E. coli and Coliform Bacteria Levels of Edgewood s Watershed Katie Schneider and Leslie Reed

Transcription

1 E. coli and Coliform Bacteria Levels of Edgewood s Watershed Katie Schneider and Leslie Reed Abstract Bacteria levels throughout the Lake Wingra watershed are a concern to the Lake Wingra community. Local lakes and water areas are monitored throughout the year for high levels of bacteria (including E. coli) by The Madison Department of Public Health. We sampled E. coli and total coliforms bacteria at three different sites in and around Lake Wingra during the months of October-March. The three sites include two springs on the Edgewood campus and the end of the dock on Lake Wingra. We compared our results to previous records taken by other natural science students over the past years. Our results support our hypothesis that every location s level of E. coli and bacteria will vary due to the season and the weather (rain, snow, etc.). Our results did not support our other hypothesis that spring 1 will have the highest levels of E. coli. We discuss implications and changes that we would want to make for a future study as well as the implications of our results. Introduction E. coli and coliform bacteria levels have been a big topic in Wisconsin, especially during the summer months. E. coli is a bacillus (Escherichia coli) normally found in the human gastrointestinal tract but can also be found in animals. E. coli can sometimes be pathogenic and can sometime be a threat to food safety. When ingesting water containing E. coli the health affects can be harmful including intestinal illness and flu like symptoms. These levels of E. coli are important because they affect those who come in contact with the water in different lakes around Wisconsin when swimming, boating or doing other recreational activities. Every year local beaches and lakes are closed down because of high and potentially unhealthy E. coli levels, especially the beach at Vilas Park. According to the Environmental Mentoring for Public Access and Community Tracking: the Final Report for the Impact Project R , within the last two years (-2007) there has been 102 beach closings in the city of Madison. The Madison Department of Public Health collects samples from the various beaches and watersheds once or twice a week to measure pathogenic contamination. The testing for bacteria began in the 1950 s and at that time the most common source of enteric viruses from the water was from untreated raw sewage. During this time the preferred indicator organism was fecal coliform, which is detected from E. coli testing. Indicator tests results are considered in beach closure decisions based upon the USEPA mentoring guidelines. These guidelines were developed based on epidemiological research that indicated an association between the presence of fecal coliforms, E. Coli, and enterococci group with swimming-associated gastrointestinal disease (Impact Project R p.1). The topic of E. coli and coliform bacteria is therefore very important when referring to Lake Wingra. The specific question we plan on addressing in our Watershed Sustainability Project is how the levels of E. coli and coliform bacteria change in and around Lake Wingra depending on the location of the sampling and on the current weather and month in which the sample took place. We sampled in three different sites in and around Lake Wingra: spring 1, the end of the dock from Edgewood s boardwalk (Dock Spring), and

2 spring 2. After studying the locations, we predict that spring 1 will have the highest E. coli levels because of its location. Spring one is located in a highly traffic area of both people because of the board walk, and animals. We assume because of the higher water level of the spring, more animals will be attracted to the area; therefore the conditions create a higher possibility for E. coli. We also predict that every location s levels of E. coli and bacteria will vary due to the season and the weather (rain, snow, etc.). If there is more precipitation to dilute the sample, less E. coli will be present. We hope to have a better understanding as to why the E. coli and coliform bacteria levels change at different locations and at different times of the year. Methods We sampled for E. coli in at three different sites, spring one, dock spring and spring two (see figure 1), with three empty, sealed, sterile jars over the months of October-March. The specific hypothesis we planned on testing was how the levels of E. coli and coliform bacteria change in and around Lake Wingra depending on the location of the sampling and on the current weather and month in which the sample took place. When taking the samples, it was important to make sure that there was little to no sediment in the water sample. It was also important when taking a sample from the dock that we collected our sample at the same depth each time. This means that we had to stick our arm into the water up to our elbow, unscrew the container, collect the water, and replace the lid. After the samples were taken, they were brought into the lab where they were tested with the Colilert Test Kit. The Colilert Test is used to determine the total amount of coliform and E. coli in water by recognizing the presence of enzymes in bacteria. The test utilizes nutrient indicators that produce a yellowish color when coliform is present and fluorescence when E. coli is present. The test can detect these bacteria when reagent is added to a sample and incubated for 24 hours ( We converted the numbers of coliform and E. coli into decimal numbers by the use of a conversion chart in order to graph our data. The table we used to convert our data provided the MPN (most probable number) of total coliforms or E. coli per 100 ml water sample. The purpose of graphing the data was to visually represent the levels of Coliform and E. coli in the three testing sites around the Edgewood campus. We graphed temperatures (obtained from The Weather Channel website) to show the temperature pattern over the course of the months that we took our samples. Figure 1 2

3 Results Coliform levels dropped during our last two testing dates(shown in table 2 and figure 2). Table 2 shows some data as being > This means that the Colilert Test kit cannot determine the exact value because our sample exceeds the limit. This would mean that the actual value of this sample would be something above The figure shows a decline in total coliform from November to February. The total coliform begins to rise again after February. Table 2 Total coliform levels (MPN/100 ml) in the three different tested sites over the sampled time period Oct Dec. 3 Feb. 9 Mar. 4 Spring Spring 2 > > > < Lake Wingra: Dock > > Figure 2 Change in total coliform levels (MPN/100 ml) in the three different tested sites over the sampled time period Total Coliform (MPN/100 ml) Testing Dates 3

4 Spring 1 had the highest level of E. coli out of the three sites and this occurred on December 3 rd (shown in table 3 and figure 3). Table 3 and figure 3 also show that the levels at spring 2 and at the Lake Wingra dock were fairly consistent with each other. The lowest levels of E. coli occurred during our first and last testing dates. Only an indicator Table 3 E. Coli levels (MPN/100 ml) in the three different tested sites over the sampled time period Oct Dec. 3 Feb. 9 Mar. 4 Spring Spring Lake Wingra: Dock Figure E. Coli levels (MPN/100 ml) in the three different tested sites over the sampled time period E. Coli (MPN/100 ml) Spring #1 Spring #2 Lake Wingra: Dock 0 Oct Dec. 3 Feb. 9 Mar. 4 Testing Dates 4

5 Table 4 and figure 4 are a comparative graph that shows previous E. coli levels tested at the Lake Wingra: Dock by past natural science students. Chart 4 & figure 4 show that the months of November always had the highest levels of E. coli out of the other tested months. The figure and table also shows very small levels of E. coli during the winter months. Table 4 E. Coli levels (MPN/100 ml) at Lake Wingra: Dock over the past sampling years 2005 Jan Mar Oct. Dec. Feb Lake Wingra: Dock Mar Figure 4 E. Coli levels (MPN/100 ml) at Lake Wingra: Dock over the past sampling years E. Coli (MPN/100 ml) Jan Mar Oct Dec. Feb Mar Lake Wingra: Dock Testing Dates 5

6 Figure 5 shows the average high temperatures in Madison, Wisconsin recorded by the Weather Channel in the months of October in March. The figure shows a downward slope from October to January, followed by an upward slope from January to March. January is the coldest month in Madison. Figure 5 Average high air temperatures (degrees Fahrenheit) in Madison, Wisconsin from October to March Temperature (in degrees Fahrenheit) October November December January February March Month 6

7 Discussion Our results generally supported our hypothesis that the E. coli bacteria levels would vary by location and by weather conditions. We see in that these levels of E. coli do indeed vary by location (see figure 2). Our other hypothesis about the level of E. coli varying due to weather was also supported in figure 2. Our two middle samples (November 12 th and December 3 rd ) had the highest levels of E. coli. These two days were the only days where some sort of precipitation had occurred prior and/or during our sampling. We had predicted that spring 1 would have the highest level of E. coli out of all three of our locations but we only found this to be true with our December 3 rd sample. This spike in E. coli levels on December 3 rd at spring 1 was very interesting. We noted that spring 1 was very muddy that day, and that it had been snowing all day. We feel that because it had snowed that day and that the spring was so muddy, this caused the big spike in the level because of the sediment that was present in the spring. The runoff and the snow around the spring might have also caused the spike when it entered the spring and our sample. We had also noted that there seemed to be a lot of sediment in the spring when we took our sample. This might have also caused the big spike in levels for that particular day because it was in our sample. There also might have been an animal that had been in the spring right before we took the sample on that day. This animal (such as a coyote or bird) might have left behind animal feces that would have caused the bacteria levels to rise dramatically. Looking back at table 4 and figure 4, we can see that the E. coli levels are fairly similar for each month over the past four years at the Lake Wingra Dock. November has the highest levels of E. coli during 2005, 2007 and at the dock. We believe that this is mainly due to the large numbers of animals present at the dock during this month. In the months after November, the levels of E. coli drop each year mainly due to migration and the lack of animals in the area during the winter months because of the cold weather (shown in figure 5). According to the Public Health Madison and Dance County (PHMDC), a single sample threshold of 1000 MPN/100 ml for bacterial quality at Madison beaches will shut the beach down because it is considered harmful to one s health. This number continues to change over years, and is based on constant monitoring of the E. coli levels. Based on the 1000 MPN/100 ml criteria for closing beaches in the Madison area, our samples show that on December 3 rd at both spring 1 and spring 2, levels of E. coli were high and harmful to ones health. For a future study, we would want to take more samples. These samples did occur over five months and during a variety of weather conditions. However, if we had taken more samples, we feel as though we might have better off drawing conclusions because we would have a bigger variety of results to study. This would be important because the variety of sampling dates would give a more precise conclusion for changes in E. coli levels. A variety of sampling dates would also chart the overall health of the Wingra Watershed over the course of a variety of months. It would also be helpful look closer at the temperature of the water and air during the dates sampled. If the temperature of the water and air was monitored more closely, 7

8 we could then answer the question as to how do levels of E. coli vary with respect to the water and air temperatures. We would also probably want to make changes to the actual testing process. Even though we feel as though our testing methods were fairly accurate, there are a few possible sources of error that we would want to look into changing. First of all, we would want to make sure that we took the samples in the exact same way, every time. During the winter months, it was very hard to stick our arm all the way into the water because of the ice cold water. It is quite possible that we did not stick our arm as far into the water during these winter months, which would have caused our samples to maybe be inaccurate. It was also very hard to take samples the same way every time in the springs because the springs are very shallow. We attempted to take the samples from the same place in the springs each time, but there were a few times where we had to change the location a little because of excess sediment that was present. Both of these issues could have influenced our results, and we would work on improving them if we were to do this study again. Overall, we feel as though there are ways to improve our study but we also feel as though our results show accurate information that can determine the health of the Lake Wingra watershed. References Coliform/E. coli Results in 24 Hours. (2009). Colilert. Retrieved March 11, 2009 from Final Report for the Empact Project R : Data Collection and Modeling of Enteric Pathogens, Fecal Indicators and Real-Time Environmental Data at Madison, Wisconsin Recreational Beaches for Timely Public Access to Water Quality Information. (2004). City of Madison. Retrieved March 11, 2009 from t%20report% pdf. Lorman, Jim, Edgewood College Professor Monthy Weather Averages and Records for Madison, WI (2009). The Weather Channel. Retrieved March 11, 2009 from thly/uswi0411?from=vac_dailyavg. Sorsa, Kirsit, Comments on the Impaired Beach Designation (). The Public Health Madison and Dane County. 8