Microbial communities in surface waters are highly responsive to perturbation, shifting with tidal cycles 
, salinity gradients 
, dissolved organic matter concentration 
, and chemical stress 
. The detection of short-term fluctuations in community composition suggests changes in environmental conditions, nutrients or bacterial sources. An effect of increased salinity due to tidal influence on bacterial composition was observed in this study where the coastal lagoon communities were more similar to creek communities with comparable salinity measurements (). Salinity was more strongly correlated to community composition than the other environmental variables measured based on canonical correspondence analysis (data not shown). This result corroborated observations by others 
. In addition to being highly sensitive to environmental fluctuations, the response time of community composition shift was within a 24-hour period.
The detection of this rapid community response could be useful for indication of external bacterial inputs, such as from fecal sources. FSAO, derived from the human fecal and untreated sewage samples, were used to represent fecal communities. One caveat is that the OTUs in the FSAO list are specific to the 3 fecal samples used in this study, and do not represent all fecal communities in all environments. However, the prevalent bacterial phyla found in the FSAO are the same as those observed in published studies of human gastrointestinal tract samples 
and turkey cecal samples 
. Therefore, community similarity to FSAO could potentially indicate the presence of fecal bacteria. This hypothesis was tested by comparing the community distances between FSAO and variable/stable subpopulations at each of the site ().
Examination of the variable and stable subpopulations brings to light the bacterial temporal fluctuations across the 3 days. The variable subpopulation represents OTUs with highly fluctuating relative abundances, perhaps due to rapid growth, decay or large sporadic influx of bacterial sources. The stable subpopulation represents OTUs with constant relative abundances. These stable subpopulation OTUs are likely associated with endemic bacteria that are able to grow and persist under the in situ environmental conditions or are from consistent external sources.
UniFrac analysis showed that the variable subpopulation of M6 was the most similar to the FSAO (). This suggested intermittent exposure to fecal sources at this site, which was supported by elevated but numerically variable HBM densities and FIB MPN (Figure S3
). The prevalence of Enterobacteriales
in the variable subpopulation falls in line with the high FIB MPN observed at site M6, and further supports the use of similarity of the variable subpopulation with FSAO for demonstrating fecal pollution. Similarity of M9 variable subpopulation to FSAO was not significantly different from that of the M6 (). This indicated that there were OTUs in the M9 variable subpopulation that were also found in the FSAO, but they were mostly from the order of Campylobacterales
, and not represented by FIB or HBM detection. The similarity to FSAO decreased gradually from drains to downstream sites (i.e. M9 to M7 and M6 to M4), illustrating possible fecal community presence at the drains and die-off or dilution effects as the communities flow downstream.
Interestingly, the stable subpopulation at M9 was most similar to FSAO out of all the sites, even though the FIB densities met the California water quality standards on 2 out of the 3 days and no HBM was detected ( and Figure S3
). The non-detection of HBM at M9 could be due to Bacteroides
DNA concentration being below the quantitative PCR detection limit of 0.5×103
targets L−1 
or that the fecal source was non-human. The top three families present in the M9 stable subpopulation were Bacillaceae
. While Bacillaceae
have been observed in non-aquatic environments 
are primarily associated with cow rumen 
, human bowel 
and anaerobic digesters 
. Therefore, the data suggested that some of the OTUs detected at M9 could have a fecal, but non-human, origin. However, further confirmatory work is needed to distinguish between a consistent fecal source or bacterial re-growth as the cause for the similarity between M9 stable subpopulation and FSAO.
The FSAO includes OTUs that contain fecal coliforms, which have been demonstrated to re-grow and persist in the environment leading to false-positive water quality diagnoses 
. This study further explores the potential of using alternative organisms that are independent of coliforms as fecal indicators by introducing the BBC
A ratio. The ratio excludes coliform bacteria, thus, potentially avoids false-positive results associated with coliforms, and integrates counts for organisms widespread in non-fecal “pristine” environments to assess ecosystem health.
are enriched within the gut microbiota of many mammals 
, and specific species within these 2 classes have been proposed as fecal indicators 
. However, they are also found in anoxic saline aquatic environments 
, estuaries 
, the deep ocean 
, and high elevation lakes 
. The class of Bacilli
, which includes the indicator species Enterococcus
, is commonly found in fecal samples such as the human gastrointestinal tract 
, turkey intestines 
and aerobic thermophilic swine wastewater bioreactors 
. All 3 classes are dominant groups found in a chicken fecal metagenomic study 
, have been found as primary surface colonizers in coastal marine waters 
and have the ability to thrive under low-nutrient conditions 
. The BBC
A ratio incorporates the relative richness of OTUs prevalent in these 4 bacterial classes associated with fecal and non-fecal samples to reflect possible fecal inputs, rather than the use of single organism presence or absence. Previous studies have suggested the use of ratios for indicating human or non-human fecal pollution 
, determining fecal age and enteric viral content 
, representing the nutrient status of soil ecosystems 
, identifying land use in wetland soils 
, and eutrophy in aquatic systems 
In order to assess the applicability of the observations from our watersheds to other samples, we calculated the BBC
A ratio from previously published and unpublished studies (Table S2
A ratios of gut samples analyzed by DNA sequencing or PhyloChip are not completely comparable, mainly due to differences in sample processing including primers used, PCR conditions and coverage differences across phylogenetic groups on the PhyloChip. However, within communities analyzed by sequencing from different research groups employing varying protocols, the gut, sewage-associated and non-fecal samples exhibited the same BBC
A ratio trend as those communities analyzed by PhyloChip processed with a consistent standardized protocol. The distribution of BBC
A ratios from these studies illustrates that gut and sewage-associated samples have higher BBC
A ratio than non-fecal samples regardless of analysis methods (). Anoxic non-fecal polluted environments also have similar ratios of BBC
A as sewage-associated samples (). This is most likely an attribute of similar growth conditions favoring both anaerobic and fecal bacteria. The indication of anoxic non-fecal environments is often times pertinent for determining public health risks. Anoxic conditions could lead to eutrophication in both fresh and salt water environments, which changes nutrient cycling, water quality and biodiversity 
. Eutrophication has led to toxic algal blooms that adversely affect human and wildlife health 
Kendall rank correlation of FIB, HBM, FSAO and BBC
A ratios from all sites indicated significant positive correlations of BBC
A ratios with HBM, total coliform, enterococcus and FSAO counts, but not with E. coli
). However, many of the samples had reached the total coliform measurement maximum detection limit of 24,196 MPN, therefore, the correlation of total coliform with BBC
A ratio might be misleading. The result also illustrated that even though the BBC
A ratio did not contain fecal coliforms, the fecal pollution pattern was similar to that indicated by the FSAO where coliforms were included. The drain site M6 was the only site where all lines of evidence, i.e. similarity of variable subpopulations to FSAO, FIB, HBM, and BBC
A ratios, pointed to the presence of fecal contamination. At site M1 (ocean), all data indicated a community with the least fecal influence. The data for the rest of the sites (M2, M3, M4, M5, M7, M8 and M9) indicated varying degrees of influence by fecal sources. Also, communities from drains (M6 and M9) were the most similar to organisms found in the fecal samples, although different fecal organisms were detected in the two drains.
Knowledge of who is there and how they change over time and location is the hallmark of an ecosystems approach to studying urban watersheds. We used this concept to track the microbial community dynamics over a three-day period at a location with a history of frequent fecal contamination. In spite of the confounding effect of the movement of water through this watershed, several patterns that correlated with the presence of human fecal contamination were observed. By using the PhyloChip we are able to identify a significantly greater number of bacterial OTUs than is typically examined in coastal watersheds. Comparison of the microbial inventory of the watershed samples with local sewage samples and a human fecal sample led to the identification of specific organisms that were associated with either potential human fecal sources or with the watershed. From this information we observed 503 OTUs that were common to the three fecal samples (FSAO) and the ratios of observed classes of organisms that demonstrated the largest differences between human fecal sources and the receiving waters (BBC
A ratio). Whereas most research for measuring fecal influences on coastal watersheds uses a bottom-up approach to hypothesize that a specific organism is representative of the source, we employed a top-down approach that looked at a large number of potential bacterial contaminants from a majority of the known bacterial diversity to identify a diverse collection of organisms associated with fecal pollution. The advantage of this approach is that we can use the findings of the BBC
A ratio and the FSAO as the basis for additional bottom-up, controlled experiments to examine their applicability at other locations and with other human fecal sources. Using this more detailed microbial community characterization, it may be possible to move away from generic, single indicators to a community-indicator approach for assessing fecal contamination or environments conducive to pathogen growth.