Academic literature on the topic 'Predominant desertification factor'

Aksu City, located in the southern region of Xinjiang, China, holds the position of being the fifth largest city in Xinjiang. It holds significant ecological importance as a vital functional region for the management of desertification in China. To safeguard the ecological security of Xinjiang and preserve the ecological stability of Aksu City, it is crucial to examine the relationship between ecological service value and ecological risk, as well as the geographical and temporal changes in land use characteristics in Aksu City. This study examines the evolutionary characteristics and spatial correlation between ecological service value and ecological risk in Aksu City, using Aksu City as a case study. The analysis is based on five periods of land use data from 2000, 2005, 2010, 2015, and 2020. The study revealed the spatial and temporal patterns of landscape ecological risk and ecosystem service value in Aksu City from 2000 to 2020 using the landscape pattern index, ecological service value estimation, and ecological risk index. In addition, the study explored the interrelationship between ecological service value and ecological risk. The findings indicated that: (1) Bare land constituted the predominant land use category in Aksu City, accounting for over 81% of the total land use transfer over a 20-year period, encompassing a total area of 459.83 km2. (2) The total ecological service value (ESV) in the area experienced a decline of CNY 3.41 × 108 within the study’s time frame, exhibiting a decrease rate of 6.73%. Notably, grass and shrubland emerged as the primary contributor to the ESV, accounting for 33.25% of the total. (3) The ecological risk index (ERI) in Aksu City, within the period of 2000–2020, showed an increase in the interval from 0.2686 to 0.2877. The results indicated a decline in the overall ecological condition. The ecological risk level in Aksu City from 2000 to 2020 was dominated by lower and medium ecological risks. (4) Moran’s I values in Aksu City between 2000 and 2020 ranged from 0.428 to 0.443, which suggested a positive spatial correlation between ESV and ERI in the study area. The primary factor contributing to the heightened ecological risk in the study region was predominantly attributed to human activities such as urban expansion, agricultural production, and overgrazing.

AbstractThe authors explore a new approach to monitoring of desertification that is based on use of results on the relation between albedo and surface temperature for the Sonoran Desert in northwestern Mexico. The criteria of predominance of radiation by using the threshold value of Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) were determined. The radiation mechanism for regulating the temperature of the surface and the definition of threshold values for AVHRR and MODIS NDVI have an objective justification for the energy budget, which is based on the dominance of radiation surface temperature regulation in relation to evapotranspiration. Changes in the extent of arid regions with AVHRR NDVI of <0.08 and MODIS NDVI of <0.10 can be considered to be a characteristic in the evolution of desertification in the Sonoran Desert region. This is true because, in a certain year, the time span of the period when radiation factor predominates is important for the desertification process.

Arid and semiarid regions are geographic units that cover approximately 43% of the earth’s surface worldwide, and conditions of extreme drought and reduced vegetation cover predominate in these regions. In Mexico, arid and semiarid ecosystems cover more than half of the territory, with desertification, mainly caused by anthropogenic activities and climatic events, as the main problem in these regions. The present research aimed to assess, identify, and classify arid and semiarid zones by employing a methodology based on multicriteria evaluation analysis (MCA) using the weighted linear combination (WLC) technique and geographic information systems (GIS) in the hydrological administrative regions (HARs) of the North Pacific, Northwest, and Baja California Peninsula, located in Northwest Mexico. Data related to aridity, desertification, degradation, and drought were investigated, and the main factors involved in the aridity process, such as surface temperature, soil humidity, precipitation, slopes, orientations, the normalized difference vegetation index (NDVI), and evapotranspiration, were obtained. For the standardization of factors, a fuzzy inference system was used. The weight of each factor was then determined with the analytical hierarchy process (AHP). To delimit arid regions, the classification of arid zones proposed by the United Nations Environment Program (UNEP) was used, and the result was an aridity suitability map. To validate the results, the sensitivity analysis method was applied. Quantitative and geospatial aridity indicators were obtained at the administrative hydrological level and by state. The main results indicated that semiarid and dry subhumid zones predominated, representing 40% and 43% of the surface of the study area, respectively, while arid regions represented 17%, and humid regions represented less than 1%. In addition, of the states for which 100% of the surface lay in the study area, it was observed that Baja California and Baja California Sur had the largest arid and semiarid zones, while subhumid regions predominated in Sonora and Sinaloa.

This paper aims to analyze the distribution patterns of the Yunnan, Guangxi, and Guizhou rocky desertification area, and provide efficient protection and development strategies. This region has a complex geographical environment, and it is distinguished by hosting China’s largest ethnic minority population and the highest concentration of autonomous ethnic counties among contiguous impoverished areas, with numerous traditional villages. Thus, it is significant to conduct a comprehensive study of traditional villages within this domain, with a particular focus on their centralized preservation and strategic utilization. This research employed ArcGIS and Geodetector software for a rigorous analysis of the spatial distribution characteristics and influential factors of traditional villages in the Yunnan, Guangxi, and Guizhou rocky desertification area. The key findings can be summarized as follows. (1) The traditional villages in this region predominantly exhibit an agglomerative distribution pattern, with pronounced concentrations in southeast Guizhou and secondary concentrations in Anshun and Guilin. (2) Natural environmental factors, social economic factors, and national cultural factors impact the distribution of traditional villages synthetically by positive, median, or negative correlation. (3) The results of the Geodetector show that, significantly, social economic and national cultural factors exert a more pronounced influence than natural environmental factors, especially population density and intangible heritage quantity. The interaction of multiple factors shows an enhanced trend. (4) From the perspective of formation mechanism, natural environmental factors serve as foundational elements shaping the original distribution pattern; national cultural factors act as dominant determinants, accentuating spatial distribution distinctions across various regions and social economic factors emerge as critical catalysts for the sustainable development of traditional villages. The interaction factors can have a more profound impact. Furthermore, it is expected that this study will contribute to the effectiveness of ecology and economy in this area and more analogous regions.

Following an operational framework derived from earlier research, our study research estimates the specific contribution of biophysical and socioeconomic factors to soil sensitivity to degradation at two-time points (Early-1990s and Early-2010s) in Italy, a Mediterranean hotspot for desertification risk. A total of 34 variables associated (directly or, at least, indirectly) with different processes of soil degradation (erosion, salinization, sealing, contamination, and compaction) and climate change were considered here, delineating the predominant (underlying) cause (i.e., biophysical or socioeconomic). This set of variables represented the largest (quantitative) information available from national and international data sources including official statistics at both national and European scale. Contribution of biophysical and socioeconomic dimensions to soil sensitivity to degradation was heterogeneous in Italy, with the level of soil sensitivity to biophysical factors being the highest in less accessible, natural areas mostly located in hilly and mountainous districts. The highest level of soil sensitivity to socioeconomic drivers was instead observed in more accessible locations around large cities and flat rural districts with crop intensification and low (but increasing) population density. All these factors delineated an enlarged divide in environmental quality between (i) flat and upland districts, and between (ii) Northern and Southern Italian regions. These findings suggest the appropriateness of policy strategies protecting soils with a strong place-specific knowledge, i.e., based on permanent monitoring of local (biophysical and socioeconomic) conditions.

Abstract. Since the turn of the millennium various scientific publications have been discussing a re-greening of the Sahel after the 1980s drought mainly based on coarse-resolution satellite data. However, the author's own field studies suggest that the situation is far more complex and that both paradigms, the encroaching Sahara and the re-greening Sahel, need to be questioned.This paper discusses the concepts of desertification, resilience, and re-greening by addressing four main aspects: (i) the relevance of edaphic factors for a vegetation re-greening, (ii-iii) the importance of the selected observation period in the debate on Sahel greening or browning, and (iv) modifications in the vegetation pattern as possible indicators of ecosystem changes (shift from originally diffuse to contracted vegetation patterns).The data referred to in this paper cover a time period of more than 150 years and include the author's own research results from the early 1980s until today. A special emphasis, apart from fieldwork data and remote sensing data, is laid on the historical documents.The key findings summarised at the end show the following: (i) vegetation recovery predominantly depends on soil types; (ii) when discussing Sahel greening vs. Sahel browning, the majority of research papers only focus on post-drought conditions. Taking pre-drought conditions (before the 1980s) into account, however, is essential to fully understand the situation. Botanical investigations and remote-sensing-based time series clearly show a substantial decline in woody species diversity and cover density compared to pre-drought conditions; (iii) the self-organised patchiness of vegetation is considered to be an important indicator of ecosystem changes.

Airborne dust derived from desertification in northern China can be transported to East Asia and other regions, impairing human health and affecting the global climate. This study of northern China dust provides an understanding of the mechanism of dust generation and transportation. The authors used dust storm and climatological data from 129 sites and normalized difference vegetation index (NDVI) datasets in northern China to analyze spatiotemporal characteristics and determine the main factors controlling dust storms occurring during 1960–2007. Dust storm–prone areas are consistent with the spatial distribution of northern China deserts where the average wind speed (AWS) is more than 2 m s−1, the mean annual temperature (MAT) ranges from 5° to 10°C, and the mean annual precipitation (MAP) is less than 450 mm. Dust storms commonly occur on spring afternoons in a 3- to 6-h pattern. The three predominant factors that can affect DSF are the maximum wind speed, AWS, and MAT. During 1960–2007, dust storm frequency (DSF) in most regions of northern China fluctuated but had a decreasing trend; this was mainly caused by a gradual reduction in wind speed. The effect of temperature on DSF is complex, as positive and negative correlations exist simultaneously. Temperatures can affect source material (dust, sand, etc.), cyclone activity, and vegetation growth status, which influence the generation of dust storms. NDVI and precipitation are negatively correlated with DSF, but the effect is weak. Vegetation can protect the topsoil environment and prevent dust storm creation but is affected by the primary decisive influence of precipitation.

Soil salinity is one of the major factors causing land degradation and desertification on earth, especially its important damage to farming activities and land-use management in arid and semiarid regions. The salt-affected land is predominant in the Keriya River area of Northwestern China. Then, there is an urgent need for rapid, accurate, and economical monitoring in the salt-affected land. In this study, we used the electrical conductivity (EC) of 353 ground-truth measurements and predictive capability parameters of WorldView-2 (WV-2), such as satellite band reflectance and newly optimum spectral indices (OSI) based on two dimensional and three-dimensional data. The features of spectral bands were extracted and tested, and different new OSI and soil salinity indices using reflectance of wavebands were built, in which spectral data was pre-processed (based on First Derivative (R-FD), Second Derivative (R-SD), Square data (R-SQ), Reciprocal inverse (1/R), and Reciprocal First Derivative (1/R-FD)), utilizing the partial least-squares regression (PLSR) method to construct estimation models and mapping the regional soil-affected land. The results of this study are the following: (a) the new OSI had a higher relevance to EC than one-dimensional data, and (b) the cross-validation of established PLSR models indicated that the β-PLSR model based on the optimal three-band index with different process algorithm performed the best result with R2V = 0.79, Root Mean Square Errors (RMSEV) = 1.51 dS·m−1, and Relative Percent Deviation (RPD) = 2.01 and was used to map the soil salinity over the study site. The results of the study will be helpful for the study of salt-affected land monitoring and evaluation in similar environmental conditions.

Abstract The global climatic changes consisting of the increased in the average air temperature and changes in the rainfall regime have led in the last decades to the extension of the agricultural areas affected by the drought phenomenon, both worldwide and in Romania. During the last half century, the drought and the phenomena associated with it, namely aridization and desertification, are a major problem for mankind. The limiting factor affecting field crops on the largest surface is the drought, the extent and intensity of this type of risk causing annual reduction of agricultural production by at least 30-50%. Drought represents the natural phenomenon determined by the amounts of precipitations below the normal values. The absence of rainfall is due to the predominance of the anti-cyclonic type. The most frequent phenomena occur in the extra-Carpathian agricultural regions of southern and south-eastern Romania Muntenia is located in the drought-sensitive area, where the influx of continental anti-cyclones is higher. Although this phenomena is possible in all seasons and in all agricultural areas, it doesn’t occur simultaneously and doesn’t have the same intensity. In the 21st century, the agricultural years 2001-2002, 2002-2003, 2006-2007, 2011-2012 and 2014-2015 are included in the list of the most recent years in terms of rainfall quantities, the heat units recorded in the warm season, as well as the soil moisture reserve available to winter wheat and maize plants during maximum water consumption. The objective of this paper is to highlight the correlation between the pluviometric regime analyzed during periods of maximum consumption of water from winter wheat and maize crops, the phenomenon of "heat" and the soil moisture reserve. The analysis of these specific indices helped us characterize the mentioned agricultural years, in the context of analysing the phenomenon of pedological drought with an impact in agriculture in Muntenia Region. An important element in the development of agricultural management strategies is to improve scientific knowledge and capacities to better manage climate variability by examining climate data and risks and opportunities analysis. The decrease in production of winter wheat and maize wheat crops occurs in extreme dry agricultural years due to the shortening of the vegetation season as a result of the increase in air temperature and water stress during the period of accumulation of the dry matter in the grain (the filling phase grain) caused by the reduction of precipitation amounts. Drought periods are increasingly common in Romania and are a major problem for agriculture with high impact on the agricultural production.

AbstractVegetation restoration in dryland regions may be a powerful way to control desertification and promote local habitat recovery. In these artificial revegetation systems, ecosystem processes and functioning are strongly determined by nitrogen (N) availability, while soil inorganic N (SIN) is the major available N form and is absorbed as a main N source for plants. However, SIN dynamics, their influencing factors, and their relative importance to the ecosystem of these N‐limited systems are not well understood. A field investigation was conducted to examine the monthly variations in SIN and its response to planting age and vegetation type in a typical artificial sand‐fixing system in northwestern China. The SIN content in topsoil (0–20 cm) during the growing season ranged from 7.10 to 95.65 mg kg−1, with a mean value of 27.14 mg kg−1. Soil nitrate N had a dominant role in determining SIN monthly dynamics, which showed a fluctuating trend with two peak values in early July and late August. SIN showed a significant increasing trend with the planting age of sand‐fixing vegetation, and it was highest for Nitraria sphaerocarpa (55.66 ± 5.76 mg kg−1), followed by Haloxylon ammodendron (29.81 ± 3.47 mg kg−1) and interspace (11.39 ± 1.13 mg kg−1). SIN displayed a hump‐shaped relationship with air temperature (R2 = 0.96, p < 0.01) and had a maximum at 19.88°C. The change rate of SIN was positively correlated with accumulated precipitation (R2 = 0.99, p < 0.05). SIN was correlated significantly with soil organic carbon (SOC), total nitrogen (TN), and soil clay content. Our results revealed that climatic (air temperature and precipitation), abiotic (soil texture), plant (planting age and vegetation type), and nutrient‐related (SOC and TN) factors regulate SIN dynamics in artificial sand‐fixing vegetation systems. Climate was the predominant factor affecting soil ammonium N, and soil nutrients (SOC and TN) were the predominant factor affecting soil nitrate N. Therefore, these factors should be integrated into optimizing regional vegetation establishment and improving ecosystem management practices in sand‐fixing lands.

La désertification, en tant que problématique majeure affectant la vie sur Terre, a d’énormes conséquences qui dégradent la qualité de vie des hommes, leurs activités quotidiennes et leurs moyens de subsistance. Pour lutter contre son avancée, les organisations internationales ont mis en place des actions pour ralentir ou arrêter son expansion et réduire ses impacts.Cette thèse s’inscrit dans la lutte contre la désertification en modélisant le processus de dégradation des terres conduisant à la désertification. Deux modèles sont développés : le premier combine des automates cellulaires continus et l'évaluation MEDALUS, évaluant la désertification sur la base des indices des facteurs sol, végétation, climat et management. Le deuxième modèle simule la dégradation des terres en utilisant le couple automates cellulaires/Modèle MEDALUS, enrichi par des facteurs anthropiques comme les pratiques d'utilisation des terres, le facteur d'exploitabilité et l’appartenance foncière, formant le Modèle Amélioré de Désertification. Ce modèle sert de base au logiciel DESERTIfication Cellular Automata Software (DESERTICAS), permettant de simuler l'évolution spatio- temporelle de la dégradation des terres. DESERTICAS facilite l'exploration de scénarios de dégradation des terres dans le temps et l'espace.Ces modèles développés intègrent des processus dynamiques dans le modèle MEDALUS à la base statique et permettent d’étendre la notion d’état des automates cellulaires classiques à des états continus. L’identification d’un facteur prédominant permet d’agir sur tout le système conduisant à la désertification. Notre étude met en évidence le management, action humaine, comme facteur prédominant affectant indirectement les autres facteurs. Agir positivement sur le management permet d’interrompre les sources de dégradation, de ralentir ou arrêter la dégradation des terres. La théorie du contrôle est également appliquée au modèle d'automates cellulaires développés et permet d’agir sur le facteur prédominant à partir des algorithmes génétiques. En intégrant des actions de protection des terres dans les simulations liées à la désertification, le logiciel DESERTICAS devient un outil d'aide à la décision
Desertification, as a significant challenge impacting life on Earth, has extensive consequences that degrade human life quality, daily activities, and livelihoods. In response, international organizations have implemented actions to slow or stop its progress and reduce its impacts. This thesis focuses on combating desertification by modelling the process of land degradation leading to desertification. Two models are developed: the first combines continuous Cellular Automata and the MEDALUS assessment, evaluating desertification based on soil, vegetation, climate, and management. The second model simulates land degradation using cellular automata approach, enriched with anthropogenic factors like land use practices, exploitability factor and ownership, forming the Enhanced Model of Desertification. This model serves as the basis for DESERTIfication Cellular Automata Software (DESERTICAS), simulating spatio- temporal land degradation evolution. DESERTICAS facilitates scenario exploration by simulating land degradation progression over time and space. The models incorporate dynamic processes into the MEDALUS model, expanding classical Cellular Automata to continuous states. Identifying a predominant factor influencing desertification, management emerges as crucial, affecting other factors indirectly. Positive management actions can interrupt degradation sources, slowing or halting land degradation. The thesis also applies control theory to the Cellular Automata model, aiming to influence the predominant factor using Genetic Algorithms. By integrating land protection actions into desertification simulations, the DESERTICAS software becomes a decision support tool