Search Results (6)

In desertified regions, monitoring vegetation phenology and elucidating its relationship with climatic factors are of crucial significance for understanding how desertification responds to climate change. This study aimed to extract the spatial-temporal evolution of land surface phenology metrics from 2001 to 2020 using MODIS NDVI products (NASA, Greenbelt, MD, USA) and explore the potential impacts of climate change on land surface phenology through partial least squares regression analysis. The key results are as follows: Firstly, regionally the annual mean start of the growing season (SOS) ranged from day of year (DOY) 130 to 170, the annual mean end of the growing season (EOS) fell within DOY 270 to 310, and the annual mean length of the growing season (LOS) was between 120 and 180 days. Most of the desertified areas demonstrated a tendency towards an earlier SOS, a delayed EOS, and a prolonged LOS, although a small portion exhibited the opposite trends. Secondly, precipitation prior to the SOS period significantly influenced the advancement of SOS, while precipitation during the growing season had a marked impact on EOS delay. Thirdly, high temperatures in both the pre-SOS and growing seasons led to moisture deficits for vegetation growth, which was unfavorable for both SOS advancement and EOS delay. The influence of temperature on SOS and EOS was mainly manifested during the months when SOS and EOS occurred, with the minimum temperature having a more prominent effect than the average and maximum temperatures. Additionally, the wind in the pre-SOS period was found to adversely impact SOS advancement, potentially due to severe wind erosion in desertified areas during spring. The findings of this study reveal that the delayed spring phenology, precipitated by the occurrence of a warm and dry spring in semi-arid desertified areas of northern China, has the potential to heighten the risk of desertification. Full article

In recent years, multiple disturbances have significantly altered terrestrial ecosystems in arid and semi-arid regions, particularly on the Mongolian Plateau (MP). Net primary productivity (NPP) of vegetation is an essential component of the surface carbon cycle. As such, it characterizes the state of variation in terrestrial ecosystems and reflects the productive capacity of natural vegetation. This study revealed the complex relationship between the natural environment and NPP in the ecologically fragile and sensitive MP. The modified Carnegie–Ames–Stanford Approach (CASA) model was used to simulate vegetation NPP. Further, the contributions of topography, vegetation, soils, and climate to NPP’s distribution and spatiotemporal variation were explored using the geographic detector model (GDM) and structural equation model (SEM). The study’s findings indicate the following: (1) NPPs for different vegetation types in the MP were in the order of broad-leaved forest > meadow steppe > coniferous forest > cropland > shrub > typical steppe > sandy land > alpine steppe > desert steppe. (2) NPP showed an increasing trend during the growing seasons from 2000 to 2019, with forests providing larger vegetation carbon stocks. It also maintained a more stable level of productivity. (3) Vegetation cover, precipitation, soil moisture, and solar radiation were the key factors affecting NPP’s spatial distribution. NPP’s spatial distribution was primarily explained by the normalized difference vegetation index, solar radiation, precipitation, vegetation type, soil moisture, and soil type ($q$-statistics = 0.86, 0.71, 0.67, 0.67, 0.57, and 0.57, respectively); the contribution of temperature was small ($q$-statistics = 0.26), and topographic factors had the least influence on NPP’s distribution, as their contribution amounted to less than 0.20. (4) A SEM constructed based on the normalized difference vegetation index (NDVI), solar radiation, precipitation, temperature, and soil moisture explained 17% to 65% of the MP’s NPP variations. The total effects of the MP’s NPP variations in absolute values were in the order of NDVI (0.47) > precipitation (0.33) > soil moisture (0.16) > temperature (0.14) > solar radiation (0.02), and the mechanisms responsible for NPP variations differed slightly among the relevant vegetation types. Overall, this study can help understand the mechanisms responsible for the MP’s NPP variations and offer a new perspective for regional vegetation ecosystem management. Full article

One of the major barriers to hindering the sustainable development of the terrestrial environment is the desertification process, and revegetation is one of the most significant duties in anti-desertification. Desertification deteriorates land ecosystems through species decline, and remote sensing is becoming the most effective way to monitor desertification. Mu Us Sandy Land is the fifth largest desert and the representative area under manmade vegetation restorations in China. Therefore, it is essential to understand the spatiotemporal characteristics of artificial desert transformation for seeking the optimal revegetation location for future restoration planning. However, there are no previous studies focusing on exploring regular patterns between the spatial distribution of vegetation restoration and human-related geographical features. In this study, we use Landsat satellite data from 1986 to 2020 to achieve annual monitoring of vegetation change by a threshold segmentation method, and then use spatiotemporal analysis with Open Street Map (OSM) data to explore the spatiotemporal distribution pattern between vegetation occurrence and human-related features. We construct an artificial vegetation restoration suitability index (AVRSI) by considering human-related features and topographical factors, and we assess artificial suitability for vegetation restoration by mapping methods based on that index and the vegetation distribution pattern. The AVRSI can be commonly used for evaluating restoration suitability in Sandy areas and it is tested acceptable in Mu Us Sandy Land. Our results show during this period, the segmentation threshold and vegetation area of Mu Us Sandy Land increased at rates of 0.005/year and 264.11 km²/year, respectively. Typically, we found the artificial restoration vegetation suitability in Mu Us area spatially declines from southeast to northwest, but eventually increases in the most northwest region. This study reveals the revegetation process in Mu Us Sandy Land by figuring out its spatiotemporal vegetation change with human-related features and maps the artificial revegetation suitability. Full article

Mixed forests play a key role in the environmental restoration of desert ecosystems and in order to address the improvement of soil properties by different mixed vegetation types. We selected four typical mixed vegetation types (including: Populus alba var. pyramidalis × Caragana korshinskii, P. pyramidalis × Hedysarum mongdicum, P. pyramidalis × Hedysarum scoparium and Hedysarum scoparium × Salix cheilophila) that have been restored for 22 years and the moving sandy land in the transition zone between the desert and the Yellow River in northern China. We compared the differences in soil properties using a total of 45 soil samples from the 0–30 cm soil layer (10 cm units). We found that revegetation had a significant positive effect on fine particles, soil nutrients, soil bulk density (SBD), and soil fractal dimension (D) values. Soil D values under different types of vegetation range from 2.16 to 2.37. Soil nutrients and fractal dimension showed highly significant or stronger negative correlations with SBD and sand and highly significant or stronger positive correlations with clay and silt. The construction of P. pyramidalis × C. korshinskii improved the soil texture better than other vegetation restoration types. Compared to the mobile sandy land, organic carbon (SOC), available phosphorus (AP), available potassium (AK), alkaline hydrolysis nitrogen (AN), total nitrogen (TN), total potassium (TK), clay, and silt increased by 161%, 238%, 139%, 30%, 125%, 69%, 208%, and 441% respectively. As mentioned above, P. pyramidalis × C. korshinskii is a suitable type of mixed vegetation restoration for the area. In addition, establishing vegetation with high nitrogen fixation rates in desert ecosystems tolerant to drought and aeolian conditions is beneficial in reversing the trend of desertification. This research will suggest vegetation building strategies for controlling desertification. Full article

The Taklimakan Desert is a typical arid area. Due to the needs of production and life, a total of 2 km² of constructed green land (hereinafter referred to as CGL) has been formed in the sand dune, resulting in the uniform underlying surface of the desert having been changed, which has led to the change in the near-surface energy distribution pattern and the formation of a local climate of the CGL that is obviously different from that of the desert climate. Therefore, it is necessary to study the varied interval of the threshold of meteorological factors and the regional climate characteristics of the CGL under the background of desert. The main results are as follows. Firstly, from sunrise to noon, the increasing rate of temperature in natural sandy land (hereafter, NSL) was higher than that in CGL, and the opposite results occurred between noon and sunset. The peak temperature of CGL was 2 h later than that of NSL. At night, the temperature at the boundary of the CGL was generally higher than that of the NSL and the central area of the CGL. In addition, the results show that under the combined influence of underlying conditions, local circulation and small terrain, the CGL (middle) daily range of temperature > NSL (west) > CGL (east) > CGL (west). The positive temperature change period of CGL was significantly shorter than that of NSL in all seasons. However, temperature inversion occurred at night in all seasons. The intensity of the temperature inversion was strongest in winter, with a maximum temperature difference of 12.8 °C, followed by autumn, spring, and summer, with a maximum difference of 6.4 °C. Secondly, the wind speed in the daytime was higher than that at night, and the wind speed in NSL was higher than that in CGL. In summer, if the average wind speed of the NSL was quantified as 1.0 m/s, the wind speed lapse rate reached 30% at the boundary of the CGL. Similarly, in the central area of CGL, the wind speed lapse rate reached 71%. Full article

Biological soil crusts (BSCs) play an essential role in desert ecosystems. Knowledge of the distribution and disappearance of BSCs is vital for the management of ecosystems and for desertification researches. However, the major remote sensing approaches used to extract BSCs are multispectral indices, which lack accuracy, and hyperspectral indices, which have lower data availability and require a higher computational effort. This study employs random forest (RF) models to optimize the extraction of BSCs using band combinations similar to the two multispectral BSC indices (Crust Index-CI; Biological Soil Crust Index-BSCI), but covering all possible band combinations. Simulated multispectral datasets resampled from in-situ hyperspectral data were used to extract BSC information. Multispectral datasets (Landsat-8 and Sentinel-2 datasets) were then used to detect BSC coverage in Mu Us Sandy Land, located in northern China, where BSCs dominated by moss are widely distributed. The results show that (i) the spectral curves of moss-dominated BSCs are different from those of other typical land surfaces, (ii) the BSC coverage can be predicted using the simulated multispectral data (mean square error (MSE) < 0.01), (iii) Sentinel-2 satellite datasets with CI-based band combinations provided a reliable RF model for detecting moss-dominated BSCs (10-fold validation, R² = 0.947; ground validation, R² = 0.906). In conclusion, application of the RF algorithm to the Sentinel-2 dataset can precisely and effectively map BSCs dominated by moss. This new application can be used as a theoretical basis for detecting BSCs in other arid and semi-arid lands within desert ecosystems. Full article