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Tarim River Basin (TRB), located at the Eurasia center, is a typical arid inland basin. It is critical to maintain the ecological security of TRB for the sustainable development of oases. With the inputs of four period land use data, the landscape ecological risk assessment model, the minimum cumulative resistance model, and network analysis were a...
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... A total of 21 ecological water conveyances were completed in the following two decades, totaling 8.43 billion m 3 . The water conservancy head reached Taitema Lake numerous times to form a large waterbody area, and double-channel water delivery was realized on multiple occasions [19,33,34]. Long-term monitoring data indicated that the groundwater level in the TRlr within 1 km of the mainstream rose from the original 8-12 m to <4 m [26]. ...
... The predictions indicated that the TRlr landscape would suffer further from marked fragmentation and worsening degrees of patch isolation. This finding is consistent with other landscape patterns observed in the TRB [19,22,38]. Specifically, landscape pattern risks were predicted to increase between 2020 and 2030, which would be primarily manifested in the Gobi/other deserts, bare soils, and the Taitema Lake Basin located downstream, as well as the buffers and transition zones on both riverbanks. ...
Natural vegetation on both sides of the Tarim River Basin (TRB) is the only barrier—a critical ecological niche—between the economic belt in the artificial oasis and the Taklimakan Desert. To understand the impact of human activities on the TRB, we explored the spatial and temporal variations in land use/land cover change (LUCC) and landscape pattern evolution from 2000 to 2020. These variations were simulated for 2030 with the 20 years of data using the cellular automata–Markov model and geographical information system analyses. The results predicted substantial LUCCs in the lower reaches of the Tarim River (TRlr), with 3400 km2 (20.29%) of the total area (16,760.94 km2) undergoing changes. Wetland, artificial land, grassland, farmland, and forestland areas increased by 578.59, 43.90, 339.90, 201.62, and 536.11 km2, respectively, during the period from 2020 to 2030. The only decreases were in the Gobi/other deserts and bare soils (1700.13 km2). We also determined current and future changes in TRlr landscape pattern indices at the class and landscape levels. Combined with a field survey and hydrological data, theoretical support for effective land use management strategies is provided. The findings offer a scientific basis for future ecological civilization construction and sustainable development in the TRB.
... LESSI evaluates the security of the landscape structure from three perspectives, namely landscape vulnerability, boundary fragmentation, and landscape type fragmentation [35], and it has been widely used in the landscape ecological security assessment [36,37]. LESSI is calculated using the following formula: ...
The ecological barrier is a complex ecosystem that couples the human–nature relationship, and the ecologically critical area is an irreplaceable area with a special value in the ecosystem. Therefore, protecting the ecologically critical area is vital for maintaining and improving regional ecological security. Limited research has been conducted on the evolution of ecologically critical areas, and none of the studies have considered the spatiotemporal heterogeneity of the driving factors for different evolution modes and types. Therefore, this research adopts the ecologically critical index, landscape expansion index, and the random forest model to analyze the pattern, driving factors, and its spatial-temporal heterogeneity to the evolution modes and specific types of ecologically critical areas in the Sichuan–Yunnan ecological barrier area in the last 15 years. The results showed that: (1) the ecologically critical areas in the Sichuan–Yunnan ecological barrier have changed dramatically, with the area reduction being 61.06%. Additionally, the spatial distribution characteristics of the ecologically critical area from north to south include planar, point, and linear forms. (2) The evolution trend of the ecologically critical area is ‘degradation–expansion–degradation’. Spread is the predominant type of expansion mode, whereas atrophy is the predominant type of degradation mode, indicating that the evolution mainly occurs at the edge of the original ecologically critical areas. (3) In general, precipitation, area of forest, area of cropland, and GDP have contributed significantly to the evolution of ecologically critical areas. However, the same driving factor has different effects on the expansion and degradation of these areas. Expansion is driven by multiple factors at the same time but is mainly related to human activities and land use change, whereas for degradation, climate and policy are the main driving factors. The present research aimed to quantitatively identify the evolution modes and specific types of ecologically critical areas and explore the spatiotemporal heterogeneity of driving factors. The results can help decision-makers in formulating ecological protection policies according to local conditions and in maintaining and enhancing the regional ecological functions, thereby promoting the sustainable development of society-economy-ecology.
Context ‘Happy River’ is a new goal of river management in the new era of China. Aims To quantitatively evaluate the status of ‘Happy River’. Methods The evaluation model of ‘Happy River Index’ was established in this study through the analytic hierarchy process according to the three levels of ‘objective–criterion–index’. The criterion layer includes the following five parts (including weights): water protection (0.25), ecological construction (0.22), landscape aesthetics (0.20), water culture (0.18) and social functions (0.15); three to six indicators are set under each criterion layer as the index layer. On the basis of this, the main rivers in six regions of Shaoxing City were evaluated and the scores calculated comprehensively. Key results The results showed that the total scores of Shangyu District, Yuecheng District and Xinchang County were 89, 87 and 85 respectively, indicating that the rivers are in a very good state; the total scores of Zhuji City, Shengzhou City and Keqiao District were 82, 80 and 75 respectively, indicating that the state of rivers is relatively poor compared to the first three regions. Conclusions The follow-up work can be promoted from the aspects of ecological construction, water culture construction, water protection and social functions. Implications The established model and empirical study have provided a theoretical basis and data basis for the comprehensive evaluation of modern rivers.
