang (Yang Liu-jing)-Ban (Banbang)”. Then, we divided Guangnan County into three ecologically vulnerable zones. Following that, we proposed sustainable agricultural models for various zones. In slightly to mildly vulnerable zones, we propose constructing economic–ecological agricultural models, including woody oil, plateau characteristic fruiting forest, ecological tea plantations, suburban agriculture, and cultural–ecological tourism. In moderately to severely vulnerable zones, we recommend developing a stereoscopic agriculture model that combines planting and breeding, vegetation restoration, and herbivorous animal husbandry. In extremely vulnerable zones, we suggest constructing an ecologically natural restoration model and an agricultural ecological–tourism model. Our research provides references for ecological restoration, agricultural development, poverty alleviation consolidation, and rural revitalization in ecologically vulnerable karst areas of southeast Yunnan and similar regions.

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Eco-engineering controls vegetation trends in southwest China karst

Cited by 77 publications

References 77 publications

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Mapping Forest Restoration Probability and Driving Archetypes Using a Bayesian Belief Network and SOM: Towards Karst Ecological Restoration in Guizhou, China

Sustainable Agricultural Development Models of the Ecologically Vulnerable Karst Areas in Southeast Yunnan from the Perspective of Human–Earth Areal System

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