Land Degradation & Development最新文献

In contemporary times, managing land resources and green energy from the COP27 perspective is a burning issue, attracting the attention of policymakers and scholars to attaining sustainable economic growth. In emerging economies, the adoption of both green energy and land resources is rapidly increasing to encourage economic productivity. In this regard, the current research explores the impact of oil resource fluctuations on the economic growth of the BRICS economies. In addition, this research contemplates the role of technological innovation, energy efficiency, and gross capital formation during 1990–2021. Using several econometric approaches, the results indicate the variables' stationarity and the cointegration between variables. Since most of the study variables follow a nonnormal distribution, this work employs a novel moments quantile regression. The estimation outcomes revealed that oil resource fluctuations, energy efficiency, technological innovation, and gross capital formation are substantial economic performance and growth drivers. The robustness of the empirical model is also tested via parametric (robust least squares) and nonparametric (quantile regression) approaches. Bidirectional causality estimates are reported between these variables except for the oil resource fluctuations that unidirectionally cause economic performance. Based on these estimates, this research recommends the sustainable management of oil resources and further investment in energy efficiency and technological innovation to attain sustainable economic performance.

Sand dunes are the primary factor influencing wind-sand disasters. To explore the evolution law of wind-blown sand dunes surrounding high vertical-type sand fences along desert railways, numerical simulation analyses based on computational fluid dynamics coupled with a discreet element method of the wind-sand flow field and sand particles trajectories around sand fences were conducted. The focus of this study was the Yandun section of the Lanzhou-Xinjiang Railway in Xinjiang, China (42.38°N, 93.95°E). By combining ERA5 wind data with field measurements and monitoring, a three-dimensional coupling model was established. According to the results of L9 (3³) orthogonal tests, the sensitivity of the three factors to the evolution of sand dunes can be ordered as wind speed > porosity > height, indicating that wind speed is closely related to sand dune evolution (p < 0.05). The results of single-factor tests indicate that the structure of wind-sand flow fields, sand accumulation patterns, and sand particle movement trajectories vary significantly under different wind speeds. The sand accumulation rates on the windward slope of the sand dune are 29.67%, 25.91%, and 20.04%, while on the leeward slope, these rates are 40.33%, 34.09%, and 29.96%, respectively. The obtained information on the evolution law of sand dunes surrounding high vertical-type sand fences provides a scientific basis for wind-sand prevention measures along railways in desert regions.

Overgrazing affects the grass-livestock balance and endangers grassland ecological security. Despite extensive studies conducted on identifying and quantifying grazing intensity, there is still room for improvement in the research on gridding grazing intensity, particularly in areas with limited data on the Qinghai–Tibet Plateau. Therefore, we proposed a grazing intensity spatialization method using geographically weighted random forest (GWRF) to gain further insights into the spatial heterogeneity of alpine grassland grazing intensity. This method incorporates multiple remote sensing data related to human activities and natural factors, as well as annual livestock statistics at the township level over several years, while adequately considering the spatial autocorrelation of grazing intensity. Additionally, we employed Lindeman Merenda Gold (LMG), the geographical detector model, and the structural equation model (SEM) to assess the contribution and influence path of driving factors to grazing intensity. We also utilize partial correlation analysis and dual-phase mapping to examine the impact of natural and human activities on the spatial distribution of grazing intensity. The results demonstrate that the GWRF-based grazing intensity spatial model accurately predicts grazing intensity by demonstrating its consistency with township-scale livestock data (R ² = 0.92 (p < 0.01), RMSE = 1.07). This provides valuable technical support for quantifying grazing intensity in alpine pastoral areas with limited data availability. We evaluate trends in grazing intensity and observe an increase in Gar and Purang counties. Furthermore, population density, normalized difference vegetation index (NDVI), and temperature are identified as three influential factors affecting grazing intensity in alpine pastoral areas. Additionally, other factors indirectly impact grazing intensity by influencing population density and NDVI levels, while their interactions amplify their overall influence. The dual-phase mapping technique has demonstrated a significant impact of population density on 45.92% (p < 0.01) of the study area, emphasizing the substantial influence of human activities on grazing intensity. Our study provides a novel framework for spatially analyzing grazing intensity and unraveling the intricated driving mechanisms behind spatiotemporal changes, particularly in areas with limited data availability.

The use of biochar as a soil amendment for acid soil, particularly acid sulfate soil, has garnered significant interest due to its capacity to improve soil properties, which is further accentuated when combined with dolomite. However, the extent to which the magnitude and direction of this effect vary with biochar produced at different pyrolysis temperatures remains uncertain. We conducted an incubation by mixing soil with dolomite and biochar types derived from Melastoma malabathricum (MMBC) and Dicranopteris linearis (DLBC) at three temperatures (300, 500, and 700°C). The incorporation of dolomite with both biochar types led to significant improvements in soil pH, available P, available Fe, exchangeable K, and exchangeable Ca compared to soil amended with dolomite only. These enhancements were likely attributed to the release of alkalinity, which further raised soil pH, as well as the direct dissolution of P, K, and Ca from the biochar. Moreover, the reduced Fe availability was likely due to the complexation of Fe onto surface functional groups of biochar. Furthermore, these improvements surpassed the effect of the initial feedstock and became increasingly pronounced with higher pyrolysis temperatures. However, an antagonistic effect of dolomite and biochar co-incorporation was observed, particularly in the relative reduction of soil exchangeable Mg with both biochar types, and a decrease in the soil available N with MMBC produced at 300 and 500°C compared to dolomite addition alone, which could be due to the adsorption of Mg and N onto biochar surface. The results indicate that concurrent application of dolomite and biochar can change the acid sulfate soil properties to varying magnitudes and in different directions, largely regulated by the characteristics of biochar as well as the probable interplay with dolomite. Consequently, selecting the appropriate biochar that aligns with the desired soil properties is crucial in managing dolomite-treated acid sulfate soil.