Science, Faculty of
Earth, Ocean and Atmospheric Sciences, Department of
DSpace
Boardman, Anya
Chelswick, Kailey
Collins, Sophia
Law, Pui Yi
Fecal contamination in shellfish harvesting areas in British Columbia affects human health, ecosystem function, and industry. Previous studies have investigated fecal contamination of marine environments, however, sources of contamination and the dispersal of contaminants throughout marine environments is contingent on the specific environmental conditions at a given site. In collaboration with the BC Centre for Disease Control (BCCDC), this report addresses fecal contamination in marine waters across three vital shellfish harvesting locations on Vancouver Island (Saanich Inlet, Comox Harbour, and Baynes Sound), through the analysis of fecal coliform concentration data obtained from Environment and Climate Change Canada. FC concentration data spans from 1982 to 2022, and was analyzed in relation to environmental factors including rainfall, salinity, air temperature, land use, flushability and streamflow at the three study sites. Our findings highlight significant seasonal FC concentration variations, with peaks during fall, closely linked to increased precipitation and runoff. Land use analysis points to agriculture, residential development, and mining as key contamination sources. In addition, this study examined the relationship between river streamflow, proximity to river mouths, and FC concentration, providing nuanced insights into how freshwater inputs affect marine water quality and how this varies by river. This research also investigates coastal flushability, which refers to the ability of an area to clear pollutants through the movement of tidal waters. Results indicate that regions with increased water flow have reduced FC concentrations, highlighting how hydrodynamics play a role in dispersing contaminants. Conversations with stakeholders and investigation into regional sewage management practices suggest that private and central sewage management practices are likely an important source of fecal contamination. Elevated FC concentrations across all study areas reinforce concern regarding fecal contamination in this region. The results of our study lead us to recommend 1) increased regulation and monitoring of sewage infrastructure, 2) alternative sampling methods to identify sources of contamination, and 3) continued monitoring of FC concentration patterns in conjunction with the specific environmental factors in this region. These actions can maintain longevity of shellfish harvesting enterprises, improve the health of the marine environment, and decrease health risks to Indigenous Peoples practicing traditional harvesting.
Spatial and Temporal Indicators of High Fecal ColiformConcentrations at Three Sites With Marine ShellfishHarvesting Activity on Vancouver IslandBy Anya Boardman, Kailey Chelswick, Sophia Collins and Pui Yi LawMay 2, 20241AbstractFecal contamination in shellfish harvesting areas in British Columbia affects human health,ecosystem function, and industry. Previous studies have investigated fecal contamination ofmarine environments, however, sources of contamination and the dispersal of contaminantsthroughout marine environments is contingent on the specific environmental conditions at agiven site. In collaboration with the BC Centre for Disease Control (BCCDC), this reportaddresses fecal contamination in marine waters across three vital shellfish harvesting locationson Vancouver Island (Saanich Inlet, Comox Harbour, and Baynes Sound), through the analysisof fecal coliform concentration data obtained from Environment and Climate Change Canada.FC concentration data spans from 1982 to 2022, and was analyzed in relation to environmentalfactors including rainfall, salinity, air temperature, land use, flushability and streamflow at thethree study sites. Our findings highlight significant seasonal FC concentration variations, withpeaks during fall, closely linked to increased precipitation and runoff. Land use analysis points toagriculture, residential development, and mining as key contamination sources. In addition, thisstudy examined the relationship between river streamflow, proximity to river mouths, and FCconcentration, providing nuanced insights into how freshwater inputs affect marine water qualityand how this varies by river. This research also investigates coastal flushability, which refers tothe ability of an area to clear pollutants through the movement of tidal waters. Results indicatethat regions with increased water flow have reduced FC concentrations, highlighting howhydrodynamics play a role in dispersing contaminants. Conversations with stakeholders andinvestigation into regional sewage management practices suggest that private and centralsewage management practices are likely an important source of fecal contamination. ElevatedFC concentrations across all study areas reinforce concern regarding fecal contamination in thisregion. The results of our study lead us to recommend 1) increased regulation and monitoring ofsewage infrastructure, 2) alternative sampling methods to identify sources of contamination, and3) continued monitoring of FC concentration patterns in conjunction with the specificenvironmental factors in this region. These actions can maintain longevity of shellfish harvestingenterprises, improve the health of the marine environment, and decrease health risks toIndigenous Peoples practicing traditional harvesting.2Land AcknowledgmentWe would like to acknowledge that our work for this study took place on the University of BritishColumbia campus, on the ancestral, unceded, and traditional territories of the xwməθkwəy̓əm(Musqueam) People. The land on which the data we used was collected spans the ancestral,unceded, and traditional territories of the K’ómoks, We Wai Kai,Homalco, Cowichan, W̱SÁNEĆ,Malahat and Songhees nations. We recognize that data collection relating to marinecontamination often largely serves to benefit colonial economic interests, rather than contributeto the sovereignty of Indigenous Peoples, and hope that in future years data collectors willbetter encompass areas that are key to Indigenous traditional harvesting. We have conductedthe work of this report as a small step towards reducing marine contamination and improving thehealth of the marine environment, and are grateful for the Indigenous Peoples living along thecoast who have been stewards of these environments since time immemorial.3Author ProfilesAnya Boardman is an Environmental Science major with a concentration in SustainabilityScience and a minor in English Literature. She spent the past semester in Svalbard, Norwaycompleting coursework in Arctic Technology, and she has worked as a Tundra Ecology fieldresearch assistant in British Columbia, Iceland and Ellesmere Island. She is passionate aboutarctic and alpine research, and is interested in the intersection between scientific research,policy, and communication.Kailey Chelswick is an Environmental Sciences major with a concentration in land, air, andwater systems. She is also completing a Masters of Management and a minor in GeographicInformation Systems and Geographic Computation. Her previous experience includes thedevelopment of environmental systems specialized for major construction projects delivery atTeck Resources Ltd. In addition, she has developed GIS Labs for the Faculty of Forestrycentered around coding and remote sensing. She is passionate about expanding her skills,particularly in the areas of GIS, statistics, and communication.Pui Yi Law majored in Environmental Science, focusing on land, air, and water. She has had theopportunity to do practical work in environmental science because of this report. She has beentaking courses in R, Python, and GIS at UBC to sharpen her skills in spatial analysis.Sophia Collins is an Environmental Sciences major with a concentration in sustainabilityscience. She is also doing a minor in Indigenous Studies. She has been working forenvironmental research labs at UBC for the past 4 years, and during this time has developedskills in using R and Python for spatial analysis. She is passionate about environmental justiceresearch that intersect disciplines.4Table of ContentsAbstract....................................................................................................................................................... 1Land Acknowledgment...............................................................................................................................2Author Profiles............................................................................................................................................ 31. Introduction............................................................................................................................................. 61.1 Fecal Contamination of Coastal Environments...........................................................................61.1.1 Fecal Coliform Testing..........................................................................................................61.2.1 Sewage Contamination........................................................................................................ 81.3 Environmental Factors that Influence Fecal Contamination....................................... 81.3.1 Precipitation and River Outflow.......................................................................................... 91.3.2 Coastline Shape and Tidal Flushing................................................................................... 91.3.3 Land Use..............................................................................................................................102. Methods................................................................................................................................................. 112.1 Study Site Description................................................................................................................. 112.1.1 Location............................................................................................................................... 112.1.2 Climate................................................................................................................................. 122.1.3 Sewage Management..........................................................................................................132.2 Survey Extent Analysis................................................................................................................152.3 Preprocessing Data......................................................................................................................192.4 Environmental Data Sources and Processing...........................................................................202.4.1 Climate Data........................................................................................................................ 202.4.2 River Data............................................................................................................................ 202.4.3 Flushability Data................................................................................................................. 202.5 Statistical Analysis.......................................................................................................................212.5.1 Spatial and Temporal Analysis.......................................................................................... 212.5.2 Comparison with Environmental Factors.........................................................................212.5.2.1 Temperature............................................................................................................... 212.5.2.2 Precipitation...............................................................................................................212.5.2.3 Streamflow and Precipitation Near River Mouths.................................................. 222.5.2.4 Flushability.................................................................................................................222.5.2.5 Land Use.................................................................................................................... 233. Results................................................................................................................................................... 243.1 Spatial and Temporal Description of FCs.................................................................................. 243.2 Climate Analysis...........................................................................................................................293.3 Flushability....................................................................................................................................313.3 Land Use....................................................................................................................................... 323.4 River Analysis...............................................................................................................................353.4.1 Comox Harbour...................................................................................................................353.4.2 Saanich Inlet........................................................................................................................373.4.3 Baynes Sound..................................................................................................................... 4054. Discussion.............................................................................................................................................434.1 Baynes Sound...............................................................................................................................434.2 Comox Harbour............................................................................................................................ 454.3 Saanich Inlet................................................................................................................................. 465. Conclusion............................................................................................................................................ 48Acknowledgements.................................................................................................................................. 50Appendix....................................................................................................................................................51References.................................................................................................................................................6161. Introduction1.1 Fecal Contamination of Coastal EnvironmentsFecal contamination of marine sites is a widespread problem in British Columbia, withimplications for marine ecosystem health, aquaculture, and human health. Fecal pollution ofcoastal habitats causes an overabundance of nutrients and organic material in the water leadingto eutrophication, hypoxia and toxic algae blooms (Islam & Masaru Tanaka, 2004). This disruptsmarine ecosystems by depleting oxygen in the water, altering plant community composition, andproducing biotoxins which can harm marine species as well as humans (Islam & MasaruTanaka, 2004). Human sewage in marine environments can compromise food sources bycontaminating seafood. Bodily contact with contaminated water can lead to gastric illness, andear, skin and lung infections (Windom, 1992). In addition to pathogens, sewage often containsheavy metals and toxic chemicals (Islam & Masaru Tanaka, 2004).1.1.1 Fecal Coliform TestingIn British Columbia, fecal contamination is monitored through fecal coliform concentrationtesting. Fecal coliforms (FC) are a type of bacteria found in the intestines of warm-bloodedanimals, which are then shed in feces. They are commonly used as an indicator species tosignal the presence of feces and associated pathogens and contaminants (Das et al., 2020).Fecal coliform testing is the primary method utilized for determining water quality in BritishColumbia, however, it has limitations as it does not indicate the source of the fecal pollution (i.e.human or animal), and does not directly test for contaminants of concern (i.e. Norovirus andpathogenic E. Coli). Fecal coliforms may be elevated while other contaminants are absent,leading to unnecessary closures. Alternatively, fecal coliform may exist at acceptableconcentrations while Norovirus or other contaminants are present, allowing contaminated sitesto go undetected (Berg et al., 1978).1.1.2 Fecal Contamination of Shellfish Harvest Areas in British ColumbiaShellfish harvest is economically and culturally important along the coast of Vancouver Island,and the focal sites in this study encompass important shellfish harvest regions on the easterncoast of Vancouver Island. In 2022, British Columbia totaled $399 million dollars in shellfishexports (British Columbia Ministry of Agriculture and Food, 2022). Additionally, many First7Nations groups on the Pacific Coast depend on shellfish harvest for food security, economichealth and important cultural practices (Fleming, 2019). However, fecal contamination ofshellfish harvest areas is an ongoing problem. Because shellfish are filter feeders, theybioaccumulate contaminants including pathogens, biotoxins, and heavy metals (Environmentand Climate Change Canada, 2023). The Government of Canada tests FC concentration inshellfish harvest areas to ensure that the shellfish are safe to eat. The median fecal coliformmost probable number (MPN) cannot exceed 14/100 mL, and no more than 10% of samplesmay exceed a fecal coliform MPN of 43/100 mL, for a five-tube decimal dilution test(Environment and Climate Change Canada 2023). If these standards are exceeded, the areawill be closed to shellfish harvest. In 2021, 34% of Canadian Pacific waters tested byEnvironment Canada were closed to harvest due to high levels of fecal contamination(Environment and Climate Change Canada, 2023). In 2022, 301 cases of norovirus andgastrointestinal distress were reported in BC, linked to contaminated oyster farms (Governmentof Canada, 2022). Thus, characterizing the problem of contamination of shellfish harvest sites iscritical in order to protect industry, Indigenous Peoples, and overall human health.1.2 Sources of Fecal ContaminationFecal contamination can originate from humans, wildlife, and domestic animals (Harwood et al.,2009). Animal sources of fecal contamination include farmed domestic animals such as cattle(Zhu et al., 2010), as well as wild animals including mammals and birds (Belsky et al., 1999).Animal sources of contamination depend largely on the species present in the watershed, aswell as the abundance of farmed or wild animals and their proximity to water sources (Zhu et al.,2010).Human sources have been overwhelmingly to blame for elevated FC levels in previous fecalcoliform investigations (Vitro et al., 2017; You et al., 2023). Land-based human sewage mayenter marine systems through overflowing sewage pathways, leaking septic systems,groundwater leaching or direct dumping of sewage into freshwater channels or onto land (Chenet al., 2019; Oun et al., 2014). The extent to which an area is contaminated often depends onits proximity to sewage processing plants (Eregno et al., 2016). Marine sources of sewageinclude discharge from ships and houseboats (Pettibone et al., 2021).81.2.1 Sewage ContaminationRecent contamination reports in British Columbia and concerns raised by stakeholders stronglyindicate that human sewage is likely to blame for fecal contamination in this study region.Industry representatives from the BC Shellfish Grower’s Association expressed that leakage ofsewage from mismanaged septic systems was their greatest concern regarding shellfishcontamination (A. Munro, personal communication, October 11, 2023). Issues regarding sewagemanagement were detailed by the The Sewerage System Regulation Improvement Coalition(SSRIC) in a report titled “Reforming the Regulation of BC’s Sewerage Systems: An UrgentNeed to Protect Public Health” (2008). This report states that British Columbia is the only placein North America where government inspection and approval is not required in order to installsewage systems, and raises concern that independent contractors and homeowners may not beable to adequately manage sewage without third party oversight, due to inadequate training andthe motivation of both to cut costs (The Sewerage System Regulation Improvement Coalition,2009). The concerns of the SSRIC are supported by recent reports of human sewagecontamination in British Columbia. CBC News reported that sewage from boats or on-landseptic systems was the likely culprit for a 2022 norovirus outbreak traced back to Baynes SoundOysters (Petrovich, 2022). Further, a 2018 report from the BCCDC determined that humansewage originating from multiple sources was the most likely cause of a Norovirus outbreakfrom contaminated oysters (Miller et al., 2018). A 2012 study in Bamfield Inlet, located on theWest Coast of Vancouver Island, found that human sewage was the primary source ofbacteriological contamination (Hahn, 2012). This result was indicated by microbial sourcetracking and caffeine water testing that was paired with FC concentration findings. Consideringthe recent history of human sewage contamination events, improper sewage disposal is a likelysource of current fecal contamination in shellfish harvest areas.1.3 Environmental Factors that Influence Fecal ContaminationRegardless of the source of contamination, environmental factors including precipitation,temperature, salinity, and hydrological dynamics all influence the input and dispersal of fecalcontamination into marine environments (Burkhardt et al., 2000; Lipp et al., 2001; St Laurent &Mazumder, 2014; Vitro et al., 2017).91.3.1 Precipitation and River OutflowPrecipitation has been indicated by many studies as the strongest predictor for fecal coliformconcentration in marine environments (Ackerman, D., & Weisberg, S. B., 2003; Noble et al.,2004). Existing research agrees that rainfall events are highly correlated with sewagecontamination (Eregno et al., 2016; Jalliffier-Verne et al., 2016; Shamkhali Chenar & Deng2016). Heightened precipitation increases runoff, which allows feces to enter the ocean directly,or via rivers and streams. River outflow is linked to precipitation, and has also been cited inmany studies to be one of the most important factors for determining fecal contamination(Burkhardt et al., 2000; Lipp et al., 2001). Typically, river height and flow rate are positivelycorrelated to FC concentration in estuaries. This is because increased runoff due to precipitationand snowmelt corresponds to heightened input of FCs into freshwater river systems, which inturn increases FC input into estuaries (St Laurent & Mazumder, 2014). Many papers describeclear seasonal trends in FC concentration, which are typically specific to the unique conditionsof a given site (e.g. proximity to rivers, melt dominated or rain dominated hydrological regime,seasonal temperature and precipitation patterns; Chigbu et al., 2005). Seasonal cycles incontamination are often present and usually correlated with rainfall and snowmelt, though theycan be disrupted by multi-year weather cycles such as El Niño–Southern Oscillation events(Chigbu et al., 2005). Changes in FC concentration patterns may be observed due to climatechange, in response to changes in temperature, and the volume and timing of precipitation (StLaurent & Mazumder, 2014).1.3.2 Coastline shape and tidal flushingCoastline shape can influence the retention or dispersal of fecal coliform in response to tidalflushing, as areas that are less susceptible to water exchange by tides often exhibit higher fecalcontamination (Streets & Holde, 2003). Studies of the dispersal of pollution from fish farms havefound that tidal flushing and water exchange due to currents allow for decreased contaminationwithin fish farming regions (Merceron et al., 2002). Currents and stratification of the watercolumn were found by Pommepuy et al. (2005) to be highly influential in predicting fecalconcentration in marine sites.101.3.3 Land usePrevious studies indicate the importance of land use as an impact on fecal contamination,notably, a study taking place in the Capital Regional District (CRD) of Vancouver Island in whichresidential areas exhibited the highest fecal contamination (Xu, 2018). Agricultural areas areanother common source area for marine contamination in part due to manure applicationpractices and the high levels of fecal contamination this imparts on a system, oftentimes in theform of manure runoff (Jacquemin et al., 2023). Lastly, land specific factors such as elevationand forest cover can impact runoff, drainage and contaminant transport (Vitro et al., 2017; Xu2018; Xu et al., 2019).1.4 Study OverviewIn partnership with British Columbia Center for Disease Control (BCCDC), the objective of thisstudy is to investigate and describe spatial and temporal trends in fecal contamination ofshellfish harvest areas off the eastern coast of Vancouver Island. This report provides ananalysis of fecal coliform concentration data obtained from Environment and Climate ChangeCanada in three regions with important shellfish harvest activities: Baynes Sound, ComoxHarbour and Saanich Inlet.Existing research has characterized the many factors that may influence FC concentration in agiven area. However, these factors vary with the social, environmental and topographicalconditions of a given site. This report provides a localized analysis of three important shellfishharvest sites in British Columbia by first describing the change in FC concentrations over time,and then investigating the correlation between FC concentrations and rainfall, air temperature,land use, coastline shape, streamflow and proximity to river mouths. The findings of this reportmay be used to inform industry, the BCCDC, First Nations, and other local harvesters in thestudy area, and are an important step towards predicting contamination events, informingclosure and opening of harvest sites, and assisting in the creation of future management andmitigation plans. Research has been informed by discussions with stakeholders, whoserecommendations and concerns are described in this report. Gaps in existing understanding offecal contamination in the region are included such that the needs of stakeholders can beaddressed by future research and management action.1.4.1 Study Objectives111) To assess how fecal coliform concentrations and sampling extent for each of the studysites (Saanich Inlet, Comox Harbour and Baynes Sound) have changed over time.2) To assess the influence of temperature, salinity, precipitation, streamflow, flushability,and land-use type on fecal contamination for each site.3) To make recommendations for fecal contamination management based on the factorsfound to be contributing to contamination.2. Methods2.1 Study Site Description2.1.1 LocationBaynes Sound, Comox Harbour and Saanich Inlet are located on the East Coast of VancouverIsland in British Columbia Canada (Figure 1). Baynes Sound and Comox Harbour are a part ofthe Comox Valley Regional District, on the traditional and unceded territory of the K’ómoks FirstNation. Comox Harbour is located at the outflow of the Courtenay River, between the cities ofCourtenay and Comox. Baynes Sound is directly to the south, between the mainland andDenman Island. Saanich Inlet is managed by the Cowichan Valley Regional District and theCapital Regional District, which includes the capital city of Victoria. Saanich Inlet lies within thetraditional and unceded territories of the ək̓ʷəŋən peoples represented by the Songhees andEsquimalt Nations and the W̱SÁNEĆ peoples represented by the Tsartlip, Pauquachin, Tsawout,Tseycum and Malahat Nations (District of Saanich, 2024).12Figure.1 Map representing southern Vancouver Island and the study sites Baynes Sound, Comox Harbour, and Saanich Inlet.2.1.2 ClimateThe region investigated in this study experiences a regular seasonal precipitation pattern, withincreased precipitation in Winter and Fall months, and dryer weather in the Spring and Summer.Since 1951, average temperature and precipitation in the south coast of British Columbia hasbeen increasing in all seasons (Spittlehouse, 2017).132.1.3 Sewage ManagementThe Comox Valley Regional District (CVRD) estimates that there are 9,000 septic systems inuse in rural homes within the district (Comox Valley Regional District, 2024a). It is the homeowner’s responsibility to maintain these septic systems, or hire the appropriate professional todo so (Island Health, 2024). In 2016, the CVRD Liquid Waste Management plan sought toaddress risks of failing septic systems by connecting some communities to the central sewagemanagement system (Comox Valley Regional District, 2024b). Now, the central sewage systemin proximity to Comox Harbor and Baynes sound is currently undergoing construction to rerouteraw sewage pipes to run further from the coast line (Comox Valley Sewer Conveyance Project)in an effort to prevent large-scale sewage spills into marine waters (Comox Valley RegionalDistrict, 2024c).In Saanich Inlet, action is underway to prevent improper dumping of raw sewage. In March of2024, the Saanich Peninsula Wastewater Commission mandated that waste from septic tanksbe transported to the Saanich Peninsula Wastewater Treatment Plant. The meeting minutesstate that this mandate aims to reduce unnecessary transportation of septic waste, and to rectify“the curious practice of dumping our septage in other peoples’ backyards” (Saanich PeninsulaWastewater Commission, 2024). Beyond the problem of private sewage management, the CRDis currently constructing a Long-term Biosolids Management Plan. Presently, biosolids arelandfilled at the Hartland Landfill, and land application of biosolids is considered as a part of themanagement plan, despite being banned by the CRD Board in 2011. This action is “contrary toprovincial regulatory direction”, which seeks “beneficial reuse” of biosolids, such as burning forfuel for cement manufacturing. However, due to insignificant funding, biosolids disposal inlandfills is still in practice in the Capital Regional District. The current efforts to manage sewagein the CRD reflect the fact that sewage disposal is an ongoing issue in this region, and isrelevant to our project since the land application of biosolids can result in microbial pollution ofsurface and groundwater (Oun et al., 2014).In summary, sewage management practices in our study site show potential to causecontamination, and infrastructure changes are currently underway to address concerns withboth private and central sewage management.142.2 Survey Extent AnalysisAn analysis of the survey extent was conducted in order to understand the extent of FCconcentration data available from Environment and Climate Change Canada. The number ofsamples at each site was compared across each study area over time. Sampling increased involume around 2002, and the most samples were collected at Baynes Sound for the duration ofthe study period (Figure 2).Figure 2. The number of samples taken at each study location from 1982 to 2022.The number of samples at each site was compared by season. Baynes Sound and ComoxHarbor had the most samples in Spring followed by Winter, while the majority of sampling inSaanich Inlet took place during Winter, followed by Fall (Figure 3).15Figure 3. The total number of samples taken in each season at each study location for all years.As shown in Figure 4, sampling quality, in terms of number of sites and consistency over time,was best at Baynes Sound. Saanich Inlet had a comparable number of sampling sites (149 inSaanich Inlet, 151 in Baynes Sound), however many of these sites did not have samples for theduration of the study period, even though some samples dated back to 1982. Comox Harbourhad fewer sites (67), though approximately one third of these sites had relatively consistentsampling across the study period. Results of the survey extent analysis are summarized in Table1.16Figure 4. Sampling extent and continuity at each study site. For each figure, horizontal bars represent individual sampling sites, andcells within the bars represent individual samples. The length of each bar is given by the number of samples taken at each site. Thecolor of each cell is given by the year the sample was taken, with red cells being the oldest samples (starting in 1982) and greencells being the newest (until 2022). Vertically, the number of sites per study area can be seen. Sites with the most samples and themost continuous color gradient are considered the best sampled sites. These sites were visually selected, indicated with a red bar,and displayed on the corresponding maps. Baynes Sound (A) has the most samples and sites, as well as the most sites withcontinuous temporal sampling. Comox Harbour (B) has the least number of sites, though has more samples than Saanich Inlet (C).Saanich Inlet has the least consistent temporal sampling, with the fewest number of sites that were continuously visited over theduration of the study period. The number of sites and samples for each study location is summarized in the table in the figure.17BaynesSoundComoxHarbourSaanichInletTotalNumber of sites 151 67 149 367Number of samples 17782 4841 5039 27662Samples per site (average) 118 72 34 65Number of samples1982-1992 2432 1285 1475 51921992-2002 3647 818 1055 55202002-2012 5452 1363 1407 82222012-2022 6251 1375 1102 8728Number of sites with samples1982-1992 102 48 110 2601992-2002 111 54 97 2622002-2012 112 31 78 2212012-2022 122 28 69 219Table 1. The number of sites and number of samples per site in each study area, in total and over time.2.3 Preprocessing DataPrior to data analysis, data were preprocessed in order to screen out data samples that mayskew the results of the study. For example, outliers were checked using the three-sigma criteriaor the interquartile range method. Then, three different types of plots (bar plots, box plot and lineseries plot) were created to see fluctuations and distribution of the total and mean FCconcentrations per 100mL over nearly four decades across three study sites repectively (FigureA1, A2 and A3). Three box plots also were created to see the monthly distribution of mean FCconcentration per 100 mL across three study sites from 1982 to 2022 (Figure A4). Thus, themean calculation of daily FC per 100 mL by each study site was included to manage thepresence of extreme values and enhance the comparability of observations at the selected siteswithin the same period. Each study site’s data were also aggregated by season and year fortime series analysis purposes. As a result, this analysis simplified the datasets' complexity,allowing for spatial patterns to be seen and facilitating a comparative analysis. Last but not18least, a contamination threshold was set at the mean “most probable number (MPN)” of at most14 fecal coliforms per 100 mL in water where shellfish is collected (Environment and ClimateChange Canada, 2023).2.4 Environmental Data Sources and ProcessingEnvironmental data for use in bivariable analysis with fecal coliform data was obtained frommultiple sources, as detailed below.2.4.1 Climate DataPrecipitation and temperature data was obtained from the Pacific Climate Impacts Consortium(PCDS; BC Station Data, n.d.). For Baynes Sound and Comox Harbour, data was obtained fromfour weather stations for each study area. For Saanich Inlet, nine weather stations were utilized.Before analyzing these two climate factors, if data were missing for certain days, the recordeddata from the previous day was used to replace these missing values, maintaining continuityand completeness in the dataset. To analyze temperature, the mean daily temperature for thegiven period was calculated. For the precipitation analysis, data was grouped based on whetherthe weather stations were on or off the coast, as some PCDS weather stations were near thecoast and some were further inland. This categorization allowed for consideration of howlocation influences the relationship between precipitation and fecal contamination.2.4.2 River DataFor streamflow, data was obtained from the Government Canada Water Office (Government ofCanada, 2024). Streamflow data was available for 6 rivers within the study region, with onestreamflow data station for each of these rivers. These are Cowichan River and ShawniganRiver in Saanich Inlet, Nile Creek and Tsable River in Baynes Sound, and Tsolum River andPuntledge River in Comox Harbour.In order to assess the relationship between precipitation and FC for selected sites near thestream mouths, precipitation data was taken from the weather station closest to the samplesites. This precipitation data is from the same source as the data used for the all-siteprecipitation analysis, BC station data PCDS (BC Station Data, n.d.). This analysis was limitedby gaps in the precipitation data due to non-continuous monitoring.192.4.3 Flushability DataFlushability is the potential of a coastal region to clean pollution with tidal water movement. Forthe geographic regions that encompass FC concentration data, the characteristics of eachsample site were examined to evaluate the flushability of the site. A corresponding score wasassigned to indicate each sample site's presumed flushability (see Figure A5). The scale rangeswere set from 1 to 4; a score of 1 indicates low flushability, a score of 2 indicates relatively lowflushability, a score of 3 indicates relatively high flushability, and a score of 4 indicates highflushability. Sample sites in open waters close to shorelines received high scores as these areasallow for better exchange and dilution of pollutants, leading to high flushability. Areas with lessflushability, such as partially enclosed bays, received lower scores.2.5 Statistical Analysis2.5.1 Spatial and Temporal AnalysisAggregated data was examined individually by study site on a seasonal and yearly basis totrace contamination and its persistence and changes over time. Data visualization was used tounderstand and identify specific trends and anomalies. Therefore, two box plots were created toanalyze the trend of FC concentrations: one for seasonal variations and another for annualtrends. These box plots visualized the trend and spread of contaminations and identifiedoutliers. A contamination threshold line was included in these box plots to determine the extentof fecal contamination by comparing FC concentrations to the contamination threshold.2.5.2 Comparison with Environmental FactorsTo identify key environmental factors influencing FC concentration, the direct pairwisecorrelation of all environmental metrics (x) and FC concentration (y) was calculated.2.5.2.1 TemperatureFC data and climate data were compared to study the relationship between temperature and FCconcentration. This was accomplished using values for mean daily temperature and FCconcentrations. The correlation between the FC concentration and the mean daily temperatureduring a period of time was assessed. This analysis showed how temperature changes mightrelate to FC concentration, providing insights into the relationship between temperature and20precipitation fluctuations and FC concentration. However, the current analysis did not considerpossible temporal lag between temperature and FC concentration.2.5.2.2 PrecipitationFC concentration data was compared with climate data to assess the relationship betweenprecipitation and FC concentration. The correlation between precipitation and FC concentrationfor each group was plotted to explore how rainfall affects FC concentration differently in coastalversus inland areas.2.5.2.3 Streamflow and Precipitation Near River MouthsThe correlation between streamflow and FC concentration was calculated for selected samplesites near the six river mouths. The selected sample sites were grouped into positions based onrelative distance from the river mouth, as shown in Figure 5 (position distances in metersindicated in Figures 13-23). The relationship between streamflow and FC concentration wasfound for all of the samples within each position, and for each of these sites individually. Thiswas done to determine if rivers are transporting fecal coliforms. Only contaminated samples(those samples with FC > 14/100mL) were used in the river analysis.Figure 5. Example of position made by grouping sample sites, for Puntledge River in Comox Harbour. Note that positions 5 and 6are a subset of sites within positions 2 and 3, and that Puntledge River and Tsolum River merge to outflow at the same location.For each of these sites and positions, the correlation between precipitation and FCconcentration was calculated as well. The relationship between precipitation and FC21concentration was examined in order to determine if precipitation could explain fecalcontamination in sample sites near the river when streamflow could not.2.5.2.4 FlushabilityEarly exploration of FC concentration data revealed that contaminated sites appeared to occurmore frequently in areas with an enclosed coast line shape. It was posited that the coastlineshape and thus the susceptibility of a region to tidal flushing may impact FC concentrations.Specifically, areas with bays may have limited flushability and show higher FC levels, whileregions without bays were expected to have more flushing and lower FC concentrations. To testthis hypothesis systematically, a rating system was developed to visually evaluate theflushability in each study site. After establishing the scores of flushability, results were illustratedusing box plots in order to compare FC concentrations across regions with high, relatively high,relatively low and low flushability.2.5.2.5 Land UseThe aim of these methods was to compare the relative correlation between the various land useclasses and the values observed at the end point of a river that said land use areas couldplausibly relate to. These methods were generated with the following assumptions.1) River Intersection: The longer a particular river segment intersects with a particular landcover class, the more the FC concentration of that river segment is related to that landcover class.2) Distance Weighting: Land cover classes and river segments further away from the mouthof the river are less related to end-point FC concentrations than land cover areas closerto the end point.Based on these assumptions, the following equation was generated with respect to each landcover classification. This analysis was conducted with the intention of determining whether thestrength of the relationship between land cover class and the fecal coliform values obtained forthe end of the river differed based on the land cover classification of interest. However, thisanalysis was limited to Saanich Inlet, which was the only study area that had complete coverageof land cover polygons in the land cover data utilized. The data was obtained from the Data BCcatalog and is titled “Non Legal Planning Features - Current - Polygon” (2000). The land cover22classifications from this dataset have a spatial resolution of 250m. This dataset is the result ofvectorization of raster data from landsat 5 and landsat 7 satellites. However, it should be notedthat this dataset is circa 2000, which should be considered as a limitation for this land coveranalysis (DataBC, 2000).LandCoverAssociation represents the estimated relationship between a specific land coverclass and fecal coliform levels in the river. Lengthi represents the length of the ith segment thatgoes into the land cover equation. Distancei represents the euclidean distance from the ithsegment from a river mouth. FCrm represents the fecal coliform value at the river mouth and n isthe number of river segments associated with a particular land cover class.In ArcGIS Pro, points were created at the end points of rivers with averaged values fromsampling sites within 400m. Land cover polygons were then spatially joined to rivers andassociated with the river end point for that particular river. An intersection was performed todetermine the length (m) that the river passed through a given land cover polygon. Next, a nearfunction was performed to determine the euclidean distance from a river endpoint to themidpoint of a given river segment. A weighted fecal coliform calculation was then calculated forevery land cover class by grouping all river segments by land cover class as an input into theLandCoverAssociation equation.3. Results3.1 Spatial and Temporal Description of FCsThe frequency of extreme FC concentration levels is decreasing overall, but there are stillregularly contamination levels above the contamination threshold at all three study sites, asseen in Figure 6. However, for the majority of testing after 2009, the FC concentration at BaynesSound is below the threshold line.232425Figure 6. Average monthly and yearly fecal coliform per 100 mL across the three study sites. The log time series plot illustrates the distribution of mean FCs per 100mL in BaynesSound, Comox Harbour, and Saanich Inlet from 1982 to 2022. The black dots represent the mean FCs per 100mL by month and year. The red line connects all the dots together. Thehole represents no data in this period. The dotted lines represent the Canadian government's established threshold: 14/100mL FC (Environment and Climate Change Canada, 2023).26Saanich Inlet and Comox Harbour have higher variability of FC concentrations in the Fall andWinter, which suggests the possibility of seasonal influences, as seen in Figure 7. BaynesSound has lower variability of FC concentrations, fewer outliers, and lower ranges across allseasons, which might indicate more stable environmental conditions or effective management.Figure 7. Seasonal variation of fecal coliform per 100mL in for the three study sites. The log box plot illustrates the seasonaldistribution of mean FC per 100mL in Baynes Sound, Comox Harbour, and Saanich Inlet over 40 years. Seasonal divisions aredefined as Winter (Dec-Feb), Spring (Mar-May), Summer (Jun-Aug), and Fall (Sep-Nov). The dotted lines represent the Canadiangovernment's established threshold: 14/100mL FC (Environment and Climate Change Canada, 2023).3.2 Climate AnalysisThe three study sites have a positive correlation between the mean of precipitation and FC per100mL near the shoreline and on the land, as seen in Figure 8. Overall, Comox Harbour showsa stronger correlation (r = 0.38), while Saanich Inlet shows the weakest correlation (r = 0.16).27There is a stronger correlation with weather stations near the shoreline than stations on land.This correlation suggests that increased rainfall contributes to higher fecal contamination.Figure 8. Correlation between fecal coliform per 100mL mean and daily precipitation mean (near the shoreline or on the land) across3 study sites. These scatterplots illustrate the relationship between the log-transformed FC per 100mL mean and thelog-transformed daily precipitation mean (near the shoreline or on the land) at Baynes Sound, Comox Harbour, and Saanich Inlet.Due to missing near shoreline data at Comox Harbour, there is an empty one on the bottom right. The dotted lines represent theCanadian government's established threshold: 14/100mL FC (Environment and Climate Change Canada, 2023). The PearsonCorrelation coefficients (r) are provided to assess the strength of the relationship, with corresponding p-values to test the statisticalsignificance. The trend lines indicate the direction and steepness of these relationships, with confidence intervals shown as shadedareas around the lines.Figure 9 shows a weak correlation between the mean logarithm of the FC per 100mL and themean logarithm of the daily temperature at all three study sites. The three study sites havedifferences in the direction of the correlation coefficients (positive at Baynes Sound and negative28at Comox Harbour and Saanich Inlet). This indicates that factors other than temperature alsosubstantially influence fecal levels in these environments.As seen in Figure 9, there is a statistically significant and negative correlation between themean logarithm of the FC per 100mL and the mean logarithm of the daily salinity at all threestudy sites. Water salinity is highest at Comox Harbour and lowest at Saanich Inlet.Figure 9. Correlation between fecal coliform per 100mL mean and daily temperature and salinity mean across 3 study sites. Thesescatterplots illustrate the relationship between the log-transformed FC per 100mL mean levels and log-transformed dailytemperature and salinity means at Baynes Sound, Comox Harbour, and Saanich Inlet. The dotted lines represent the Canadiangovernment's established threshold: 14/100mL FC (Environment and Climate Change Canada, 2023). The Pearson Correlationcoefficients (R) are provided to assess the strength of the relationship, with corresponding p-values to test the statisticalsignificance. The trend lines indicate the direction and steepness of these relationships, with confidence intervals shown as shadedareas around the lines.3.3 FlushabilityAcross the three study sites, the mean FC concentration increased as flushability decreased, asseen in Figure 10. Compared to Comox Harbour and Baynes Sound, Saanich Inlet's overall29flushability is lower, and the mean FC concentration only exceeds the threshold line when theflushability is low.Figure 10 . Comparative analysis of fecal coliform per 100mL across varying flushability in Saanich Inlet. Box plots for the logarithmof FC concentration mean were illustrated for Baynes Sound, Saanich Inlet and Comox Harbour, respectively. A red dashed linemarked the threshold set by the government at 14/100mL for FC concentration (Environment and Climate Change Canada, 2023).Range from 1 (low) to 4 (high).3.3 Land UseFor Saanich Inlet, land cover impact values, calculated using the Land Cover Association Indexwere highest for land cover categories of ‘agriculture’, ‘agricultural mixtures’, and ‘mining’(Figure 11). However, not all of the described land cover class had the same number of riversegments that went into this calculation. For example, the mining classification only covered a30small region for which the observed end point FC values could have been impacted by otherenvironmental factors. Land cover classification categories estuaries and salt water had novalues. The land use classification “Young Forest” had the highest number of associated riversegments and a slightly higher land cover association value than that of Urban (n=55). Landcover classifications in Saanich Inlet are pictured in Figure 12.Figure 11. Relative impact relationship of land cover class on FC concentrations at end point river mouths.31Figure 12. Map of land cover classifications throughout Saanich Inlet, the river network, and the values of FC concentrationsproximate to river mouths.323.4 River AnalysisVariation exists across study sites for the relationship between river streamflow and FCconcentration, and precipitation near river and FC concentration.3.4.1 Comox HarbourFor Comox Harbour, Tsolum River and Puntledge River both merge into the same river mouth,meaning the same FC concentration sample site positionings were used for both rivers. There isa positive relationship between streamflow and FC for all positions for both of these rivers, but itis generally weak, and no clear pattern is observed between distance from river mouth and anincrease in the streamflow and FC relationship, as seen in Figure 13 (Puntledge River) andFigure 14 (Tsolum River).Figure 13. Log (FC) vs log(streamflow) by sample site positioning for Puntledge River. Plots are ordered in increasing positiondistance from river mouth. Note that due to differing numbers of sites within each position, position number doesn’t necessarilycorrespond with each position's respective average distance from river mouth. The Pearson Correlation coefficients (R) are providedto assess the strength of the relationship, with corresponding p-values to test the statistical significance. The trend lines indicate thedirection and steepness of these relationships, with confidence intervals shown as shaded areas around the lines. See Figure 1 insection 2.2.2.3 for site positionings.33Figure 14. Log (FC) vs log(streamflow) by sample site positioning for Tsolum River. Plots are ordered in increasing position distancefrom river mouth. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship, withcorresponding p-values to test the statistical significance. The trend lines indicate the direction and steepness of these relationships,with confidence intervals shown as shaded areas around the lines. See Figure 1 in section 2.3.2.3 for site positionings.Precipitation data was taken from a weather station near both Tsolum and Puntledge River, soonly one precipitation and FC analysis needed to be performed. As seen in Figure 15, it wasfound that there is a moderately positive relationship between FC concentration andprecipitation for all sites except for the position closest to the river mouth, which exhibits norelationship.34Figure 15. Log (FC) vs precipitation by each position (no log for precipitation) for Comox Harbour. Ordered in increasing positiondistance from river mouth. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship, withcorresponding p-values to test the statistical significance. The trend lines indicate the direction and steepness of these relationships,with confidence intervals shown as shaded areas around the lines. See Figure 1 in section 2.3.2.3 for site positionings.3.4.2 Saanich InletSaanich Inlet has two major rivers with available streamflow data, Cowichan River andShawnigan River. For the Cowichan River, there is generally an increasingly positiverelationship between FC concentration and streamflow, with distance from the river mouth, asseen in Figure 16.35Figure 16. Log (FC) vs log(streamflow) by positions for Cowichan River. No graph made for position 4 and 5 as these only have 2and 3 observations respectively. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship,with corresponding p-values to test the statistical significance. The trend lines indicate the direction and steepness of theserelationships, with confidence intervals shown as shaded areas around the lines. See Figure A6 for site positionings.For precipitation and FC concentration by Cowichan River, the relationship between FCconcentration and streamflow generally weakens with distance, as shown in Figure 17.36Figure 17. Log (FC) vs precipitation by positions for Cowichan River. No graph made for position 4 and 5 as these only have 2 and 3observations respectively. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship, withcorresponding p-values to test the statistical significance. The trend lines indicate the direction and steepness of these relationships,with confidence intervals shown as shaded areas around the lines. See Figure A6 for site positionings.For Shawnigan River, the relationship between FC concentration and streamflow weakens withdistance, with the site nearest to the river mouth exhibiting the strongest positive relationship,and the other two further position data exhibiting a negative relationship, as shown in Figure 18.Figure 18. Log (FC) vs log(streamflow) by positions for Shawnigan River. No graph made for position 3 and 5 as this position onlyhas 1 observation. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship, withcorresponding p-values to test the statistical significance. The trend lines indicate the direction and steepness of these relationships,with confidence intervals shown as shaded areas around the lines. See Figure A5 for site positionings.37Only one sample site had precipitation data available for its sampling dates, making it difficult todetermine how distance from the river mouth impacts the relationship between precipitation andFC concentration. However, there is a strong positive relationship seen between precipitationand FC concentration for the position closest to the river mouth, as seen in Figure 19. Note thatthis relationship is not statistically significant.Figure 19. Log (FC) vs precipitation by positions for Shawnigan River. The Pearson Correlation coefficients (R) are provided toassess the strength of the relationship, with corresponding p-values to test the statistical significance. The trend lines indicate thedirection and steepness of these relationships, with confidence intervals shown as shaded areas around the lines.See Figure A5 forsite positionings.3.4.3 Baynes SoundBaynes Sound has two rivers with data, Nile Creek and Tsable River. For Nile Creek, bothsample site positions exhibit a negative relationship between streamflow and FC concentration,as seen in Figure 20. No clear trend is exhibited with regards to distance from the river mouth.38Figure 20. Log (FC) vs log(streamflow) by positions for Nile Creek. The Pearson Correlation coefficients (R) are provided to assessthe strength of the relationship, with corresponding p-values to test the statistical significance. The trend lines indicate the directionand steepness of these relationships, with confidence intervals shown as shaded areas around the lines. See Figure A8 for sitepositionings.The same negative relationship is exhibited between precipitation and FC concentration, asseen in Figure 21.Figure 21. Log (FC) vs precipitation by positions for Nile Creek. No graph made for positions 2, 4, and 5 due to insufficientobservations. The Pearson Correlation coefficients (R) are provided to assess the strength of the relationship, with correspondingp-values to test the statistical significance. The trend lines indicate the direction and steepness of these relationships, withconfidence intervals shown as shaded areas around the lines. See Figure A8 for site positionings.39Tsable River exhibits a slightly positive or negative relationship for FC concentration andstreamflow for all positions as seen in Figure 22, with no clear trend exhibited with regards todistance from the river mouth.Figure 22. Log (FC) vs log(streamflow) by positions for Tsable River. The Pearson Correlation coefficients (R) are provided toassess the strength of the relationship, with corresponding p-values to test the statistical significance. The trend lines indicate thedirection and steepness of these relationships, with confidence intervals shown as shaded areas around the lines. See Figure A7 forsite positionings.As seen in Figure 23, there is a negative relationship between precipitation and FCconcentration for all positions except position 5, where a weakly positive relationship isdisplayed.40Figure 23. Log (FC) vs precipitation by positions for Tsable River. The Pearson Correlation coefficients (R) are provided to assessthe strength of the relationship, with corresponding p-values to test the statistical significance. The trend lines indicate the directionand steepness of these relationships, with confidence intervals shown as shaded areas around the lines. See Figure A7 for sitepositionings.4. DiscussionThe variability of fecal contamination across these three study regions follows a seasonalpattern. FC contamination matches the trends in rainfall visible inside the coastal provinces, withincreased rain in fall months correlating with increased fecal contamination (You et al., 2023).These results suggest that rainfall impacts fecal contamination as runoff may incorporatepollution into water bodies during this time.4.1 Baynes SoundIn Baynes Sound, FC concentrations demonstrate only weak correlations with temperature andprecipitation, suggesting that these factors have a limited role in directly influencing fecal levels.However, there is a significant negative correlation between FC concentration and water columnsalinity, such that FC concentration increases as water column salinity decreases. This trendmay show the influence of streamflow and runoff on FC concentration, as high rainfall increases41freshwater inflow, decreasing salinity while potentially introducing fecal contaminants fromland-based sources. Additionally, current results are in support of existing literature in whichbacterial cells are more likely to be inactivated in higher salinity environments (Florini et al.,2020). A possible reason for the weak correlation with temperature is the inverse relationshipbetween rainfall and temperature typical of the Fall season. Precipitation in Baynes Soundseems to have a less pronounced effect on coliform bacteria levels compared to other sites onthe coast and the land. This could indicate that the post-dilution effect of heavy rainfall, wherebyintense rainfall initially increases but then dilutes the concentration of pollutants (Carroll et al.,2005), is more pronounced in Baynes Sound, effectively reducing fecal bacteria concentrationsover time.In Baynes Sound, FC concentration is primarily below the contamination threshold for allflushability classes except the lowest flushability, and FC concentration levels overall are lowerthan those of the other two study sites. The Baynes Sound region appears to have higherflushability than the other two study areas, so it is possible that the susceptibility of this area toexchange by currents and tides is one reason for this pattern. However, multiple other factorsdifferentiated Baynes Sound from nearby Comox Harbor, including proximity to urban areas andthe Courtenay River, and thus more investigation is required in order to a) differentiateflushability from additional environmental factors and b) specifically compare flushability acrosssites. The strong relationship between visually determined flushability and FC concentrationindicates that coastline shape and currents may play an important role in the dispersal of fecalcontamination, which is in keeping with the findings of existing literature. Future studies shouldfurther investigate this factor by utilizing more quantitative indicators for water exchange such asocean current modeling.While it has previously been acknowledged in research that urban and rural developmentadversely affect the health of watersheds feeding into Baynes Sound, there has not been aspecific analysis of the role of Nile Creek and Tsable River in transporting fecal contamination(Joughin et al., 2000). This research did not find either of these rivers to be driving forces offecal contamination. Sample site positions near Tsable River have slightly positive or slightlynegative relationships between streamflow and FC concentration, with no clear trend of anincreasingly positive relationship for sites closer to the river mouth. For these site positions nearTsable River, precipitation does not seem to be contributing to fecal contamination either, with42generally a negative relationship observed between FC concentration and precipitation. NileCreek exhibited even less of a relationship between streamflow and FC concentration, andprecipitation and FC concentration, with none of the sites near Nile Creek outflow exhibiting apositive relationship between these variables. These findings suggest that rivers andprecipitation are not driving contamination for Baynes Sounds sites near these two river mouths.Land use data was not available for this study site in the chosen land use dataset; futureresearch should utilize a different land use classification data source, such as MODIS landclassification data.4.2 Comox HarbourThe positive correlation between precipitation and FC concentration for Comox Harbour is thestrongest compared to the other two study sites. These findings are in keeping with existingliterature, in which increased precipitation corresponds with increased FC concentration(Ackerman and Weisberg, 2003; Noble et al., 2004). FC concentration exhibits a negativecorrelation with salinity, which is expected as decreased salinity corresponds with increasedprecipitation and/or streamflow. The negative correlation between temperature and FCconcentration is likely due to the fact that increased precipitation occurs in the fall and winter inthis region, when temperature averages are lower.The flushability analysis in Comox Harbor followed a similar trend to the other two study areas,in which FC concentration declines with increased flushability. However, mean FC concentrationexceeds the safety threshold for all flushability levels except high flushability.A positive relationship between streamflow and FC concentration is observed for both rivers inComox Harbour, which meet and flow together as the K'ómoks Estuary (also known as CourtenayEstuary). This positive relationship suggests that the rivers are transporting fecal coliformbacteria into these marine sites, with increased streamflow coinciding with an increased fecalcoliform load. However, the strength of the relationship does not generally increase withdecreasing distance of site position to river mouth for these rivers, suggesting that therelationship could be more complicated than just river bacteria deposits. When the relationshipof precipitation near the river mouths to FC concentration is examined, the strength variesamong the positions, with the site position closest to the river mouth exhibiting no relationship,43and the other positions exhibiting a slightly positive relationship. This suggests that streamflow,not precipitation, can explain contamination for the position closest to the estuary mouth, butthat both environmental factors could be contributing for positions farther away. Given that theestuary has a history of fecal contamination due to poor sewage management in the area, it isunsurprising that streamflow is driving contamination (ECL Envirowest Consultants Limited,2000).Land use data was not available for this study site in the chosen land use dataset; futureresearch should utilize a different land use classification data source, such as MODIS landclassification data.4.3 Saanich InletLike Comox Harbour, FC concentrations in Saanich Inlet are negatively correlated withtemperature and salinity and positively correlated with precipitation. In Saanich Inlet, FCconcentrations increase with temperature and reach a maximum concentration when thetemperature is around twenty degrees Celsius, and then decrease. This result partiallycoincides with the results of a previous study in which FC concentrations increased withincreasing temperature and were highest at the optimal temperature of twenty-five to thirtydegrees Celsius (Cho, 2016). The negative correlation with salinity is consistent with other sites.Saanich Inlet is enclosed from the open ocean for the entirety of the study region, and thus doesnot have any sites that are considered high flushability. As observed in the other two studyregions, fecal concentrations decrease with increased flushability. The low and relatively lowcategories have significantly higher FC concentrations compared to the relatively high category,which is in keeping with expectations regarding coastal flushing and FC concentration, as wellas the observed pattern at the other two study sites. Notably, the range of FC concentrationvalues in each flushability category in Saanich Inlet is larger than the other sites, especially therelatively low category. The wide range of FC concentration values for each flushability levelmay imply unpredictability in the relationship between flushability and FC concentration.The results of this analysis indicate that, at least for the region of Saanich Inlet, Agriculturalareas, Agricultural Residential Mixtures, and Mining land use classes have the greatestrelationship with high levels of fecal contamination. However, as the utilized land use dataset iscirca 2000, some of the land use classes may have become out of date and may poorly44describe the relationship with more recent fecal coliform values. Future analysis should considertaking MODIS land cover data for 2001 and 2010, and using these more complete datasets tonot only obtain land use relationships relevant to all three monitoring sites but also to separatelyanalyze data before and after 2005 to compare fecal coliform values against land cover valuesmore appropriate for their temporal positioning. Additionally, this particular land use analysisdoes not consider the relationship between the observed values and other environmentalvariables such as streamflow or precipitation. In order to augment this analysis, considerationshould be placed as to how far fecal coliforms travel through rivers, how this varies with streamflow, and whether the strength of the observed land cover relationships are consistent whencompleted for the other two study areas of interest. Ultimately, this initial land cover analysisindicates the potential importance of Agricultural areas, Agricultural Residential mixtures, andMining land use classes, however, as there were only three river segments impacted by Miningland use area following the given methods, this particular trend should be observed in moredetail before drawing conclusions.For sample site positions near Cowichan River, there is generally a stronger relationshipbetween FC concentration and streamflow sites at positions further away from the river mouth.The relationship between precipitation and fecal contamination for positions near the CowichanRiver mouth decreases in strength with distance from the river mouth, suggesting thatprecipitation can better explain contamination than streamflow for sites near the CowichanRiver, in the form of runoff from terrestrial land into the marine waters. This is also the case forShawnigan River, which exhibits a strong relationship between precipitation and FCconcentration for the sample site position closest to the river mouth, though there is also apositive relationship between streamflow and FC concentration here. Positions further from theriver mouth exhibit a negative relationship between streamflow and FC concentration.Due to a lack of precipitation data near Shawnigan River, it is difficult to determine the extent towhich precipitation versus streamflow is driving contamination here. The Cowichan WatershedBoard research has directly tested Cowichan River for fecal contamination, and found highcontamination in the river at times. Testing for the source of these fecal coliforms has foundthem to be primarily human or bovine, with the river being used for human recreation as well astreated sewage outflow (Cowichan Watershed Board, 2024). No formal research has beenconducted on the role of Shawnigan River in marine contamination.455. ConclusionThis study sought to characterize patterns in Fecal Coliform (FC) concentrations off the coast ofVancouver Island for the purpose of understanding and managing fecal contamination ofshellfish harvest areas. The analysis utilizes FC concentration samples in three study siteslocated in Saanich Inlet, Comox Harbour and Baynes Sound, with sample dates spanning from1982 to 2022.The temporal analysis of fecal contamination reveals a strong seasonal trend in whichsignificantly elevated FC concentrations are observed in the Fall at each study site. The highrainfall experienced during the Fall in this region is expected to be the reason for this temporalassociation. Comparison of FC concentration to precipitation reveals that increased precipitationcorresponds to increased FC concentrations, corroborating the previous expectation.Temperature shows a weaker correlation with FCs than precipitation, though there is someassociation between high temperatures and low FC concentrations. This could be a product ofseasonal patterns in which warm temperatures are associated with low precipitation in summertime.One possible mechanism for elevated FCs after increased precipitation is the input of FCs intowater via rivers and streams. A spatial analysis of the data was conducted to check forassociations between proximity and streamflow of river mouths and contamination. It is foundthat for six major rivers with streamflow data available, there are four rivers that generallydemonstrated a positive relationship between FC concentration and streamflow for sites nearriver mouths, but this relationship doesn’t necessarily increase in strength with decreasingdistance from the sample sites to the river mouth. For the selected sites across the six rivers,precipitation and FC concentration have a positive relationship for all rivers except those inBaynes Sound, with the Saanich Inlet rivers exhibiting an increase in the strength of thisrelationship with decreasing distance from sample site to river mouth. This could suggest thatprecipitation drives FC concentration more than streamflow for sites near land. In order to betterassess how rivers could be driving fecal contamination, streamflow data should be collected formore rivers than the six assessed here.The correlation analysis of FC concentration and land cover class reveal a potential relationshipbetween the types of land cover upstream of river mouths and fecal levels. Fecal levels show46the greatest effect from domestic agricultural combinations, mining, and agriculture. Althoughthis analysis does not indicate the strength of the relationship between land cover classificationand resultant FC concentration, this analysis does indicate differences in relative impact of landuse classification on fecal contamination depending on the observed land cover mixtures.Further analysis should be undertaken in order to better understand the statistical correlationbetween each of these separate land use classifications and resulting fecal contamination.Overall, it should be considered that fecal coliforms do ultimately arise from a source, andfurther investigation into the relationship between land cover classification and fecalcontamination could provide insight into trends around these sources.Ultimately, this analysis of FC concentration data was not able to detect single point sources ofcontamination, though fecal coliform concentrations exceeding contamination guidelines wereobserved across all study sites and study years. Future analysis of microbial contaminationshould use additional sampling beyond FC concentration in order to distinguish between humanand animal sources. The GEMSTONE project led by researchers at UBC and the BCCDC is anexample of ongoing work in this region to identify sources of contamination, utilizinggenomic-derived technology to identify origins of fecal contamination (Genome British Coumbia,2024). Discussion with stakeholders and investigation of current sewage management practicessuggest that future work should focus on improved monitoring of sewage management. Sewagemanagement is a complex issue with a multitude of political and financial contingencies, thoughcontinued focus on planning and funding sewage infrastructure and regulatory projects issupported by the findings of this study. The results of our study lead us to recommend 1)increased regulation and monitoring of sewage infrastructure, 2) alternative sampling methodsto identify sources of contamination, and 3) continued monitoring of FC concentration patternsin conjunction with the specific environmental factors in this region. These actions will supportthe overall aim of maintaining the longevity of shellfish harvesting enterprises, improving thehealth of the marine environment, protecting Indigenous People’s access to traditionalharvesting sites, and promoting human health and safety through maintenance of clean marineenvironments.47AcknowledgementsThank you, Micheal Lee and Lorraine McIntyre of the BCCDC for their guidance and supportthroughout this project. Thank you to our Teaching Assistant, Christina Draeger, for hercontinued feedback and assistance, and to Micheal Lipsen and Sara Harris for their work incoordinating ENVR400. Ron Hein of Coast Mountain Earth Sciences provided us with acomprehensive background in sewage management on Vancouver Island. Thank you to TimWenmen of Environment and Climate Change Canada for background on river outflow andenvironmental monitoring. Thank you to Alex Munro and other representatives from the BCShellfish Growers association for sharing industry perspectives.48Appendix49Figure A1. Temporal evolution of FC concentrations per observation across the 3 study sites. The log bar plot shows thefluctuations in the number of total FC concentrations per 100mL over nearly four decades in (a) Baynes Sound, (b) Comox Harbour,and (c) Saanich Inlet, with the red line indicating the warning level of log(FC) = 14. The Canadian government has established amaximum level of 14/100mL FC presence to serve as a standard (Environment and Climate Change Canada, 2023). Peaks abovethis line mean periods of elevated fecal contamination.50Figure A2. Average yearly fecal coliform per 100 mL across the three study sites. The log box plot illustrates the distribution of meanfecal coliform (FC) per 100mL in Baynes Sound, Comox Harbour, and Saanich Inlet from 1982 to 2022. Outliers are represented asa dot. The dotted lines represent the Canadian government's established threshold: 14/100mL FC (Environment and ClimateChange Canada, 2023).51Figure A3. Average yearly fecal coliform per 100 mL across the three study sites. The yearly time series plot illustrates thedistribution of log-transformed mean fecal coliform per 100 mL in Baynes Sound, Comox Harbour, and Saanich Inlet from 1980 to2022. The dotted lines represent the Canadian government's established threshold (14/100 mL FC; Environment and ClimateChange Canada, 2023).52Figure A4. Average monthly fecal coliform per 100 mL across the three study sites from 1982 to 2022. The dotted lines representthe Canadian government's established threshold: 14/100mL FC (Environment and Climate Change Canada, 2023). From April toAugust, the fecal coliform per 100 mL at the three study sites consistently remained below the safety threshold. However, inNovember, the FC concentrations surpassed the safety threshold across all locations.53Figure A5. Assessment of Presumed Flushability at Comox Harbour. Range from 1(low) to 4 (high). Low flushability means higherFC retention; high flushability indicates higher FC dilution.54Figure A6. Sample site positioning for Shawnigan River.Figure A7. Sample site positioning for Cowichan River. Multiple maps due to position 7, 8, and 9 encompassing positions 2,3 and 6.55Figure A8. Sample site positioning for Tsable River.Figure A9. Sample site positioning for Nile Creek.56Figure A11. ArcGIS Pro Model Builder flow used to associate land cover areas with the river objects running through them, calculate the length of that association, and determineeuclidean distance from their output fecal coliform point.57Figure A12. ArcGIS Model Builder flow used to create aggregated end of river points containing averaged values of fecal coliform from the surrounding fecal coliform monitoring sites.Fecal coliform monitoring locations and river features are spatially joined with a proximity of 400 meters in order to only select rivers proximal to fecal coliform monitoring sites. Pointswere generated representing the end of the objects using the feature vertices to points tool. Average values were then calculated for each end of the river point using a series ofcalculate field, summary statistics, and dissolve operations.58ReferencesAckerman, D., & Weisberg, S. B. (2003). Relationship between rainfall and beach bacterialconcentrations on Santa Monica Bay beaches. Journal of water and health, 1(2), 85-89.BC Station Data. BC Station Data | Pacific Climate Impacts Consortium. (n.d.).https://www.pacificclimate.org/data/bc-station-dataBelsky, A. J., Matzke, A., & Uselman, S. (1999). Survey of livestock influences on stream andriparian ecosystems in the western United States. Journal of Soil and waterConservation, 54(1), 419-431.Berg G, Dahling DR, Brown GA, Berman D.1978.Validity of fecal coliforms, total coliforms, andfecal streptococci as indicators of viruses in chlorinated primary sewage effluents. ApplEnviron Microbiol36:.https://doi.org/10.1128/aem.36.6.880-884.1978British Columbia Ministry of Agriculture and Food. (2022). Sector Snapshot 2022 SeafoodPrimary Production and Processing. Gov.bc.ca.https://www2.gov.bc.ca/assets/gov/farming-natural-resources-and-industry/agriculture-and-seafood/statistics/industry-and-sector-profiles/sector-snapshots/af_sector_snapshots_seafood.pdfBritish Columbian. (n.d.). Current Streamflow Conditions and Flood Forecast Modeling.https://www2.gov.bc.ca/gov/content/environment/air-land-water/water/drought-flooding-dikes-dams/river-forecast-centre/current-streamflow-conditions-and-flood-forecast-modelingBritish Columbian. (n.d.). Land Use Planning Spatial Data.https://www2.gov.bc.ca/gov/content/industry/crown-land-water/land-use-planning/spatial-dataBurkhardt III, W., Calci, K. R., Watkins, W. D., Rippey, S. R., & Chirtel, S. J. (2000). Inactivationof indicator microorganisms in estuarine waters. Water Research, 34(8), 2207-2214.Carroll, S., Hargreaves, M., & Goonetilleke, A. (2005). Sourcing faecal pollution from onsitewastewater treatment systems in surface waters using antibiotic resistance analysis.Journal of Applied Microbiology, 99(3), 471-482.Chigbu, P., Gordon, S., & Tchounwou, P. B. (2005). The seasonality of fecal coliform bacteriapollution and its influence on closures of shellfish harvesting areas in Mississippi Sound.International journal of environmental research and public health, 2(2), 362-373.59Cho, K. H., Pachepsky, Y. A., Kim, M., Pyo, J., Park, M. H., Kim, Y. M., ... & Kim, J. H. (2016).Modeling seasonal variability of fecal coliform in natural surface waters using themodified SWAT. Journal of Hydrology, 535, 377-385.Comox Valley Regional District. (2024a). Septic System Education.https://www.comoxvalleyrd.ca/septicComox Valley Regional District. (2024b). Comox Valley Regional District Sewer Extension SouthDraft Addendum – Summary Report.https://hdp-ca-prod-app-comoxvalley-engage-files.s3.ca-central-1.amazonaws.com/3517/0493/4508/20240110_Draft_Addendum_Summary_FINAL.pdfComox Valley Regional District. (2024c). Comox Valley Sewer Service Liquid WasteManagement Plan. https://www.comoxvalleyrd.ca/LWMP.Das, O., Lekshmi, M., Kumar, S., & Bhusan Nayak, B. (2022). Incidence of norovirus in tropicalseafood harboring fecal indicator bacteria. Marine Pollution Bulletin, 150, 110777.https://doi.org/10.1016/j.marpolbul.2019.110777Data BC (2000). Non Legal Planning Features - Current [Shapefile].https://catalogue.data.gov.bc.ca/dataset/non-legal-planning-features-current-polygonDistrict of Saanich. (2024). Indigenous Relations. Saanich.https://www.saanich.ca/EN/index.html#d=21&m=3&y=2024&v=monthECL Envirowest Consultants Limited. (2000). Courtenay River Estuary Management Plan.Prepared for Fisheries and Oceans Canada, Nanaimo, B.C.https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/314594.pdfEnvironment and Climate Change Canada (2023) Canadian Environmental SustainabilityIndicators: Shellfish harvest area water quality. Consulted on Month day, year. Availableat:https://www.canada.ca/en/environment-climate-change/services/environmental-indicators/shellfishharvest-area-water-quality.html.Environmental Monitoring and Analysis Branch. (2019). Meteorological Monitoring Sites .https://catalogue.data.gov.bc.ca/dataset/meteorological-monitoring-sitesEregno, F. E., Tryland, I., Tjomsland, T., Myrmel, M., Robertson, L., & Heistad, A. (2016).Quantitative microbial risk assessment combined with hydrodynamic modelling toestimate the public health risk associated with bathing after rainfall events. Science of60the Total Environment, 548-549, 270–279.https://doi.org/10.1016/j.scitotenv.2016.01.034Fleming, T. B. (2019). Health, risk, and environmental justice for Indigenous shellfish harvestersin British Columbia, Canada (Doctoral dissertation, University of Saskatchewan)Florini, S., Shahsavari, E., Ngo, T., Aburto-Medina, A., Smith, D. J., & Ball, A. S. (2020). Factorsinfluencing the concentration of fecal coliforms in oysters in the River BlackwaterEstuary, UK. Water, 12(4), 1086.Genome British Columbia. (2024, March 25) From Poop to Proof: GEMSTONE Project Aims toFlush Out Source of Marine Fecal Pollution. Genome British Columbia.https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/reference_list_electronic_sources.htmlGovernment of Canada. (2022). Public Health Notice: Outbreak of norovirus and gastrointestinalillnesses linked to raw oysters from British Columbia.https://www.canada.ca/en/public-health/services/public-health-notices/2022/outbreak-norovirus-gastrointestinal-illness-linked-raw-oysters-british-columbia.htmlGovernment of Canada. (2024). Water Level and Flow - Environment Canada.https://wateroffice.ec.gc.ca/mainmenu/real_time_data_index_e.htmlHahn, M. (2012). Community of Bamfield Conceptual Study for Wastewater Treatment. Santec.https://www.acrd.bc.ca/cms/wpattachments/wpID278atID1346.pdfHarwood, V. J., Brownell, M., Wang, S., Lepo, J., Ellender, R. D., Ajidahun, A., ... & Flood, C.(2009). Validation and field testing of library-independent microbial source trackingmethods in the Gulf of Mexico. Water Research, 43(19), 4812-4819.Islam, M. S., & Tanaka, M. (2004). Impacts of pollution on coastal and marine ecosystemsincluding coastal and marine fisheries and approach for management: a review andsynthesis. Marine pollution bulletin, 48(7-8), 624-649.Island Health. (2024). Sewerage & Subdivision.https://www.islandhealth.ca/learn-about-health/environment/sewerage-subdivisionJacquemin, S. J., Birt, J., Senger, Z., Axe, B., Strang, B., Ewing, C., Kinney, B., & Newell, S. E.(2023). On the potential for reconstructed wetlands to remediate fecal coliform loading inan agricultural watershed. Hydrobiologia, 850(18), 3879-3891.https://doi.org/10.1007/s10750-022-05078-261Jalliffier-Verne, I., Heniche, M., Madoux-Humery, A.-S., Galarneau, M., Servais, P., Prévost, M.,& Dorner, S. (2016). Cumulative effects of fecal contamination from combined seweroverflows: Management for source water protection. Journal of EnvironmentalManagement, 174, 62–70. https://doi.org/10.1016/j.jenvman.2016.03.002Joughin B., C. Bruels, & O. Pinho. (2000). Baynes Sound Stewardship Initiatives, April 1,1999-May 31, 2000 : Final Report. Prepared for Environment Canada, Ministry ofFisheries.https://publications.gc.ca/collections/collection_2017/eccc/En40-892-2000-eng.pdfLipp, E. K., Kurz, R., Vincent, R., Rodriguez-Palacios, C., Farrah, S. R., & Rose, J. B. (2001).The effects of seasonal variability and weather on microbial fecal pollution and entericpathogens in a subtropical estuary. Estuaries, 24, 266-276.Merceron, M., Kempf, M., Bentley, D., Gaffet, J. D., Le Grand, J., & Lamort‐Datin, L. (2002).Environmental impact of a salmonid farm on a well flushed marine site: I. Current andwater quality. Journal of Applied Ichthyology, 18(1), 40-50.Miller, A., Cumming, E., & McIntyre, L. (2018). Executive Summary of the EnvironmentalTransmission of Norovirus into Oysters. BCCDC.http://www.bccdc.ca/resource-gallery/Documents/Guidelines%20and%20Forms/Guidelines%20and%20Manuals/Health-Environment/ETNO%20Executive%20Summary.pdfNoble, R. T., Lee, I. M., & Schiff, K. C. (2004). Inactivation of indicator micro‐organisms fromvarious sources of faecal contamination in seawater and freshwater. Journal of appliedmicrobiology, 96(3), 464-472.Oun, A., Kumar, A., Harrigan, T., Angelakis, A., & Xagoraraki, I. (2014). Effects of biosolids andmanure application on microbial water quality in rural areas in the US. Water, 6(12),3701-3723.Petrovich, C. (2022). Investigators search for culprit behind norovirus outbreak in B.C. oysters.CBC News.https://www.cbc.ca/news/canada/british-columbia/oysters-norovirus-bc-1.6452571Pettibone, G. W., Irvine, K. N., & Monahan, K. M. (1996). Impact of a ship passage on bacterialevels and suspended sediment characteristics in the Buffalo River, New York. Waterresearch, 30(10), 2517-2521.Pommepuy, M., Hervio-Heath, D., Caprais, M.P., Gourmelon, M., Saux, J.C.L., Guyader, F.L.(2005). Fecal Contamination in Coastal Areas: An Engineering Approach. In: Belkin, S.,62Colwell, R.R. (eds) Oceans and Health: Pathogens in the Marine Environment. Springer,Boston, MA. https://doi.org/10.1007/0-387-23709-7_14River Forecast Centre. (2023). COFFEE MODEL FORECAST OF DISCHARGES FORVANCOUVER ISLAND.WATERSHEDShttp://bcrfc.env.gov.bc.ca/fallfloods/coffee/VI.PDFSaanich Peninsula Wastewater Commission (2024). Report to Capital Regional District BoardMeeting of Wednesday, March 13, 2024.https://www.crd.bc.ca/docs/default-source/crd-document-library/committeedocuments/saanichpeninsulawastewatercommission/20240321/spwwc2024-03-21agendapkg.pdf?sfvrsn=aca5a4ce_4Shamkhali Chenar, S., & Deng, Z. (2016). Environmental indicators for human norovirusoutbreaks. International Journal of Environmental Health Research, 27(1), 40–51.https://doi.org/10.1080/09603123.2016.1257705Soueidan, J., Warren, A., Pearson, M., & Montie, E. W. (2021). A changing estuary:Understanding historical patterns in salinity and fecal coliform levels in the May River,SC. Marine Pollution Bulletin, 168, 112384.Spittlehouse, D. L. (2017). Long-term daily air temperature and precipitation record for the LakeCowichan area. Prov. BC, Victoria. BC Tech. Rep. 112. www. for. gov. bc.ca/hfd/pubs/Docs/Tr/Tr112. htm.St Laurent, J., & Mazumder, A. (2014). Influence of seasonal and inter-annualhydro-meteorological variability on surface water fecal coliform concentration undervarying land-use composition. Water Research (Oxford), 48, 170-178.https://doi.org/10.1016/j.watres.2013.09.031Steets, B. M., & Holden, P. A. (2003). A mechanistic model of runoff-associated fecal coliformfate and transport through a coastal lagoon. Water Research, 37(3), 589-608.The Sewerage System Regulation Improvement Coalition. (2009). Reforming the Regulation ofBC’s Sewerage Systems: An Urgent Need to Protect Public Health. SSRIC.https://www.elc.uvic.ca/wordpress/wp-content/uploads/2014/08/SSR-Reform-Submission-Mar4.09-FINAL.pdfVitro, K. A., BenDor, T. K., Jordanova, T. V., & Miles, B. (2017). A geospatial analysis of land useand stormwater management on fecal coliform contamination in north carolina streams.63The Science of the Total Environment, 603-604, 709-727.https://doi.org/10.1016/j.scitotenv.2017.02.093Water quality target. Cowichan Watershed Board. (2024, April 3).https://cowichanwatershedboard.ca/water-quality-target/Windom, H. L. (1992). Contamination of the marine environment from land-based sources.Marine Pollution Bulletin, 25(1-4), 32-36.Xu, K. (2018). Spatial and temporal analysis of the distribution of bacterial contamination innearshore areas of Southern Vancouver Island (Doctoral dissertation).Xu, K., Valeo, C., He, J., & Xu, Z. (2019). Climate and land use influences on bacteria levels instormwater. Water, 11(12), 2451.You, S., Huang, X., Xing, L., Lesperance, M., LeBlanc, C., Moccia, L. P., ... & Zhang, X. (2023).Dynamics of fecal coliform bacteria along Canada's coast. Marine Pollution Bulletin, 189,114712You, S., Huang, X., Xing, L., Lesperance, M., LeBlanc, C., Moccia, L. P., Mercier, V., Shao, X.,Pan, Y., & Zhang, X. (2023). Dynamics of fecal coliform bacteria along Canada's coast.Marine Pollution Bulletin, 189, 114712-114712.https://doi.org/10.1016/j.marpolbul.2023.114712Zhu, Z., Broersma, K. & Mazumder, A. Model Assessment of Cattle and Climate Impacts onStream Fecal Coliform Pollution in the Salmon River Watershed, British Columbia,Canada. Water Air Soil Pollut 215, 155–176 (2011).https://doi.org/10.1007/s11270-010-0467
Report
eng
Unreviewed
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Undergraduate
University of British Columbia. ENVR 400
Spatial and Temporal Indicators of High Fecal Coliform Concentrations at Three Sites With Marine Shellfish Harvesting Activity on Vancouver Island
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