Abstract
Fecal pollution of surface water is a pervasive problem that negatively affects waterbodies concerning both public health and ecological functions. Current assessment methods monitor fecal indicator bacteria (FIB) to identify pollution sources using culture-based quantification and microbial source tracking (MST). These types of information assist stakeholders in identifying likely sources of fecal pollution, prioritizing them for remediation, and choosing appropriate best management practices. While both culture-based quantification and MST are useful, they yield different kinds of information, potentially increasing uncertainty in prioritizing sources for management. This study presents a conceptual framework that takes separate human health risk estimates based on measured MST and E. coli concentrations as inputs and produces an estimate of the overall fecal impairment risk as its output. The proposed framework is intended to serve as a supplemental screening tool for existing monitoring programs to aid in identifying and prioritizing sites for remediation. In this study, we evaluated the framework by applying it to two primarily agricultural watersheds and several freshwater recreational beaches using existing routine monitoring data. Based on a combination of E. coli and MST results, the proposed fecal impairment framework identified four sites in the watersheds as candidates for remediation and identified temporal trends in the beach application. As these case studies demonstrate, the proposed fecal impairment framework is an easy-to-use and cost-effective supplemental screening tool that provides actionable information to managers using existing routine monitoring data, without requiring specialized expertize.
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References
An XL, Wang JY, Pu Q, Li H, Pan T, Li HQ, Pan FX, Su JQ (2020) High-throughput diagnosis of human pathogens and fecal contamination in marine recreational water. Environ Res 190. https://doi.org/10.1016/j.envres.2020.109982
Aw TG, Sivaganesan M, Briggs S, Dreelin E, Aslan A, Dorevitch S, Shrestha A, Isaacs N, Kinzelman J, Kleinheinz G, Noble R, Rediske R, Scull B, Rosenberg S, Weberman B, Sivy T, Southwell B, Siefring S, Oshima K, Haugland R (2019) Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C). Water Res 156:465–474. https://doi.org/10.1016/j.watres.2019.03.014
Ballesté E, Demeter K, Masterson B, Timoneda N, Sala-Comorera L, Meijer WG (2020) Implementation and integration of microbial source tracking in a river watershed monitoring plan. Sci Total Environ 736. https://doi.org/10.1016/j.scitotenv.2020.139573
Baughn AD, Malamy MH (2004) The strict anaerobe Bacteroides fragilis grows in and benefits from nanomolar concentrations of oxygen. Nature 427(6973):441–444. https://doi.org/10.1038/nature02285
Boehm AB, Graham KE, Jennings WC (2018) Can we swim yet? Systematic review, meta-analysis, and risk assessment of aging sewage in surface waters. Environ Sci Technol 52(17):9634–9645. https://doi.org/10.1021/acs.est.8b01948
Caldwell JM, Levine JF (2009) Domestic wastewater influent profiling using mitochondrial real-time PCR for source tracking animal contamination. J Microbiol Methods 77(1):17–22. https://doi.org/10.1016/j.mimet.2008.11.007
Cao Y, Raith MR, Griffith JF (2015) Droplet digital PCR for simultaneous quantification of general and human-associated fecal indicators for water quality assessment. Water Res 70:337–349. https://doi.org/10.1016/j.watres.2014.12.008
Cao Y, Sivaganesan M, Kelty CA, Wang D, Boehm AB, Griffith JF, Weisberg SB, Shanks OC (2018) A human fecal contamination score for ranking recreational sites using the HF183/BacR287 quantitative real-time PCR method. Water Res 128:148–156. https://doi.org/10.1016/j.watres.2017.10.071
Chigor VN, Ozochi CA, Umoh VJ (2019) Microbial Freshwater Pollution and the Associated Risks. Niger J Microbiol 33(1), 4597–610
Cyterski M, Brooks W, Galvin M, Wolfe K, Carvin R (2013) Virtual Beach 3: User ’ s Guide Virtual Beach 3: User ’ s Guide. December, 1–83. https://www.epa.gov/sites/production/files/2014-01/documents/vb3_manual_final.pdf
DeFlorio-Barker S, Wing C, Jones RM, Dorevitch S (2018) Estimate of incidence and cost of recreational waterborne illness on United States surface waters. Environ Health: A Glob Access Sci Sour 17(1):1–10. https://doi.org/10.1186/s12940-017-0347-9
Dila DK, Corsi SR, Lenaker PL, Baldwin AK, Bootsma MJ, McLellan SL (2018) Patterns of host-associated fecal indicators driven by hydrology, precipitation, and land use attributes in great lakes watersheds. Environ Sci Technol 52(20):11500–11509. https://doi.org/10.1021/acs.est.8b01945
Drovetski SV, O’Mahoney M, Ransome EJ, Matterson KO, Lim HC, Chesser RT, Graves GR (2018) Spatial organization of the gastrointestinal microbiota in urban Canada Geese. Sci Rep 8(1):1–10. https://doi.org/10.1038/s41598-018-21892-y
Dufour A (2021) A short history of methods used to measure bathing beach water quality. J Microbiol Methods 181:106134. https://doi.org/10.1016/j.mimet.2021.106134
Dufour AP (1984) Bacterial indicators of recreational water quality. Can J Public Health 75(1):49–56
EGLE (2022) Water Quality and Pollution Control in Michigan 2022 Sections 303(d), 305(b), and 314 Integrated Report. 303(5), 1–93.
Fleisher JM, Fleming LE, Solo-Gabriele HM, Kish JK, Sinigalliano CD, Plano L, Elmir SM, Wang JD, Withum K, Shibata T, Gidley ML, Abdelzaher A, He G, Ortega C, Zhu X, Wright M, Hollenbeck J, Backer LC (2010) The BEACHES study: health effects and exposures from non-point source microbial contaminants in subtropical recreational marine waters. Int J Epidemiol 39(5):1291–1298. https://doi.org/10.1093/ije/dyq084
Greaves J, Stone D, Wu Z, Bibby K (2020) Persistence of emerging viral fecal indicators in large-scale freshwater mesocosms. Water Res X 9:100067. https://doi.org/10.1016/j.wroa.2020.100067
Green HC, Haugland RA, Varma M, Millen HT, Borchardt MA, Field KG, Walters WA, Knight R, Sivaganesan M, Kelty CA, Shanks OC (2014) Improved HF183 quantitative real-time PCR assay for characterization of human fecal pollution in ambient surface water samples. https://doi.org/10.1128/AEM.04137-13
Green H, Weller D, Johnson, S Michalenko E (2019) Microbial source-tracking reveals origins of fecal contamination in a recovering watershed. In Water (Vol. 11, 10). https://doi.org/10.3390/w11102162
Haas CN Rose JB, Gerba CP (2014) Quantitative Microbial Risk Assessment. Wiley. https://doi.org/10.1002/9781118910030
Hancock DD, Rice DH, Herriott DE, Besser TE, Ebel ED, Carpenter LV (1997) Effects of farm manure-handling practices on Escherichia coli O157 prevalence in cattle. J Food Prot 60(4):363–366. https://doi.org/10.4315/0362-028X-60.4.363
Hart JJ, Jamison MN, McNair JN, Woznicki SA, Jordan B, Rediske RR (2023a) Using watershed characteristics to enhance fecal source identification. J Environ Manag 336:117642. https://doi.org/10.1016/j.jenvman.2023.117642
Hart JJ, Tardani RA, Ruetz CR, Rediske RR (2023b) Seems fishy: environmental DNA impacts on sketa22 quality control in salmonidae dominated waterbodies using qPCR and ddPCR. Environ Res Commun 5(5):051008. https://doi.org/10.1088/2515-7620/acd513
Harwood VJ, Staley C, Badgley BD, Borges K, Korajkic A (2014) Microbial source tracking markers for detection of fecal contamination in environmental waters: relationships between pathogens and human health outcomes. FEMS Microbiol Rev 38(1):1–40. https://doi.org/10.1111/1574-6976.12031
Health Canada (2012) Guidelines for Canadian Recreational Water Quality, Third Edition. Water, Air and Climate Change Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario. (Catalogue No H129-15/2012E)
Health Canada (2023) Guidelines For Canadian recreational water quality: indicators of fecal contamination. https://www.canada.ca/en/health-canada/services/publications/healthy-living/recreational-water-quality-guidelines-indicators-fecal-contamination.html
Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Colston BW (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83(22):8604–8610. https://doi.org/10.1021/ac202028g
Hinojosa J, Green J, Estrada F, Herrera J, Mata T, Phan D, Pasha AB MT, Matta A, Johnson D, Kapoor V (2020) Determining the primary sources of fecal pollution using microbial source tracking assays combined with land-use information in the Edwards Aquifer. Water Res 184. https://doi.org/10.1016/j.watres.2020.116211
Jamieson RC, Joy DM, Lee H, Kostaschuk R, Gordon RJ (2005) Resuspension of sediment-associated Escherichia coli in a natural stream. J Environ Qual 34(2):581–589. https://doi.org/10.2134/jeq2005.0581
Jamison MN (2022a) Improving the characterization of fecal contamination in southeast michigan water bodies through microbial source tracking modification. [Master’s thesis, Oakland University]
Jamison MN, Hart JJ, Szlag DC (2022b) Improving the identification of fecal contamination in recreational water through the standardization and normalization of microbial source tracking. ACS ES&T Water. https://doi.org/10.1021/acsestwater.2c00185
Jentes J (2000) How to win back the beaches. Twine Line -Ohio Sea Grant 22(3):1–4
Kildare BJ, Leutenegger CM, McSwain BS, Bambic DG, Rajal VB, Wuertz S (2007) 16S rRNA-based assays for quantitative detection of universal, human-, cow-, and dog-specific fecal bacteroidales: a Bayesian approach. Water Res 41(16):3701–3715. https://doi.org/10.1016/j.watres.2007.06.037
Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, Bushman FD, Knight R, Kelley ST (2011) Bayesian community-wide culture-independent microbial source tracking. Nat Methods 8(9):761–763. https://doi.org/10.1038/nmeth.1650
Kollarcikova M, Faldynova M, Matiasovicova J, Jahodarova E, Kubasova T, Seidlerova Z, Babak V, Videnska P, Cizek A, Rychlik I (2020) Different bacteroides species colonise human and chicken intestinal tract. Microorganisms 8(10):1–14. https://doi.org/10.3390/microorganisms8101483
McLellan SL, Eren AM (2014) Discovering new indicators of fecal pollution. Trends Microbiol 22(12):697–706. https://doi.org/10.1016/j.tim.2014.08.002
Michigan Public Health Code and Rule 323.1062(1), (1994)
Mieszkin S, Yala JF, Joubrel R, Gourmelon M (2010) Phylogenetic analysis of Bacteroidales 16S rRNA gene sequences from human and animal effluents and assessment of ruminant faecal pollution by real-time PCR. J Appl Microbiol 108(3):974–984. https://doi.org/10.1111/j.1365-2672.2009.04499.x
Nguyen KH, Senay C, Young S, Nayak B, Lobos A, Conrad J, Harwood VJ (2018) Determination of wild animal sources of fecal indicator bacteria by microbial source tracking (MST) influences regulatory decisions. Water Res 144:424–434. https://doi.org/10.1016/j.watres.2018.07.034
Pell AN (1997) Manure and microbes: public and animal health problem. J Dairy Sci 80(10):2673–2681. https://doi.org/10.3168/jds.S0022-0302(97)76227-1
Penakalapati G, Swarthout J, Delahoy MJ, McAliley L, Wodnik B, Levy K, Freeman MC (2017) Exposure to animal feces and human health: a systematic review and proposed research priorities. Environ Sci Technol 51(20):11537–11552. https://doi.org/10.1021/acs.est.7b02811
Pendergraph DP, Ranieri J, Ermatinger L, Baumann A, Metcalf AL, DeLuca TH, Church MJ (2021) Differentiating sources of fecal contamination to wilderness waters using droplet digital pcr and fecal indicator bacteria methods. Wilderness Environ Med 32(3):332–339. https://doi.org/10.1016/j.wem.2021.04.007
Petersen F, Hubbart JA (2020) Physical factors impacting the survival and occurrence of escherichia coli in secondary habitats. Water (Switz) 12(6):1–15. https://doi.org/10.3390/w12061796
Petterson S, Grøndahl-Rosado R, Nilsen V, Myrmel M, Robertson LJ (2015) Variability in the recovery of a virus concentration procedure in water: implications for QMRA. Water Res 87:79–86. https://doi.org/10.1016/j.watres.2015.09.006
Rabinovici SJM, Bernknopf RL, Wein AM, Coursey DL, Whitman RL (2004) Economic and health risk trade-offs of swim closures at a Lake Michigan Beach. Environ Sci Technol 38(10):2737–2745. https://doi.org/10.1021/es034905z
Ryu H, Griffith JF, Khan IUH, Hill S, Edge TA, Toledo-Hernandez C, Gonzalez-Nieves J, Domingoa JS (2012) Comparison of gull feces-specific assays targeting the 16S rRNA Genes of Catellicoccus marimammalium and Streptococcus spp. Appl Environ Microbiol 78(6):1909–1916. https://doi.org/10.1128/AEM.07192-11
Safaie A, Weiskerger CJ, Nevers MB, Byappanahalli MN, Phanikumar MS (2021) Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach. Water Res 190:116671. https://doi.org/10.1016/j.watres.2020.116671
Santo Domingo JW, Bambic DG, Edge TA, Wuertz S (2007) Quo vadis source tracking? Towards a strategic framework for environmental monitoring of fecal pollution. Water Res 41(16):3539–3552. https://doi.org/10.1016/j.watres.2007.06.001
Shanks OC, Atikovic E, Blackwood AD, Lu J, Noble RT, Domingo JS, Seifring S, Sivaganesan M, Haugland RA (2008) Quantitative PCR for detection and enumeration of genetic markers of bovine fecal pollution. Appl Environ Microbiol 74(3):745–752. https://doi.org/10.1128/AEM.01843-07
Shenhav L, Thompson M, Joseph TA, Briscoe L, Furman O, Bogumil D, Mizrahi I, Pe’er I, Halperin E (2019) FEAST: fast expectation-maximization for microbial source tracking. Nat Methods 16(7):627–632. https://doi.org/10.1038/s41592-019-0431-x
Sinigalliano C, Kim K, Gidley M, Yuknavage K, Knee K, Palacios D, Bautista C, Bonacolta A, Lee HW, Maurin L (2021) Microbial source tracking of fecal indicating bacteria in coral reef waters, recreational waters, and groundwater of saipan by real-time quantitative PCR. Front Microbiol 11:1–20. https://doi.org/10.3389/fmicb.2020.596650
Soller JA, Schoen ME, Bartrand T, Ravenscroft JE, Ashbolt NJ (2010) Estimated human health risks from exposure to recreational waters impacted by human and non-human sources of faecal contamination. Water Res 44(16):4674–4691. https://doi.org/10.1016/j.watres.2010.06.049
Steinbacher SD, Savio D, Demeter K, Karl M, Kandler W, Kirschner AKT, Reischer GH, Ixenmaier SK, Mayer RE, Mach RL, Derx J, Sommer R, Linke R, Farnleitner AH (2021) Genetic microbial faecal source tracking: rising technology to support future water quality testing and safety management. Österreichische Wasser- Und Abfallwirtsch 73(11–12):468–481. https://doi.org/10.1007/s00506-021-00811-y
Stevenson AH (1953) Studies of bathing water quality and health. Am J Public Health 43(5:1):529–538. https://doi.org/10.2105/ajph.43.5_pt_1.529
Tomer MD, Porter SA, Boomer KMB, James DE, Kostel JA, Helmers MJ, Isenhart TM, McLellan E (2015) Agricultural conservation planning framework: 1. developing multipractice watershed planning scenarios and assessing nutrient reduction potential. J Environ Qual 44(3):754–767. https://doi.org/10.2134/jeq2014.09.0386
Unno T, Staley C, Brown CM, Han D, Sadowsky MJ, Hur HG (2018) Fecal pollution: new trends and challenges in microbial source tracking using next-generation sequencing. Environ Microbiol 20(9):3132–3140. https://doi.org/10.1111/1462-2920.14281
US EPA (1986) EPA’s Ambient Water Quality Criteria for Bacteria – 1986. U.S. Environmental Protection Agency: Washington, DC. EPA440/5-84-002
US EPA (2011) Using microbial source tracking to support TMDL development and implementation. 1–64
US EPA (2012) Recreational water quality criteria. U. S. environmental protection agency, 1–69
US EPA (2019) Office of water method 1696: characterization of human fecal pollution in water by HF183/BacR287 TaqMan ® Quantitative Polymerase Chain Reaction (qPCR) Assay i. EPA Off Water 821:2–19.
Von Wulffen J, Sawodny O, Feuer R, Takors R, Löffler M, Simen J, Ederer M, Lischke J, Kunz S, Rieß O, Schäferhoff K, Sprenger G, Trachtmann N (2016) Transition of an anaerobic Escherichia coli culture to aerobiosis: Balancing mRNA and protein levels in a demand-directed dynamic flux balance analysis. PLoS One 11(7):1–17. https://doi.org/10.1371/journal.pone.0158711
Wade TJ, Arnold BF, Schiff K, Colford JM, Weisberg SB, Griffith JF, Dufour AP (2022) Health risks to children from exposure to fecally-contaminated recreational water. Plos One 17(4):e0266749. https://doi.org/10.1371/journal.pone.0266749
Wade TJ, Calderon RL, Sams E, Beach M, Brenner KP, Williams AH, Dufour AP (2006) Rapidly measured indicators of recreational water quality are predictive of swimming-associated gastrointestinal illness. Environ Health Perspect 114(1):24–28. https://doi.org/10.1289/ehp.8273
Wang D, Silkie SS, Nelson KL, Wuertz S (2010) Estimating true human and animal host source contribution in quantitative microbial source tracking using the Monte Carlo method. Water Res 44(16):4760–4775. https://doi.org/10.1016/j.watres.2010.07.076
Wapnick CM, Harwood VJ, Singleton T, Morrison G, Staley C, Staley ZR (2009) Application of the bacteria decision-support tool in the hillsborough river watershed. Proc Water Environ Fed 2009(6):307–328. https://doi.org/10.2175/193864709793958282
Zhang Q, Gallard J, Wu B, Harwood VJ, Sadowsky MJ, Hamilton KA, Ahmed W (2019) Synergy between quantitative microbial source tracking (qMST) and quantitative microbial risk assessment (QMRA): a review and prospectus. Environ Int 130:104703. https://doi.org/10.1016/j.envint.2019.03.051
Acknowledgements
We wish to thank the Macomb County Health Department for sample collection in the beach monitoring case study. We would like to thank Michael Vu, Nicholas Castle, and Josie Kuhlman for conducting initial analysis at Oakland University. We would like to thank Michigan Department of Environment, Great Lakes, and Energy through the 319 Nonpoint Source Grant 2018-0021 and the Beaches and Environmental Assessment and Coastal Health Act Grant Number: 2021-7210; Grand Valley State Universities Presidential Research Grant; and The West Michigan Air & Waste Management Association’s individual scholarship for funding this project. This work was done in partial fulfillment of requirements for a Master of Science in Biology at the Robert B. Annis Water Resources Institute.
Author Contributions:
JJH: Conceptualization, Funding Acquisition, Methodology, Investigation, Formal Analysis, Data Curation, Visualization, Writing - Original Draft, Writing - Review and Editing. MNJ: Methodology, Investigation, Formal Analysis, Data Curation, Writing - Original Draft, Writing - Review and Editing. AMP: Formal Analysis, Visualization, Writing - Review and Editing. JNM: Formal Analysis, Visualization, Writing - Review and Editing. DCS: Funding Acquisition, Writing - Review and Editing. RRR: Funding Acquisition, Methodology, Supervision, Writing - Review and Editing.
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Hart, J.J., Jamison, M.N., Porter, A.M. et al. Fecal Impairment Framework, A New Conceptual Framework for Assessing Fecal Contamination in Recreational Waters. Environmental Management 73, 443–456 (2024). https://doi.org/10.1007/s00267-023-01878-x
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DOI: https://doi.org/10.1007/s00267-023-01878-x