Investigation of tuberculosis clusters in Dehradun city of India

Objective:To investigate the presence of statistically significant geographical clusters of tuberculosis(TB) using Geographical Information System and spatial scan statistics in Dehradun, India.Methods:The spatial scan statistic implemented with a software program,SaTScan v6.1, was used to test the presence of statistically significant spatial clusters of TB and to identify their approximate locations(P【0.05 for primary clusters and P【0.1 for secondary clusters). Geographical Information System was used for geographical analysis.Results:Significant high rate spatial clusters were identified in seven wards of the Dehradun Municipal area. Conclusions:There is sufficient evidence about the existence of statistically significant TB clusters in seven wards of Dehradun,India.The purely spatial scan statistics methodology used in this study has a potential use in surveillance of TB for detecting the true clusters of the disease.

Shared-role of vegetation types,elevation and soil affecting plant diversity in an old-tropical mountain hotspot

Despite the exceptional species richness and endemism,the environmental drivers of plant diversity along old tropical mountains remain underexplored.The respective importance of vegetation types,elevation,slope,and soil to drive diversity across life-forms is poorly addressed.Here,we tested whether environmental variables drove local and regional plant diversity along an old tropical mountain according to the three main life-forms:graminoids,herbaceous and woody species.We sampled all Angiosperm species on 180 plots across five elevations,at the tropical old-mountain region of Serra do Cipó,South-eastern Brazil.We assessed soil,slope,and vegetation types,and calculated richness and beta-diversity,applying generalized least square models,linear mixed-models and partial Mantel tests to test for relationships.Richness of graminoids and herbaceous species increased with greater elevation and more nutrient-impoverished soils,while woody richness showed the inverse pattern.Beta-diversity was primarily driven by species turnover,correlated with elevation and soil and higher in less dominant vegetation types,with unique species.Despite the limited elevational range in these old mountains,it still played an important role in filtering woody species,while fostering graminoid and herbaceous species.Conservation and restoration actions need to foster the high regional diversity supported by the old mountain heterogeneous landscape and the diversity of life-forms,especially the dominant and highly diverse grassy component.

Gully erosion mapping susceptibility in a Mediterranean environment: A hybrid decision-making model

Gully erosion is one of the main natural hazards,especially in arid and semi-arid regions,destroying ecosystem service and human well-being.Thus,gully erosion susceptibility maps(GESM)are urgently needed for identifying priority areas on which appropriate measurements should be considered.Here,we proposed four new hybrid Machine learning models,namely weight of evidence-Multilayer Perceptron(MLP-WoE),weight of evidence–K Nearest neighbours(KNN-WoE),weight of evidence-Logistic regression(LR-WoE),and weight of evidence-Random Forest(RF-WoE),for mapping gully erosion exploring the opportunities of GIS tools and Remote sensing techniques in the El Ouaar watershed located in the Souss plain in Morocco.Inputs of the developed models are composed of the dependent(i.e.,gully erosion points)and a set of independent variables.In this study,a total of 314 gully erosion points were randomly split into 70%for the training stage(220 gullies)and 30%for the validation stage(94 gullies)sets were identified in the study area.12 conditioning variables including elevation,slope,plane curvature,rainfall,distance to road,distance to stream,distance to fault,TWI,lithology,NDVI,and LU/LC were used based on their importance for gully erosion susceptibility mapping.We evaluate the performance of the above models based on the following statistical metrics:Accuracy,precision,and Area under curve(AUC)values of receiver operating characteristics(ROC).The results indicate the RF-WoE model showed good accuracy with(AUC=0.8),followed by KNN-WoE(AUC=0.796),then MLP-WoE(AUC=0.729)and LR-WoE(AUC=0.655),respectively.Gully erosion susceptibility maps provide information and valuable tool for decision-makers and planners to identify areas where urgent and appropriate interventions should be applied.