Land Degradation In Arid Regions Research Articles

Ecological influence of oasisation on peripheral regions

Sustainable development of oases enhances the capability of ecosystems to reverse land degradation in arid regions. However, it is unclear to what extent oasisation leads to ecological quality (EQ) degradation in the peripheral environment. To comprehensively evaluate the ecological effects of oasisation, this study developed a remote sensing ecological quality index to characterise spatiotemporal patterns and driving mechanisms of EQ in different oasis-type areas. Results show that the oasis area has increased by 37.4 % in the past 22 years. The EQ of the core area was stable, but EQ declined in newly developed urban areas. The effect range of the oasis on the peripheral regions EQ is 12 km, and the expansion of the oasis is improving the EQ of peripheral regions. The driving factors of EQ varied widely among different oasis areas. The vegetation index showed significant explanatory power (q-mean is 0.45) in each oasis area. Human activities and soil moisture showed the most significant explanatory power (0.76) in the core area, but weak power is observed in the changed and peripheral areas. Climate factors have the strongest influence on the changed and peripheral areas. The findings provide an in-depth understanding of the spatial heterogeneity of EQ and could be implemented in Oasis urban planning and sand prevention belt construction.

Inversion of soil pH during the dry and wet seasons in the Yinbei region of Ningxia, China, based on multi-source remote sensing data

Dynamic monitoring of soil pH changes across different seasons is crucial to understanding soil alkalization and preventing land degradation in arid regions. Here, we explored the potential use of ground-measured hyperspectral data and Landsat 8 OLI remote-sensing images in the inversion of soil pH during the dry and wet seasons. The measured and image data of spectral reflectance and corresponding soil pH data obtained in the laboratory were used to analyze the spatiotemporal patterns of soil pH in the Yinbei region, Ningxia, China. First, the hyperspectral data were resampled to match the range of the image bands; then 11 spectral indices were calculated based on the two sets of spectral data. Principal component analysis (PCA), stepwise regression (SR), and gray relational analysis (GRA) were used to select feature variables (sensitive bands and spectral indices) from the spectral data. The back propagation neural network (BPNN), support vector machine (SVM), ridge regression (RR), and geographically weighted regression (GWR) were used to construct soil pH inversion models. A total of 24 models established using the different methods were compared in terms of the determination coefficients of the calibration set (Rc2) and prediction set (Rp2), root mean square error (RMSE), and relative percent deviation (RPD). The results revealed that the mean soil pH in the study area was higher during the dry season (9.28) than the wet season (9.11). The resampled hyperspectral data correlated well with the image data under different levels of soil alkalization (R2 > 0.9652). Of the different models examined, the global regression models (BPNN, SVM, and RR) were superior to the local regression model (GWR), with better inversion results obtained in the wet than the dry season. The BPNN and SVM models performed better than the RR model, and the PCA-SVM model based on measured data in the dry season achieved the best overall performance (Rp2 = 0.9724 and RPD = 5.76). These findings provide valuable information on the distribution of Solonetzs land in the study area, facilitating management of soil alkalization and degradation in the Yinbei region.

Impact of off-road vehicles on soil and vegetation in a desert rangeland in Saudi Arabia.

Off-road vehicle driving is considered as main contributor to land degradation in arid regions. This study examined the impact of off-road vehicles (ORV) on soil and vegetation in a natural recreational desert meadow of Raudhat Khuraim, Saudi Arabia. Vegetation canopy cover and plant height away from road tracks were assessed. Also, species density and canopy cover, bare ground cover and soil attributes were assessed in four microhabitats; tracks, inter-tracks, verges, and away from vehicle tracks (undisturbed natural areas). Results show that the cover of forbs and grasses was negatively associated with distance from road verges. It was observed that the height of woody species responded negatively to distance away from tracks. Cover of native species decreased under verge, inter-track and track microhabitats giving more opportunity for weeds to flourish. Bare ground was highest (60.7%) in tracks. ORV impact on soil bulk density was clear with an increase of 38% under tracks compared to soils of undisturbed natural vegetation and a similar decrease in porosity was observed. On the other hand, soil electrical conductivity was significantly higher (5.45 mS cm−1) under disturbance compared to 1.32 mS cm−1 in undisturbed natural vegetation. Organic matter and nitrogen were not affected significantly by ORV disturbance. The results emphasize that managing off-road vehicle driving is essential for conserving native vegetation.

Reflectance spectroscopic approach for estimation of soil properties in hot arid western Rajasthan, India

Periodic and regular assessment of land degradation in arid regions of the world is essential for implementing suitable corrective measures in time. Assessment of soil properties based on soil sampling from hot arid tracts followed by laboratory analysis is a formidable task. Reflectance spectroscopy appears to be an emerging technology for the assessment of soils in extreme environment. In this study, soil spectral library of 138 soil samples from hot arid western Rajasthan have been created in visible, near-infrared and short wave infrared (350–2500 nm) region of the electromagnetic spectrum along with the measurements of basic soil properties. Further, spectral reflectance-based algorithms have been developed for rapid assessment of soil resources of arid regions. Results showed that sand and clay content may be satisfactorily estimated from linear models involving principal components (PCs) or derived band reflectance as the input variables (R 2 = 0.41–0.43). Organic carbon (OC) content of soil was also found satisfactorily correlated with spectral data (R 2 = 0.27). Derived band reflectance corresponding to Operational Land Imager bands of Landsat-8 has been found best to predict soil properties. Soil OC content has been found to be best estimated by derived spectral band data corresponding to spectral bands of IRS-P6 satellite. Partial least square regression-based models were found even better than the PCs-based and band reflectance-based multiple regression models for estimating soil properties. Thus, the present study indicates that soil spectral reflectance data captured by remote sensing satellites may have a great potential for rapid assessment of soil resources in arid regions.

Natural bioremediation of a nitrate-contaminated soil-and-aquifer system in a desert environment

Mining activities are a major source of land degradation in arid regions, and remediation methods developed for mesic sites may not be appropriate for arid sites. In climates where potential evapotranspiration exceeds precipitation, it might be possible to prevent the migration of contaminants away from a mine site by controlling the site water balance through vegetation, and allowing natural attenuation processes to reduce pollutant levels over time. We investigated the feasibility of remediating a nitrate-contaminated source-plume system in a desert environment using biological methods. The study site was a former uranium mill in Monument Valley, Arizona, where NO 3 − used in ore processing had leaked from the soil beneath a tailings pile (referred to as the source area) into an alluvial aquifer (referred to as the plume) spreading away from the source area. We used 15N/ 14N ratios and direct assays of denitrification to show that biological denitrification occurred in both the source area and plume, and could reduce NO 3 − levels over time. Denitrification in the source area could be stimulated by providing additional moisture to the soil through irrigation, whereas providing a carbon source (ethanol) stimulated denitrification in samples from the plume. We used 18O/ 16O and H/deuterium signatures in water and plant samples to show that the native saltbush ( Atriplex canescens) and black greasewood ( Sarcobatus vermiculatus) plant community was extracting water from the plume, offering a possible means of preventing migration of the plume by controlling grazing over the site. We conclude that biological remediation is a feasible alternative to pump/treat solutions at this type of site.