贵州省岩溶洼地发育的空间分布格局及控制因素

Karst depressions are common negative topographic landforms formed by the intense dissolution of soluble rocks and are widely developed in Guizhou province.In this work,an inventory of karst depressions in Guizhou was established,and a total of approximately 256,400 karst depressions were extracted and found to be spatially clustered based on multidistance spatial cluster analysis with Ripley’s K function.The kernel density(KD)can transform the position data of the depressions into a smooth trend surface,and five different depression concentration areas were established based on the KD values.The results indicated that the karst depressions are clustered and developed in the south and west of Guizhou,while some areas in the southeast,east and north have poorly developed or no clustering.Additionally,the random forest(RF)model was used to rank the importance of factors affecting the distribution of karst depressions,and the results showed that the influence of lithology on the spatial distribution of karst depressions is absolutely dominant,followed by that of fault tectonics and hydrological conditions.The research results will contribute to the resource investigation of karst depressions and provide theoretical support for resource evaluation and sustainable utilization.

Geographic distribution of echinococcosis in Tibetan region of Sichuan Province,China

Background:Echinococcosis is a parasitic zoonosis caused by Echinococcus larvae parasitism causing high mortality.The Tibetan Region of Sichuan Province is a high prevalence area for echinococcosis in China.Understanding the geographic distribution pattern is necessary for precise control and prevention.In this study,a spatial analysis was conducted to explore the town-level epidemiology of echinococcosis in the Sichuan Tibetan Region and to provide guidance for formulating regional prevention and control strategies.Methods:The study was based on reported echinococcosis cases by the end of 2017,and each case was geo-coded at the town level.Spatial empirical Bayes smoothing and global spatial autocorrelation were used to detect the spatial distribution pattern.Spatial scan statistics were applied to examine local clusters.Results:The spatial distribution of echinococcosis in the Sichuan Tibetan Region was mapped at the town level in terms of the crude prevalence rate,excess hazard and spatial smoothed prevalence rate.The spatial distribution of echinococcosis was non-random and clustered with the significant global spatial autocorrelation(I=0.7301,P=0.001).Additionally,five significant spatial clusters were detected through the spatial scan statistic.Conclusions:There was evidence for the existence of significant echinococcosis clusters in the Tibetan Region of Sichuan Province,China.The results of this study may assist local health departments with developing better prevention strategies and prompt more efficient public health interventions.