UNESCO Chair of Aflaj Studies, Arco-hydrology, University of Nizwa, Nizwa, Oman.
PLoS One. 2024 May 14;19(5):e0301832. doi: 10.1371/journal.pone.0301832. eCollection 2024.
This study investigates the spatial distribution patterns and environmental factors influencing the Aini Falaj system in a specific study area. The research findings are presented through the lens of the following four categories: collinearity diagnostics, spatial autocorrelation analysis, kernel density (KD) findings, and multivariate geographically weighted regression (MGWR) analysis. The collinearity diagnostics were applied to examine the interrelationships among 18 independent environmental variables. The results indicate the absence of significant multicollinearity concerns, with most variables showing values below the critical threshold of five for variance inflation factors (VIFs). The selected variables indicate minimal intercorrelation, suggesting that researchers should be confident utilizing them in subsequent modelling or regression analyses. A spatial autocorrelation analysis using Moran's Index revealed positive spatial autocorrelation and significant clustering patterns in the distribution of live and non-functional Aini Falajs. High concentrations of live or dead Falajs tended to be surrounded by neighbouring areas with similar characteristics. These findings provide insights into the ecological preferences and habitat associations of Aini Falajs, thereby aiding conservation strategies and targeted studies. The kernel density (KD) analysis depicted distribution patterns of live and dry Aini Falajs through hotspots and cold spots. Specific regions exhibited high-density areas of live Falajs, indicating favourable environmental conditions or historical factors contributing to their concentrated distribution. Identifying these high-density zones can enhance our understanding of the spatial patterns and potential factors influencing the prevalence and sustainability of Aini Falajs. The multivariate geographically weighted regression (MGWR) models revealed strong associations between the live or dead status of Aini Falajs and environmental factors. The precipitation, topographic wetness index (TWI), aspect and slope exerted positive impacts on the live status, while evaporation, solar radiation, distance to drains and drain density exerted negative influences. Similar associations were observed for the dead status, emphasising the importance of controlling evaporation, shading mechanisms, proper drainage planning and sustainable land-use practices. This study provides valuable insights into the spatial distributions and factors influencing the live and dead status of Aini Falajs, thereby contributing to our understanding of their ecological dynamics and guiding conservation efforts and management strategies.
本研究旨在调查特定研究区域内艾因法拉杰系统的空间分布模式和影响因素。研究结果通过以下四个类别呈现：共线性诊断、空间自相关分析、核密度（KD）分析和多元地理加权回归（MGWR）分析。共线性诊断用于检查 18 个独立环境变量之间的相互关系。结果表明，不存在显著的多重共线性问题，大多数变量的方差膨胀因子（VIF）值低于 5 的临界阈值。所选变量之间的相互关系最小，这表明研究人员在后续建模或回归分析中可以放心使用这些变量。利用 Moran 指数进行的空间自相关分析显示，活的和非功能的艾因法拉杰的分布存在正空间自相关和显著的聚类模式。活的或死的法拉杰的高浓度区域往往被具有相似特征的相邻区域包围。这些发现深入了解了艾因法拉杰的生态偏好和栖息地关联，从而为保护策略和有针对性的研究提供了依据。核密度（KD）分析通过热点和冷点描绘了活的和干涸的艾因法拉杰的分布模式。特定区域表现出活的法拉杰的高密度区域，表明存在有利于其集中分布的环境条件或历史因素。确定这些高密度区域可以增强我们对艾因法拉杰空间模式和潜在影响因素的理解，从而提高其存在和可持续性。多元地理加权回归（MGWR）模型揭示了艾因法拉杰的活的或死的状态与环境因素之间的强烈关联。降水、地形湿度指数（TWI）、方位和坡度对活的状态产生积极影响，而蒸发、太阳辐射、到排水渠的距离和排水渠密度对死的状态产生消极影响。对死的状态也观察到了类似的关联，强调了控制蒸发、遮阳机制、合理的排水规划和可持续土地利用实践的重要性。本研究为艾因法拉杰的空间分布及其影响因素提供了有价值的见解，从而加深了我们对其生态动态的理解，并为保护努力和管理策略提供了指导。
