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The article discusses the issues involved in using remote sensing techniques to detect anthropogenic pollutants in the Mount (Mt.) Everest region of Nepal. Topics include an overview of project of the American Climber Science Program (ACSP) aimed at determining some of the harshest environments on Earth, the dynamics of vegetation surrounding Mt. Everest and how high alpine ecosystems are impacted by warfare tourism and climate variability and change.

This study aimed to identify different environmental microbiota in animal farms adjacent to produce fields and to understand their potential flow pattern. Soil and water samples were collected from 16 locations during the winter, spring, summer, and fall seasons. In addition, a high-resolution digital elevation model helped to create a stream network to understand the potential flow of the microbiome. Metagenomic analysis of the 16 S rRNA gene revealed that soil and water samples from the four seasons harbor diverse microbiome profiles. The phylogenetic relationship of operational taxonomic units (OTUs) is separated by a maximum of 0.6 Bray-Curtis distance. Similarly, the Principal Component Analysis (P = 0.001) demonstrated the soil and water microbiome clustering across different locations and seasons. The relative abundance of Proteobacteria, Bacteroidetes, and Firmicutes was higher in the water samples than in the soil samples. In contrast, the relative abundance of Actinobacteria and Chloroflexi was higher in the soil compared to the water samples. Soil samples in summer and water samples in spring had the highest abundance of Bacteroidetes and Firmicutes, respectively. A unique microbial community structure was found in water samples, with an increased abundance of Hydrogenophaga and Solirubrobacter. Genera that were significantly abundant at a 1% false discovery rate (FDR) among seasons and soil or water samples, include Nocardioides, Gemmatimonas , JG30-KF-CM45, Massilia, Gaiellales, Sphingomonas , KD4-96, Bacillus, Streptomyces, Gaiella , and Gemmatimonadaceae. The relative abundance of pathogenic genera, including Mycobacterium, Bacteroides, Nocardia, Clostridium, and Corynebacterium , were significantly (at 1% FDR) affected by seasons and environmental type. The elevation-based stream network model suggests the potential flow of microbiomes from the animal farm to the produce fields. • Most abundant genera: Mycobacterium, Bacteroides, Nocardia, Clostridium, and Corynebacterium. • The prevalence of Proteobacteria is more likely to increase during the winter months. • The prevalence of pathogenic genera is relatively more abundant in water than soil across all seasons. • Meteorological parameters alter the presence of environmental microbiota, including pathogenic genera. • Animal farms carry a high potential to contaminate the produce fields, as suggested by the stream network model. [ABSTRACT FROM AUTHOR]