Occurrence of traditional and alternative fecal indicators in tropical urban environments under different land use patterns

• Main Authors: Saeidi, Nazanin, Gu, Xiaoqiong, Tran, Ngoc Han, Goh, Shin Giek, Kitajima, Masaaki, Kushmaro, Ariel, Schmitz, Bradley William, Gin, Karina Yew-Hoong
• Other Authors: Elkins, Christopher A.
• Format: Article
• Language: English
• Published: 2019
• Subjects: Fecal Indicators; DRNTU::Engineering::Materials; Land Use
• Online Access: https://hdl.handle.net/10356/105747; http://hdl.handle.net/10220/47410
• Institution: Nanyang Technological University

This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P < 0.01) compared to traditional FIB (rho = 0.583; P < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P < 0.05).