Vegetation Greenness Variations and Response to Climate Change in the Arid and Semi-Arid Transition Zone of the Mongo-Lian Plateau during 1982–2015

Identification of suitable vegetation restoration areas and carrying capacity thresholds on the Loess Plateau

The Loess Plateau is one of the most ecologically fragile areas in the world. It has long faced the twin dilemmas of ecological degradation and water resource shortage. In recent decades, large-scale vegetation restoration projects have been carried out on the Loess Plateau with the aim of improving the ecological environment. However, as the vegetation cover increases, the water consumption of vegetation also increases, which further exacerbates the problem of water resource shortages. In order to effectively utilize water resources and balance the relationship between forests and water use, suitable vegetation restoration areas were identified on the Loess Plateau by constructing a vegetation suitability evaluation model based on multiple index factors (precipitation, temperature, altitude, slope, aspect, soil texture, soil depth, soil organic matter and ecological water consumption). The suitable restoration area results are given as follows: trees comprised 18.58% of the total vegetation coverage area and were mainly distributed across the central and southern Loess Plateau; shrublands comprised 32.58% of the total vegetation coverage area and were mainly distributed across the northern part of the Loess Plateau; and grasslands comprised 48.84% of the total vegetation coverage area and were mainly distributed across the western and northeastern regions of the Loess Plateau. On this basis, the Eagleson model was used to identify the bearing capacity of vegetation in the suitable restoration area. The optimal simulated vegetation coverage values of the suitable restoration areas are given as follows: grassland, 0.246-1.000; shrubland, 0.186-0.783; and trees, 0.137-0.868. These results can help guide the local ecological environment construction, offer theoretical support for the ecological restoration of similar areas and provide a scientific reference for the effective use of water resources and vegetation restoration on the Loess Plateau.

Satellite observed dryland greening in Asian endorheic basins: Drivers and implications to sustainable development

A large portion of Central-Western Asia is made up of contiguous closed basins, collectively termed as the Asian Endorheic Basins (AEBs). As these retention basins are only being replenished by the intermittent and scarce rainfall, global warming coupled with ever-rising human demand for water is exerting unprecedented pressures on local water and ecological security. Recent studies revealed a persistent and widespread water storage decline across the AEBs, yet the response of dryland vegetation to this recent hydroclimatic trend and a spatially explicit partitioning of the impact into the hydroclimatic factors and human activities remain largely unknown. To fill in this knowledge gap, we conducted trend and partial correlation analysis of vegetation and hydroclimatic change from 2001 to 2021 using multi-satellite observations, including vegetation greenness, total water storage anomalies (TWSA) and meteorological data. Here we show that much of the AEB (65.53 %), encompassing Mongolia Plateau, Northwest China, Qinghai Tibet Plateau, and Western Asia (except the Arabian Peninsula), exhibited a significant greening trend over the past two decades. In arid AEB, precipitation dominated the vegetation productivity trend. Such a rainfall dominance gave way to TWSA dominance in the hyper-arid AEB. We further showed that the decoupling of rainfall and hyper-arid vegetation greening was largely due to a significant expansion (17.3 %) in irrigated cropland across the hyper-arid AEB. Given the extremely harsh environment in the AEB, our results therefore raised a significant concern on the ecological and societal sustainability in this region, where a mild increase in precipitation cannot catch up the rising evaporative demand and water consumption resulted from global warming and agriculture intensification.

Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran

Vegetation plays a crucial role in providing organic matter and regulating energy exchange on the Earth's surface. This study investigates the changes in vegetation cover, temperature, and precipitation in northeastern Iran during 2001-2020. MODIS-NDVI time series data and climatic data from 11 synoptic stations were utilized. The nonparametric Mann-Kendall method was employed to detect trends in vegetation cover and climatic variables. Additionally, the correlation between climatic parameters and vegetation was examined. Trend analysis revealed significant increases/decreases in vegetation cover in 32%/26% of the region, respectively. The increasing trend in vegetation cover was predominantly observed in highlands, suggesting that a warmer climate has enhanced the living conditions for plants in these regions. The vegetation trend map indicates an expansion of vegetation cover in the northern and central parts of Iran during the past 20 years, whereas the southern and eastern portions experienced declines. The relationship between vegetation and elevation revealed that vegetation increased above 1,850 m and decreased below 850 m. Trend analysis showed no significant trend in precipitation data since the beginning of the twenty-first century, but an increasing trend in temperature was observed in 82% of the region's area, excluding the western strip. Correlation coefficients between temperature, precipitation, and vegetation indicated that declining temperatures are the limiting factors for vegetation in the highlands, while in lowland areas, the decrease in precipitation significantly diminishes vegetation growth.

Influences of Climatic Factors and Human Activities on Forest–Shrub–Grass Suitability in the Yellow River Basin, China

Natural and human factors co-drive changes in vegetation type and distribution. In this study, we constructed an index system covering 17 natural and human activity indicators in six dimensions by using climate data, county-level human activity data, and forest–shrub–grass suitability data from 448 sample counties in the Yellow River Basin of China in 2018. On this basis, we evaluated the influence of human activities and climatic factors on vegetation suitability using multiple regression and relative importance analysis methods. The multiple regression results demonstrate that climatic factors had positive effects on vegetation suitability in the Yellow River Basin, while the influence of human activities on vegetation suitability varied according to the situation. Specifically, economic factors such as per capita disposable income of urban residents and per capita disposable income of rural residents; urbanization factors such as population density, urbanization rate, and construction land area proportion; social development factors such as road density; and agricultural production factors such as the cultivated acreage proportion and the value added of the primary industries proportion all influence vegetation suitability. There is a great regional heterogeneity in the effects of human activities such as economic factors and urbanization factors on vegetation suitability. The relative importance analysis results show that the relative importance of the factors influencing vegetation suitability in the Yellow River Basin was as follows, in order of importance: climatic factors > agricultural production factors > urbanization factors > ecological projects > social development factors > economy factors; however, except for climatic factors, the importance of other influencing factors varied from region to region. This study provides a theoretical basis for optimizing vegetation adjustment schemes and forest and grass ecosystem layout according to regional characteristics.

Dynamic Change of Vegetation Index and Its Influencing Factors in Alxa League in the Arid Area

While there have been various studies on global vegetation dynamics, limited studies have been conducted to understand vegetation changes in arid areas. Vegetation distribution patterns can be affected by multiple factors, so understanding their interactions can help improve the capability of predicting future vegetation dynamics. This study, therefore, analyzed the dynamic vegetation changes in Alxa League, China, using the Normalized Difference Vegetation Index (NDVI) dataset (2000–2019), with the consideration of land cover types, digital elevation model, air temperature, precipitation, soil moisture, total evaporation, and air quality. The results show that the NDVI in Alxa League is small. Before 2012, the NDVI value fluctuated, while after 2012, the NDVI value dropped sharply and then slowly recovered after 2015. High NDVI values were found in areas with high and frequent human activities (city centers). The NDVI in the northwest region showed a slight degradation trend, and the southeast showed a slight improvement trend. According to the land cover type analysis, the NDVI value was the largest when the land cover type was tree cover, and the NDVI value was the smallest when the land cover type was bare/sparse vegetation. Alxa League was dominated by a bare/sparse vegetation distribution. The terrain analysis indicates that when the height was between 1800 and 3492 m, the NDVI value was the highest, and high NDVI values were mainly distributed in the area with a slope > 25°. When the slope was flat, the NDVI value was the smallest. Considering climate factors, the NDVI was negatively correlated with air temperature, precipitation, soil moisture, and total evaporation in space, and only precipitation and soil moisture were positively correlated in time. Moreover, the population size has a strong positive correlation with the NDVI in this area. The monthly variation of the NDVI and absorbable particulate matter (PM10) was negatively correlated, i.e., strongly negatively correlated in spring, summer, and autumn, but only weakly positively correlated in winter. The seasonal variation of the NDVI was as follows: summer > autumn > spring > winter, and the seasonal variation of PM10 was spring > winter > summer > autumn. The interannual variation of the NDVI and PM10 was positively correlated. This suggests that the absorbable particulate matter (PM10) may be an essential factor for the normalized vegetation index to underestimate the dynamic changes of vegetation in arid regions. This study provides a theoretical basis for the dynamic changes of vegetation in the dry Alxa League.