Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds
Surface water environments are inherently heterogenous, and little is known about variation in microbial water quality between locations. This study sought to understand how microbial water quality differs within and between Virginia ponds. Grab samples were collected twice per week from 30 sampling...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-03-01
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| Series: | Journal of Food Protection |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0362028X23067121 |
| _version_ | 1797788434690998272 |
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| author | Claire M. Murphy Daniel L. Weller Reza Ovissipour Renee Boyer Laura K. Strawn |
| author_facet | Claire M. Murphy Daniel L. Weller Reza Ovissipour Renee Boyer Laura K. Strawn |
| author_sort | Claire M. Murphy |
| collection | DOAJ |
| description | Surface water environments are inherently heterogenous, and little is known about variation in microbial water quality between locations. This study sought to understand how microbial water quality differs within and between Virginia ponds. Grab samples were collected twice per week from 30 sampling sites across nine Virginia ponds (n = 600). Samples (100 mL) were enumerated for total coliform (TC) and Escherichia coli (EC) levels, and physicochemical, weather, and environmental data were collected. Bayesian models of coregionalization were used to quantify the variance in TC and EC levels attributable to spatial (e.g., site, pond) versus nonspatial (e.g., date, pH) sources. Mixed-effects Bayesian regressions and conditional inference trees were used to characterize relationships between data and TC or EC levels. Analyses were performed separately for each pond with ≥3 sampling sites (5 intrapond) while one interpond model was developed using data from all sampling sites and all ponds. More variance in TC levels were attributable to spatial opposed to nonspatial sources for the interpond model (variance ratio [VR] = 1.55) while intrapond models were pond dependent (VR: 0.65–18.89). For EC levels, more variance was attributable to spatial sources in the interpond model (VR = 1.62), compared to all intrapond models (VR < 1.0) suggesting that more variance is attributable to nonspatial factors within individual ponds and spatial factors when multiple ponds are considered. Within each pond, TC and EC levels were spatially independent for sites 56–87 m apart, indicating that different sites within the same pond represent different water quality for risk management. Rainfall was positively and pH negatively associated with TC and EC levels in both inter- and intrapond models. For all other factors, the direction and strength of associations varied. Factors driving microbial dynamics in ponds appear to be pond-specific and differ depending on the spatial scale considered. |
| first_indexed | 2024-03-13T01:36:29Z |
| format | Article |
| id | doaj.art-0aa46e4fcebc4eaca1f1ed2ebeb2cc4d |
| institution | Directory Open Access Journal |
| issn | 0362-028X |
| language | English |
| last_indexed | 2024-03-13T01:36:29Z |
| publishDate | 2023-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Food Protection |
| spelling | doaj.art-0aa46e4fcebc4eaca1f1ed2ebeb2cc4d2023-07-04T05:08:03ZengElsevierJournal of Food Protection0362-028X2023-03-01863100045Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between PondsClaire M. Murphy0Daniel L. Weller1Reza Ovissipour2Renee Boyer3Laura K. Strawn4Department of Food Science and Technology, Virginia Tech, Blacksburg, VA 24061, USADepartment of Food Science and Technology, Virginia Tech, Blacksburg, VA 24061, USA; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY USADepartment of Food Science and Technology, Virginia Tech Seafood Agricultural Research and Extension Center, Hampton, VA 23669, USADepartment of Food Science and Technology, Virginia Tech, Blacksburg, VA 24061, USADepartment of Food Science and Technology, Virginia Tech, Blacksburg, VA 24061, USA; Corresponding author at: Department of Food Science and Technology, Virginia Tech, 1230 Washington Street, SW, Blacksburg, VA 24061, USA.Surface water environments are inherently heterogenous, and little is known about variation in microbial water quality between locations. This study sought to understand how microbial water quality differs within and between Virginia ponds. Grab samples were collected twice per week from 30 sampling sites across nine Virginia ponds (n = 600). Samples (100 mL) were enumerated for total coliform (TC) and Escherichia coli (EC) levels, and physicochemical, weather, and environmental data were collected. Bayesian models of coregionalization were used to quantify the variance in TC and EC levels attributable to spatial (e.g., site, pond) versus nonspatial (e.g., date, pH) sources. Mixed-effects Bayesian regressions and conditional inference trees were used to characterize relationships between data and TC or EC levels. Analyses were performed separately for each pond with ≥3 sampling sites (5 intrapond) while one interpond model was developed using data from all sampling sites and all ponds. More variance in TC levels were attributable to spatial opposed to nonspatial sources for the interpond model (variance ratio [VR] = 1.55) while intrapond models were pond dependent (VR: 0.65–18.89). For EC levels, more variance was attributable to spatial sources in the interpond model (VR = 1.62), compared to all intrapond models (VR < 1.0) suggesting that more variance is attributable to nonspatial factors within individual ponds and spatial factors when multiple ponds are considered. Within each pond, TC and EC levels were spatially independent for sites 56–87 m apart, indicating that different sites within the same pond represent different water quality for risk management. Rainfall was positively and pH negatively associated with TC and EC levels in both inter- and intrapond models. For all other factors, the direction and strength of associations varied. Factors driving microbial dynamics in ponds appear to be pond-specific and differ depending on the spatial scale considered.http://www.sciencedirect.com/science/article/pii/S0362028X23067121Escherichia coliFSMAMicrobial water qualityProduce Safety RuleRepresentative sampleWater testing |
| spellingShingle | Claire M. Murphy Daniel L. Weller Reza Ovissipour Renee Boyer Laura K. Strawn Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds Journal of Food Protection Escherichia coli FSMA Microbial water quality Produce Safety Rule Representative sample Water testing |
| title | Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds |
| title_full | Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds |
| title_fullStr | Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds |
| title_full_unstemmed | Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds |
| title_short | Spatial Versus Nonspatial Variance in Fecal Indicator Bacteria Differs Within and Between Ponds |
| title_sort | spatial versus nonspatial variance in fecal indicator bacteria differs within and between ponds |
| topic | Escherichia coli FSMA Microbial water quality Produce Safety Rule Representative sample Water testing |
| url | http://www.sciencedirect.com/science/article/pii/S0362028X23067121 |
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