Many of Auckland’s beaches and waterways are subject to intermittent microbiological contamination, which can pose a risk to human health through recreational contact. Regular monitoring of faecal indicator bacteria (FIB) is undertaken at beaches over the summer months, consistent with national guidelines, and can result in beach closures.
The presence of microbiological contamination within the marine environment is often presumed to be the result of human related sources, such as wet weather-induced combined sewer and designed wastewater overflows into streams or directly from coastal outfalls. In addition, aging infrastructure, private septic systems or cross connections may contribute microbiological contaminants to the stormwater network and associated open waterways. However, non-human related sources of contamination from domestic, wild and farmed animals and birds also enter the aquatic environment directly or via overland flow.
Effective management of microbiological contamination requires knowledge of the source animal so that appropriate interventions can be applied. FIB results are unable to determine the source of microbiological contamination and are therefore limited in terms of informing management interventions. Recent advancements in molecular techniques have permitted the use of genetic markers to distinguish between sources of faecal pollution.
This paper will present a meta-analysis of several investigations initiated by Auckland Council to investigate the sources of FIB contamination across the region. A tiered approach using FIB and genetic based analysis (‘ microbial source tracking’) was undertaken in a range of marine and freshwater environments in an attempt to determine the animal source of contamination (i.e. human, canine, avian or ruminant).
Identifying the source of faecal contamination within a catchment is challenging and is influenced by a variety of factors in different receiving environments. The use of faecal source tracking can provide information on the sources of microbiological contamination, allowing the implementation of efficient and effective management responses to meet water quality outcomes.