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Wetlands play an important role in regional development and environmental protection. Under the impact of natural and artificial factors, the plateau wetlands have degenerated and even disappeared, resulting in serious problems for society and the ecological environment. It is necessary to establish a reasonable risk assessment method to evaluate the risk of wetland degradation, and then to analyze changes in the range and features of risk. For this work, the Zogie Plateau wetland was selected as the study area. For this site, a wetland degradation risk assessment method was established based on the conceptual model of Ecological Risk Assessment (ERA). The method included nine indicators used to analyze the wetland hazard index, wetland vulnerability index, and wetland degradation risk synthetically. From the spatial-temporal pattern, the wetland degradation risk was analyzed using data from 2000 to 2014. The calculated results revealed the following: (1) from 2000 to 2014, the wetland hazard index (WHI) showed a trend of increase, the value of which increased from 0.29 to 0.42, with a growth rate of 44.83%. Similarly, the wetland vulnerability index (WVI) significantly increased from 0.30 to 0.54, with a growth rate of 80%. Over the same time, the total wetland area decreased from 3910.25 km 2 to 2777.38 km 2 , a reduction of 28.97%. (2) Using the equidistant method, the risk value was divided into three risk grades. The wetland degradation risk in the whole region is increasing, and the risk rank has changed from the low risk zone (0.092) to the medium risk zone (0.25). The degradation risk becomes greater with distance from the center to fringe areas. [ABSTRACT FROM AUTHOR]

To understand the variation and patterns of vegetation coverage in the Yellow River Basin, as well as to promote regional ecological protection and maintain ecological construction achievements, MOD13Q1 data at a resolution of 250 m were used to calculate the annual average normalised difference vegetation index (NDVI) in a time series from 2000 to 2010. Using a variation coefficient, a Theil–Sen Median trend analysis, the Mann–Kendall test, and the Hurst index method, this study investigated the temporal and spatial variations of vegetation coverage characteristics of the Yellow River Basin. The results showed that (1) the vegetation coverage of the Yellow River appeared to have an overall trend of high in the southeast and west and low in the northwest; (2) the averaged NDVI of the whole basin fluctuated in a range of 0.3 to 0.4 from 2000 to 2010 (from 2000 to 2004 there were larger variations and these have been growing rapidly since 2005); (3) the NDVI was stable, 73.4% of the vegetation-coverage area fluctuated with a low-to-medium amplitude, while 27.6% of the area varied by a large amplitude; (4) the regions with improved vegetation coverage (62.9%) were far greater than the degraded regions (27.7%), while the sustained invariant area accounted for 9.4% of the total vegetation coverage regions; and (5) 86% of the vegetation-covered area was positively sustainable. The areas with sustainable improvement accounted for 53.7% of the total vegetation coverage area; the invariant area accounted for 7.8%. The area with sustainable degradation was 24.5%; the future variation in trends of the residual (14%) could not be determined. Therefore, continuous attention must be given to the variation in trends of vegetation in the sustainably degraded and underdetermined regions. [ABSTRACT FROM AUTHOR]

• Urban water bodies in China showed a significant spatial autocorrelation in spatial distribution. • About 40% and 60% of total cities were detected with a mutation point in urban permanent and seasonal water bodies, respectively. • GDP explained about 13 %∼35 % of spatiotemporal variations of urban water bodies in China. Urban water bodies constitute a vital element within the urban ecosystem. Knowledge of the spatiotemporal changes in urban water bodies and their relationship with economic development in China is critical for sustainable development. However, previous studies usually investigated the spatiotemporal changes of urban water bodies at discrete time points and ignored the relationship between urban water bodies and economic development. Here, this study first corrected freely available water body products based on spatiotemporal majority filter, thereby obtaining an improved yearly urban water body dataset. Then, the research adopted Moran's I and Anselin Local Moran's I to explore the spatial distribution patterns of urban water bodies and employed linear regression and segmented linear regression to investigate the temporal abrupt change and long-term trend of urban water bodies. Finally, we used geodetector to evaluate the relative contributions of GDP to the spatial heterogeneity of trends in urban water bodies. The study revealed a significant spatial autocorrelation in the distribution of urban water bodies, particularly notable in the "High-High" cluster within the Yangtze and Pearl River Deltas. It was observed that approximately 40 % and 60 % of total cities experienced an abrupt change in permanent and seasonal urban water bodies, respectively. Specifically, the majority of these abrupt changes occurred during 2010–2013. When considering both long-term trends and abrupt changes, permanent urban water bodies in Chinese cities exhibited primarily a steadily increasing trend, while seasonal water bodies in Chinese cities displayed two distinct temporal patterns: a steadily increasing trend and a decreasing trend followed by a subsequent increasing trend. Furthermore, it was noted that GDP exhibited a significantly positive correlation with the temporal changes of permanent urban water bodies from 2000 to 2020 at the national scale while it first showed a significantly negative correlation with the temporal changes of seasonal urban water bodies from 2000 to 2012 and then showed a significantly positive correlation from 2012 to 2020 on a national scale. In conclusion, we found that GDP played a more important role in driving the spatial heterogeneity of trends in urban water bodies during 2012–2020 compared to 2000–2012, with the relative contribution of ∼ 32.5 %. [ABSTRACT FROM AUTHOR]