Knights of Science online

Journal 2014

Table of Contents

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A BS T R A C T The objective of this experiment was to determine if Total Dissolved Solids (TDS), or the concentration of dissolved material in water, correlates to the level of the turbidity, or the murkiness of the water. At Drumlin Farms in Lincoln, MA, three ponds were selected to gather and test samples from: Bathtub, Ice, and Poultry. Water was collected and tested for turbidity and TDS, then these measurements were used to determine if there was a signifigant correlation between the two variables. It was expected that the higher the turbidity, the more turbid the water would be because water with many particles dissolved in it allow for many microorganisms to grow, clouding the water. The results showed that there was a trend that supported the hypothesis. Between each of the ponds, the TDS and turbidity conclusively increased or decreased respectively, supporting the correlation. However, because the r2

value was about 0.53, the data was not entirely conclusive. I N T R O D U C T I O N

Turbidity is the measurement the intensity of light scattered at 90 degrees as a beam of light passes through a sample of water. Turbidity is mainly affected by the amount of total suspended solids in water, such as phytoplankton, sediment from erosion, waste discharge, algae growth, runoff from construction, mining, agriculture, and urban runoff. Because turbidity is a result of substances entering a body of water, it is considered to be an effective way of determining water quality (www.lenntech.com). As a result, water turbidity is important in a manufacturing sense, especially when producing drinking water. As well as being aesthetically unappealing, excessive turbidity in drinking water may be a health concern. Turbidity can promote the regrowth of pathogens by providing food and shelter for them, leading to outbreaks of waterborne diseases. Although turbidity is not a direct cause for health concerns, there is ample evidence supporting a strong correlation between the reduction of turbidity and the removal of protozoa. Data collected in many studies in the past has also suggested that controlling turbidity in drinking water is a safeguard against pathogens and diseases (EPA, www.epa.gov). In response, The World Health Organization (WHO) has recommended turbidity levels under 1 Nephelometric Turbidity Unit (NTU) and no higher than 5 NTU for human consumption (www.lenntech.com). A higher measurement in NTU correlates to a lower measurement in centimeters less than 10 NTU is equivalent to greater than 54.7 cm.

A turbidity measurement that is too high can be harmful to aquatic life and organisms as well as humans. The suspended particles in the water absorb heat and scatter light, making the water warmer. This reduces its concentration of dissolved oxygen, decreases the amount of light that reaches farther down in water, and hinders the growth of aquatic plants (www.lenntech.com). Species that may rely on these plants, such as fish and shellfish, are then harmed as well. As aforementioned, high turbidity also may suggest that deadly bacteria is in water, which can hurt the organisms living there. In general, an excessively high turbidity measurement is harmful to most aquatic organisms, but turbidity can also indicate that essential nutrients are in the water, increasing the productivity and prosperity of life (Boyd, Water Quality: An Introduction). In some mangrove areas, high turbidity measurements are necessary in supporting certain species. For example, it can protect juvenile fish from larger predators (U.S. Fish and Wildlife Service, Decline of Submerged Plants in Chesapeake Bay). In addition, some species, such as the Vernal Pool Tadpole Shrimp, can tolerate and even flourish in muddy, highly turbid waters (Vernal Pool Tadpole Shrimp (Lepidurus Packardi)). This is because life may prosper as more essential nutrients are made available due to healthy soil and materials being washed into water by rain (www.snh.org.uk).

Finding the amount of total dissolved solids (TDS) in a body of water will indicate the amount of inorganic and organic materials dissolved in the water. The right amount of TDS will help organisms maintain a proper density and contribute beneficial nutrients into water, which will increase aquatic life (www.tdsmeter.com). Through an increase of life, such as algae and

phytoplankton, turbidity will also increase (www.snh.org.uk). In this case, a higher turbidity measurements would indicate a healthy ecosystem. However, if anything harmful found its way into the water, or algae growth got to the point of depriving other life forms of oxygen, the entire ecosystem could become unhealthy as a result of the high turbidity.

In a similar experiment that was conducted at these ponds (Evenchik and Yuen, The effect of water turbidity (cm) on water conductivity ), some of the results indicated that there was a correlation between water conductivity and water turbidity. Water conductivity is caused by and related closely to TDS. When the conductivity was 247 µS, the turbidity was 34.90 cm; when the conductivity was 494 µS, the turbidity was 51.2 cm; when the conductivity was 550 , the turbidity was 75.0 cm. Although these points cannot accurately represent all of the data, there does seem to be a trend. When there was an increase of the conductivity, meaning that the TDS was also higher, the turbidity was higher as well.

The objective of this experiment is to determine the correlation between TDS (ppm) and turbidity (cm). The independent variable is the TDS (ppm), and the dependent variable is the turbidity of the water (cm). Eight points along each pond will be randomly selected using a TI Nspire calculator, and water will be collected from each point. The turbidity will be measured using a Water Testing Equipment and Supplies turbidity tube, and the TDS of that sample will be measured using a Hanna Instruments TDS meter. Some important controlled variables include: the distance from the shore the sample is taken from (cm), the depth the sample was taken from (cm), the person doing the testing (eyesight may vary), the measuring tools used, and the data collection tools used. The hypothesis in this experiment is: If the TDS is higher, then the turbidity will also be higher, because higher TDS contributes more nutrients into the water, allowing for an increase in organism growth, which will increase turbidity (EPA, www.uri.edu). The more nutrients in the water, the more opportunity for growth there is. Organisms, such as algae, are main contributors to the turbidity, and a higher TDS promotes their survival and growth (www.lenntech.com).

The experiment will take place at Drumlin Farm in Lincoln, Massachusetts. Three of the five ponds at Drumlin Farm Bathtub Pond, Ice Pond, and Poultry Pond will be testing sites for this experiment. Poultry Pond is downhill of animal pastures, Ice Pond is surrounded by a small forest, and Bathtub Pond has dense thicket surrounding its perimeters and is located in a field. It is hypothesized that Poultry Pond will have the highest TDS and turbidity because it will most likely have the greatest amount of runoff entering its waters. The lowest measurements are hypothesized to come from Bathtub Pond, because the surrounding thicket will prevent erosion and runoff. Ice Pond is located near only a fair amount of trees, and the moderate amount of erosion this results in would cause some materials to enter the pond. Therefore, its data should fall in the middle.

Once the data is collected, Drumlin Farm can have a better understanding of how the human activities that take place on the Farm affect their aquatic life. The Farm will be able to realize the best way to control what enters their ponds in order to create the optimal living conditions for the organisms that live there. Since a higher turbidity measurement may prevent the sterilization of water using chlorine or ultraviolet rays, this makes it harder for water to be sanitized. Human activities like construction, mining, and agriculture can cause sediment to get in water through runoff during a rainstorm, and storm water can carry pollution from bridges, roads, and sidewalks (EPA, National Management Measures to Control Nonpoint Source Pollution from Urban Areas). If how the TDS specifically affects turbidity is discovered, then efforts can be made to decrease the amount of runoff and pollution that enters the water, causing the higher TDS. Ultimately, the spreading of disease will be prevented, and organisms living in bodies of water will have healthier living conditions.

M A T E RI A LS A ND M E T H O DS The effect of total dissolved solids (TDS) on turbidity of water (cm) was tested at three separate

locations at Drumlin Farm in Lincoln, MA: Bathtub Pond, Poultry Pond, and Ice Pond. To determine the exact point of sample collection along the perimeter of the pond, the center of the pond was determined. Eight numbers -one for each trial- from zero to three hundred and sixty were randomly generated on a TI Nspire cx calculator from Texas Instruments. Each of those numbers represented where the sample would be taken from in relation to the aforementioned center of the pond. The compass was used to determine the specific points at which those angles intersected with the shore. The angles for Bathtub Pond were: 16, 53, 72, 122, 146, 185, 264, and 358 degrees; for Ice Pond the angles were: 2, 3, 39, 80, 113, 287, 337, and 343 degrees; and for Poultry Pond, the angles for the sample collection were: 19, 44, 99, 100, 198, 260, 308, and 352 degrees. Those locations, 50 centimeters from the edge of the pond, were where the water samples were collected. To test the turbidity, which was tested first, the open end of the turbidity tube was placed at the sample point. The tube was filled to the top with the sample water. The turbidity (cm) was then measured by looking down from the top of the tube while the tube was slowly emptied from the valve at the bottom. A small portion of the water sample was then poured into a 50 mL beaker to measure the TDS. With the Hanna Instruments TDS meter (Figure 1), all of the instructions accompanying the device were followed to produce the most accurate response, which entailed placing one end of the meter in the water and waiting for the measurement to stabilize. Both of these measurements were recorded in the field notebooks of the scientists involved, and each of the steps were repeated first for the individual trial, and then for the separate sites.

Figure 1: Hanna Instruments HI 98311 EC/TDS/Temperature Tester (www.hydrogalaxy.com) !

R ESU L TS Table 1: The effect of TDS (ppm) on turbidity (cm) all three ponds.

TDS (ppm) Turbidity (cm)

BP Trial 1 0 107.1

BP Trial 2 14 121.0

BP Trial 3 20 85.0

BP Trial 4 14 69.8

BP Trial 5 16 60.1

BP Trial 6 14 97.8

BP Trial 7 21 53.2

BP Trial 8 14 97.2

IP Trial 1 212 121*

IP Trial 2 239 26.0

IP Trial 3 148 13.2

IP Trial 4 182 40.0

IP Trial 5 217 14.0

IP Trial 6 214 69.1

IP Trial 7 154 60.0

IP Trial 8 157 52.1

PP Trial 1 339 16.4

PP Trial 2 395 42.6

Table 2: The effect of TDS (ppm) on turbidity (cm) averages and standard deviation at each pond.

TDS (ppm) Averages

TDS (ppm) Standard Deviation

Turbidity (cm) Averages

Turbidity (cm) Standard Deviation

Bathtub 14 3.2 86.4 23.7

Ice 190 36.2 49.4 22.3

Poultry 337 68 27.7 7.6

G raph 1: The effect of TDS (ppm) on turbidity (cm) at all three ponds.

PP Trial 3 258 28.8

PP Trial 4 250 24.3

PP Trial 5 349 24.7

PP Trial 6 346 29.5

PP Trial 7 301 24.1

PP Trial 8 454 31.2

BP = Bathtub Pond

IP = Ice Pond

PP = Poultry Pond

*error

G raph 2: The effect of TDS (ppm) on turbidity (cm) at all three ponds.

Graph 1 shows the combined data collected from all the pond locations: Bathtub Pond, Ice Pond, and Poultry Pond. With an r2 value of about .53, the trend line exhibits an increase in the turbidity (cm) where there was an increase in the TDS (ppm). The r2 value indicates that there was a relatively low correlation between the two variables. In the case of turbidity, a lower measurement in centimeters means that it the overall turbidity is higher. Although the turbidity measurement decreased, causing the line to slope downwards on Graph 1, this still indicated an upward trend in the turbidity. In Graph 2, the turbidity error bars of Bathtub Pond and Ice Pond, and of Ice Pond and Poultry Pond both overlap slightly, but their averages indicate a downward trend. For TDS, no error bars overlap, and there is a clear upward trend.

Bathtub Pond, which had the lowest average TDS and turbidity (14 ppm, 86.4 cm), was surrounded by highly concentrated thorn bushes, trees, and thicket. The surrounding land was mostly flat and muddy, except for the occasionally drier, elevated Southwest and South sides of the partially frozen over pond. Poultry Pond had the highest average TDS and turbidity measurements (337 ppm, 27.7 cm). It was downhill of a busy road on its Southwest side, and it was situated closely by a farmyard that housed animals and was most likely fertilized. Ice Pond had the average TDS and turbidity levels (395 ppm, 42.6 cm) that were in the middle of the three ponds, and it was seen to be was bordered by slightly elevated ground with evenly spaced out trees.

The three outliers that affected Graph 1 were mostly caused by malfunctioning equipment. In an attempt to make the graph more accurately represent the data collected, an outlier of 121.0 cm in Trial 1 from Ice Pond was removed from the final graph. Removing this data point ultimately brought the r2 up from .44, improving the two variables correlation in this experiment. In Trial 1, a malfunctioning turbidity tube resulted in a measurement of 121.0 cm, and in Trial 2, a malfunctioning TDS meter resulted in a measurement of 0 ppm. The two other errors from Trial 1 and 2 were not removed from the data, because doing so would have decreased the r2 value.

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When the outliers were disregarded, the highest TDS recorded was 454 ppm from Trial 8 from Poultry Pond. The lowest recorded TDS was 14 ppm, shared by three trials: Trial 3 from Bathtub Pond, Trial 6 from Bathtub Pond, and Trial 8 from Bathtub Pond. The highest turbidity belonged to Trial 3 from Ice Pond with the measurement of 13.2 cm. The lowest turbidity recorded was from Trial 6 with 97.8 cm.

D ISC USSI O N This experiment was conducted to determine the correlation between total dissolved solids (TDS) and turbidity in the water of Bathtub Pond, Ice Pond, and Poultry Pond at Drumlin Farms. The hypothesis for this experiment was: If the TDS is higher, then the turbidity will also be higher, because higher TDS contributes more nutrients into the water, allowing for an increase in organism growth, which will increase turbidity (EPA, www.uri.edu). This hypothesis was supported, because as the measurement of TDS (ppm) increased the measurement of turbidity (cm) increased. The decrease in turbidity (cm) indicates a higher turbidity, because it is harder to see through the water. As the level of TDS in the water rises, the turbidity levels will also increase because of the organisms in the water (Maczulak, www.fofweb.com). As the concentrations of inorganic and organic particles in the water increased, which causes the TDS to increase, the amount of microorganisms that could grow also increased (Maczulak, www.fofweb.com). The more surface area of particles floating in the water there were, the more plant life could grow. The TDS of the ponds ranged from 0 ppm to 454 ppm, and none of the error bars overlapped for each pond. This shows that each of the ponds had a conclusively different level of TDS. This significant difference in TDS level was caused by many factors. In Poultry Pond, a fairly large road moved close to the pond, and runoff from roads and road salts caused higher TDS (www.safewater.org). The runoff from the chicken pens that were nearby, and uphill of, the pond also contributed to the high TDS levels (www.safewater.org). Ice Pond was not as close to a main road nor a chicken pen and Bathtub Pond was even further from both, so the TDS levels were significantly lower at both locations. The r2 value for this experiment was 0.528. This shows a correlation, but it is not conclusive. Although a trend was visually represented, the r2 value does not suggest a strong correlation. The measurements of TDS from one of the ponds all clustered around 15 ppm, which may have disrupted the r2 value, making the data less conclusive. In the bar graph, the TDS levels from each of the ponds were was conclusively different, increasing from Bathtub, to Ice, to Poultry Pond. The turbidity levels also decreased in the same order, showing the trend continues. Sufficient data was not collected at Drumlin farm. There were gaps in the data between the ponds, which provided uncertainty in the trend. A wider range of data, perhaps from ponds with an even greater range of TDS and turbidity, would close those gaps. Taking more samples from each site, and therefore having more data points, would eliminate errors and outliers from reducing the r2 value. Changes to the procedure may yield more accurate results. Removing the opportunity for human error would make this data more reliable, if not more conclusive. Using a meter that automatically measured the turbidity, instead of relying on the eyes of the scientist, could improve the accuracy of the turbidity readings. Also, taking the measurements in a more controlled environment, instead of trying to do so while avoiding getting caught in brambles would make the experiment more reliable. There were a few errors that may have impacted the outcome of the experiment. The turbidity tube was subject to human error and interpretation. There was some confusion over when the flow of water from the bottom of the tube should be stopped, leading to turbidity reading that may have been slightly higher or lower than they would have been otherwise. The TDS meter was also slightly faulty. When the measurement for the first trial was taken from Bathtub Pond, the turbidity meter would not move from zero, even though the level of TDS was obviously higher. This could have been caused by an error on the part of the scientists, such as not setting the meter properly, but it was more likely the result of a mechanical malfunction, because a similar error occurred during the preliminary tests. For two trials, the turbidity tube was not tall enough to measure accurately. The measurements for those trial were recorded as 121 cm, and noted that there was an error. This error occurred in trial 2 at Bathtub Pond and trial 1 at Ice Pond.

Performing this experiment raised many questions. The variation in the TDS between the ponds led to the question: What factors caused these locations to be so thoroughly different? The trees around each pond were of differing species. Does that have anything to do with the TDS or turbidity? The differences in algae growth appeared to correlate with the turbidity being higher, but an experiment could be designed and completed to prove or disprove that. A C K N O W L E D G E M E N TS

I, Addie Millman Bevis, would like, first and foremost, to thank my partner, Rachel Avram, for all her hroughout the

Catherine, our three teacher naturalists at Drumlin Farms, for guiding us through the stressful day of collecting samples. Finally, I d like to thanks everyone who helped us to edit, and make this the best it can be.

I, Rachel Alexandra Avram, would like to thank my lab partner, Addie Millman Bevis, for being extremely helpful, reliable, and flexible throughout this entire process. I also appreciate Mr. Ewins for helping us out whenever we had a question or needed advice, as it was essential to our success. I want to thank him for editing our work during the project as well. I also want to thank all of the teachers who went on the Drumlin Farm field trip and worked hard to make it run smoothly. In particular, I thank Ms. Jamison, Mr. Dwyer, and Ms. Brooks, who all were at our different testing stations. Thank you to Ms.

naturalists at Drumlin Farm for aiding us in the navigation around the farm and making sure that we all could collect data in the most efficient way possible. Another huge thank you to everyone at Drumlin Farm for allowing our class to experiment on their farm assistance and willingness to have us there.

W O R KS C I T E D Author 1: Daphne, Low Hui Xiang, Handojo Djati Utomo, and Lim Zhi Hao Kenneth. "Correlation

between Turbidity and Total Suspended Solids in Singapore Rivers." Journal of Water

Sustainability 1.3 (2011): n. pag. JWSP Online. Division of Civil Engineering, School of

Architecture and the Built Environment, Singapore Polytechnic, Dec. 2011. Web. 28 Feb.

2014.<http://www.jwsponline.com/uploadpic/Magazine/pp%20313-322%20JWS-

A013%20New.pdf>.

Hydro Galaxy. "Hanna Instruments DiST 5 Waterproof EC/TDS Temperature

Tester HI 98311 716825." Hydro Galaxy. Hydro Galaxy, 2014. Web. 13 Mar. 2014.

<http://www.hydrogalaxy.com/meters-testing-ph/combination-meters/hanna-dist-5-waterproof-

ec-tds-temperature-tester-hi-98311/>.

Maczulak, Anne. "water quality." Science Online. Facts On File, Inc. Web. 15 Apr. 2014.

<http://www.fofweb.com/activelink2.asp?ItemID=WE40&SID=5&iPin=EMBIO0187&SingleRe

cord=True>.

Safe Drinking Water Foundation. "TDS AND PH." Safewater.org. Safe Drinking Water

Foundation, n.d. Web. 12 Apr. 2014.

<www.safewater.org/PDFS/resourcesknowthefacts/TDS_AND%20_pH.pdf>.

United States. Environmental Protection Agency. Why Test Your Well Water For Turbidity?

N.p.: n.p., n.d. Print. <http://www.uri.edu/ce/wq/has/PDFs/Turbidity%20sum.pdf>

"Water Pollution." The New Book of Popular Science. 16th ed. Vol. 3. Danbury, CT: Grolier,

2006. 85. Print.

Author 2: Boyd, Claude E. (1999). Water Quality: An Introduction. The Netherlands: Kluwer Academic Publishers

Group.

"Fathead Minnow (Pimephales Promelas)." RSS. Texas Parks and Wildlife, N.d. Web. 15 Apr. 2014.

"Rivers and Their Catchments: Causes and Effects of Turbid Water." Rivers and Their Catchments:

Causes and E ffects of Turbid Water. Scottish Natural Heritage, N.d. Web. 30 Mar. 2014.

<http://www.snh.org.uk/publications/on-line/advisorynotes/22/22.htm>.

"Turbidity." Turbidity. Lenntech, N.d. Web. 02 Mar. 2014. <http://www.lenntech.com/turbidity.htm>.

United States. Environmental Protection Agency. Why Test Your Well Water For Turbidity?N.p.: N.p.,

N.d. Print. <http://www.uri.edu/ce/wq/has/PDFs/Turbidity%20sum.pdf>.

U.S. Environmental Protection Agency (EPA). Washington, D.C. "National Management Measures to

Control Nonpoint Source Pollution from Urban Areas." Chapters 7 and 8. Document No. EPA

841-B-05-004. November 2005.

"Vernal Pool Tadpole Shrimp (Lepidurus Packardi)." Beacham's Guide to the Endangered Species of

North America. Ed. Walton Beacham, Frank V. Castronova, and Suzanne Sessine. Vol. 3.

Detroit: Gale, 2001. Science in Context. Web. 15 Apr. 2014.

"What Is TDS?" - HM Digital. HM Digital, N.d. Web. 28 Jan. 2014. <http://www.tdsmeter.com/what-

is/>.

APPE NDI X

TDS (ppm) Turbidity (cm)

Trial 1 212 error 121 error

Trial 2 239 26.0

Trial 3 148 13.2

Trial 4 182 40.0

Trial 5 217 14.0

Trial 6 214 69.1

Trial 7 154 60.0

Trial 8 157 52.1

Average 190 49.4

St. Deviation 36.2 22.3

TDS (ppm) Turbidity (cm)

Trial 1 0 error 107.1 error

Trial 2 14 error 121 error

Trial 3 20 85.0

Trial 4 14 69.8

Trial 5 16 60.1

Trial 6 14 97.8

Trial 7 21 53.2

Trial 8 14 97.2

Average 14 86.4

St. Deviation 3.2 23.7

G raph 3: The effect of TDS (ppm) on turbidity (cm) at Ice Pond

G raph 4: The effect of TDS (ppm) on turbidity (cm) at Bathtub Pond Pond

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TDS (ppm) Turbidity (cm)

Trial 1 339 16.4

Trial 2 395 42.6

Trial 3 258 28.8

Trial 4 250 24.3

Trial 5 349 24.7

Trial 6 346 29.5

Trial 7 301 24.1

Trial 8 454 31.2

Average 337 27.7

St. Deviation 68.0 7.6

Table 3: The effect of TDS (ppm) on turbidity (cm) at Ice Pond

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The Effect of Type of Animal Manure on Soil Conductivity By Ezra Berg and Avi Madsen

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Table of Contents Section Author Page Abstract Berg 2 Introduction Madsen 2 Materials and Methods Berg 3 Results Madsen 7 Discussion Berg 8 Acknowledgements Berg & Madsen 10 Works Cited Berg 10 Works Cited Madsen 11

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ABSTRACT Soil in different habitats contains various levels of soil conductivity. This experiment was conducted in order to discover whether animal manure has an effect on soil conductivity, and which animals’ manure effects it the most. The procedure for this experiment was to determine and compare the soil conductivity between the cow, goat, chicken and a non inhabited field. These locations were at Drumlin Farm in Lincoln, MA. The names of the locations are Farmyard, and Overlook Field. It was expected that the manure would increase the soil conductivity at each habitat because manure makes the soil more acidic. The results of the experiment showed that only the chicken habitat had a conclusively higher soil conductivity from the non inhabited field, however, the soil conductivity increased in areas where the most manure was excreted. It was discovered that chickens have a different diet than cows and goats. Chickens are fed corn, oats, weeds, vegetables, and any bugs they can find, whereas goats and cows are fed grains and hay. Hay was found on the non inhabited field, which could be the cause for the similar soil conductivity. Vegetables are more acidic than grains, and acid increases soil conductivity, therefore, vegetables increase soil conductivity. INTRODUCTION Soil conductivity is the measure of how well soil conducts electricity and this has an effect on plant growth and health. It also correlates with particle size and soil texture because of the relationship between high soil conductivity and clay soils. (Barbosa, www.lsuagcenter.com/) Soil conductivity is measured in micro Siemens per centimeter (!S/cm) and comes from a variety of sources. The main source of conductivity is rainwater or pond and ocean water. However, it can also be increased with the addition of manure to the soil. The manure mineralizes and releases salts into the soil, therefore increasing the soil conductivity. Therefore, the correlation between types of animal manure and the soil conductivity was investigated. Prior research found a correlation was found between animal manure and soil conductivity. Taylor and Francis (http://dx.doi.org/) conducted where these researchers compared the soil conductivity of four fields that were exposed to different types animal manure. The experiment showed that fields that had been exposed to animal manure had a higher soil conductivity than those that did not. These findings support the hypothesis of this experiment as the scientists here at BBN believe that the exposure of any type of animal manure will result in higher soil conductivity than the control field, (http://dx.doi.org/) which did not have any manure based fertilizer for about a year. (Stone, Martha. Personal interview. 7 Apr. 2014.) This experiment was conducted at the fields in Drumlin Farm in Lincoln, MA, specifically, fields that are the residence of cows, chickens, goats, and no animals. These fields were

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Farmyard field, which houses cows, goats and chickens, and Overlook field which does not have any animals making it the control field. These fields will be tested to find whether there is a correlation between animal manure and soil conductivity. The hypothesis for this experiment is: If animal manure is present on a field then the soil conductivity of that field will increase because when an animal defecates, the salt that was in its feed stays in the manure and therefore increases the soil conductivity because the measure of soil conductivity is the measure of salts in a soil sample. (http://dx.doi.org/) (http://www.dpi.nsw.gov.au/) The independent variable in this experiment was the presence of animal manure and the type of animal manure. The dependent variable was the soil conductivity in all the manure and non-manure habitats. The variables that were controlled on the day of collection of data, procedure for collection, the type of probe, and the amount of soil collected. The data were collected from the fields at Drumlin Farm

This experiment can potentially help farmers buy the most effective manure to encourage crop growth. This information can also help manure producers produce the most effective manure for healthy plants and help those farmers choose the correct amount of manure to reach a desired level of soil conductivity. These data could potentially aid farmers worldwide and take the mystery out of buying different types of manure based fertilizer. MATERIALS AND METHODS Data was collected from different habitats at Drumlin Farm in Lincoln Massachusetts in order to compare the level of soil conductivity (!S/cm) with different types of manure. The habitats were Overlook field, the cow habitat at Farmyard, the goat habitat at Farmyard, and the chicken habitat at Farmyard (see pictures). At each habitat, measurements were taken at 25 different random locations. The random locations were found by laying a 15 by 9 numbered grid over each habitat, and using a TI-nspire Cx calculator to give 25 random squares on the grid. Before any data was taken from the habitats, a Drumlin Farm naturalist was asked about the soil in Overlook field and how often it is fertilized because that was presumed to be the field that is manure free. The soil at Overlook was found to be fertilized once a year and had not been fertilized since last spring so the data was not affected by that factor.

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Figure 1: Map of Drumlin Farm Data was collected from Sandpit (2), and different habitats within Farmyard (6).

Figure 2: Map of Overlook Field This is a map of randomized areas to collect data at Overlook field.

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Figure 3: Map of Farmyard cow habitat This is a map of randomized areas to collect data at the cow habitat at Farmyard.

Figure 4: Map of Farmyard goat and chicken habitat This is a map of randomized areas to collect data at the goat and chicken habitat at Farmyard.

To begin the test, a Hanna HI 98331 soil conductivity probe was put together (see figure 5), and then placed approximately 4 centimeters into the soil at one of the 25 random locations given from the TI-nspire Cx calculator. Once the Hanna HI 98331 soil conductivity probe

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received a measurement of the soil conductivity (!S/cm), the measurement of soil conductivity (!S/cm) was then read, and recorded. Once the measurement had been read, the Hanna HI 98331 soil conductivity probe was taken out of the soil. The HI 98331 soil conductivity probe was then rinsed off with distilled water so it could be used at the next location. After the last sample was taken at the habitat, a soil smudge was put into a field notebook to later observe and compare with soil smudges at other habitats. These steps were repeated for all 100 trials (25 at each habitat). Figure 5: Hanna HI 98331 conductivity probe This is a picture of the Hanna HI 98331 conductivity probe.

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RESULTS Table 1: The Effect of Animal Manure Type on Soil Conductivity

Graph 1: The Effect of Type of Animal Manure on Soil Conductivity

Graph #1 and Table #1 shows the data that was collected at Drumlin Farm. There are several trend that can easily be seen by looking at the graph. The chicken manure location had much higher soil conductivity (!S/cm) than any other location. The goat manure location was much less precise than the rest of the locations. The chicken had the highest average (0.44 ms/cm)

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and the goat field the lowest average (0.05 ms/cm). The goat habitat was very large and spread out compared to other habitats even the area that the goats mostly grazed around in (and defecated in) was very small. The chicken field at Drumlin Farm had housed the chickens all winter long and compared to other habitats was tiny. None of the sites were very precise and the cow and control had almost the exact same average and standard deviation. DISCUSSION This experiment was conducted to test the effect that manure has on soil conductivity, and also to find out if one animal species’ manure makes soil more conductive than other animal manure. The hypothesis for this experiment was: If animal manure is on a field then the soil conductivity of that field will increase because when an animal excretes, the salt that was in its feed stays in the manure and therefore increases the soil conductivity (http://dx.doi.org/). This hypothesis was supported because two of the three fields with manure on it (cow and goat habitat at Farmyard), had close to the same conductivity levels as the field with no manure on it (Overlook), but there appeared to be an increase in soil conductivity when closer to where the animals spend most of their time, which is where more manure was found, therefore it can be concluded that manure increases soil conductivity. The manure that the chickens produced caused the soil conductivity to increase to an average of 0.44 mS/cm. When measuring the conductivity around the chicken house, it was extremely high, versus when measuring the soil conductivity from further away from the chicken pen, it decreased. This was presumably due to the fact that the chickens spend a lot more time around their pen, and therefore produced more manure in that area which raised the conductivity. The chickens’ diet also had something to do with the increase in soil conductivity. Chickens are fed corn, oats, weeds, vegetables, and any bugs they can find (Martha Stone, personal communication). This is a different diet from the cows and goats at Farmyard. The diet of the chickens also is more acidic than the other animals, and higher levels of acid increases the soil conductivity (Rail, http://www.livestrong.com). The cows’ diet of hay and grains is the same as the goats’ diet. The soil conductivity is very similar in the two habitats with the cow habitat at an average of 0.07 mS/cm, and the goat habitat at an average 0.05 mS/cm, which were both much less conductive than the chicken habitat. The goat habitat had an increase in soil conductivity when closer to the barn, where the goats live and seemed to spend more time at than the rest of the habitat. This means that goat manure increases the soil conductivity. The cows, however, had a much more equal level of soil conductivity throughout the habitat, except along the edge near the forest. Taking away the data taken near the Red Pine forest because it is assumed that it affected the measurement of soil conductivity (Zoltak, http://depts.alverno.edu), the whole cow habitat had fairly equal levels of soil conductivity. The cows spend a lot more time all over the habitat, and do not stay in a single area as much (Martha Stone, personal communication), which means that more

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equal amounts of manure was spread out across the field, which explains the similar levels of conductivity within the cow habitat. The hay and grains that are fed to the goats and cows, which is then excreted onto the soil, is similar to the hay found at Overlook field (Debby, personal communication). This is the reason for the similarity in the cow, goat, and Overlook habitat. The similar hay is on all three of those fields. The chickens’ different diet is the reason for such high levels of conductivity. They excrete bugs, vegetables, and weeds which then goes into the soil and increases the soil conductivity. When food is digested, the stomach acid breaks down the food and causes the manure to be acidic. Vegetables, something that the cows and goats are not fed, are higher in acidity than grains. Acid increases the level of soil conductivity because when ions are added to soil, the conductivity increases, and acids add ions to the soil (Benoit, http://environmentalet.hypermart.net/), which is why the chicken habitat has higher soil conductivity than the other habitats. The similarity in the cow, goat, and Overlook field are shown on the bar graph as well. The error bars are all overlapping, which means that the data is similar and inconclusive. However, the chicken habitat on the graph has no overlaps and is above all the other habitats, which means that the soil conductivity is conclusively higher in the chicken habitat than the other three locations. The most precise data was collected at the cow habitat. The next most precise data was collected at Overlook and then the chicken habitat. The data collected at the goat habitat was the least precise. The only error that occurred during the testing was that there was a rock at one of the points for testing. This was easily solved by testing right next to the rock, which was about 2 feet away from the correct testing location. The field study could be improved by testing habitats that are inhabited by animals with different diets. Only one habitat stood out in the experiment, and it was the only habitat with a species that had a different diet. More conclusions could be drawn if testing soil conductivity in animal enclosures with different diets. The data collected was sufficient because the amount of trials taken at each habitat was enough to be able to accurately compare the soil conductivity of each habitat. The chicken habitat and the increase in soil conductivity when near areas with more manure is proof that the animals’ diet affects the soil conductivity. Data collection could be improved by staying away from the borders of the habitats because the data around the edges could be affected by surrounding variables, as was the cow habitat. The tests taken around the borders of the cow habitat at Farmyard could not provide data about the effect manure has on soil conductivity because the Red Pine forest’s soil was too close, and possibly was affecting the trial. For future experiments, the diet of the animals should be figured out before collecting data, and it would be interesting to test a wider variety of diets.

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ACKNOWLEDGEMENTS Avi Madsen I would like to thank my parents for helping with ideas for the experiment and editing the drafts. I would also like to thank the helpful naturalists at Drumlin Farm, especially Martha Stone and Debbie. Last of all my science teacher Ms. Svatek who helped with ideas, conducting the experiment, writing, formatting, and presenting this experiment. Ezra Berg I would like to thank my parents for going out to buy materials to make this possible and help with ideas for the experiment. I would also like to thank the naturalists at Drumlin Farm, especially Debby and Martha Stone for giving us information to use for testing, and allowing us to use their farm habitats. My science teacher Ms. Svatek is the one who made this all possible. I would like to thank her for walking us through the steps to successfully doing an experiment and also giving us permission to use materials from the science lab. We could not have done our experiment without her. WORKS CITED Ezra Berg:

Benoit, Anthony. "PH and Conductivity." PH and Conductivity. N.p., n.d. Web. 17 Apr. 2014.

<http://environmentalet.hypermart.net/env1221/phcondtds.htm>.

"Dynamics of Soil PH and Electrical Conductivity with the Application of Three Animal

Manures." Taylor and Francis. Department of Crop Sciences , Tshwane University of

Technology , Pretoria , South Africa, 27 Mar. 2012. Web. 14 Apr. 2014.

<http://www.tandfonline.com/doi/abs/10.1080/00103624.2012.653022#preview>.

Pein, David V. Hannah Soil EC & Temp Probe. Digital image. Soil PH and Conductivity

Meter Range. 2002-2014 David Von Pein, n.d. Web. 12 Mar. 2014.

<http://www.themeterman.com.au/images/hanna-soil-ec-temperature-meter-ol-13.jpg>.

Rail, Kevin. "High Acidic Foods List." LIVESTRONG.COM. LIVESTRONG.COM, 21 Oct.

2013. Web. 14 Apr. 2014. <http://www.livestrong.com/article/23346-high-acidic-foods-

list/>.

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xx, Debby. “Plants in soil at overlook.” Personal interview. 07 Apr. 2014.

xx, Stone Martha. "Chicken Feeding Habits." Personal interview. 07 Apr. 2014.

Zoltak, Wendy. "Comparisons of PH and Phosphorus Levels in Pine and Deciduous Soils."

Http://depts.alverno.edu/. Alverno College. Web. 5 Apr. 2014.

<http://depts.alverno.edu/nsmt/archive/zolt.htm>.

WORKS CITED Avi Madsen: Barabosa, Roberto N. What Is Soil Electrical Conductivity? Lsuagcenter. Lsuagcenter, n.d.

Web. 17 Apr. 2014. <https://www.lsuagcenter.com/NR/rdonlyres/E57E82A0-3B99-

4DEE-99B5-

CF2AD7C43AEF/77101/pub3185whatissoilelectricalconductivityHIGHRES.pdf>.

Eignberg, R.A,. Electrical Conductivity Monitoring of Soil Condition and Available N with

Animal Manure and a Cover Crop. Digitalcommons. Digitalcommons, n.d. Web. 17 Apr.

2014.

<http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1191&context=usdaarsfacp

ub>.

Spaulding, A.D. "The VALUE of SOIL ELECTRICAL CONDUCTIVITY and

TOPOGRAPHICAL INFORMATION for VARIABLE RATE NITROGEN APPLICATION:

FIRST ASSESSMENT." (n.d.): n. pag. Castonline. Web. 17 Apr. 2014.

<http://www.castonline.ilstu.edu/spaulding/EC-YIELD.pdf>.

Stone, Martha. Personal interview. 7 Apr. 2014.

http://www.google.com/url?q=http%3A%2F%2Fwater.usgs.gov%2Fedu%2Fph.html&sa=D&sntz=1&usg=AFQjCNEeGpSrSwOoUzEnOsUx-Og3-yJgZA

http://www.google.com/url?q=http%3A%2F%2Fwww.fi.edu%2Fguide%2Fbond%2Fphtesting.html&sa=D&sntz=1&usg=AFQjCNFeMCLMqnCQf8YV5MYLmOCZfEbeMA

http://www.google.com/url?q=http%3A%2F%2Fwww.lenntech.com%2Faquatic%2Facids-alkalis.htm&sa=D&sntz=1&usg=AFQjCNGCulbNoCRBPkoNrDYaTL-j4IBw0A

The Effect of Tree Species on soil pH in the pHorest

By: Benjamin Blackburn & Brendan Donovan

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TABLE OF CONTENTS Section Author Page(s) Abstract Blackburn 3 Introduction Blackburn 3-4 Materials & Methods Blackburn 4 Results Donovan 5-6 Discussion Donovan 6-7 Acknowledgements Blackburn & Donovan 8 Works Cited Blackburn 9 Works Cited Donovan 10-11 Appendix: Pictures Blackburn & Donovan 11-14

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ABSTRACT

Soil pH is the measurement of active hydrogen ions collected within the soil. The more hydrogen ions the more acidic the soil will be. This experiment was conducted to discover whether or not certain types of trees affect the pH of the soil and also potentially affect the growth of other surrounding plants. To conduct this experiment a soil sample was taken from under a tree with a soil auger and then tested with a Rapitest pH testing kit. The original hypothesis was: If a Red Pine tree is tested, then the soil pH will be the lowest, because in the northern forest region Red Pines need a 4.5 to 6.0 range in order to absorb enough nutrients (Rudolf, www.na.fs.fed.us). In the end there was no conclusive data found and it was not possible to determine whether or not the coniferous trees were more acidic because all of the error bars overlapped, despite the differentiating averages. INTRODUCTION

Soil pH measures how acidic soil is due to contributing factors from surrounding sources. The definition of pH is the measurement of active hydrogen (H) ions in any given substance or the power of hydrogen ions within the soil (Knapp, Brian J., and Mary Sanders, Acids, Bases, Salts, 182). The pH levels range from 1 to 14 with 14 being the most basic, 1 being the most acidic and 7 being neutral. Organisms like trees and flowers contribute hydrogen ions into the soil, making it more acidic. Most soils have a pH in the 3 to 9 range (Londo, Andrew J., John D. Kushla, and Robert C. Carter, www.lsuagcenter.com). Many scientists believe that more acidic trees tend to live where levels of pH are lower and often contribute to those conditions. The pH levels can also affect the amounts of other nutrients that a plant can absorb. The reactions caused by pH can either allow a plant to uptake more or less nutrients, ultimately leading to better or worse plant health.

This experiment was conducted at Drumlin Farm, in Lincoln, Massachusetts. Drumlin Farm is part of the Audubon Wildlife Sanctuary, a program to keep and protect natural habitats in Massachusetts. The Drumlin covers 312 acres of land and has 4 different forests from which BB&N has access to. The experiment was conducted at Hemlock forest located on the Northern part of the drumlin. When conducting the experiment it was helpful to note what signs the tree might show to signify too high or too low pH levels. If the pH levels are too high then there will be signs of deficiencies in nutrients because the pH levels can prevent the tree from receiving enough of a specific nutrient based on the amount of reaction with the soil (Alvey, Alexis, www.ccesuffolk.org). If the pH levels are too low then the tree won’t be able to grow as well because of the more acidic soil, resulting in smaller limbs and dying leaves. The pH in the soil also translates to the health of the animals and organisms around it. If a plant is consumed by an animal, then all of the nutrients in the plant will go to the animal. If the soil pH is too high or too low the plant won’t have as many essential nutrients and it will impact the health of the organism that relies on the nutrients from plants.

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The proposed experiment is to test how the type of tree affects pH levels in the soil. The objective of the experiment is to find out whether or not the type of tree actually affects the acidity of the soil that surrounds it leading to the growth or stagnation of the plant. This question was answered by collecting soil samples from soil found beneath different trees. Then the soil acidity was determined using a Rapitest pH testing kit and a chemical reagent mixed with distilled water. These results showed whether or not the tree does impact the soil. The independent variable is the type of tree that we take the soil samples from. The dependent variable for this test was the level of pH tested from the soil. Some variables that were controlled are the climate, the forest from which the experiment was conduct in, the day in which the experiment is conducted, the way in which data was collected, and the type of soil. The hypothesis states: If a red pine tree is tested then the soil pH will be the lowest because in the northern forest region red pine’s need a 4.5-6.0 range, in order to absorb enough nutrients (Rudolf,www.na.fs.fed.us).

This research will demonstrate how the type of tree is affecting the acidity of the soil that surrounds it. The volunteers from the Audubon Wildlife Sanctuary program can use this data to further help preserve the health of their plants. It will help them understand what plants can tolerate the living conditions of another plant and which can not. It is important to understand how the levels of pH affect a plant because then it is easier to help plants grow to become more healthy. This experiment will help contribute to the understanding of plant life and how each plant can affect one another. This will allow people to be able to create ideal living spaces for different species of plants and will help many societies like the Audubon Wildlife Sanctuary program preserve the natural forests. MATERIALS AND METHODS

The previously proposed experiment was conducted in Hemlock Forest. Hemlock Forest was selected because it had many different deciduous and coniferous groups of trees. To select what areas of Hemlock Forest this experiment would be conducted on it was necessary to run randomization method number 2 to select which areas the soil samples would be taken from. First and area of Hemlock forest with a dense population of one species of tree was identified. The type of trees that this experiment was conducted upon was Spruce, Ash, Oak and Red Pine. There were two areas with deciduous trees, two cites with coniferous trees and one cite where there were no trees to affect the soil pH. Then all of the surrounding trees were marked and numbered. Then all of the numbers of the marked trees were randomized with a calculator to fairly select which six trees the experiment was going to be conducted upon. After the trees were selected an auger was used to scoop a two-inch soil sample from under the tree. Then soil from the B-horizon was put in a pH test kit and mixed with distilled water and a chemical reagent. Then after a minute of letting the substance sit the substance color was compared to the acidity chart on the side of the test kit.

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RESULTS TABLE 1: The effect of tree species on soil pH

Tree Species

pH Level

Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Average St.Dev.

White Spruce 6.0 7.0 6.0 4.5 6.5 5.5 5.9 0.9

White Ash 6.0 6.5 6.5 5.5 5.5 6.0 6.0 0.4

Red Pine 6.0 4.5 6.0 6.0 5.5 5.5 5.6 0.6

White Oak 6.6 6.0 6.5 6.0 6.0 6.5 6.3 0.3

Control Run 5.5 6.5 7.0 6.0 6.5 6.0 6.3 0.5

GRAPH 1: The effect of tree species on soil pH

Graph 1 shows all of the tree species and their corresponding averages, from the data that was collected at Hemlock Forest. The graphed data shows that the type of tree species and the surrounding soil pH level did not correspond. The data collected was

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unusual; all of the error bars overlap, yet the data was still fairly precise. The only trends in the data came from the size of the error bars. The Red Pine trees, White Spruce and the control run had very large error bar sizes; these were the least precise data. From the data collected at Hemlock Forest, depicted in Graph 1, the highest average soil pH level was the same with the White Oaks and the control run (6.3). The lowest average pH level came from the Red Pine trees (5.6). The White Spruce tree was by far the least precise. The Red Pine trees and the control run error bar sizes were very similar, but the White Ash and White Oak trees were the most precise. The data as a whole was largely precise, with one very big outlier. An important observation was: there were many groves of trees that were occupied by only one species during the testing. DISCUSSION

This experiment was conducted in order to test the correlation between tree species and the soil pH. The hypothesis for this experiment states: If a red pine tree is tested then the soil pH will be the lowest because in the northern forest region red pine’s need a 4.5-6.0 range in order to absorb enough nutrients (Rudolf,www.na.fs.fed.us). This hypothesis was not supported by the results of the experiment because all of the error bars overlapped.

Based on the averages, the Red Pine trees were the most acidic, followed by the White Spruce, then White Ash, control run and finally White Oak. All of the trees tested are native to the Northeast Forest Region. Therefore, they need similar soil conditions in order to survive. All of these samples were taken from the same forest, where the soil is very similar. At each spot where data was collected at exactly 6.1 cm. below the surface, the color and texture of the soil was very similar. The soil was a dark brown and crumpled easily when touched. Hemlock Forest is located on a hill. As a result, each spot was elevated and some spots were higher than others. Also, each location was a grove that was predominantly occupied by the species that was being tested (with a few outliers). Many sources said that all of these trees have a similar need for pH so the readings will be alike, because of the similarity in the ranges, within these conditions (Rudolf,www.na.fs.fed.us).

There is definitely a connection between all of the species because the ranges are very similar, with a moderately precise range of data. The White Ash and White Oak trees were extremely precise, the control run and Red Pine trees were moderately precise, and the White Spruce trees were not precise at all. Although there was a large difference in error bar size, all of the error bars overlapped. There is no conclusion to be made from this experiment because the trees in this region need soil that is slightly acidic (4.5-6.0) in order to survive, especially the winter. Slightly acidic soil allows trees to soak up the largest amount of nutrients (Harrington, “Tree pH Ranges”). Although there are no conclusions to be made, the data is still precise. Confidence in data comes from the size of the error bars and how much outlying data there is. In this experiment there was not a lot of outlying data within each species type, therefore there is a lot of confidence.

The field study was well thought out and proved very successful in the field, and it needed little modifications. This allowed for sufficient data collection. Perhaps, if the soil was collected deeper at around 25.4 cm., this could have provided a much different range of pH levels because at this depth there is a horizon that contains much more

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nutrients that the trees absorb. Although there was confidence in the data, maybe if more samples were collected other outliers would appear.

Errors occurred very rarely throughout this experiment. The only errors that occurred were: once dropping the container with the solution, this error could have been eliminated by being more careful; rushing through the process at the end and not getting samples deep enough, and this could have been eliminated by better time management. Future ideas for this experiment are: the correlation between groves of mixed species of trees and non-mixed species on soil pH, and tree height on soil pH around the tree. This experiment, if researched again, could be improved by collecting soil samples deeper and collecting samples from a variety of forests. If this experiment was conducted on a much larger scale, it could help farmers and arborists plant their tree’s in prime locations and maintain them efficiently.

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Acknowledgements This project wouldn’t have been a success without the help from many different

people throughout the way. I would like to thank Drumlin Farm and all of its volunteers for giving their time to supervise the testing and helping to make everything run smoothly. I would also like to thank the teacher chaperones for volunteering their day to accompany us on the trip to Drumlin Farm and providing us with guidance whenever possible. And last but certainly not least I would like to thank the BB&N Middle School science department for organizing and developing the entire trip while helping each and every person with this extensive project. Without the help of all of these people this project wouldn’t have been nearly as successful and I am very thankful for their support.

Throughout the course of this experiment, from brainstorming to concluding, several people have helped my partner and I. First, I would like to thank Mrs. Larocca for teaching us about all of the different topics that we could explore and for helping us revise our experiment. Mrs. Larocca played a key role in getting the basics down for us and even guiding us through our experiment. Next, I would like to thank the entire Drumlin Farm crew for keeping the Farm in such a beautiful condition, and for their great knowledge on all the outdoor topics that came up in our many questions. Also, I would like to thank Mr. Rossiter, Ms. Bomfim and Mrs. Brooks for being in our general location and keeping watch over us and ready to help us in any way possible. Lastly, I would like to thank my entire class for making science such an amazing experience for me and also for providing my partner and I with help/advice, especially on the writing pieces. Thank you so much to everyone involved in our experiment and God Bless.

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WORKS CITED: Benjamin Blackburn: Alvey, Alexis. "Trees Tolerant of High Soil PH* (pH up to 8.2)." Www.ccesuffolk.org.

Cornell Cooperative Extension of Suffolk County, 2011. Web. Apr. 2014.

<http://ccesuffolk.org/assets/galleries/Agriculture/Commercial-Nursery-and-

Landscape-Management/Trees-Tolerant-of-High-Soil-pH-1-11.pdf>.

Knapp, Brian J., and Mary Sanders. Acids, Bases, and Salts. Danbury, CT: Grolier

Educational, 1998. Print.

Londo, Andrew J., John D. Kushla, and Robert C. Carter. “Soil pH and Tree Species

Suitability in the South.” www.lsuagcenter.com. Southern Regional

Extension Forestry, Jan. 2006. Pdf. 2014 Apr. 2.

<http://www.lsuagcenter.com/NR/rdonlyres/3E784F3F-

0B26-44E9-958D-3C31CB911EFD/69963/SoilpH.pdf

“Soil pH.” nick.mcn.org. N.p., n.d. Web. 12 Mar. 2014

"Soil pH: What It Means." Soil PH: What It Means. State University of New York

College of Environmental Science and Forestry, n.d. Web. Apr. 2014.

<http://www.esf.edu/pubprog/brochure/soilph/soilph.htm>.

Whiting, David, Carl Wilson, and Jean Reeder, Ph.D. "Soil PH." Soil PH. Colorado State

University Extension, 2013. Web. N.d. Apr. 2014.

<http://www.ext.colostate.edu/mg/gardennotes/222.html>.

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#WORKS CITED: Brendan Donovan: Blumm, Barton M. "Picea Rubens Sarg." Picea Rubens Sarg. Http://www.na.fs.fed.us/,

n.d. Web. 15 Apr. 2014.

<http://www.na.fs.fed.us/pubs/silvics_manual/Volume_1/picea/rubens.htm>.

Harrington, Harry. "Tree PH Ranges." Www.bonsai4me.com. Harry Harrington, 2004.

Web. 15 Apr. 2014.

<http%3A%2F%2Fwww.bonsai4me.com%2FAdvTech%2FAT%2520tree%2520

ph%2520ranges.htm>.

Innovation! Big Green Cartoon Tree. N.d.

Http://innovation.kpru.ac.th/web17/551121712/innovation/index.php/1-1-5-

0. Innovation.kpru.ac.th. Web. 1 May 2014.

<http://innovation.kpru.ac.th/web17/551121712/innovation/index.php/1-1-5-0>.

Jett, John W. "Horticulture." Www.wvu.edu. Extension Service West Virginia University,

May 2005. Web. 15 Apr. 2014.

<http://www.wvu.edu/~agexten/hortcult/homegard/pHpref.pdf>.

Rudolf, Paul O. "Red

Pine."Http://www.na.fs.fed.us/pubs/silvics_manual/Volume_1/pinus/resinosa.htm.

Www.na.fs.fed.us, n.d. Web. 15 Apr. 2014.

<http%3A%2F%2Fwww.na.fs.fed.us%2Fpubs%2Fsilvics_manual%2FVolume_1

%2Fpinus%2Fresinosa.htm>.

Sander, Ivan L. "Quercus Muehlenbergii Engelm." Quercus Muehlenbergii Engelm.

!!"

Www.na.fs.fed.us, n.d. Web. 15 Apr. 2014.

<http://www.na.fs.fed.us/pubs/silvics_manual/volume_2/quercus/muehlenbergii.ht

m>

Schlesinger, Richard C. "White

Ash.”http://www.na.fs.fed.us/pubs/silvics_manual/volume_2/fraxinus/am

Trails at Drumlin Farm. 2014. Www.massaudubon.org.Www.massaudubon.org. Web. 1

May 2014. <http://www.massaudubon.org/get-outdoors/wildlife-

sanctuaries/drumlin-farm/about/trails>.

!"#

APPENDIX

Figure 1: Red Pine and White Oak testing sites. Many different types of leaves filled the forest floor. The soil was damp and very close to Ice Pond.

Figure 2: The White Ash testing site. Ashes, can be identified by their triangular shaped trunks. Only White Ash leaves covered the ground, the ground was damp and there were several fallen trees.

!"#

Figure 3: The White Spruce testing site. Spruces, can be identified by the several notches

in their bark. This ground was not so damp, but still a lot of fallen trees.

Figure 4: The control run at Hemlock Forest. This was extremely close to Ice Pond, there

were many varieties of leaves on ground and not many trees nearby.

!"#

Figure 5: This is a pH Rapitest testing kit with the chemical reagent creating a color to compare with the color chart (Right).

Figure 6: This is an overview map of Drumlin Farm (left).

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AMMONIUM PANDEMONIUM

THE EFFECT OF AMMONIUM LEVELS ON TURBIDITY LEVELS

By: Claudia Inglessis and Madeline Burns

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!TABLE OF CONTENTS Section: Author: Page: ________________________________________________________________________ Abstract Madeline Burns 3 Introduction Claudia Inglessis 3 Materials and Methods Madeline Burns 4 Results Claudia Inglessis 6 Discussion Madeline Burns 8 Acknowledgments Claudia Inglessis 10 Acknowledgements Madeline Burns 10 Works Cited Claudia Inglessis 10 Works Cited Madeline Burns 11

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ABSTRACT The objective of this experiment was to determine how ammonium levels affect

turbidity and plant growth in bodies of water. The hypothesis was: if the ammonium levels in pond water increase, then the turbidity levels of the water will decrease, because ammonium promotes plant life which increases the suspended solids in water (Lumcon, lumcon.edu). The study was conducted at Drumlin Farm in Vernal Pool, Bathtub Pond, and Ice Pond. Water samples were collected and tested for ammonium levels using a Vernier probe. In addition turbidity levels were tested using a turbidity tube. It was clear in the results that the hypothesis was not supported. Error bars overlapped for each pond, and low r2 values showed that there was no correlation among data points. Overall the data was inconclusive. INTRODUCTION Ammonium, or NH4

+, is a polyatomic ion formed when bacteria joins nitrogen and hydrogen. It is often used in fertilizers, because it promotes healthy plant growth. Ammonium can enter water through the nitrogen cycle, where it is created by nitrogen fixing bacteria, or as runoff from fertilizers (Gastagno, 242). Bodies of water cannot sustain thriving ecosystems without ammonium to aid algae or plant growth, but toxic amounts of it can kill aquatic animals and plants. Turbidity is the measure of the amount of suspended solids, such as silt, sand, bacteria, or chemical precipitates in a liquid (who.int/).

The data for this experiment will be collected at Drumlin Farm, a Massachusetts Audubon Wildlife Sanctuary in Lincoln, MA. The land covers 312 acres, and contains 5 different ponds. The experiment will be conducted at Ice Pond, Bathtub Pond, and Vernal Pool. Ice Pond is located next to a footpath, and is surrounded by moderately dense trees. Bathtub Pond is next to Bathtub Field, which uses natural fertilizers, and is surrounded by very thick thorn bushes. Vernal Pond is small and close to a few farm buildings. Ammonium is created through the nitrogen cycle. Nitrogen fixing bacteria combine nitrogen with hydrogen to make ammonium, which is easier for plants to absorb than pure nitrogen. The process of plants absorbing ammonium is called nitrogen assimilation. When animals eat plants that contain ammonium, they return the ion to the the soil through excrement. Runoff then carries the ammonium into the water, where it can promote algae growth (Moulton, depts.washington.edu/). An experiment done at Cambridge University found that ammonium greatly increases the growth of plants (Widdowson, journals.cambridge.org/). Since turbidity is defined as a measure of cloudiness or suspended solids, algae in water could increase turbidity (Maczulak, fofweb.com/). It is extremely important to measure turbidity in drinking water (who.int/). High turbidity might indicate high amounts of mud in water, which can clog pipes and filters. It can also prevent chlorine from effectively killing germs and bacteria in water. When drastic environmental changes occur (such as floods or high levels of rain) the turbidity in natural bodies of water can be greatly affected. Depending on the situation, high levels of rainwater can either increase or decrease cloudiness in water. This experiment measures the effect of ammonium levels on water turbidity. The objective is to determine whether there is a strong correlation between ammonium, water turbidity, and plant growth. The experiment will be conducted by collecting 10 samples

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from 3 different ponds at Drumlin Farm. The independent variable will be ammonium levels (mg/L) and the dependent variable will be water turbidity (cm). Controlled variables will be freshwater, distance of sample location from shore (1 meter), amount of water used for sample (1 gallon), how long the sample sits before tested, and depth of sample (1 foot). The hypothesis is: if the ammonium levels in pond water are 22.2 milligrams per liter (higher),then the turbidity levels of the water would be 52.1 centimeters (decrease), because ammonium promotes plant life which increases the suspended solids in water (www.lumcon.edu). This experiment will show how runoff affects water bodies through ammonium. It will also demonstrate possible causes for turbidity in ponds. Drumlin Farm could use these results to limit the amounts of natural fertilizers they use around ponds. If toxic amounts of ammonium are recorded, it could be because of high ammonium fertilizer levels in surrounding soil. The data could also be used to analyze whether or not increased levels in turbidity are dangerous. The information collected on ammonium and water turbidity in this experiment could greatly affect the way Drumlin Farm and other organizations approach fertilization and water examinations. MATERIALS AND METHODS

First, three fresh-water ponds were located on the Drumlin Farm property in Lincoln, MA. Vernal Pool was located West of the sheep grazing area. West of the Corner Field was Ice Pond. The third pond, Bathtub, was north of Bathtub Field. To start off, the circumference of each pond was measured using a tape measure. While one partner stood on the end of the tape measure, the other partner continued to walk around the perimeter of the pond, releasing more tape. The measurement was read when the tape measure wrapped around half of the pond. This number (the circumference) was then multiplied by two using a Texas Instruments Scientific Calculator, as a way to estimate the perimeter of the entire pond. This procedure of estimating the perimeter allowed there to be more time spent measuring the turbidity and ammonium. The location in which each sample was taken from was marked by stakes (see figure 1). A yellow stake was placed at a random spot near the shore line for each location. Starting at the first yellow stake, yellow stakes were placed at intervals of 1/10 the perimeter of the pond. The intervals were calculated by dividing the estimated perimeter by 10 using a Texas Instruments Scientific Calculator. After each stake was moved to the appropriate position, ! of a meter was measured from the shore line into the water. 3.9 liters of water was then filled at each white flag at a depth of a hundred centimeters, making sure the sample taken was perpendicular to the flag on the shore. Tall wading boots were worn to avoid getting wet. A timer was checked throughout this process to make sure time was being spent effectively.

In the process of preparing for testing at Drumlin Farm, an Ammonium Ion Selective Electrode (see figure 2) was calibrated. This was done by soaking the tip of the probe in the Ammonium Chloride Standard (high solution, 1000 ml concentration) for 30 minutes. After arriving at Drumlin and plotting out the location of samples, a T-Inspire calculator was plugged into an ammonium probe using a USB adaptor. After one sample was collected, the container holding the water was shaken and the probe was ready to be used. The tip of the probe was submerged in the sample at a depth in which the white dot on the side of the probe rested on the meniscus of the sample. Wait time was sixty seconds, and the number on the T-Inspire calculator was recorded in the data table.

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Distilled water was used to rinse the tip of the probe after each sample was tested, to ensure that each reading was accurate. This was repeated for every ten samples at each pond and the data collected at each pond was averaged using a Texas Instruments Scientific Calculator.

The final process in the experiment was to test the turbidity of the samples. A turbidity tube (127 cm) from the Water Monitoring Equipment and Supplies (see figure 3) was used to test the turbidity. One sample was tested at a time. The water sample was poured slowly in the top of the turbidity tube, making sure the spout at the bottom was closed. While one partner peered through the top of the tube, the other partner released water using the spout. A small plastic tub was used to hold the drained water. The spout was closed when a pattern that sits on the bottom of the tube was just visible to the partner looking from above. After reading the height of the water in centimeters from the side of the tube, the measurement was recorded on the data table in the field notebook. Next the water in the turbidity tube and the plastic tub would be dumped back into the pond. Each sample was tested at all 30 data points and the data recorded was averaged for each pond using a Texas Instruments Scientific Calculator. Figure 1: Plot sampling in ponds

Figure 2: Ammonium Ion Selective Electrode

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Figure 3: A turbidity tube and the pattern found at the bottom.

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Graph One plots the effect of the environment on ammonium and turbidity levels. Bathtub Pond has the highest average turbidity level (63.5 cm) and the largest error bar for that parameter. Its average ammonium level is in the middle (36.4 mg/L), and it also has the largest error bar for ammonium levels. Ice Pond’s average turbidity level is 46.1 cm and the error bar is moderately large. Its average ammonium level is 29.4 mg/L, and the error bar is also medium sized. The average turbidity level for the Vernal Pond is 46.6 cm, and its error bar is the smallest. The average ammonium level is 1.27 mg/L, and the error bar is much smaller than the others. Because the data points for the Vernal Pool are so different from the others, they are most likely outliers.

Graph Two shows the effect of ammonium levels on turbidity levels. The trend line indicates that higher ammonium levels result in higher turbidity levels, but the r-squared value is only about .02. The data is spread out with the exception of a few clusters. Most of the data is not located near the trend line. The highest turbidity level is recorded for Bathtub Pond (90 cm), and the highest ammonium level is recorded for Ice Pond (39.1 mg/L). The lowest turbidity level is recorded in Ice Pond (15 cm), and the lowest ammonium level is recorded in Bathtub Pond (20.0 mg/L). The data from Vernal Pool is not used in this graph.

Graph Three displays the effect of ammonium levels on turbidity levels in all three environments. The trend lines each indicate different trends. The trend line for the Vernal Pool data shows that a slight increase in ammonium levels results in a large increase in turbidity levels, and it has an r squared value of .13. The trend line for the Ice Pond shows that turbidity levels increase when ammonium levels increase; it has an r-squared value of .45. The trend line for the Bathtub Pond shows that when ammonium levels increase the turbidity levels decrease; it has an r-squared value of .10.

DISCUSSION

The purpose of the proposed experiment was to study the effect of ammonium on turbidity levels. The hypothesis states that if the ammonium levels in pond water

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increase, then the turbidity levels of the water will decrease, because ammonium promotes plant life which increases the suspended solids in water (Lumcon, lumcon.edu). There was no consistent correlation of high ammonium levels and low turbidity levels, therefore the hypothesis was not supported.

There was no correlation in the graphs that justified the hypothesis. Therefore one could not be confident in the results of this experiment. The error bars often overlapped for both ammonium and turbidity levels. This means that among the three sites, the data was similar. For instance, when it came to turbidity all three ponds had overlapping error bars, so most of the data points were the same or similar. The same error bar pattern occurred for the ammonium levels with one exception. Vernal Pool’s error bar did not overlap with any other error bars. This is because ammonium levels for Vernal Pool were significantly lower compared to the other sites. Although most error bars were quite long for both the ammonium and turbidity levels, the turbidity for Bathtub Pond had the largest error bar. This shows that the data was not precise, instead there was a large range of data points. As a result of the long and overlapping error bars, the data was inconclusive because the data could not be compared. The r2 value of 0.02 was less than 0.6 meaning that there was not a strong correlation between the ammonium and turbidity levels in the pond. This shows that the data points did not fit the trend line well, instead there were multiple outliers.

The confidence in this research is in the amount of data collected. A total of 60 data points were taken, 20 from three different ponds in various locations on Drumlin Farm, which was a sufficient amount of data. Some of the turbidity data points weren’t very accurate because they had a NTU reading below 5. The human eye can only see the turbidity of 5 NTU and greater (Michigan Technological University, cas.umn.edu). In addition it is possible that from walking in the water to collect samples, resuspension occurred. Resuspension occurs when sediments at the bottom of the pond are stirred up (LUMCON,lumcon.edu) This error is significant because turbidity is mainly affected by soil particles (Jay Nixon and Sara Parker Pauley, dnr.mo.gov), which would explain why most data points were similar for turbidity. All three ponds were affected by runoff. Runoff is made up of rainwater and melted snow, this precipitation can carry ammonium in manure and fertilizer (John Sawyer, extension.edu). When ammonium is present in ponds, it can promote algae growth, which affects the turbidity of the pond water. Vernal Pool is made completely of runoff, the majority of the runoff comes from the farmyard which may carry a large amount of manure (John Sawyer, extension.iastate.edu). Bathtub pond is affected by runoff from fertilizer and Ice pond was also in close proximity to manure runoff. This runoff may have also made data from all three ponds similar. The main source of ammonium is from runoff and the coinciding amount of runoff from each location would lead to similar ammonium and turbidity levels. The main explanation for the greatly lower data for Vernal Pool’s ammonium level is that an error occurred in the ammonium probe. The ammonium probe being used was not working and was replaced by another ammonium probe while the data was being collected for Vernal Pool.

Many changes could be made to improve the results of this experiment. To start off it would be helpful if the data could be collected in one pond throughout each season. By testing data for each season it is easier to see in the long run how ammonium and turbidity is affected. Also it would help if the chosen pond was easy to access in order to make sure that resuspension did not occur. To make sure there were no errors in

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collecting the ammonium levels, 1 ammonium probe would be used as opposed to 2 different probes. It may help in the future if an experiment was conducted to test how nitrogen, in fertilizer, effects ammonium. This would help give a better explanation for how runoff affects both ammonium and turbidity. Throughout the nitrogen cycle ammonium is formed when nitrogen and hydrogen react. This ammonium is used as fertilizer in the form of manure. When the manure decomposes it turns back into nitrates. It is possible that this decomposition may occur in pond water after the manure is carried by runoff. Figuring more about the decomposition of manure would help give more of an explanation to how runoff affects the turbidity and ammonium of pond water. Figuring out more about the decomposition of manure would help give more of an explanation to how runoff affects the turbidity and ammonium of pond water. ACKNOWLODGEMENTS Claudia Inglessis:

First, I would like to thank Drumlin Farm for allowing us to collect and test data in their ponds. I would like to thank Heather Larocca for guiding my partner and me through our study, as well as the rest of the BB&N Middle School science department for making this whole project possible. I would like to thank the naturalists at Drumlin Farm for helping us understand the terrain. Finally, I would like to thank Maddie Burns for all the work she has done to complete this study. Madeline Burns:

Without support from others this research would not have been possible. I would like to thank Ms. LaRocca for always keeping me on track and correcting my papers throughout the process of writing. I would also like to thank my peers in Lab 8 who gave me input on how to improve my writing and different views on how to execute certain assignments. Specifically, my partner Claudia for always giving useful suggestions to add to my notes and for working with throughout the project to create a successful piece of writing and research. In addition I would like to thank all of the chaperones and naturalists at Drumlin Farm that took time out of their day to support us in collecting our data. Finally I would like to acknowledge the members of the science department that made this project run as smoothly as possible. VI. WORKS CITED Claudia Inglessis:

Brody, Jane E. "Personal Health: On Tap Water." The New York Times [New York City]

18 July 2000: n. pag. Print.

Gastagno, Joseph M. Popular Science. Vol. 3. Philippines: Scholastic, 2004. Print.

Maczulak, Anne. "Water Quality." Science Online. Facts On File, Inc. Web. 13 Mar.

2014. .

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Moulton, Orissa. "Nitrogen-Driven Interactions." University of Washington. N.p., n.d.

Web. 13 Mar. 2014.

<http://depts.washington.edu/fhl/enews/autumn2012/moulton.html>.

"Nitrogen Cycle." Encyclopaedia Britannica Online. Encyclopaedia Britannica, 2014.

Web. 10 Mar. 2014.

"Turbidity." Turbidity. N.p., n.d. Web. 13 Mar. 2014.

<http://www.lumcon.edu/education/Teacher/Resources/Runoff/Pollutant_Pages/T

urbidity.htm>.

Widdowson, F. V., A. Penny, and RJ B. Williams. "Experiments Measuring Effects of

Ammonium and Nitrate Fertilizers, with and without Sodium and Potassium, on

Spring Barley."Cambridge Journals Online - Microscopy and Microanalysis -

Abstract - Animal Models of Lafora Disease. Cambridge University Press, Oct.

1967. Web. 13 Mar. 2014.

<http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=455

865>.

"The Importance of Measuring Turbididty." Www.who.int. World Health Organization,

2014. Web. 3 Apr. 2014.

<http://www.who.int/water_sanitation_health/hygiene/emergencies/fs2_33.pdf>.

Madeline Burns:

CHM 110. "Elmhurst College: Elmhurst, Illinois." Elmhurst College: Elmhurst,

Illinois. Elmhurst College, 2014. Web. 17 Apr. 2014.

<http://www.elmhurst.edu/>.

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Health Orginization, World. "World Immunization Week 2014: Know, Check, Protect."

WHO. WHO, 2014. Web. 3 Apr. 2014. <http://www.who.int/>.

Hudson River Education and Stewardship Program. "Turbidity." Hudson River Education

and Stewardship Program. NYU Hudson, 2014. Web. 13 Mar. 2014.

<http%3A%2F%2Fsteinhardtnapps.es.its.nyu.edu>.

Inc., Xylem. "YSI Ammonia and Ammonium." YSI Ammonia and Ammonium. Xylem

Inc., 2013. Web. 10 Mar. 2014.

<http://www.ysi.com/parametersdetail.php?Ammonia---Ammonium-16>.

Lumcon. "Louisiana Universities Marine Consortium (LUMCON) - Home." Louisiana

Universities Marine Consortium (LUMCON) - Home. Louisiana Universities

Marine Consortium, 2014. Web. 13 Mar. 2014. <http://www.lumcon.edu/>.

Michigan Technological University. "Welcome to the Center for Austrian Studies."

Center for Austrian Studies : University of Minnesota. Michigan Technological

University, Apr. 2006. Web. 16 Apr. 2014. <http://www.cas.umn.edu/>.

"Missouri Department of Natural Resources." Missouri Department of Natural

Resources. Missouri Department of Natural Resources, 2014. Web. 16 Apr. 2014.

<http://www.dnr.mo.gov/>.

Sawyer, John. "Surface Waters: Ammonium Is Not Ammonia – Part Two." Ammonium

and Ammonia in Drinking Water. Iowa State University, 2 May 2008. Web. 9

Mar. 2014.

<http://www.extension.iastate.edu/CropNews/2008/0502JohnSawyer.htm>.

Science, Popular. The New Book of Popular Science - Volume 3. Philippines: Scholastic,

2004. Print.

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Vernier. "Ammonium Ion-Selective Electrode." Vernier Software & Technology. Vernier,

2014. Web. 10 Mar. 2014. <http://www.vernier.com/products/sensors/ion-

selective-electrodes/nh4-bta/>.

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Turrific Turbidity!

The effect of turbidity (NTU) on dissolved oxygen (mg/L)

By: India Cabot, Colin Lamphier, and Henry Ross

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TABLE OF CONTENTS

Section Author Page

ABSTRACT Cabot 3 INTRODUCTION Cabot 3 MATERIALS & METHODS Cabot 5 RESULTS Ross 8 DISCUSSION Lamphier 13 WORKS CITED Cabot 14 WORKS CITED Lamphier 14 WORKS CITED Ross 14 ACKNOWLEDGEMENTS Cabot & Lamphier & Ross 16

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ABSTRACT

The objective of this experiment was to find the effect of turbidity on dissolved oxygen levels using three different ponds at Drumlin Farm in Lincoln, Massachusetts. Fifteen water samples were collected at each of the three ponds: Ice, Boyce, and Bathtub pond. Once the water samples were collected, the turbidity levels were measured with a Vernier Turbidity Sensor, and the dissolved oxygen levels were measured with a Vernier Dissolved Oxygen Probe. It was predicted that if the turbidity was higher, then the dissolved oxygen levels would be lower, because sunlight cannot shine through the more turbid water to reach the vegetation, so less oxygen is created resulting in lower dissolved oxygen levels (Heest, Burkhart, Curry). The data collected showed that there was no significant correlation between turbidity and dissolved oxygen. INTRODUCTION

The turbidity level is the amount of suspended particles in water, and is essentially the clarity of the water. High turbidity levels are dangerous for underwater organisms because the particulate can clog fish gills, and smother fish eggs. The flow rates in a body of water, soil erosion, fish, and decomposing organisms all effect turbidity. The dissolved oxygen level is how much oxygen is dissolved into a body of water. Low dissolved oxygen levels can kill off underwater creatures from the lack of oxygen. There are several factors contributing to the pond’s dissolved oxygen levels including sunlight, vegetation, underwater organisms, and precipitation.

Most of the dissolved oxygen enters streams and bodies of water through the atmosphere. As rain falls onto land, the rain percolates into the soil, and then run through the soil to a body of water, carrying nutrients, dissolved oxygen molecules, and sediment (Perlman, http://water.usgs.gov). Underwater vegetation, like phytoplankton, also effects dissolved oxygen. In the presence of sunlight, underwater vegetation will release oxygen into the water during photosynthesis. During the period when sunlight is not present, like night or cloudy days, the vegetation will consume oxygen for respiration. Fortunately the underwater vegetation produces more oxygen than it consumes, therefore leaving oxygen for the underwater creatures. Sunlight cannot easily reach vegetation on the bottom of a body of water when the water is more turbid, or thick in particles and sediment, therefore the vegetation on the bottom that remains in the dark, cannot contribute to increasing the dissolve oxygen levels (Causey, http://agrilifeextension.tamu.edu). Another factor affecting dissolved oxygen levels is a process called eutrophication. During this process, a body of water acquires a high concentration of nutrients such as nitrates and phosphates. From these nutrients algae will thrive, and once decomposed, the organic matter will deplete the water of available oxygen. Underwater organisms, like fish, rely on a specific amount of dissolved oxygen. When the level changes, it can affect the organisms’ habits and or health (http://water.epa.gov). When dissolved oxygen levels drop, the bottom of ponds and lakes are the first to go anoxic. Anoxic means that a body of water becomes unhealthily depleted of oxygen. It is more difficult for sunlight to reach the bottom of the pond, and therefore deeper vegetation cannot create oxygen to release into the deeper water. When the dissolved oxygen levels are low, cold-water fish are forced up to warmer, and

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more oxygenated waters. The fish will become stressed because of the instant climate change, and they can die (Robinson, http://www.mass.gov). There is typically no more than ten part per million of oxygen dissolved into water bodies. It is known for moving water like large rivers, or mountain streams to have higher dissolved oxygen levels than still waters like ponds.

Turbidity directly affects temperatures in bodies of water. When a pond has a higher concentration of suspended particles, they absorb heat and this increases the waters temperature. Due to this, when temperatures are higher it is expected that dissolved oxygen will be lower (Perlman, http://water.usgs.gov). When the turbidity levels are lower, the water is capable of holding less specific fish and organisms. In water with higher turbidity levels there is less range of species because high turbidity is potentially dangerous.

Flow rate directly affects turbidity in water. When the rate is faster, the water is capable of holding more particles, and larger sediment. Soil erosion occurs in the construction of buildings or roads. The eroded sediment can be washed into surface water like ponds and rivers, therefore increasing turbidity levels. Bottom feeding fish can stir up particles while searching for food. Decomposing animal life will release suspended organic particles into the water, thus increasing the turbidity level. When turbidity levels are high in a body of water, it is more difficult for sunlight to reach the depths of water. Therefore the vegetation that does not receive the sunlight cannot create oxygen to release into the water, making an uninhabitable habitat.

The proposed experiment is the effect of turbidity (NTU) on the dissolved oxygen level (Mg/L). Collecting water samples from different locations at three specific ponds will conclude whether turbidity and dissolved oxygen have a correlation. A sample will be held in one 118 mL plastic container, and tested with a dissolved oxygen Vernier probe. Following the dissolved oxygen test will be the turbidity test. The turbidity will be tested with a Vernier Turbidity Sensor. The independent variable for this experiment is the turbidity level (NTU). The dependent variable is the dissolved oxygen level (mg/L). Important controlled variables include taking samples from same depth, washing off probes between each test, and taking same number of samples from each pond. The hypothesis is, if the turbidity is higher, then the dissolved oxygen levels will be lower because sunlight cannot shine through the more turbid water to reach the vegetation, so less oxygen is created resulting in lower dissolved oxygen levels (Heest, Burkhart, Curry).

This experiment will be conducted at Drumlin Farm in Massachusetts. Drumlin Farm spans 312 across acres of forests, fields, and five ponds and pools. For this experiment three locations will be tested: Bathtub Pond, Ice Pond, and Boyce Pond. Bathtub is surrounded by thick vegetation, and is south of the drumlin. Ice Pond is downhill from the parking lot, and is north of the drumlin. Boyce is placed southeast of the Drumlin, and is quite small. It is next to Boyce Field in the woods. What is unique about Boyce Pond is that it is a vernal pool. A vernal pool is a pool of water that only occurs in the spring, hence “vernal” which means spring.

What can be learned from this experiment is how turbidity is affecting the dissolved oxygen levels. The dissolved oxygen levels directly affect the underwater organisms. Their habits are affected when the dissolved oxygen level is affected, and turbidity is a main reason why dissolved oxygen can change. This can be an indicator

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that dissolved oxygen levels is unhealthy when there is minimal fish and aquatic life in the water. It is important to realize what is affecting our underwater organisms for the worse, and to find ways to prevent this from happening. MATERIALS AND METHODS When collecting samples from the ponds at Drumlin Farm in Lincoln Massachusetts, it was necessary to execute it without being biased, so a clock method was used. The clock method was figuratively drawing a clock around a specific pond that was to be tested. North was 12 o'clock, South was 6 o’clock etc. Increments of 2.5 minutes were used, and a flag was marked on the shore of the pond at each point. A water sample was collected and tested on each mark. To mark every 2.5 minutes, 24 marking flags were necessary. To hold the water sample, a 118 mL plastic container with water was used. The clock method was used on Ice Pond, Boyce Pond, and Bathtub Pond (See figure four for location 12, 13, and 15).

To test the water sample’s dissolved oxygen level and turbidity level, a Vernier Dissolved Oxygen Probe (see figure two), and Turbidity Sensor were essential (see figure three). Both testing devices were calibrated according to instructions. Starting with the turbidity probe, the glass cuvette was filled to the line with the water sample, and making sure it was dry, it was placed into the open slot of the Vernier Turbidity Sensor. Making sure the arrow on the cuvette and the arrow on the sensor aligned, the sensor was plugged into an interface. In this case a Labquest (see figure one) was vital to the data recording. The NTU of the waters sample was recorded for fifteen seconds, and averaged to give a final answer. Then the cuvette was emptied, rinsed with distilled water, and filled with another sample to test.

Following the turbidity test was the dissolved oxygen level test. The probe’s cable was connected to the Labquest, and then plunged into 4-6 cm of water. The probe stirred in the water while the Labquest was recording the dissolved oxygen level for fiteen seconds. Then, once the data collection finished, the data was averaged to give the sample’s dissolved oxygen level in mg/L. The Dissolved Oxygen Probe was then rinsed, dried off with a lint free cloth, and began testing another sample.

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Figure 1: Labquest

Figure 2: Vernier Dissolved Oxygen Probe

Figure 3 Vernier Turbidity Sensor

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Figure 4: Drumlin Farm Map

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RESULTS Table 1: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Ice Pond

Trial Turbidity

(NTU) Dissolved Oxygen

(mg/L) 1 101.1 8.5 2 70.6 9.2 3 51.8 11 4 51.9 9.1 5 66.0 6.2 6 35.7 6.2 7 63.9 6.1 8 53.4 5.4 9 58.7 7.0

10 37.9 10.1 11 50.3 9.8 12 50.8 8.2 13 32.0 7.9 14 60.0 9.2 15 64.1 6.1

Average 56.5 8.0 Standard Deviation 16.7 1.7

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Table 2: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Boyce Pond

Trial Turbidity

(NTU) Dissolved

Oxygen (mg/L) 1 44.5 7.2 2 52.5 5.1 3 85.4 7.3 4 33.3 8.6 5 26.3 7.2 6 34.9 7.3 7 31.6 7.2 8 35.1 6.5 9 28.8 5.6

10 42.4 6.2 11 40.2 7.7 12 54.4 5.5 13 34.9 8.7 14 26.6 7.2 15 30.2 7.0

Average 40.1 7.0 Standard Deviation 15.2 1.0

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Table 3: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Bathtub Pond

Trial Turbidity

(NTU) Dissolved

Oxygen (mg/L) 1 54.2 6.1 2 48.8 7.2 3 36.8 7.5 4 66.9 6.8 5 67.8 5.9 6 68.3 6.4 7 73.1 7.0 8 30.8 7.6 9 55.6 6.4

10 49.3 7.9 11 60.0 7.1 12 60.5 7.2 13 46.1 7.9 14 42.4 7.8 15 50.9 8.1

Average 54.1 7.1 Standard Deviation 12.2 0.7

Graph 1: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Ice Pond

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Graph 2: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Boyce Pond

Graph 3: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Bathtub Pond

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Graph 4: The overall effect of turbidity (NTU) on dissolved oxygen levels (mg/L)

The data shown in graphs 1-4 show the effect of turbidity (NTU) on dissolved oxygen levels (mg/L). Graph 4 shows all of the data collected, and indicates that at the sites tested, the turbidity levels didn’t have an effect on dissolved oxygen. Both Ice pond and Boyce pond had one outlier recorded, but no extreme outliers were recorded at Bathtub pond. The r2 values were generally low, with the lowest being recorded at Ice pond (0.004) and the highest at Bathtub pond (0.38). There were a couple of outliers in the data that could have affected the accuracy of the data. The most extreme outlier was recorded at Ice pond, with 8.5 mg/L of dissolved oxygen and 101.1 NTU of turbidity. The outliers were included in the graphs. The highest data point recorded at Ice pond was 101.1 NTU and the lowest was 32.0 NTU. The highest data point recorded at Boyce pond was 85.4 NTU and the lowest was 26.3 NTU. The highest data point recorded at Bathtub pond was 73.0 NTU and the lowest was 30.6 NTU. Overall the dissolved oxygen levels were very similar at all the ponds with the average at Ice pond being 8.0 mg/L, at Boyce pond 7.0 mg/L, and at Bathtub pond 7.1 mg/L. The standard deviations of the dissolved oxygen levels were all bellow two. It was observed at Ice and Bathtub pond there was still a layer of ice on the pond. Bathtub pond had approximately 75% cover and Ice pond had approximately 25% cover. This could have affected the dissolved oxygen levels because the ice could’ve prevented sunlight from reaching the vegetation on the bottom. It was also observed that the ponds were all surrounded by lose mud. This could have affected the turbidity levels because while the samples were being collected the mud could have been disturbed, increasing the turbidity. The precision of the data was overall low. Although the precision of the dissolved oxygen was much higher than that of the turbidity, the dissolved oxygen had a smaller range in possible levels. The data was the least precise at Ice pond, and the most precise at Bathtub pond. Overall the r2 values were low, and the data precision was low.

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DISCUSSION

The experiment studied the relation between turbidity and dissolved oxygen. It focused on dissolved oxygen and turbidity in three freshwater ponds. It was hypothesized that if the turbidity is higher, then the dissolved oxygen levels will be lower because sunlight cannot shine through the water to reach the vegetation, so less oxygen is created resulting in lower D.O. Levels (Heest, Burkhart, Curry). The hypothesis of the experiment was not supported according to the results. The r2 value was low, so the results indicated that turbidity levels are not related to dissolved oxygen levels.

Graph 1 shows an extremely weak correlation (R2=0.00427) between turbidity and dissolved oxygen at Ice pond, and there is no specific trend between the two variables. When turbidity was greater it did not necessarily mean that dissolved oxygen would be lower or vice versa. For example, at location 1 the turbidity level was 101.1 NTU while the dissolved oxygen was 8.5 mg/L, while location 7 had a turbidity of 63.9 NTU and dissolved oxygen of 6.1 mg/L. The highest r squared value was .38257. The averages for turbidity and dissolved oxygen in table 1 were 56.5 NTU for turbidity and 8.0 mg/L for dissolved oxygen. Tables 2’s averages are 40.1 NTU and 7.0 mg/L, and 54.1 NTU and 7.1 mg/L for Table 3. The graph of all locations combined show that the data is not precise, because the r2 value .02032.

The samples collected did not have good enough data. Fewer samples were collected because the short amount of time and insufficient data collection. The shortage in samples may have been a reason for inconclusive results. With more samples tested outliers could have been eliminated making data more precise.

The data may not have been accurate because of the cold weather. Dissolved oxygen is greater in colder weather, while turbidity is lower (http://water.epa.gov/type/rsl/monitoring/vms55.cfm). This may have affected the data, making it less accurate.

The field study came with many difficulties such as inaccessible areas of the ponds at Drumlin Farm, mud on the shore of the ponds, and many trees and branches to walk over to collect samples. If the field study could be changed, it would be by being more prepared for these difficulties. Boots could have been worn to make the water more accessible. Sufficient data was not collected at all times because less samples were collected because of short time. Some parts of the ponds that were set for collecting samples were inaccessible, so collection locations were improvised.

Due to the difficulties in collection, data may have been negatively affected, leading to weaker correlation. This also caused samples to be taken closer together, possibly making the data similar. For future research in this topic boots would be worn to make rough terrain easier to walk on. The ability to go into water would allow easier, and most likely quicker collection. Many precautions should be made if this topic were to be put to further experimentation.

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WORKS CITED AUTHOR 1: Causey. "Dissolved Oxygen « AQUAPLANT." Dissolved Oxygen « AQUAPLANT.

Agrilifeextension.tamu.edu, n.d. Web. 16 Apr. 2014.

<http://aquaplant.tamu.edu/faq/dissolved-oxygen/>.

EPA. "5.5 Turbidity." Home. Www.epa.gov, 6 Mar. 2012. Web. 13 Mar. 2014.

<http://water.epa.gov/type/rsl/monitoring/vms55.cfm>.

Perlman, Howard. "Turbidity." - Water Properties, USGS Water Science School.

Usgs.gov, n.d.

Web. 17 Apr. 2014. <http://water.usgs.gov/edu/turbidity.html>.

Perlman, Howard. "Water Properties: Dissolved Oxygen." Dissolved Oxygen, from

USGS Water Science for Schools: All about Water. Www.usgs.gov, n.d. Web. 11

Mar. 2014. <http://water.usgs.gov/edu/dissolvedoxygen.html>.

United States. Dpt of Conservation and Recreation.Office of Water Resources. The

Massachusetts Lake and Pond Guide. By Michelle Robinson. United States Dpt

of Conservation and Recreation, 2005. Web. 23 Jan. 2014.

<Http://www.mass.gov/eea/docs/dcr/watersuply/lakepond/downl

AUTHOR 2: "5.5 Turbidity." Home. Environmental Protection Agency, n.d. Web. 14 Apr. 2014.

"Dissolved Oxygen." And Water Quality. KY Water Watch, n.d. Web. 16 Apr. 2014.

<http://www.state.ky.us/nrepc/water/wcpdo.htm>.

"Measuring Dissolved Oxygen (DO)." Measuring Dissolved Oxygen (DO). VCCS, n.d.

Web. 17 Apr. 2014. <http://water.me.vccs.edu/concepts/domeasure.html>.

Turbidity Measurement. 2.33. N.p.: Who.int, n.d. Print. Fact Sheet.

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"Turbidity." Turbidity. Lenntech, 2014. Web. 17 Apr. 2014.

<http://www.lenntech.com/turbidity.htm>.

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ACKNOWLEGEMENTS Cabot: I would like to strongly thank my partners Henry Ross, and Colin Lamphier for being persuasive and consistent scientists by my side. They did a great job pulling through unexpected obstacles like time, and setting up systems to execute the experiment efficiently. I would also like to thank these teachers: Ms. Hardy, Ms. Jamison, and Mr. Sarzana. They looked out for us and answered any questions they could at each of the ponds we visited. I would also like to thank the Drumlin Naturalists for providing us with information like short cuts, or wildlife. Finally I would like to thank Ms. Svatek for conducting the science field trip smartly, and carefully. Ms. Svatek supplied materials and knowledge, and helped out group come up with an experiment that intrigued all three of us. If it weren’t for these people, the experiment would have been much harder and unpleasant to conduct. Lamphier: I would like to thank my group members India Cabot, and Henry Ross for being hard, consistent, and rational workers. Without them the Experiment would have been a huge failure. I would also like to thank Drumlin Farm for letting us test at their locations, as well as the guide that helped point us at the right direction when switching from site to site. The guide also helped us get to places that we needed to collect samples from. The teachers who supervised the sites were also very important for not only our safety, but for giving us ideas on how to compromise our procedure. Lastly I would like to thank Ms. Svatek for helping to set up our experiment, and providing the materials needed. Ross: I would like to thank Ms. Svatek for helping us develop our experiment, learn how to use our materials, and for helping edit our reports. I would also like to thank my partners for completing this experiment with me. I would like to thank Mrs. Hardy for administering a Band-Aid when I cut myself on a thorn. I would like to thank the bus drivers for getting us to and from Drumlin Farm. Finally I would like to thank the Drumlin Farm teacher naturalists for giving us directions, and for all the overall help the gave us throughout our visit there.

The Effect of Turbidity (NTU) on Dissolved

Oxygen (mg/L)

By India Cabot, Colin Lamphier, and Henry Ross

Terrific Turbidity

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TABLE OF CONTENTS

Section Author Page

ABSTRACT Lamphier 3 INTRODUCTION Ross 3 MATERIALS & METHODS Lamphier 4 RESULTS Ross 6 DISCUSSION Lamphier 11 ACKNOWLEDGEMENTS Cabot & Lamphier & Ross 12 WORKS CITED Cabot 13 WORKS CITED Lamphier 13 WORKS CITED Ross 13

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ABSTRACT

The objective of the experiment was to find the relationship between turbidity and dissolved oxygen. The experiment was conducted at Drumlin Farm in Lincoln, MA on Monday, April 7. The procedure was to test certain spots on the water of three ponds for turbidity and dissolved oxygen. Each test was recorded into a data table. It was expected that if turbidity was higher, then dissolved oxygen would be lower because of lack of sunlight getting through to create dissolved oxygen from plants at the bottom of the ponds. The results showed that the turbidity had little effect on dissolved oxygen. The average r2 value was about .003. All three ponds did not show a strong enough correlation between turbidity and dissolved oxygen to support our hypothesis. INTRODUCTION

Turbidity is the amount of suspended particles in water. These particles can be soil particles, algae, plankton, and/or particles washed into the water. If too high, turbidity can make water unsafe to drink, and highly turbid water can be dangerous for animal life. If there are too many suspended particles, dirt can get stuck in the gills of fish (EPA, http://water.epa.gov). Fish also rely on dissolved oxygen to breathe. Dissolved oxygen is tiny bubbles of oxygen in water. Dissolved oxygen is created by photosynthesis from vegetation on the bottom of the pond. Dissolved oxygen can be depleted by eutrophication. Eutrophication is a process where bodies of water gain to many nutrients, resulting in increased algal growth. The algae then uses up the dissolved oxygen, “killing” the body of water. The body of water is “dead” because it can no longer sustain animal life (http://toxics.usgs.gov).

The proposed experiment will be conducted at Drumlin Farm, a wildlife sanctuary, in Lincoln, Massachusetts. Drumlin Farm has five ponds and pools that sustain plant and animal life. For this experiment three locations will be tested: Bathtub Pond, Ice Pond, and Boyce Pond. Ice Pond is surrounded by thick bushes and trees and also has a porch and a deck on two sides. It is just north of the drumlin (S8 Ice Pond poster). Bathtub Pond is surrounded by trees and covered in duckweed, and it is located just south of the drumlin (S8 Bathtub Pond poster). Boyce Pond is east of the drumlin right next to Boyce field, separated by trees (S8 Boyce Field poster). There are many variables in these ponds that could affect both turbidity and dissolved oxygen.

There are several ways that turbidity effects water. Turbidity can vary based on how close the body of water is to a road or how many animals live in it. Turbidity could also be affected by rain runoff, or by humans adding stuff to the water. Turbidity can increase the temperature of water. This happens because the suspended particles in the water absorb heat, so if there is higher turbidity the water will be warmer (EPA, http://water.epa.gov). A study at Hope College in Michigan tested the effect of turbidity on dissolved oxygen levels. This study found that there was a correlation between the turbidity and the dissolved oxygen levels. It was concluded that water with higher turbidity did in fact have lower dissolved oxygen levels. The researchers found that the suspended particles in the water were blocking the sunlight from getting to the lower levels of the lake. Since the majority of the vegetation grows on the lake floor, the lack of sunlight made it hard for the plants to photosynthesize, thus lowering the dissolved oxygen levels (Heest, Burkhart, Curry). Along with decreased dissolved oxygen levels affecting fish, when the suspended particles in the water settle they can smother fish eggs. This will result in a decrease in fish reproduction (EPA, http://water.epa.gov).

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The proposed experiment is the effect of turbidity (NTU) on dissolved oxygen levels (mg/L). The objective of this experiment is to see what water is suitable for plant and animal life based on the turbidity levels. 15 turbidity and dissolved oxygen tests will be performed. To find the point for testing, the pond will be mapped out and north will be found. Next mark out every 2.5 minutes around the map of the pond, as if the pond were a clock, with north being 12. The independent variable of this experiment is the turbidity level, and the dependent variable will be the dissolved oxygen level. It will be important to control the depth at which the samples are collected, the probes used for testing, how far away from the shore the testing is done, how long the testing is done for, and the methods used. The hypothesis set forth for this experiment is, if the turbidity is higher, then the dissolved oxygen levels will be lower because sunlight cannot shine through the water to reach the vegetation, so less oxygen is created resulting in lower dissolved oxygen levels (Heest, Burkhart, Curry).

This experiment can help people understand what bodies of water are suitable for plant and animal life in a simpler way. Instead of having to do a dissolved oxygen test with a probe, people can just do a simple turbidity test. One can then take the findings from the turbidity test to figure out the approximate dissolved oxygen levels. This could also help Drumlin Farm with regulating the stuff that gets into their ponds. Something that that could be further regulated is road salt used on roads next to the ponds. If the farm is able to regulate things that enter the ponds, the plant and animal life in the ponds can thrive, and make visits to the farm more interesting. This would not only help the environment, but also could give the farm a chance to make more money. MATERIALS AND METHODS

At Drumlin Farm in Lincoln MA, forty five samples of water were collected from three ponds. The ponds that the water was collected from were Boyce (1), Ice( 13), and Bathtub (12) (See Figure 1). The samples were collected, and tested with a Vernier turbidity probe (See Figure 2), and a Vernier dissolved oxygen probe (See Figure 3). The probes were calibrated before use, and cleaned with distilled water after every use. A clock was drawn on the maps of every pond, and one sample was taken at 2 ! minute increments on the clock with north being twelve.

To test the samples for dissolved oxygen a dissolved oxygen probe was calibrated by filling the membrane cap with 1 mL of Electrode Filling Solution. Then the probe was placed in 100 mL of distilled water. The probe was warmed up by placing it in the water while connected to the Labquest for 10 minutes. To begin collecting data the probe was submerged into the water about 4-6cm. The results were then recorded. To test the samples for turbidity the turbidity probe was then connected to the Labquest. The test was taken for fifteen seconds and recorded in a data table.

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Figure 1

Figure 2

Figure 3

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RESULTS Table 1: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Ice Pond

Trial Turbidity

(NTU) Dissolved Oxygen

(mg/L) 1 101.1 8.5 2 70.6 9.2 3 51.8 11 4 51.9 9.1 5 66.0 6.2 6 35.7 6.2 7 63.9 6.1 8 53.4 5.4 9 58.7 7.0 10 37.9 10.1 11 50.3 9.8 12 50.8 8.2 13 32.0 7.9 14 60.0 9.2 15 64.1 6.1

Average 56.5 8.0 Standard Deviation 16.7 1.7

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Table 2: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Boyce Pond

Trial Turbidity

(NTU) Dissolved

Oxygen (mg/L) 1 44.5 7.2 2 52.5 5.1 3 85.4 7.3 4 33.3 8.6 5 26.3 7.2 6 34.9 7.3 7 31.6 7.2 8 35.1 6.5 9 28.8 5.6 10 42.4 6.2 11 40.2 7.7 12 54.4 5.5 13 34.9 8.7 14 26.6 7.2 15 30.2 7.0

Average 40.1 7.0 Standard Deviation 15.2 1.0

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Table 3: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Bathtub Pond

Trial Turbidity

(NTU) Dissolved Oxygen

(mg/L) 1 54.2 6.1 2 48.8 7.2 3 36.8 7.5 4 66.9 6.8 5 67.8 5.9 6 68.3 6.4 7 73.1 7.0 8 30.8 7.6 9 55.6 6.4 10 49.3 7.9 11 60.0 7.1 12 60.5 7.2 13 46.1 7.9 14 42.4 7.8 15 50.9 8.1

Average 54.1 7.1 Standard Deviation 12.2 0.7

Graph 1: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Ice Pond

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Graph 2: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Boyce Pond

Graph 3: The effect of turbidity (NTU) on dissolved oxygen levels (mg/L) at Bathtub Pond

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Graph 4: The overall effect of turbidity (NTU) on dissolved oxygen levels (mg/L)

The data shown in graphs 1-4 show the effect of turbidity (NTU) on dissolved oxygen levels (mg/L). Graph 4 shows all of the data collected, and indicates that at the sites tested, the turbidity levels did not have an effect on dissolved oxygen. Both Ice pond and Boyce pond had one outlier recorded, but no extreme outliers were recorded at Bathtub pond. The r2 values were generally low, with the lowest being recorded at Ice pond (0.004) and the highest at Bathtub pond (0.38). There were a couple of outliers in the data that could have affected the accuracy of the data. The most extreme outlier was recorded at Ice pond, with 8.5 mg/L of dissolved oxygen and 101.1 NTU of turbidity. The outliers were included in the graphs. The highest data point recorded at Ice pond was 101.1 NTU and the lowest was 32.0 NTU. The highest data point recorded at Boyce pond was 85.4 NTU and the lowest was 26.3 NTU. The highest data point recorded at Bathtub pond was 73.0 NTU and the lowest was 30.6 NTU. Overall the dissolved oxygen levels were very similar at all the ponds with the average at Ice pond being 8.0 mg/L, at Boyce pond 7.0 mg/L, and at Bathtub pond 7.1 mg/L. The standard deviations of the dissolved oxygen levels were all bellow two. It was observed at Ice and Bathtub pond there was still a layer of ice on the pond. Bathtub pond had approximately 75% cover and Ice pond had approximately 25% cover. This could have affected the dissolved oxygen levels because the ice could have prevented sunlight from reaching the vegetation on the bottom. It was also observed that the ponds were all surrounded by lose mud. This could have affected the turbidity levels because while the samples were being collected the mud could have been disturbed, increasing the turbidity. The precision of the data was overall low. Although the precision of the dissolved oxygen was much higher than that of the turbidity, the dissolved oxygen had a smaller range in possible levels. The data was the least precise at Ice pond, and the most precise at Bathtub pond. Overall the r2 values were low, and the data precision was low.

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DISCUSSION The experiment studied the relation between turbidity and dissolved oxygen. It focused on dissolved oxygen and turbidity in three freshwater ponds. It was hypothesized that if the turbidity is higher, then the dissolved oxygen levels will be lower because sunlight cannot shine through the water to reach the vegetation, so less oxygen is created resulting in lower dissolved oxygen levels (Heest, Burkhart, Curry). The hypothesis of the experiment was not supported according to the results. The r2 value was low, so the results indicated that turbidity levels are not related to dissolved oxygen levels.

Graph 1 shows an extremely weak correlation (R2=0.00427) between turbidity and dissolved oxygen at Ice pond, and there is no specific trend between the two variables. When turbidity was greater it did not necessarily mean that dissolved oxygen would be lower or vice versa. For example, at location 1 the turbidity level was 101.1 NTU while the dissolved oxygen was 8.5 mg/L, while location 7 had a turbidity of 63.9 NTU and dissolved oxygen of 6.1 mg/L. The highest r squared value was .38257. The averages for turbidity and dissolved oxygen in table 1 were 56.5 NTU for turbidity and 8.0 mg/L for dissolved oxygen. Table 2’s averages are 40.1 NTU and 7.0 mg/L, and 54.1 NTU and 7.1 mg/L for Table 3. The graph of all locations combined show that the data is not precise, because the r2 value .02032.

The samples collected did not have good enough data. Fewer samples were collected because the short amount of time and insufficient data collection. The shortage in samples may have been a reason for inconclusive results. With more samples tested outliers could have been eliminated making data more precise.

The data may not have been accurate because of the cold weather. Dissolved oxygen is greater in colder weather, while turbidity is lower (http://water.epa.gov/type/rsl/monitoring/vms55.cfm). This may have affected the data, making it less accurate.

The field study came with many difficulties such as inaccessible areas of the ponds at Drumlin Farm, mud on the shore of the ponds, and many trees and branches to walk over to collect samples. If the field study could be changed, it would be by being more prepared for these difficulties. Boots could have been worn to make the water more accessible. Sufficient data was not collected at all times because less samples were collected because of short time. Some parts of the ponds that were set for collecting samples were inaccessible, so collection locations were improvised.

Due to the difficulties in collection, data may have been negatively affected, leading to weaker correlation. This also caused samples to be taken closer together, possibly making the data similar. For future research in this topic boots would be worn to make rough terrain easier to walk on. The ability to go into water would allow easier, and most likely quicker collection. Many precautions should be made if this topic were to be put to further experimentation.

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ACKNOWLEDGMENTS Cabot: I would like to strongly thank my partners Henry Ross, and Colin Lamphier for being persuasive and consistent scientists by my side. They did a great job pulling through unexpected obstacles like time, and setting up systems to execute the experiment efficiently. I would also like to thank these teachers: Ms. Hardy, Ms. Jamison, and Mr. Sarzana. They looked out for us and answered any questions they could at each of the ponds we visited. I would also like to thank the Drumlin Naturalists for providing us with information like short cuts, or wildlife. Finally I would like to thank Ms. Svatek for conducting the science field trip smartly, and carefully. Ms. Svatek supplied materials and knowledge, which helped our group come up with an experiment that intrigued all three of us. If it was not for these people, the experiment would have been much harder and unpleasant to conduct. Lamphier: I would like to thank my group members India Cabot, and Henry Ross for being hard, consistent, and rational workers. Without them the Experiment would have been a huge failure. I would also like to thank Drumlin Farm for letting us test at their locations, as well as the guide that helped point us at the right direction when switching from site to site. The guide also helped us get to places that we needed to collect samples from. The teachers who supervised the sites were also very important for not only our safety, but for giving us ideas on how to compromise our procedure. Lastly I would like to thank Ms. Svatek for helping to set up our experiment, and providing the materials needed. Ross: I would like to thank Ms. Svatek for helping us develop our experiment, learn how to use our materials, and for helping edit our reports. I would also like to thank my partners for completing this experiment with me. I would like to thank Mrs. Hardy for administering a Band-Aid when I cut myself on a thorn. I would like to thank the bus drivers for getting us to and from Drumlin Farm. Finally I would like to thank the Drumlin Farm teacher naturalists for giving us directions, and for all the overall help the gave us throughout our visit there.

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WORKS CITED Cabot: EPA. "5.5 Turbidity." Home. Www.epa.gov, 6 Mar. 2012. Web. 13 Mar. 2014. <http://water.epa.gov/type/rsl/monitoring/vms55.cfm>. Perlman, Howard. "Turbidity." - Water Properties, USGS Water Science School. Usgs.gov, n.d.

Web. 17 Apr. 2014. <http://water.usgs.gov/edu/turbidity.html>. Perlman, Howard. "Water Properties: Dissolved Oxygen." Dissolved Oxygen, from

USGS Water Science for Schools: All about Water. Www.usgs.gov, n.d. Web. 11 Mar. 2014. <http://water.usgs.gov/edu/dissolvedoxygen.html>.

United States. Dpt of Conservation and Recreation.Office of Water Resources. The Massachusetts Lake and Pond Guide. By Michelle Robinson. United States Dpt of Conservation and Recreation, 2005. Web. 23 Jan. 2014. <Http://www.mass.gov/eea/docs/dcr/watersuply/lakepond/downl

WORKS CITED Lamphier: "5.5 Turbidity." Home. Environmental Protection Agency, n.d. Web. 14 Apr. 2014.

"Dissolved Oxygen." And Water Quality. KY Water Watch, n.d. Web. 16 Apr. 2014.

<http://www.state.ky.us/nrepc/water/wcpdo.htm>.

"Measuring Dissolved Oxygen (DO)." Measuring Dissolved Oxygen (DO). VCCS, n.d. Web. 17

Apr. 2014. <http://water.me.vccs.edu/concepts/domeasure.html>.

Turbidity Measurement. 2.33. N.p.: Who.int, n.d. Print. Fact Sheet.

"Turbidity." Turbidity. Lenntech, 2014. Web. 17 Apr. 2014.

<http://www.lenntech.com/turbidity.htm>.

WORKS CITED Ross: Art. "Eutrophication." Definition Page. Www.usgs.gov, n.d. Web. 13 Mar. 2014.

<http://toxics.usgs.gov/definitions/eutrophication.html>.

Eighth Grade BB&N Students. Bathtub Pond Poster. Rep. Print.

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Eighth Grade BB&N Students. Boyce Field Poster. Rep. Print.

Eighth Grade BB&N Students. Ice Pond Poster. Rep. Print.

EPA. "5.5 Turbidity." Home. Www.epa.gov, 6 Mar. 2012. Web. 13 Mar. 2014.

<http://water.epa.gov/type/rsl/monitoring/vms55.cfm>.

Heest, Peter Van, Rachel Burkhart, and Wyatt Curry. Effect of Turbidity on Dissolved Oxygen in

the Lake Macatawa Watershed. Rep. N.p.: n.p., n.d. Infobase Learning - Login. Hope

College. Web. 12 Mar. 2014. <http://www.fofweb.com/Science/default.asp>.

Perlman, Howard. "Water Properties: Dissolved Oxygen." Dissolved Oxygen, from USGS Water

Science for Schools: All about Water. Www.usgs.gov, n.d. Web. 11 Mar. 2014.

<http://water.usgs.gov/edu/dissolvedoxygen.html>.

United States. Dpt of Conservation and Recreation.Office of Water Resources. The

Massachusetts Lake and Pond Guide. By Michelle Robinson. United States Dpt of

Conservation and Recreation, 2005. Web. 23 Jan. 2014.

<http://www.mass.gov/eea/docs/dcr/watersuply/lakepond/downloads/lakebook.pdf.file.

1

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The Staple Maples

The effect of

Distance Between Trees (m)

on Glucose

Level (Bx˚)

By Mila Camargo Cortes (S86-4) and John Floros (S86-7)

2

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,

The Perks of Percolation

The effect of canopy cover on soil percolation

By Molly Carney and Athena Chu !!!

! "!

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! "!

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! "!

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The pHun,

Rapid Test! The Effect of Distance from Summit

(m) on Soil pH

By: Yuji Chan & Sophia Scanlan

!!!!

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1

2

Table of Contents ABSTRACT 3 INTRODUCTION 4 MATERIALS AND METHODS 6 RESULTS 8 DISCUSSION 11 ACKNOLEDGMENTS 15 WORKS CITED 16

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ABSTRACT When studying soil pH and leaves, it was discovered that soil pH is increased by acidic coniferous leaves. Because of the curiosity about this subject, this study was designated to discover if the distance from a tree had a correlation with soil pH, knowing that soil because more acidic due to the leaf pH being absorbed in the soil. The hypothesis was collected was if the distance from the tree increases, then the soil pH will increase, because the acidity decreases from the lack of leaves decomposing. The results exhibited the fact that the pH of the soil was affected by the amount of leaves that were absorbed into the soil. In each graph there was a large r2 value for the experiment, meaning a strong correlation, but when compared with the two other forests graphs, it was seen that the correlation was not applicable, due to different data point ranges. The data did not have a steady growth from the first data point at zero meters from the tree trunk to the end at a 4 meters distance from the tree or vice versa. Though there was no correlation in the data, both Spruce and Red Pine Forest showed, the soil got more acidic as the distance from the tree increased.

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INTRODUCTION The pH in any substance, including soil and water, is the measurement of the amount of hydrogen ions within the substance. Depending on the pH, substances could be acidic, basic, or neutral. When a material has a pH of seven, it is neutral. If the pH is less than seven, it is acidic, whereas if it is greater than seven, it is basic. PH is measured on a scale of 0-14. The pH of soil affects plant growth, as some plants are more likely to survive with either higher or lower pH. Some plants are already very acidic, such as coniferous pine trees, while others are less so, such as celtis occidentalis (common hackberry). Since the pH affects plant growth, it is observed that trees get their acidity from the soil, yet it is known that the acidity from pine needles affects soil. So this whole process turns into an endless cycle with the tree affecting the soil, and vice versa. Does the pH of soil affect the pH of a tree, or does the tree actually affect the soil instead? The data for this experiment will be collected at Drumlin Farm in Lincoln, MA . The forests within the farm will be Spruce, Hemlock, and Red Pine. Spruces, Hemlocks, and Red Pines are all coniferous. The data collected cannot be compared with all tree types because of the lack of deciduous trees in the experiment. Pine tree needles are known for acidity, so the Red Pine Forest is a good place to conduct the experiment. Above Hemlock Forest, there is an open pasture, so the soil acidity may be affected by the leaves from the deciduous trees. The sheep grazing field is next to the Spruce Forest, across a little stream, which could also affect the soil pH. Soil pH affects the growth and survival rate of trees as the acidity level could increase, and the amount of nutrients absorbed will either increase or decrease significantly, causing the trees’ health to be unstable and in danger. The pH could decrease as a result of rainwater leaching out ions, namely calcium, magnesium, potassium and sodium. When the acidity of the soil is too high, lime can be added to decrease conductivity (Bickelhaupt, www.esf.edu). Also, when leaves decompose, the nutrients and pH from the leaf are absorbed into the ground, and dragged down through the layers of soil due to gravity. As the distance from trees increases, the amount of leaves on the ground also decreases, ignoring the possibility of wind blowing the leaves around. With less leaves, the nutrients and acidity are not absorbed by the soil. For the majority of trees, a soil pH around 6.0-7.0 is preferred, though, coniferous trees typically prefer to grow in more acidic soils(http://ccesuffolk.org/). When the organic matter that rests on top of the soil is more acidic, the acidity slowly mixes with the soil, lowering the pH (Shinn, www.hortmag.com) . The leaves from coniferous trees are a greater contributor to increase in soil acidity than deciduous leaves. According to a past experiment, pine needles are known for making the soil around the tree slightly more

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acidic than further away from the tree (www.epa.gov). It adds another possibility that it is the pH of the tree that is affecting the pH of the soil. The proposed experiment will look into the effect of the distance from a tree in meters on soil pH, as compared with the pH of a leaf from the tree. The objective of this experiment is to see if the tree is affecting the acidity of the soil, or if the soil is affecting the state of the tree. If the soil pH decreases as the distance grows bigger, then it can be assumed that the pH of the tree is affecting the pH of the soil. However, if the soil pH increases as the distance from the tree grows, it can be inferred that the pH of the tree is affect by the soil pH, and leaches the nutrients out of the soil. This experiment will be conducted by testing the pH of the soil every two meters from the tree, to see whether it increases or decreases. If the soil pH increases as the distance from the tree grows bigger, then it can be assumed that soil pH affects the pH of the tree. Five soil samples and one leaf will be taken from each tree, and there will be three trees randomly selected from each forest. The independent variable is the distance (m) from the tested tree. The dependent variable is the soil pH. A contributing factor in this experiment will be the pH of the leaves from the trees. The controlled variables are the amount of soil/leaf used, the use and amount of distilled water (mL), the rapid-tester (pH testing capsules), the distance from the trees (m), the level from which the soil is collected from, and the type of litmus paper for measuring the pH of the leaves. There will be no controlled run in this experiment. The hypothesis for this experiment is: If the distance from the tree increases, then the pH in the soil will increase, because the acidity decreases from the lack of leaves decomposing (Rabin, http://njsustainingfarms.rutgers.edu). This research demonstrates how the pH in soil is affected by the distance from the trees. Since plants can only survive with certain pH levels in the soil, it will help gardeners, and people will know which plants could be paired up with other plants, depending on their acidity level. If more information is shared about the pH levels, and how it affects and is affected, the research could help for future experiments and plant growth. That way, less chemicals will be used to enhance the growth of plant species. All plants have different preferences for growing soil, and when a farmer is attempting to grow food, or a gardener wants to grow flowers, the soil pH can either make the plants prosper or die. Unnecessary resources and chemicals will then not be needed for the growth of plants, destroying the natural nutrients.

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MATERIALS AND METHODS The data was tested at three forests of Drumlin farm in Lincoln, MA. The three forests were Hemlock, Spruce and Red Pine Forest, all of which hold some coniferous trees. The procedure for this experiment was broken down into two main parts, which was the data collection and data testing. At each of the forests walk down 5 meters from the initial path, for non-biased results. To ensure that controlled soil samples were being taken, randomized locations were identified using the rand function on a TI-nspire calculator, within a 50 meter by 50 meter of a box shape, in the forest. With the randomization tests using the rand function on the TI-nspire calculator, two random places were chosen in each of the three forests. After having arrived 50 meters into the forest at the area and having found the random tree within the 50 by 50 meter area of measurement, five samples were taken from each tree using a small soil auger from 6 cm within the soil next to the tree, facing north with a one meters distance between each soil sample measured by meter sticks. Six trees will be tested in total from all the forests, two from each of the three areas, the samples were put into a plastic bag, labeled with the distance from the tree, which number tree and which forest the tree was from. After finishing these steps, a leaf was taken from all of the trees analyzed. These steps were repeated for all of the trees that were analyzed.

1. 2. Image 1: Rapitest ph Soil Tester (www.amazon.com) Image 2: Map of Drumlin Farm: blue = Hemlock Forest, red = Spruce forest, purple = Red Pine forest (www.massaudubon.org) Take out the Rapitest (pH testing capsules). Fill in the soil to the lowest line of the rapitest capsule, then fill to the 10 mL line of a 10 mL beaker with distilled water. After this add one pH Wide Range Test Tab Cap and mix by inverting until the tablet has disintegrated. Wait for 1 minute. Bits of material may remain in the sample. Compare

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the color of the sample to the pH color chart. Record the result as a pH measurement. To test the pH of the leaf, take out a pestle and mortar. Put 5-15 of the trees sampled needles in the mortar and add 10 mL of distilled water. Grind the leaves with the pestle for two minutes with force. After that, take out a strip of litmus paper and drop the liquid from the mortar on to the strip of litmus paper. Compare this to the pH color strip. Do this for all of the trees leaves from which soil samples were collected.

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RESULTS

Table 1: The effect of distance from a tree (m) on soil pH, as compared with the pH of a leaf from the tree (Spruce) Soil pH in Spruce Forest Distance (m) Tree A Tree B Average

0 7.250 6.500 6.875 1 6.500 6.250 6.375 2 6.750 6.250 6.500 3 6.300 6.250 6.275 4 6.250 6.500 6.375

Leaf pH = 7.00 Leaf pH = 6.00 Leaf pH = 6.50

Table 2: The effect of distance from a tree (m) on soil pH, as compared with the pH of a leaf from the tree (Hemlock)

Soil pH in Hemlock Forest

Distance (m) Tree C Tree D Average 0 6.750 6.000 6.375 1 6.500 6.250 6.375 2 6.000 6.500 6.250 3 7.250 5.500 6.750 4 7.500 6.250 6.875

Leaf pH = 5.00 Leaf pH = 5.00 Leaf pH = 5.00

Table 3: The effect of distance from a tree (m) on soil pH, as compared with the pH of a leaf from the tree (Red Pine)

Soil pH in Red Pine Forest

Distance (m) Tree E Tree F Average 0 6.0 6.0 6.0 1 5.8 6.5 6.1 2 5.5 5.5 5.5 3 6.3 5.0 5.6 4 6.0 5.3 5.6

Leaf pH = 4.5 Leaf pH = 5 Leaf pH = 4.75

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Graph 1: The effect of distance from a tree (m) on soil pH (Tree A & B)

Graph 2: The effect of distance from a tree (m) on soil pH (Tree C & D)

Graph 3: The effect of distance from a tree (m) on soil pH (Tree E & F)

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In this project, two trees were tested within each of the three forests. The soil pH was tested next to the tree up to 4 meters away, with 1-meter increments between each soil test. A soil pH for one tree was usually similar to the soil pH for the other tree within that forest. So was the pH of the leaves. However, other than these small similarities, there was no specific increase in the trends or patterns within the data. It could be assumed that the r2 value was so high because of the few data points. For practically all of the data samples, it became apparent that there originally seemed to be some pattern with the increase or decrease of the soil pH. Then the last couple of data points were outliers. For the data collected at Spruce Forest, the soil pH was on average around 6.5, with one outlier at 7.25. The outlier greatly affected the trend lines for the graph, as it offset the whole balance. The r-squared value for the average of the Spruce Forest was 0.55 (rounded). The leaf pH for the first tree in Spruce was neutral, so it affected the soil pH closer to the tree. In this forest, the averages seemed to follow a trend of increasing, and then decreasing as the distance to the tree grew. For Hemlock, the pH ranged from 5.5 to 7.5, not following any pattern. It was more of a collection of random values. The r-squared value for Hemlock was approximately 0.64. This is surprising, considering that one data point for pH was noticeably smaller than the rest. Other than that one data point, the soil pH followed a trend of decreasing, as the soil samples were slowly taken further away from the trees. The leaf pH remained consistent. With the data collected from Red Pine Forest, the pH seemed to follow a trend at first, but it was disrupted. The r-squared value for Red Pine Forests was about 0.53. Much like the soil pH of Hemlock Forest, the data eventually seemed like there was no trend. There were two apparent outliers for this graph (6.1 and 5.5). All of the data points fell around 5.0-6.0. The samples were the most acidic here.

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DISCUSSION This experiment was conducted to test the correlation between the distance from a tree (m) on soil pH, as compared to the pH of a leaf from the tree. The hypothesis for this experiment was: If the distance from the tree increases, then the pH in the soil will increase, because the acidity decreases from the lack of leaves decomposing (http://sustainable-farming.rutgers.edu). This hypothesis was not supported because factors such as wind could not be controlled. Therefore leaves shifted to different areas making the soil more acidic in certain areas and less acidic when there were less leaves absorbed at another soil data points. Even if this was controlled, the trees proximity to one another was roughly about 2-3 meters close, and the boundaries of the leaves overlapped, making some areas much more acidic than others. The repercussion of data contradicting the original hypothesis was due to variables that were not controllable. The data that was collected was precise and followed the procedure for the experiment at all times, for every step. Based on these facts, there was no experimental error, but simply no correlation in the data between the three forests that were tested at Drumlin Farm, Lincoln, MA. The majority of reliable sources answered that there is in fact a correlation between the distance from tree and soil pH. When leaves of coniferous plants that have acidic leaves sink into the O layer of the soil, that area where the leaves are absorbed into the soil becomes more acidic than others. Therefore less or no leaves are absorbed due to the higher level of acidity from the leaf. Therefore, resources on this subject claim that the closer the soil sample is to the tree, the more leaves the soil is able to absorb. This is supported because that leaves fall closer to their trees trunk, and so more acidic leaves will be absorbed thus creating a more acidic soil layer (lsuagcenter.com). In this experiment the sampling was also conducted at only coniferous locations, but showed considerably different results than the topic resources that were viewed for information. Other applicable causes for there being no correlation between the three forests are because of variables that were beyond control. Such variables being the wind changing the ideal landing point of the leaves destination to the ground. If all of the leaves had landed to the ground without any other applied movements, the original hypothesis would have had a higher likelihood of being supported. Factoring in these point would have been beneficial to the hypothesis. Another reason for no correlation was the time of season that the data collection took place. It was taken on March 7th, 2014, when all of the leaves had been absorbed in the soil for a few months already, and the leaves were working there way down into the A or B level of the ground. This made data collection less precise as the leaves were not fresh in the first O level of the ground with acidity.All

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data samples were taken six cm into the ground, though the soil sample that was put in the rapitest pH tester was from the top most part of the soil auger within two cm of the top most layer. Thus the soil sample being taken from the O level of the soil. The final reason for the inconclusive data was the close proximity from one tree to another. At all the three forests, the trees were all two to three meters apart. This caused an overlap between the trees and therefore, if there was no wind there still would have been overlap in acidity between the trees, thus creating very high acidity areas at points of overlap and also lower areas (http://www.fao.org). For these reasons the results between the three forests had no correlation, and is improper to suggest that there is any assurity in these results. The r2 value for the experiment was high, approximating at .6 for the three forests, but in the experiment there had to be a trend showing that the pH of the soil either got more acidic as the distance increased or less, in this case the data was to ranged to make any conclusions. Demonstrated in the graphs there were two major outliers for each one. If these were taken out then the data would show that there was a steady increase in acidity in both Spruce and Red Pine Forest. But Hemlock Forests data without the two outliers would have shown that the more the distance increased the more basic the soil got. The data was precise though, ranging in data by only .8 in soil pH. Yet due to the fact that outliers cannot be canceled, and two, not three forests showed similar data, the forests had no correlation that could be noted. Though there was no correlation between the distance and soil pH, there was a small correlation between the acidity of a leaf and the acidity of the soil under the tree. At Red Pine forest the leaves pH was very low, thus being more acidic. After doing tests in the soil pH it came to be that the pH was more acidic than the Spruce and Hemlock forest. This meant that the trees’ leaf pH had a direct correlation between the soil pH. This being because the leaves were absorbed by the soil after they fell, and thus collected the acidity of the leaf after it decomposed. The new hypothesis for this experiment would be that if the leaves of the tree is acidic then the soil will be more acidic because the leaves acidity is absorbed by the soil (trees of the world, 121). There are ways that this experiment could have been modified for better results in the future. So that there can be a better understanding of this concept of the effects of distance from tree on soil pH. The most ideal way to conduct the experiment is to get your own private indoor greenhouse from your money sponsor. Plant six trees, three different species of trees, with two of each, all ten meters apart. Let all of the plants grow adding the same amount of fertilizer and water to each of them. Then wait for all of the leaves to fall and then a month to two months later do the take the soil samples, as the leaves will be fresh in the O layer. Doing this would prevent any outside disturbance such as wind, season, and proximity, all of which would have been able to be controlled

13

at this greenhouse (http://www.lsuagcenter.com). Following this process would ensure no errors and variables that were not able to be controlled, due to outside weather, could be controlled doing the experiment in this way. Sufficient data was collected to test the hypothesis in this experiment, with a total of 30 data points in total, five from soil samples from each of the six trees. The new hypothesis then being: if the leaves of the tree is acidic then the soil will be more acidic because the leaves acidity is absorbed by the soil (trees of the world, 121). Some other errors in the testing, in which the samplers did have control over were not rinsing the soil auger after every sample, which led to errors; such as later soil samples being contaminated by the previous ones, partially changing its pH. The quantity of soil was not too large to have a major effect on the pH though future scientists would not want to make this mistake. To avoid this, soil auger must be washed everytime. During the first six tests with the rapitest pH testing kit, the inside was thrown into the soil, contaminating the soil with chemicals, but starting from approximately the seventh test the inside slurry of the kit was put in a bottle for later chemical disposal. To avoid polluting the environment, dump the slurry of the rapitest kit into the bottle for every pH test of the experiment. Questions about this experiment would be how the size of the tree may affect the soil pH as more leaves would have fallen on the ground. This was not factored in when conducting the experiment, and when comparing with different trees, the size of the tree should have been more close. Red Pine Forests tree size was a lot larger than Hemlock and Spruce Forest, and Red Pine similarly had a higher acidity that may have been due to the naturally larger size of this species of trees (http://www2.hawaii.edu). Another question that arose was how fast leaves fully absorbed into the soil. When conducting the experiment on March 7th all the leaves had fallen from the trees approximately five months ago, yet it was seen that there still were a lot of leaves on the ground, meaning that all the leaves were not absorbed in the O or deeper layers such as the A, B or even the deepest, C layer. This process of the leaves deteriorating back into the soil is called the nutrient cycle. This is where the soil absorbs the leaf and takes in its nutrients such as high levels of healthy nitrogen, phosphorus and other organic matter. Seasons primarily have an effect on the decomposition of leaves, and warm weather. With the winter of 2013-2014 in Massachusetts, factors such as snow, had a large effect on the soil decomposition. Weather, and the still cold weather were the main reasons for the slow soil decomposition (http://www.fao.org). Future scientists should research more in depth on how the pH of a leaf affects the soil pH, as there was a small correlation in that. This could help to gardeners and farmers as many plants need more acidic soil to grow and the gardener may want to have a more acidic tree such as a Red Pine bordering it to provide the acidic soil it needs to thrive. This research would be beneficial to all farmers and gardeners who are curious as to why

14

some plants grow better in some areas and not others. (http://njsustainingfarms.rutgers.edu)

15

ACKNOWLEDGMENTS I, Irfan Chaudhuri, would like to thank Zetty Cho for being an outstanding lab partner throughout the Knights of Science project. She was always attentive in taking data, making sure that the process went smoothly, and providing feedback and topic ideas to the process of the experiment. I would like to thank Mr. Ewins for teaching us how to take data to conduct the experiment and providing constructive feedback in our paper. Thanks goes out to Ms. Bomfim, Ms. Brooks and Ms. Jamison, for being at the three forests that we went to at Drumlin Farm, and helping with data collection. I would also like to thank the staff of Drumlin Farm for helping to guide us through the farm, and safely send us through the farm site. Lastly I would like to thank BB&N for funding this experiment. I, Zetty Cho, would like to thank Irfan Chaudhuri for being a spectacular lab partner throughout the Knights of Science field studies and papers. He was great at getting sources to help with our research, and stayed calm, composed and on track throughout data collection, even when there were small distractions and we realized that there wasn’t much correlation within our experiment. I would like to also thank Mr. Ewins for being our teacher, editing our drafty-drafts, and showing us possible methods we could use for data collection at Drumlin Farm. Thanks to Ms. Bomfim, Ms. Brooks, and Ms. Jamison for being the chaperones at the three forest we went to during the testing day. Also, thank you to the staff at Drumlin Farm for telling us more about the tree species and locations of each forest. Finally, thank you to BB&N for creating this project, and supplying us with the necessary equipment needed for the testing.

16

WORKS CITED Citations Used For Introduction Bassuk, Nina, Marcia Eames-Sheavly, and Robert Kozlowski. "Gardening Resources,

Cornell University." Gardening Resources, Cornell University. Department of

Horticulture, Cornell University, 14 June 2013. Web. 06 Mar. 2014.

<http://www.gardening.cornell.edu/factsheets/ecogardening/mineffortorn.html

>.

Bickelhaupt, Donald. "Soil PH: What It Means." Soil PH: What It Means. ESF, 2014.

Web. 06 Mar. 2014.

<http://www.esf.edu/pubprog/brochure/soilph/soilph.htm>.

"Effects of Acid Rain - Forests." EPA. Environmental Protection Agency, 4 Dec. 2012.

Web. 27 Feb. 2014. <http://www.epa.gov/acidrain/effects/forests.html>.

Londo, Andrew J., John D. Kushla, and Robert C. Carter. "Soil PH and Tree Species

Suitability in the South." LSU AgCenter. LSU Ag Center, 13 June 2012. Web. 01

Mar. 2014.

<http://www.lsuagcenter.com/en/our_offinces/parishes/bossier/features/forest

ry_wildlife/soil-ph-and-tree-species-suitability-in-the-south.htm>.

Rabin, Jack. "Improving Soils with Leaves and Other Local Organic Wastes." Improving

Soils with Leaf Application. N.p., 2012. Web. 13 Mar. 2014.

<http://njsustainingfarms.rutgers.edu/soilcompost.html>.

Shinn, Meghan. "Leaves and Soil PH." Horticulture. N.p., 2 Nov. 2010. Web. 7 Mar.

2014. <http://www.hortmag.com/featured/leaves-and-soil-ph>.

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Citations Used For Discussion

Bassuk, Nina, Marcia Eames-Sheavly, and Robert Kozlowski. "Gardening Resources,

Cornell University." Gardening Resources, Cornell University. Department of

Horticulture, Cornell University, 14 June 2013. Web. 06 Mar. 2014.

<http://www.gardening.cornell.edu/factsheets/ecogardening/mineffortorn.html

>.

Bot, Alexander. "The Importance of Soil Organic Matter." The Importance of Soil Organic

Matter. FAO, 2005. Web. 17 Apr. 2014.

Hue, N.V. "Acid Soils in Hawaii: Problems and Management." Soil Acidity. University of

Hawaii, n.d. Web. 17 Apr. 2014.

(ISSS), International Science of Soil. "World Reference Base for Soil Resources." World

Reference Base for Soil Resources. World Reference Base for Soil Resources, 1998. Web.

17 Apr. 2014.

Londo, Andrew J., John D. Kushla, and Robert C. Carter. "Soil PH and Tree Species

Suitability in the South." LSU AgCenter. LSU Ag Center, 13 June 2012. Web. 01

Mar. 2014.

<http://www.lsuagcenter.com/en/our_offinces/parishes/bossier/features/forest

ry_wildlife/soil-ph-and-tree-species-suitability-in-the-south.htm>.

Rabin, Jack. "Improving Soils with Leaves and Other Local Organic Wastes." Improving

Soils with Leaf Application. N.p., 2012. Web. 13 Mar. 2014.

<http://njsustainingfarms.rutgers.edu/soilcompost.html>.

Russell, Tony. Trees of the World. London: Anness, 2007. Print. Lorenz Books.

pHreaky Conductivity

The effect of Soil pH on Soil Conductivity

A Study By:

Daniel Noenickx SIN S82-12-&-

Tayseer Chowdhury SIN S82-3

Table of Contents

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Section Author Page

AbstractIntroductionMaterials & MethodsResultsDiscussionAcknowledgementsWorks CitedAppendix

Tayseer ChowdhuryDaniel NoenickxTayseer ChowdhuryDaniel NoenickxTayseer ChowdhuryBoth AuthorsBoth AuthorsDaniel Noenickx

334610121314

ABSTRACT To find whether or not the pH in soil affects the electrical conductivity (EC) in any way, a group was sent to test the soil pH and conductivity in the sites of Farmyard, Vernal Pond, and Spruce Forest, at Drumlin Farm, in Lincoln, MA. The original hypothesis was that: If the pH level is low (acidic), then the conductivity will increase, because low pH means there is an increase in hydrogen ion concentration, giving more ions for electrical currents to pass through (Goodarzi, 7). However, after several data points were collected, a problem was found: Checking the EC consisted of just sticking the probe into the ground, but the pH was a bit more challenging. It was believed that to check the pH, a soil sample would be taken, and used to fill a pH Rapitest kit to the dotted line, before putting in a whole pH test pill into the solution, and allowed to settled. But it was told that the pill was supposed to be split. The white powder on the inside was supposed to be put into the mixture, and the color of the mixture was observed. The data was all collected incorrectly, so new sites were chosen to collect data: the BB&N Grounds, the Noenickx backyard, and the Chowdhury backyard. However, as the data was collected and put into graphs and tables, it was discovered that the r2 value was too low to show any correlation between the pH and the EC of the soil. This was most likely because EC is a measurement of all the ions in the soil, not just Hydrogen ions, so the number of other ions in the soil outweighed the pH’s significance as an individual to the conductivity. However, it is also possible that, because our EC meter measured in millisiemens per centimeter, which is a less precise unit than microsiemens per centimeter at this level. Therefore, the data is not as precise as it could have been. When this experiment is next done, the data should be collected in microsiemens/centimeter, as it will be more accurate and it would be possible to see a minuscule correlation between the pH and the EC of the soil.

INTRODUCTION The Power of Hydrogen (pH) measures the concentration of hydrogen ions in a solution, and tells how basic or acidic a substance is. A hydrogen ion forms when a hydrogen atom has a positive charge. Conductivity is the measure of how well a material can conduct an electrical current, higher conductivity has been found to increase the yield on farms (Grisso, 3). Crop yield is also best when soil pH is close to neutral, 7 on the pH scale (Stites). Both pH and conductivity affect the yield of crops, so it suggests that they may affect one another.

The experiment will be conducted at three different locations in Massachusetts. The three sites are: behind the BB&N Middle School Science Labs, Cambridge, MA; Noenickx Backyard, South Boston, MA; and Chowdhury Backyard, Medford, MA. BB&N has few trees and receives a large amount of sunlight. The Noenickx Backyard has large amount of grass, trees and plants. The Chowdhury Backyard is weedy, and receives a large amount of sunlight. There are differences among the sites which may change the soil pH. It is believed that when the soil pH changes it will affect the conductivity. The soil at each site is exposed to different amounts of sunlight, have

!

different plants, temperatures, animals, moistness, are cared for differently, and the texture of the soil varies at each site.

The growth and health of plants is affected by the pH of the soil (esf.edu). The pH of soil depends on the soil's parent rock, weathering, rainfall received, the structure of soil, and the overlying vegetation, many of these factors also affect the conductivity of soil. pH affects the availability of nutrients to plants (fofweb.com). Soil pH can also be affected by leaching of materials into the soil, or decomposing organisms (esf.edu). Conductivity measures how well a substance can carry electrical current. Studies have found that higher conductivity produces a higher yield in crops (Grasso, 3), and neutral soil results in higher crop yield (Stities). Higher pH would mean there are more ions in the substance, because there are more hydrogen ions in the substance there would be more ions to carry the electrical current (Goodarzi, 7).

The proposed experiment is the effect of soil pH on soil conductivity. The objective of the experiment is to see if there is a correlation between soil pH and soil conductivity. This will be tested by collecting ten soil samples from each of the three different sites, and testing the pH level and conductivity of each sample. The independent variable for the experiment will be soil pH, and will be measured using the pH scale. The dependent variable for the experiment will be conductivity, which will be measured in siemens per meter (S/m). Important controlled variables include: tool used to measure conductivity and pH, day of soil sampling, procedure for measuring conductivity and pH, the amount of soil per sample, and how deep the soil samples are collected. The hypothesis presented for this experiment is: If the pH level is low (acidic), then the conductivity will increase, because low pH means there is an increase in hydrogen ion concentration, giving more ions for electrical currents to pass through (Goodarzi, 7).

With the information collected from this experiment, farmers will have a better grasp on how fertilizers change the acidity and conductivity of soil. Using the information gathered there can be a higher yield of crops from a smaller piece of land by making the soil pH and conductivity fit the needs of the crops. Farmers can also use the information gathered from this experiment to use the fertilizers to change the pH, which in return will alter the conductivity without them having to add chemicals to change the conductivity.

MATERIALS & METHODSThe original method used to find 10 random sites was made using the quadrats-

with-coordinates technique. At each site, a 10-by-10 meter square was created, with each meter on each line marked with a single flag. Progressing from the bottom-left corner of the square, each point, chosen by the random function on a calculator, was then where we could collect our data samples. However, the error caused a need to change the method, because the new sites did not have enough space for a 10-by-10 meter square. In order to choose the 10 random soil samples from each site,a 9-meter line was measured, and at each meter was a data point. The EC was measured using the probe, and

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a small auger was used to gather the soil. This soil was used to measure the acidity of the area, using the pH Rapitest kit. To test the soil pH using the soil pH test kit, about 20 mL of soil was put into a soil pH test kit. Distilled water was then used to fill the test kit to the top of the dotted line. The test kit was then shaken for 20 seconds to easily and efficiently stir up the mixture. The color of the solution was then compared to the key on the face of the test kit. The number was recorded in the Field Notebook, and the process was repeated with all the remaining samples.

Figure 1: The pH rapid test kit. This figure shows what the soil pH kit is like, and gives us a side-by-side comparison of a solution after the pill is added, to the colors on the chart

to show the acidity of the soil.

Conductivity of the soil was tested using the EC probe, and rinse water. At each point, the EC probe was simply stuck into the ground, gently, so as not to break it, and allowed to sit for 15 seconds, before the number was recorded in the Field Notebook and the process was repeated at the remaining data points.

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Figure 2: The EC meter. The EC meter was used to find the

electrical conductivity of each data point, measuring it in

millisiemens per centimeter.

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Graph two is similar to one it the way that it shows all of the data, the difference is the linear regression line is for the data all together. Here the r squared value is 0.062, and the line is right between the Noenickx data and the other data. The line diagonally points down towards BB&N. Graph 3 shows the average pH of each location. BB&N has an average of 6.8 and a standard deviation of 0.26. Noenickx has a value of 6.s and a standard deviation of 0.42. Chowdhury has a value of 6.1 with a standard deviation of 0.21. Noenickx has major error bar overlap with Chowdhury and a slight overlap with BB&N, while BB&N and Chowdhury clear each other with BB&N higher.

S

Finally, graph 4 shows the average value of conductivity per location. BB&N has a conductivity value of 0.00, through and a standard deviation of 0.00. At BB&N all data points had a 0.00 conductivity. Noenickx has a value of 6.0, much higher than both BB&N and Chowdhury at 0.01. Noenickx’s and Chowdhury’s standard deviation is 0.01, and none of the error bars overlap.DISCUSSION

The hypothesis stated that: If the pH level is low (acidic), then the conductivity will increase, because low pH means there is an increase in hydrogen ion concentration, giving more ions for electrical currents to pass through (Goodarzi, 7). The hypothesis was not supported because the conductivity levels were too low as a group. Almost all of the points were .01 or 0 millisiemens per centimeter, but the pH varied too much for there to be any correlation, as the conductivity did not seem to move in correlation with the pH.

A very reliable source had said that the level of pH does affect the electrical conductivity (EC) in soil (Ouhadi, Shiraz). However, the data from this experiment does not show any correlation. It is possible that, because the areas tested had a large amount of leaves covering the top soil, the grass had less light to complete photosynthesis. Because of this, the plants did not photosynthesize as much, and did not release as much carbon dioxide (CO2) into the ground, causing the pH to stay acidic(faculty.clintoncc.suny.edu/). Because EC is simply like a measurement of all nutrients in the soil, it is possible that there were simply too many other variables in the soil to accurately get a reading on whether or not the pH affected the EC in a direct and large way.

However, the data collected may have been slightly inaccurate. For one, the probes measured in millisiemens per centimeter, which is about 1000 times the size of microsiemens per centimeter. Since it was not measured in microsiemens per centimeter, the readings given by the EC probe was not as accurate as possible, which explained why data like .01 ms/m would come up, rather than 100, or 75, or 22. Because it was a larger unit, more was left out, so the reading was much less accurate.

Scatter plots were used to compare the data for each individual site, but when comparing all three sites, a bar graph was used containing the averages for all the data. One scatter plot with all the data was also created, showing the huge difference in data from one site to the others. For the BB&N Grounds, the conductivity was, at most, .01 mS/cm. Since much of the data was the same, many of the points overlapped, making only four points visible. The only four points that the data had, showed that the data points either had .01 mS/cm with 6.5 pH, 0 mS/cm with 6.5 pH, .01 mS/cm with 7 pH, and 0 mS/cm with 7 pH.

Graph 2, the graph of the Noenickx backyard, is a bit more exciting. The Noenickx data, unlike any of the others, reaches heights of .08 mS/cm, with the lowest being .04 mS/cm. Again, a few of the points were overlapping, but the actual problem was the pH levels. Even though the Noenickx backyard conductivity was much higher

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than the other two sites, it’s pH levels were ranging from about 5.5 to 7. But, the conductivity grew larger as the data point’s pH got higher, instead of lower. The conductivity had increased with the decrease of Hydrogen ion concentration, which should have made it more conductive rather than less.

Graph 3, from the Chowdhury backyard, was very similar to the graph of the BB&N Grounds, most likely because the soil was very similar at both sites. It had all of the data overlapping on 4 data points, and each pair had different conductivity levels, .01 and 0, but the pH levels were the same, having pH levels like 6 and 6.5. The data was very similar to what the BB&N Grounds showed us.

The last scatter-plot graph, comparing the data from all three points, showed just how different the Noenickx backyard is from the BB&N Grounds and the Chowdhury backyard. In this graph, the data is shown more spread out. However, of the 6 points on the bottom of the graph, there are actually 20 points shown: 10 from the BB&N Grounds and 10 from the Chowdhury backyard. The rest of the data, starting with EC levels of .04 and up, are from the Noenickx backyard, showing that there is definitely something different about how the Noenickx backyard is cared for. The Noenickx soil was very different from the Chowdhury backyard and BB&N Grounds, which were very similar in data.. However, all of the points were in the same range of pH, which shows that it may be something else entirely that is affecting the conductivity.

The two bar graphs were just side-by-side comparisons of the averages of each area’s data. For the pH bar graph, it showed that the BB&N Grounds had the highest pH average, having a 6.8, while the Noenickx backyard was in second with 6.2, and Chowdhury in last with 6.1. However, in the conductivity graph, the Noenickx backyard was largest, with a .06, compared to the .01 from the Chowdhury backyard and the 0 from the BB&N Grounds.

All of the regression bars were showed almost no correlation. A r2 value of at least .5 was needed to show there was a large correlation between the IV and DV. However, none of sites got anywhere near that. The data had almost no trend, proving to the experiment that there was little to no correlation between the pH and EC of the soil.

The data wasn’t accurate enough to find a good reading. While the pH should affect the EC, it is possible that the areas had large amounts of other nutrients and ions, which would affect the amount of EC more than just the pH would. The EC was also measured in millisiemens per centimeter, rather than microsiemens per millimeter. Because of this, the data was most likely not as accurate as it would have been, because the microsiemens would have allowed us to find more precise data for the experiment, to show that there might have been differences between the data points. If it was measured in microsiemens per centimeter instead, it could have been more precise and conclusive. However, because it was not as precise as it could have been, I am standing by my 1st hypothesis: If the pH level is low (acidic), then the conductivity will increase, because

!!

low pH means there is an increase in hydrogen ion concentration, giving more ions for electrical currents to pass through (Goodarzi, 7).

The experiment was not perfect: it wasn’t conclusive enough to find out whether the hypothesis was correct. But a correlation may have been found if other data was taken. There was also one very large error at Drumlin Farm: The data had been collected wrong for the entire trip. We were supposed to split the pills and put the powder on the inside, rather than the whole pill. This rendered all past data useless, and required that the procedure be repeated for the experiment in other areas. If we had done all the data correctly, the experiment would have been over much quicker, and there would have been different data points. A new, beneficial experiment would be to see how much Hydrogen there is in the nutrients of the soil, to see if the other nutrients do overweigh the Hydrogen’s say in the soil pH.

ACKNOWLEDGMENTSI would like to thank all the specialist at drumlin farm for helping us in finding

our locations. I would also like to thank Martha at Farmyard for helping us collect data without being pestered by goats. Ms. Larocca also helped us throughout our paper and experiment, and Ms. Schultheis for attempting to collect data correctly at the end of the field trip.

I’d like to thank everyone who was with us on each step of our experiment, whether it was knowingly or unknowingly. For the very first thanks, I would like to thank the science department, especially Mrs. LaRocca, for leading us throughout the entire experiment and supplying us with the necessary tools, and Mrs. Schultheis, for pointing out we had collected nearly all of our data points incorrectly. I would also like to thank the people of Drumlin farm, for, even though we had incorrectly gathered data there, and did not use the data at all, the specialists at each site was very helpful, gave whatever data was needed, and also seemed very interested in everyone’s experiment. I would also like to thank the internet and the library, for it provided us with the data that our hypothesis could be true, and for the large amount of information that it had on the topics we needed. Of course, I must also thank Easybib, for, without it, how would I cite my sources? So, as to summarize it, thank you to everyone, for all who helped.

!"

WORKS CITEDAuthor 1 (Tayseer)"A Citizen's Guide to Understanding and Monitoring Lakes and Streams."

Www.ecy.wa.gov. Department Of Ecology, State Of Washington, n.d. Web. 8 Mar. 2014. <http://www.ecy.wa.gov/programs/wq/plants/management/joysmanual/streamph.html>.

"The Electrical Conductivity of Water." Smart-fertilizer.com. Smart!, n.d. Web. 8 Mar. 2014. <http://www.smart-fertilizer.com/articles/electrical-conductivity>.

Goodarzi, A. R., and V.R. Ouhadi. "FACTORS IMPACTING THE ELECTRO CONDUCTIVITY VARIATIONS OF CLAYEY SOILS." Www.shirazu.ac.ir. Shiraz University, Apr. 2007. Web. 7 Mar. 2014. <http://www.shirazu.ac.ir/en/files/extract_file.php?file_id=724>. PDF

Gregory, Michael. Photosynthesis. Clinton.edu. Clinton Community College, n.d. Web. 14 Apr. 2014. <http://faculty.clintoncc.suny.edu/faculty/michael.gregory/files/bio%20101/bio%20101%20laboratory/photosynthesis/photosynthesis.htm>.

Hanlon. "Soil PH and Electrical Conductivity: A County Extension Soil Laboratory Manual." Edis.ifas.ufl.edu. University Of Florida, N.d. Web. 28 Feb. 2014. <http://edis.ifas.ufl.edu/pdffiles/SS/SS11800.pdf>. PDF fileAuthor 2 (Danny)Bickelhaupt, Donald. "Soil PH: What It Means." Soil PH: What It Means. College of Environmental Science and Forestry, n.d. Web. 01 May 2014. <http:// www.esf.edu/pubprog/brochure/soilph/soilph.htm>.Goodarzi, A. R., and V.R. Ouhadi. "FACTORS IMPACTING THE ELECTRO

CONDUCTIVITY VARIATIONS OF CLAYEY SOILS." Www.shirazu.ac.ir. Shiraz University, Apr. 2007. Web. 7 Mar. 2014. <http://www.shirazu.ac.ir/en/files/extract_file.php?file_id=724>. PDF

Grisso, Robert, Mark Alley, David Holshouser, and Wade Thomason. "Precision Farming Tools: Soil Electrical Conductivity." Virginia Cooperative Extension. Virginia Cooperative Extension, n.d. Web. 1 May 2014. <http://pubs.ext.vt.edu/ 442/442-508/442-508_pdf.pdf>.Publication 442-508.PDFStites, Dean. "The Effect of Soil PH on Crop Yield." The Morning Sun [Pittsburg PA] 30 Jan. 2011: n. pag. Web. <http://www.morningsun.net/x286173897/The-effect- of-soil-pH-on-crop-yield>.Rosen, Joe, and Lisa Quinn Gothard. "pH/pOH." Science Online. Facts On File, Inc. Web. 1 May 2014. <http://www.fofweb.com/activelink2.asp? ItemID=WE40&SID=5&iPin=EPS0166&SingleRecord=True>.

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The effect of nitrate level (ppm) on pond organism density

Maïa Cullen (S81-3) Emory Sabatini (S81-13)

2

TABLE OF CONTENTS

Section Primary Author Page

Abstract Cullen, Maïa 3

Introduction Cullen, Maïa 3

Materials and Methods Cullen, Maïa 5

Results Sabatini, Emory 6

Discussion Sabatini, Emory 10

Acknowledgments Cullen, Maïa

Sabatini, Emory 14

Works Cited Cullen, Maïa

Sabatini, Emory 15

3

ABSTRACT

This experiment was conducted at Drumlin Farms, in Lincoln, MA, and was designed to test the effect of nitrate levels on organism density. Nitrates are a common component in most fertilizers, and this experiment was designed to see how these fertilizers would affect pond life and organism growth. In order to test the nitrate levels and organism density, fifteen trials were collected at each pond, first testing the nitrate levels with the Vernier Nitrate Probe, and then collecting small samples, and counting the visible organisms using a magnifying device. It was expected that the organism density would be higher if the nitrate levels were lower. This is because a higher concentration of nitrates sparks algal blooms. This sudden and large amount of algae uses most of the dissolved oxygen to fuel itself, causing other animals and plants to die of oxygen depletion. The results showed that the effect of nitrate on organism density was minimal, and almost nonexistent. The data was overall very inconclusive and imprecise. Vernal Pool had 0 organisms for all 15 trials, while the organism density for the other ponds was much higher, but still inconclusive. Poultry Pond had the least precision, and the data was very similar for nitrate levels. Boyce Pond had mixed precision, but samples with 51-60 organisms were conclusively higher in nitrate than samples with 31-40. Overall the data was inconclusive, showing a low correlation between nitrate levels and organism density.

INTRODUCTION

About 78% of the air that is breathed by animals is made up of nitrogen. In 1772 scientist Daniel Rutherford discovered nitrogen, naming it “noxious air”. Around the same time, scientists Scheele, Cavendish, and Priestley were studying dephlogisticated air, which was a theory to explain combustion. This air had no oxygen, and nitrogen became known as “air without oxygen” (http://www.webelements.com/). Nitrogen is used in fertilizer and is emitted by sewage waste. High nitrate levels in a body of water are usually associated with runoff from a water treatment plant or fertilizers in crops or fields. Nitrogen is an essential element to plant life, and is crucial to the growth and nourishment of microorganisms in water (http://water.usgs.gov). The nitrogen cycle (as shown in figure 1) shows how nitrogen moves from one state to another through air and water. It originates in the air, moving into the water in the form of algae. Organisms will consume the algae, causing decay of organic matter. The organic matter turns into nitrates, and ammonium, which slowly move up and back into the air to repeat the cycle.

This experiment will be conducted at Drumlin Farm, located in Lincoln, MA. There are 5 different ponds inside the 312 acres of the farm. The ponds that will be tested in this experiment are Poultry Pond, Bathtub Pond, and Vernal

Figure 1: Nitrogen Cycle

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Pool. Poultry Pond is located near the animal enclosures, meaning it gets the runoff water and manure. Vernal Pool is located on the edge of the farm’s perimeter, and Boyce Pond is located just south of Boyce Field, and is surrounded by fields, receiving run off from the crop soil.

When visiting Drumlin Farms in September, it was observed that Poultry Pond had a large amount of algae covering the surface. This observation can be helpful to make inferences about which ponds will have a higher density of organisms, based on how nitrate affects algae. If nitrates increase in a certain pond, the algae or plant life will increase as well, since nitrate is a source of food for many aquatic plants (peer.tamu.edu/). When there is a large amount of algae, the amount of dissolved oxygen in water decreases, because the algae are not able to complete photosynthesis at night (www.ces.ncsu.edu/). When the dissolved oxygen levels decrease, fish kills occur because fish are not able to breathe in enough oxygen through their gills to survive. This shows that nitrates can indirectly affect the organisms of a pond (www.nccwep.org/).

In this experiment, the independent variable is the nitrate levels for each pond and the dependent variable is the density of species per pond. In the proposed experiment, the variables that will be kept constant are the amount of water tested for each trial, the probe brand and model, the organism counting method, and the location of water collection within each pond. In addition, the experiment will be conducted with the same weather or water temperature throughout the testing and collecting procedures.

The hypothesis set forth is: If nitrate levels are higher in a specific pond then the organism density will decrease in that pond because when nitrate levels are higher, algae and other water plant growth increases (peer.tamu.edu). When algae increases, there is also a decrease in dissolved oxygen levels (www.sjrwmd.com). This is because the algae uses large amounts of dissolved oxygen to fuel itself during the nighttime when it cannot complete photosynthesis (www.nccwep.org). Also, bacteria use the dissolved oxygen to feed on the algae (www.lenntech.com). Because of these two factors the organism density decreases because they cannot survive without a sufficient amount of dissolved oxygen (www.ces.ncsu.edu).

This experiment has the potential to help improve overall understanding of why different ponds and environments have different organism densities, as well as what the best environment for water organisms to prosper in. This experiment will also further the comprehension of nitrates and their influence on water quality and aquatic organisms. It will help bring up new questions and experiments to increase knowledge and maybe prevent fish kills caused by too much nitrate in the future.

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MATERIALS AND METHODS This experiment took place

at Drumlin Farm in Lincoln, MA. The three ponds that were tested (see figure 1) are Boyce Pond (#15), Poultry Pond (#11) and Vernal Pool (#14). Three different ponds were being tested in this experiment, with fifteen trials each (total of 45 trials). Each pond had five different trial spots around the perimeter, where water was taken three times at each spot to test both the nitrate levels and species density for each of the three trials.

In order to randomly determine the five points of testing around the perimeter of each pond, the Ti-Nspire calculator (see figure 3) was used to generate 5 different numbers in between 1 and 360 for each pond. These points represent angles, and a compass was used to point in show the direction that was represented by the angle degree. Each of these points was then marked using stakes, to remember where the testing/data collection points were. At the first point, water was collected in three 118 mL containers, in order to have three different samples at each point around the perimeter of the pond.

The pre-calibrated Vernier Nitrate Ion Selective Electrode (see figure 2) was connected to the Ti-Inspire Calculator (see figure 3), and then rinsed using the distilled water provided. The tip of the nitrate probe was inserted into the water

sample in order to calculate the nitrate level. The probe was left in the sample for sixty seconds; long enough to settle on a reading. The reading was then recorded into the data table, as well as the Ti-Nspire Calculator. This process was repeated for each of

the three samples so that 3 different readings were obtained at each test site. These steps were repeated for each stake around the pond to have an overall idea of the pond’s nitrate levels.

Each of these water samples was also examined using the magnifying device to estimate the number of organisms each sample contained. The results were then recorded in the same table as the nitrate levels (one table per pond). These steps were repeated for the three different ponds in order to have 45 total trials for both nitrate level and organism density.

Figure 2: Vernier Nitrate Ion-Selective Probe

Figure 1: Drumlin Farm Sites

Figure 3: Ti-Nspire Calculator

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RESULTS

Table 1: The effect of nitrate level (ppm) on pond organism density at Vernal Pool

Table 2: The effect of nitrate level (ppm) on pond organism density at Boyce

Pond

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Table 3: The effect of nitrate level (ppm) on pond organism density at Poultry Pond

Graph 1: The effect of average nitrate level (ppm) on estimated pond organism density at Vernal Pool

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Graph 2: The effect of nitrate level (ppm) on pond organism density at Boyce

Pond

Graph 3: The effect of nitrate level (ppm) on pond organism density at Poultry Pond

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Graph 4: The effect of nitrate level (ppm) on pond organism density at all Ponds

Graph 4 shows that increases in nitrate levels do not correlate with increases in organism density, as results are staggered between and within each pond. At Poultry Pond, nitrate levels for organism counts between 1 and 10, 21 and 30, and 31 and 40 all averaged to 2.4 ppm, while nitrate levels for organism counts between 11 and 21 averaged to 2.7. Standard deviations for Poultry Pond organism counts were large, the highest being 1.2., creating an error bar that overlapped with all others. At Boyce Pond, results were somewhat staggered, though as shown in Graph 2, nitrate levels rose with organism counts, with the exception of counts ranging between 1 and 10. Counts ranging between 11 and 20 had an average nitrate level of 2.3 ppm, while counts between 21 and 30 had an average nitrate level of 2.9 ppm. Finally, estimations from 51 to 60 had an average nitrate level of 3.5 ppm. This shows a correlation between nitrate levels and organism density. However, error bars overlap extensively between all four-organism densities.

Graph 1 shows that Vernal Pool, while having a middle average of 2.5 ppm for the nitrate level, contained zero detectable organisms in the water. The highest nitrate level for the pond, as shown in Table 1, was 4.2 ppm, and the lowest level was 1.0 ppm. At testing Location 4 (Trials 10, 11, and 12), some of the highest nitrate levels were recorded. At this location, a fallen tree was lying in the water, it’s

Figure 1: Vernal Pool, Testing Location 4

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roots half-submerged in the pond. The water surrounding the trunk was a yellow-green color, and foam covered the surface of the water (See figure 1), but no organisms were found at the testing site.

Boyce Pond had the highest and lowest averages overall for nitrate levels, the highest being 3.5 ppm for counts between 51 and 60. The lowest was 2.3 ppm for counts between 11 and 20. Data overall was fairly imprecise, with nitrate levels ranging between 1 and 5 ppm. Organism density was also very imprecise, with the lowest amount of organism recorded being 0, and the highest being between 51 and 60. Data for organism counts between 31 and 40 at Poultry Pond proved to be the most precise, the average nitrate level being 2.4 ppm, although only one point of data was recorded for this count. The second most precise data point was at Boyce Pond, for organism counts within 51 and 60. The average nitrate level for this count was 3.5. Overall, data was shown to be fairly staggered and imprecise. DISCUSSION

This experiment was conducted to determine whether there is a correlation between nitrate levels and pond organism density. The original hypothesis for this experiment was: If nitrate levels are higher in a specific pond then the organism density will decrease in that pond because when nitrate levels are higher, algae and other water plant growth increases (peer.tamu.edu). When algae increases, there is also a decrease in dissolved oxygen levels (www.sjrwmd.com) because the algae uses large amounts of dissolved oxygen to fuel itself during the nighttime when it cannot complete photosynthesis (www.nccwep.org) and bacteria use the dissolved oxygen to feed on the algae (www.lenntech.com). Because of these two factors the organism density decreases since they cannot survive without a sufficient amount of dissolved oxygen (www.ces.ncsu.edu). The hypothesis was not supported in the experiment, as estimated organism counts did not fall as nitrate levels rose. Within and between each pond, all error bars overlapped. Therefore, the data was found to be inconclusive for all ponds. Instead of organism counts falling while nitrate levels rose, the data was fairly imprecise and unusual, as different organism counts had seemingly random average nitrate levels. The error bars indicated a wide range of data for nitrate levels, so there was little precision in the data. Because of all the imprecision, there is little confidence in the data. Sufficient data was not collected for a valid conclusion, as no conclusion could be made from the data. Research showed that organism density should fall as nitrate levels rose, as more nitrates stimulated algae growth (peer.tamu.edu). Algae takes dissolved oxygen from the organisms, which then lowers the amount of organisms in the pond (www.ces.ncsu.edu). Yet, this research was not supported by the data collected in this particular experiment. Something to note was that during the first farm visit in the fall, Poultry Pond was covered in duckweed; a type of plant that behaves similar to algae, as it’s growth is often stimulated by excessive nitrates (Ke Xue, www.ncbi.nlm.nih.gov). But, when the experiment was tested months later, in the spring, the pond did not have nearly as much duckweed on the surface. This may have been because ponds tend to have less algae during the winter, and algal blooms only usually occur in April (Lynch, ohioline.osu.edu), which is exactly when the experiment was tested. Each pond,

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during the spring/summer, may have received nitrogen run-offs from surrounding fields. But, since no crops were grown in the winter, ponds would receive less nitrogen. Therefore, organisms were able to grow and reproduce more as they had the necessary amount of oxygen since excessive nitrates were not causing algae to steal the dissolved oxygen. A similar study tested in 2009 on the effect of nitrate toxicity on aquatic animals shows that freshwater animals can be harmed by high amounts of nitrates in the water (Camargo, www.waterboards.ca.gov). This agrees with the original hypothesis stated at the beginning of the experiment. Since the original hypothesis was not supported by the results, a new one is set forth: If the nitrate levels are tested in a specific pond then that pond’s organism density will not appear to be affected by the nitrates because algae growth has not yet been stimulated by nitrate fertilizer run-offs because it is still April (Lynch, ohioline.osu.edu); therefore the organisms in that pond will be able to survive in a moderately nitrate filled environment.

Another possibility for why data did not support the original hypothesis is that errors occurred during the testing of the experiment. First, the testing procedure was not properly followed during the entire testing period of the experiment. Due to time constraints, exact organism counting procedures were not followed. Instead of counting all organisms, organism counts were estimated, which affected the precision and accuracy of the data. Therefore, this may have influenced data. This error occurred at both Poultry Pond and Boyce Pond. Boyce Pond also experienced other time constraint errors, such as nitrate probe testing being reduced from sixty seconds to ten seconds. This may have provided a less accurate reading, which affected the results. At Vernal Pool, no organisms were found, but later it was discovered that some might have been overlooked in murky water or mistaken for inorganic or other organic material. It was noted at the end of the testing period that some organisms had been found, but none had been recorded. These errors influenced data and caused imprecision and inaccuracy, which lead to an inconclusive set of results. Most of the errors that occurred during the experiment could have been eliminated if more time had been given for testing at each site.

The experiment could be changed so that data could be more conclusive and accurate. First, more time could be given at each site so that data could be better collected and testing procedure could be more accurately followed. Calculators used for testing failed more than once at each site, causing time to be taken away from testing. Also, less water could be sampled so that organisms could be better accounted for, and the data could have more accuracy. Lastly, probe technology could have been improved for better readings, as both calculators and probes sometimes did not work during the testing of the experiment. Similar experiments that could relate to this experiment are “the effect of phosphate levels (ppm) on pond organism density” or “the effect of nitrate levels (ppm) on pond organism diversity”. These experiments could be tested in the future to possibly re-answer the question posed in this experiment.

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ACKNOWLEDGEMENTS I, Maia Cullen, would like to thank Ms. Svatek for helping us and giving

us great feedback and comments on our earlier drafts, as well as for helping us plan out our experiment when we still weren’t sure exactly how to proceed or carry out the experiment. In addition, I would like to thank Ms. Schultheis for lending us a calculator after one of ours was lost, and for saving our data that would not have been possible without her. I would like to acknowledge all of the Drumlin Farms teacher naturalists that made this experiment and experience possible, as well as for giving us background information on our ponds and habitats to enhance our understanding of the surroundings, and the science department for organizing this project. I would also like to thank Olivia Friend, for her help in designing our mascot, Salvador the Swordfish, our experiment mascot. Finally, I would like to thank Emory, who was an amazing science partner, and was really fun to work with. He was a positive influence, and would always get things done. Without all of these people, we would never have been able to do this, so thank you all once again!

I, Emory Sabatini, would like to thank everyone who helped out with our experiment, both at Drumlin Farm and here at the BB&N Middle School. First, I’d like to thank Ms. Haug, Ms. Schultheis, Mr. Rossiter, and Ms. Bonfim for supporting and helping us out while we were testing in the field at Drumlin Farm. I’d especially like to thank Ms. Schultheis for lending us her calculator when we lost one of our own. I’d also like to thank all of the teacher naturalists at our testing sites for providing background information and helpful tips about the Farm and what we might find. I’d like to thank as well the entire BB&N Middle School Science Department for their amazing help and support - our experiment would not have happened without them. I’d also like to thank the department for supplying us with the proper materials to conduct our experiment, and for driving us to and from Drumlin Farm so the testing could actually occur. I’d like to acknowledge the extra hard work Ms. Svatek put in to our experiment, and how flexible she was when we changed the point of experiment multiple times. I’d also like to thank Mr. Ewins for supplying us with some helpful advice during class time. I’d also like to send a huge thank you to Olivia Friend, one of our classmates, who really helped us bring out poster together. I’d finally like to thank the most my amazing science partner Maïa Cullen, who picked up the work when I failed to do so. She was an amazing and incredibly patient science partner who really completed the project. Without the people listed above, this experiment could not have happened. Thank you!

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WORK CITED Maïa Cullen (S81-3)

"Clean Water Education Partnership." - Algae Blooms and Fish Kills. Clean Water Education Partnership, n.d. Web. 12 Mar. 2014. <http://www.nccwep.org/stormwater/effects/algae_blooms.php>.

"NC State Fisheries and Pond Management Extension-Pond Management Guide

Chapter 4." Solving Problems. NC State Fisheries and Pond Management Extension-Pond Management Guide Chapter 4, n.d. Web. 12 Mar. 2014. <http://www.ces.ncsu.edu/nreos/wild/fisheries/mgt_guide/chapter4.html>.

Nitrate Ion-Selective Electrode. Digital image. Vernier. N.p., n.d. Web. 2 Apr. 2014.

<http://www.vernier.com/products/sensors/ion-selective-electrodes/no3-bta/>.

"Nitrogen and Water." : USGS Water Science School. USGS, 17 Mar. 2014. Web. 09

Apr. 2014. <http://water.usgs.gov/edu/nitrogen.html>. Nitrogen Cycle in Water. Digital image. Biogeochemical Cycles. Siry's Ecology

Homepage, n.d. Web. 9 Apr. 2014. <http://myweb.rollins.edu/jsiry/biogeochem.html>.

"Nitrogen." Nitrogen. WebElements Periodic Table of the Elements, n.d. Web. 12 Mar.

2014. <http://www.webelements.com/nitrogen/history.html>. Texas Instruments TI Nspire™ CX CAS Color Graphing Calculator. Digital

image. SchoolMart. N.p., n.d. Web. 2 Apr. 2014. <http://www.schoolmart.com/texas-instruments-ti-nspire-cx-cas-color-graphing-calculator-classroom-pac....

"Understanding Algal Blooms." News Releases. St. John's River Management District,

n.d. Web. 12 Mar. 2014. <http://www.sjrwmd.com/algae/>. "Water's the Matter-- Introduction: Nitrates." Water's the Matter--

Introduction: Nitrates. Measuring Nitrates and Their Affects on Water Quality, n.d. Web. 12 Mar. 2014. <http://peer.tamu.edu/curriculum_modules/water_quality/module_5/index.htm>.

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"Why Oxygen Dissolved in Water Is Important." Why Is Important the Oxygen Dissolved in Water. LennTech, n.d. Web. 12 Mar. 2014. <http://www.lenntech.com/why_the_oxygen_dissolved_is_important.htm>. Emory Sabatini

B.V., Lenntech. "Why Oxygen Dissolved in Water Is Important." Why Is Important the Oxygen Dissolved in Water. Lenntech, n.d. Web. 16 Apr. 2014. <http://www.lenntech.com/why_the_oxygen_dissolved_is_important.htm>.

"Clean Water Education Partnership." - Algae Blooms and Fish Kills. Clean Water Education Partnership, n.d. Web. 16 Apr. 2014. <http://www.nccwep.org/stormwater/effects/algae_blooms.php>.

Huan Jing Ke Xue. "Result Filters." National Center for Biotechnology Information. U.S. National Library of Medicine, 24 July 2003. Web. 17 Apr. 2014. <http://www.ncbi.nlm.nih.gov/pubmed/14551954>.

"NC State Fisheries and Pond Management Extension-Pond Management Guide Chapter 4." NC State Fisheries and Pond Management Extension-Pond Management Guide Chapter 4. NC State University, n.d. Web. 16 Apr. 2014. <http://www.ces.ncsu.edu/nreos/wild/fisheries/mgt_guide/chapter4.html>.

Smith, Keith L. "Ohio State University Extension Fact Sheet." Planktonic Algae in Ponds. Ohio State University, n.d. Web. 16 Apr. 2014. <http://ohioline.osu.edu/a-fact/0009.html>.

"Understanding Algal Blooms." News Releases. St. Johns River Water Management District, 8 Feb. 2013. Web. 16 Apr. 2014. <http://www.sjrwmd.com/algae/>.

"Water's the Matter-- Introduction: Nitrates." Water's the Matter-- Introduction: Nitrates. National Institute of Environmental Health Sciences, n.d. Web. 16 Apr. 2014. <http://peer.tamu.edu/curriculum_modules/water_quality/module_5/index.htm>.

Salamanca, Annabella, Alvaro Alonso, and Julio A. Camargo. "Nitrate Toxicity to Aquatic Animals: A Review with New Data for Freshwater Invertebrates." Chemosphere 58 (2005): 1255-267.Http://www.waterboards.ca.gov. California Environmental Protection Agency, 2005. Web. 17 Apr. 2014. <http://www.waterboards.ca.gov/water_issues/programs/tmdl/records/region_2/2008/ref2426.pdf>.

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The Effect of Calcium on Water pH Levels By: Jack Deford and Bobby Tearney

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Table Of Contents Section: Page #: Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-3 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-8 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-9 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Works Cited Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

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ABSTRACT This study was conducted to find the relation, if any, between the acidity of water

and the amount of Calcium in the water of the various ponds at Drumlin Farm in Lincoln, Massachusetts. The procedure for this experiment was to take a 50 mL sample of water and measure the pH levels with litmus paper and Ca levels in the water with a Vernier Probe. Then this was repeated 14 times at 3 different locations including Poultry Pond, Vernal Pool, and Boyce Pond. Based on the hypothesis, it was assumed that the pond water with the greatest amount of calcium would have a higher pH because when there is not enough calcium in the water, the pH levels drop. The results of the data tested should no correlation between the two variables. However, all throughout this experiment no pH levels varied far between the ranges of 4-6. INTRODUCTION

Calcium is an element that not only affects the mineral and animal life in water, but also can affect the pH levels of different bodies of water. Calcium affects the materialization of the water. Calcium also affects color, texture, and taste of water (lenntech.com). Calcium is important to aquatic life because when there is too much calcium, the pH levels in water rise, but when the calcium levels are too low, the pH levels drop so low that water life cannot breathe or survive (lenntech.com).

Four percent of the Earth’s crust is made of calcium, which means that calcium is a big part of human and animal life. This is because calcium is in water, soil, and many foods that are eaten.

The habitats that are being tested in the experiment are Poultry Pond, Vernal Pool, and Boyce Pond. These habitats were being used because the ponds differed, and the mineral and animal life varied immensely as well. When visiting Poultry Pond, it was observed that the water had a large amount of algae and that the top layer of the water was a greenish color. The amount of algae might be affected by the content of calcium in the water. At the Boyce Pond, it was observed that there was a lot of mud both in and around the pond itself. At Vernal Pool, there were two rocks with algae on them in the middle of the pond. Also, there were fallen and cut down trees lying throughout the pond.

In past experiments and research, it has been shown that when calcium levels are low, pH levels are also low (ocean-acidification.net). When the pH levels drop to dangerously low levels it can be deleterious for water life (lenntech.com). Also, when calcium levels in the water increase, the minerals that are affected by the calcium can also increase. This effect can pollute the water if the calcium levels become too high (lenntech.com). When the mineral and pH levels are too high, and the water gets polluted, it is harder for the fish and other sea-life in that water to breathe and live.

The objective of this experiment is to see if calcium levels make an impact on water pH levels. By testing the levels of the calcium and pH of the water, the experiment will show the relationship between these two measurements. Three ponds will be tested for the experiment and there will be fourteen tests at each pond, to make sure that there is sufficient data to make a conclusion about this relationship. The independent variable for the experiment is the calcium levels in the water (mg/L), and dependent variable is the pH levels that are in each sample from the three different ponds. To control the

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experiment, the testing and collecting methods will be the same for all 42 of the samples taken throughout the experiment.

The calcium levels will be tested by placing a Vernier Conductivity probe into the water to see how much calcium, which is measured mg/L, is in the water. Then, litmus paper will be placed in the same water sample to see what the pH levels are in the different water samples.

The hypothesis for the experiment is: If the pond water has the greatest amount of calcium, then the pH of the water will be the greatest because when there is not enough calcium in the water, the pH levels drop to 4.5-4.9, which is too low for water life. This means that the higher the calcium levels are, the higher the pH will be as well (lenntech.com).

The significance of learning about the effect of calcium on pH levels of water is that if people have ponds near a house and the fish in the pond are dying, or not doing as well as in the past, there is a chance the reason for these events is based on the pH levels in the pond. So, if there is a positive correlation between calcium levels and pH, and if the pH is too low, the owner could add calcium to change the pH, which could ensure the health of the life in the pond. MATERIALS AND METHODS

These steps were then repeated at fourteen different sites at each of the four ponds/lakes to make a grand total of the required forty-eight data points. These fourteen spots were determined through a randomizer on a computer program on http://www.random.org/. First the lowest number (0) was entered in the top slot. Then the highest number (360) was entered. Then the program picked out 14 random degrees as test sites.

To collect samples, first the graduated cylinder was dunked under the water that the sample was taken from. Then, the graduated cylinder was removed from the water once it had been filled around half full. Then it was emptied until it was at least fifty milliliters full. Then the testing procedure took place. The first step in the procedure for this experiment was to take a sample of water the size of fifty milliliters from one of the three designated ponds using the graduated cylinder. The three ponds are Poultry Pond, Boyce Pond, and Vernal Pool. After the sample was taken, take the Vernier Calcium Probe and use it to measure the amount of Calcium in said water sample. This data must then be recorded in the aforementioned Field Notebook under the category of the pond or lake in which the sample was collected. Once this data has been recorded, a piece of Litmus Paper was dipped into the same sample of water to test the pH levels of the water. Then this data was recorded in the same Field Notebook.

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RESULTS Table 1: The effect of Calcium on water pH levels at Poultry Pond. Trials pH Levels Ca Levels (mg/L)

1 6 6 2 5 14 3 6 11 4 5 13 5 5 6 6 6 6 7 4 0 8 7 333 9 5 420

10 6 350 11 5 123 12 5 359 13 6 97 14 5 94

Avg. 5 131 Stdev. 1 160

Table 2: The effect of Calcium on water pH levels at Boyce Pond.

Trials pH Levels Ca Levels (mg/L) 1 5 88 2 3 72 3 7 50 4 4 26 5 8 30 6 5 45 7 7 43 8 8 30 9 5 29

10 4 33 11 6 55 12 6 33 13 5 47 14 6 63

Avg. 6 46 Stdev. 1 18

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Table 3: The effect of Calcium on water pH levels at Vernal Pool.

Graph 1: The effect of Calcium on water pH levels at Poultry Pond.

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Trials pH Levels Ca Levels (mg/L) 1 6 12 2 5 20 3 3 8 4 7 52 5 4 60 6 8 65 7 5 11 8 7 5 9 8 11

10 5 12 11 4 1 12 66 4 13 5 3 14 4 20

Avg. 5 20 Stdev. 1 21

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Graph 2: The effect of Calcium on water pH levels at Boyce Pond

Graph 3: The effect of Calcium on water pH levels at Vernal Pool.

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Graph 4: The effect of Calcium on water pH levels at all three of the ponds.

Graph 1 shows the effect of calcium on water pH levels at Poultry Pond. The graph shows that all of the pH levels ranged from 4 to 7 with a majority of the data around a pH of 5 or 6. On the other hand, the calcium levels (mg/L) ranged from 0 to almost 450 mg/L. Five data points were under 50 mg/L, and seven were above 100 mg/L. The average pH level for Poultry Pond was 5, and the average amount of calcium was 131 mg/L. The R2 value for the linear regression was 0.04967. There was also a positive trend-line in the data collected at the Poultry Pond. The pH levels at Poultry Pond were very precise, but the calcium levels were not precise. Finally, at Poultry Pond it was observed that the water was much more green than the other ponds.

Graph 2 shows the effect of calcium on water pH levels at Boyce Pond. Similar to the graph of Poultry Pond, the pH levels ranged from 3 to 8. At Boyce Pond, unlike Poultry Pond, not even one of the calcium data points surpassed 100 mg/L. The data that was collected grouped around calcium levels ranging from 20 to 50 mg/L. The average amount of calcium in Boyce pond was only 46 mg/L compared to Poultry’s average of 131 mg/L. The pH average was a solid 6. The R2 value for the linear regression in this graph was 0.07822, just slightly higher than that of Poultry Pond. Unlike Poultry Pond however, this trend-line had a negative slope. Unlike Poultry Pond’s calcium levels, the Standard Deviation for Boyce Pond was only 18 meaning that the calcium measurements were precise. At Boyce Pond, there was mud everywhere. This mud could have affected the pH levels of the water.

Graph 3 shows the effect of calcium on the water pH levels at Vernal Pool. Similar to Boyce Pond, the pH levels ranged from 3 to 8, with a majority of the data points lying in between 4 and 6. Also similar to Boyce, Vernal had no data points that came close to 100mg/L of calcium. In fact, only three points made it over the 50 mark of calcium. Those three points were 52 mg/L, 60 mg/L, and 65 mg/L. These measurements were taken in trials 4, 5, and 6. The average concentration of calcium in Vernal Pool was a shockingly low 20 mg/L, and the average pH level was 5. The R2 value on this graph had a negative slope, but had the smallest R2 value at 0.00256. At

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Vernal Pool it was observed that there were two rocks with what seemed like algae on them. There were also some fallen trees in the water. By looking at the Standard Deviation of the data, it is clear that Vernal Pool calcium measurements were the second most precise out of the three ponds.

The final graph shows the effect of calcium on water pH levels from all three of the different ponds. From all 42 data points collected throughout the whole experiment, only 4 calcium level data points were above 300. If these outlier were taken away from the experiment, then the slope of the trend-line and the R2 value of the regression would be less and the data would be much more precise than it was before. The highest of the four outlier data points was 420 mg/L of calcium, and the lowest of the four outliers was 333 mg/L of calcium. Shockingly, all four of these points were from the testing done at Poultry Pond. The pH levels for all the measurements ranged from 3 to 8, with two data points at 3 and 3 points at 8. The regression for this graph was nearly zero at 0.00195. The slope of the trend-line for all three of the ponds together was positive. DISCUSSION

This experiment was conducted to test if there was any connection, and, if so, what connection there was, between the levels of calcium in the water and the acidity (pH) of the water. The hypothesis for this experiment was: If the pond with the greatest amount of calcium is tested, then the pond will have the highest acidity, because when there is not enough calcium in the water, the pH levels drop to 4.5-4.9 (lenntech.com). This hypothesis was not supported by the data collected in the experiment. The only consistent data was the pH levels, which did not vary much, aside from a few outliers, from the range 4-6. There was a wide variation in the calcium levels of the pond water, but no detectable dependence or relation to the pH level.

For each of the three ponds, 14 samples of water were tested for calcium and pH. The results from Poultry Pond ranged from as little as 0 mg/L of calcium, with a pH of 4, to as much as 420 mg/L, with a pH of 5. The results from Boyce Pond ranged from a low of 26 mg/L, with a pH of 4, to a high of 88 mg/L, with a pH of 5. Vernal Pool had a low of 1 mg/L with a pH of 8, and a high of 65 mg/L, with a pH of 5. Clearly, there was no relation between the two variables because the r2 value for the experiment as a whole was 0.0019, meaning it was incredibly imprecise. It had been expected that higher calcium levels would mean higher pH levels because the calcium’s pH had been expected to add to the water’s pH as a whole, but such was not the case. (www.britannica.com) The average calcium at Poultry Pond was 131 mg/L, and the average pH there was 5. Boyce Pond’s average calcium was 46 mg/L; its average pH was 6. Vernal Pool had an average calcium of 20 mg/L, and an average pH of 5. The r2 values for the ponds were: Poultry, .0487; Boyce, .0782; and Vernal, .0026, showing little correlation between the pH and calcium levels in pond water.

Confidence in this data set is jeopardized by one main flaw that occurred about half way through data collection in Poultry Pond. The conductivity probe briefly malfunctioned, causing the amount of calcium in Poultry Pond to skyrocket. Thankfully, it was fixed before Boyce was tested. Vernal was the first pond measured, and the probe was working then. Boyce was the last pond measured, and the probe was working there also, having been fixed by one of the scientists overseeing the experiment. Only the results for a little more than half of Poultry Pond were not to be

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trusted. Another factor to take into account when assessing the results is that the pH of pond water fluctuates slightly throughout the day, due to photosynthesis and respiration by plants and animals (www.noble.org/ag/wildlife/fish-pond-water). Depending on the time of day the water is tested, the results could vary.

No link between pH and calcium was found, but the study could be modified and improved in several ways. Due to the possible fluctuations in pH levels, though, it could be useful to return to the ponds at another time of day and re-test, to see if pH levels were different. It would be prudent to have an extra conductivity probe, because apparently they are delicate instruments. Taking a larger point of view, it would be informative to assess the wildlife population of each pond to see if the pH levels and calcium content supported aquatic life. To further extend the study, other ponds in the area could be explored to compare their pH and calcium levels and their wildlife situations. ACKNOWLEGDGEMTS

I, Bobby Tearney would first like to thank Jack Deford, my partner for handling this experiment with me. I would also like to thank Mrs. Haug, and Sally for being the teacher and expert at out first site Vernal Pool. Mr. Rossiter was the Poultry teacher and helped us take our data. Also at Poultry Pond, our Vernier Probe broke down. We thought that we were doomed until Mrs. Schulteis came to the pond and saved the day. Without her, our experiment would not have happened. At our last site, we visited Boyce Pond where Mrs. Bonfim did a great job advising us as we took our final data. Finally, I would like to thank our great teacher, Mrs. Svatek. She helped Jack and I all throughout our experiment. She as well as all of our teachers and classmates have been very supportive throughout this process.

I, Jack Deford would like to thank my partner, Bobby Tearney, for being such a good sport with putting up with my laziness and all-around shenanigans. Without him, this report surely would still only be halfway done. Secondly, I would like to thank my teacher and motivator, Mrs. Svatek, for instructing me all throughout this experiment. If not for her, I would not know how to even carry out the experiment. Next, of course, I need to thank Mrs. Schulthies, for helping my partner and me repair our Vernier Conductivity Probe after it broke due to certain... COMPLICATIONS... at Poultry Pond. If she had not been there, none of the data would be useable. Finally, I would like to thank my dear mother, Laura Deford, for inspiring, helping, and compelling me towards the completion of this project. Without her, there would have never been a scientist to invent this experiment.

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WORKS CITED

Introduction: Danbury, Conn. The New Book of Popular Science. 2. Vol. 2. Danbury, Conn: Grolier, 2006. Print. The

New Book of Popular Science. Hanusa, Timothy P. "Calcium (Ca) (chemical Element)." Encyclopedia Britannica Online.

Encyclopedia Britannica, 2 Dec. 2013. Web. 10 Mar. 2014. <http://www.britannica.com/EBchecked/topic/88956/calcium-Ca>.

Helmenstine, Anne M. "Calcium Atom." About.com Chemistry. Web. 01 May 2014.

<http://chemistry.about.com/od/elementfacts/ig/Atom-Diagrams/Calcium-Atom.htm>. Hood, Martha, Editor. "Ocean Acidification Network." Ocean Acidification Network. Global IPBG

Change. Web. 7 Mar. 2014. <http://www.ocean-acidification.net/FAQeco.html>. Lenntech. "Calcium (Ca) and Water." Calcium (Ca) and Water. Water Treatment Solutions. Web. 4

Mar. 2014. <http://www.lenntech.com/periodic/water/calcium/calcium-and-water.htm>. Rainbows, Bursting. "Summer Tropical Ocean Waves Underwater Pretty Beach Surf Palm Trees

Beauty Beautiful Photography." Tumblr.com. Tumblr, 30 Nov. 2013. Web. 1 May 2014. <http%3A%2F%2Fbursting-rainbows.tumblr.com%2Fpost%2F68604153154>.

Discussion:

“Calcium (CA) and water” Lenntech Water Treatment Solutions. Rotterdamseweg, The Netherlands. 1998-2014. Online. Accessed 25 April, 2014. www.lenntech.com/periodic/water/calcium/calcium-and-water !

“Calcium (Ca).” Encyclopaedia Britannica, Inc. Online. Accessed 25 April, 2014. www.Britannica.com/EBchecked/topic/88956/calcium-Ca ! “Fish Pond Water Quality: As Simple as Chemistry 101.” Russell Stevens. The Samuel Roberts Noble Foundation. 2009. Online. Accessed 25 April 2014. www.noble.org/ag/wildlife/fish-pond-water ! “Plasma membrane of Beta vulgaris storage root shows high water channel activity regulated by cytoplasmic pH and a dual range of calcium concentrations.” K. Alleva, et al.

US Library of Medicine, National Institutes of Health. Epub 5 Jan, 2006. Online. Accessed 25 April 2014. www.ncbi.nlm.nih.gov/pubmed/16397000$!

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The Percolation is Clear!

The Effect Of Soil Percolation (cm/hr) on Water Turbidity (NTU)

By Lily Druker and Michael Tang

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T A B L E O F C O N T E N TS

Name Author Pages

Abstract Michael Tang 3

Introduction L ily Druker 3-4

Materials and Method L ily Druker 4-5

Results Michael Tang 6-9

Discussion Michael Tang 10-12

Acknowledgement Michael Tang and L ily Druker 12

Work C ited Michael Tang and L ily Druker 12-14

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A BS T R A C T During a visit to Drumlin Farm, MA, it was discovered that soil percolation has correlation with

soil and make water run through the soil to see how fast it takes. Then, water from the pond and tested the turbidity with a probe. It was then plotted onto a scattered plot to see the relationship between water turbidity and soil percolation. The results showed that there was a high correlation between turbidity and soil percolation because of the r2 value. For all three sites, the r2 value was close to 1. I N T R O D U C T I O N Soil percolation is the speed at which water travels through soil in a downward motion. If the soil is compact and has a higher clay content, then the percolation will be very slow: less than .127 cm/hr (centimeters per hour); if the soil is sandy and aggregated, then the percolation will be very rapid: over 25.4 cm/hr (http://passel.unl.edu/). Turbidity (NTU) is the cloudiness of water. It is caused by soil erosion, excessive algal growth, and urban runoff. Also, large numbers of bottom feeders (such as carp) stir up sediments. Having a high turbidity is bad for aquatic life because it can clog fish gills, reduce the resistance of disease in fish, lower growth rates, and affect egg and larval development (http://water.epa.gov/). The experiment will be conducted at Drumlin Farm, a Wildlife Sanctuary in Lincoln, Massachusetts. Drumlin Farm consists of 312 acres of land and five different ponds. For the proposed experiment three of the ponds will be used for testing, Ice Pond, Poultry Pond, and Boyce Pond. Boyce Pond is just west of Boyce Field and is surrounded by forest. Ice Pond is north of the drumlin and near sheep grazing area. Poultry Pond is located in the south west corner near the visitors center. It is surrounded by a chicken coop so the manure may affect the soil texture and type. One of the ways water becomes more turbid is from erosion. Erosion occurs when water, wind, and other natural elements change the shape of the earth as time passes. When soil is sandy and not very dense, erosion occurs easier. When erosion happens the soil is carried into the runoff creating a body of water with more turbidity (http://water.epa.gov/). Urban runoff is also a large factor on homaterials such as metal scraps, trash, and gasoline among others. When these pollutants get into bodies of water they increase the turbidity tremendously (www.lenntech.com). The objective of the experiment is to figure out if the percolation of soil affects the turbidity of water. The independent variable is soil percolation (cm/hr) and the dependent variable is water turbidity (NTU). Some of the variables that will be controlled is the soil to water ratio used to test the percolation of the soil, the probe used to test the turbidity, and the method to test the percolation of the soil. The hypothesis set forth is that if the soil around the circumference of the pond has a rapid percolation, then the water in the pond will be more turbid because runoff carries soil particles with it. More erosion occurs with soil that is less dense and sandy, because water flows through it more easily (www.nerrs.noaa.gov). After the experiment takes place, new information can be learned. Since low turbidity is bad for plants and organisms in ponds, Drumlin Farm might be able to work on some of the soil to help the water get less turbid. Preventing bodies of water from having an unsafe turbidity level

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will help different plants and animals survive in more environments, this way less fish will be endangered. A follow up experiment is to test if soil can artificially have more clay in it in order to prevent turbulation. M A T E RI A LS A ND M E T H O DS Materials and Methods

F igure 1: A map of Drumlin Farm in Lincoln, MA, where the tests were conducted. The circles are Ice Pond, Poultry Pond, and Boyce Pond where data collection took place.

At each of the four sides of Ice Pond, Boyce Pond, and Poultry Pond; north, east, south, west, (See figure 1 for location of ponds) four water samples were taken and tested for turbidity (NTU) using the Vernier Turbidity Probe. The water was

collected in a 3 cm vial, then placed into the probe which was connected to a T-inspire calculator that read the turbidity levels. After the tests, the vial was rinsed off using distilled water. One half meter off the edges of each pond, fifteen tests were conducted to find the percolation of the soil. Each test was taken 24 degrees apart around the circumference of each of the ponds. A 15.5 cm ring was placed 7.5 cm into the ground. 60 mL of bottled water was poured into the ring, then the timer was started (minutes). The timer stopped once all of the liquid in the ring had drained into the soil. On figure 2 the brown dots represent each soil percolation test and the dark blue

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dots represent each water turbidity sampling, the light blue is the pond.

F igure 2: The data collection will be taken place at Bathtub Pond, Ice Pond, and Boyce Pond at Drumlin Farm in this format.

F igure 3: This is a picture of a turbidity probe

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R ESU L TS Table 1 the effect of Soil Percolation on Water Turbidity in Ice Pond:

Graph 1 shows the correlation between water turbidity and soil percolation in the Ice Pond. The highest soil percolation at the Ice Pond was 843 (Seconds) with a water turbidity of 31.8 (mL) and the lowest is 66 (Seconds) with a water turbidity of 10.3 (mL). The Ice Pond had a higher soil percolation average but since the STDEV was much higher than the other ponds. The R2 value for graph 1 is 0.696. The STDEV for this pond is 278.806 and for the water turbidity, it is 6.4. This means the data is not precise.

Graph 1: The effect of Soil Percolation on Water Turbidity in Ice Pond

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Trials

Soil Percolation (Seconds)

Water Turbidity (mL)

1 843 31.8 2 630 27.9 3 150 23.1 4 147 22.3 5 926 32.1 6 306 18.9 7 66 10.3 8 230 15.2 9 195 12.3

10 530 27.2 11 260 17.1

12 352 19.3 13 472 20.4 14 550 24.5 15 750 28.9

AVG 427.1333 21.82 STDEV 278.806 6.383371

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Table 2 the effect of Soil Percolation on Water Turbidity in Poultry Pond:

Graph 2 shows the correlation of the soil percolation on water turbidity in the Poultry Pond. The highest soil percolation is 1840 (Seconds) with a turbidity level of 33.2 (mL) and the lowest is 182 (Seconds) and the turbidity is 21.2 (mL). The STDEV for this pond

precise. The R2 value is 0.7633.

Trials

Soil Percolation (Seconds)

Water Turbidity (mL)

1 922 30.5 2 706 29.8 3 1335 32.1 4 734 30.8 5 1840 33.2 6 105 20.9 7 144 25.2 8 432 26.8 9 499 27.9

10 608 28.6 11 678 28.9 12 182 21.2 13 1219 36.2 14 1450 36.3 15 601 25.2

AVG 396.2867 28.90667 STDEV 513.1432 4.628555

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Graph 2: The effect of Soil Percolation on Water Turbidity in Poultry Pond

Table 3: The effect of Soil Percolation on Water Turbidity in Boyce Pond:

Lastly, in table three, it shows the correlation between soil percolation and water turbidity in the Boyce Pond. This table also shows that the higher the soil percolation, the less turbid the water is. The highest soil percolation at the Poultry Pond was 144 (Seconds) with a water turbidity of 24.8 (mL) and the lowest is 71 (Seconds) with a water turbidity of 10.7 (mL). As said in graph 1, the STDEV makes the graph not precise. An interesting observation is that the soil percolation is decreased a lot meaning the water is more turbid.

Trials

Soil Percolation (Seconds)

Water Turbidity (mL)

1 105 23.1 2 132 24.2 3 71 10.7 4 144 24.8 5 116 16.7 6 122 16.9 7 143 25.3 8 143 25.8 9 113 10.8

10 109 6.6 11 122 14.4 12 116 17.1 13 143 25.9 14 118 17.3 15 103 12.3

AVG 69.06333 18.12667 STDEV 53.76964 6.390447

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Graph 3: The effect of Soil Percolation on Water Turbidity in Boyce Pond

Graph 4 the effect of soil percolation on water turbidity:

Graph 4 shows all of the data collected from all the ponds. The highest soil percolation is 1840 (seconds) and for the water turbidity, it is 36.3 (mL). The R2 value for this graph is 0.58.

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D ISC USSI O N

The goal for this experiment was to find out if there was any correlation between soil percolation and water turbidity. The hypothesis for this experiment is if the soil around the circumference of the pond has a rapid percolation, then the water in the near area will be more turbid because runoff carries soil particles with it. More erosion occurs when soil that is less dense and sandy b/because water flows through it more easier (N/A, www.nerrs.nova.gov). The results for the soil percolation and soil turbidity is in favor with the hypothesis since the data shows that whenever the soil percolation increases, then the water is less turbid.

The hypothesis is supported in many ways. Some ways that caused the results to be that way is from the material of the soil, leaf litter and the roots from trees. All of these make a big impact on the results.

For the first graph in the Ice Pond, it showed that whenever the percolation increased, then the water became less turbid (the more mL means less turbid). As the soil percolation and water turbidity were being tested, there were a few interesting observations in this location. One includes all the trees and bushes around the pond. In one source, it says that the tree roots can make a big impact on the soil percolation (N/A, http://en.wikipedia.org). It says that the tree and plant roots hold together the soil particles. This prevents them from falling into the water causing it to be more turbid. Another interesting observation is the location of the pond. The Ice Pond was in the middle of a forest causing the raindrops to fall slower from the leaves. As raindrops fall, most of it will start to hit the leaves making the kinetic energy slower and less water will be able to reach the soil (Mortlock, http://soilerosion.net/). If the water does reach the soil, it will fall much slower causing the soil particles not to break as easily. On the forest floor, there are also leaf litter and humus (Raider, http://www.geography4kids.com/) . Leaf litter is dead material that comes from trees, leaves, bark, twigs and more. All of this waste eventually forms a mat like shape protecting the soil. This layer can absorb some of the raindrops making it harder for the raindrops or water to reach the soil. The r2 value for this graph was relevantly close to 1 meaning that there is some correlation between soil percolation and water turbidity. The standard

some data points were tested further away or closer to the pond.

The highest water turbidity result came from the Poultry Pond was partly located in a forest. It had a similar environment as the Ice Pond. There were many trees blocking the rain drops. Even though there were less trees, this location had the highest water turbidity. This brings it to another reason that causes water to be less turbid. Since Drumlin Farm is preserved by human, some parts of the pond was staff only. If there are more people coming to visit this pond, it will

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cause disturbance on the soil which makes the soil particles weaker to hold it together. Eventually it will break apart and fall into the water. Since half of the pond was staff only, not many visitors will disturb the soil and it will remain its strength.

In graph 2, the soil is most likely clay since this pond was the least turbid. The clay soil is more compact and can hold more water (Leineriza, http://agverra.com/blog/soil-types/). If the soil can hold more water, then fewer particles will run through with the water. The average for the Poultry Pond was less than the average in the Ice Pond because the location. The location for graph 2 was partly located in a forest causing the Ice Pond to have a higher average and as said

a was analyzed, some data points were larger than the Ice Pond. This can be caused from more coverage by the trees since some parts of the pond had more trees. Another reason for this is thickness of the leaf litter. Also, some parts of the pond had a lot more leaf litter than part of the pond. This is what caused the sudden change in the data.

Graph three had the lowest soil percolation and which also means the water was the most turbid. This pond was located in an open area with very few trees. This caused more raindrops/ water to go into the soil and carrying more soil particles with the water. Also, the soil for this pond was a lot more loose and less compact. Most likely, the type of soil is sandy. The soil particles for sandy are large chunks and have much water in the soil causing it all to drain into the water. Also, this location was the most precise. This can be explained because on the other locations, there were many fallen trees, roots and many other things blocking the actual test places. For the Ice Pond, one of the tests was taken right next to the fallen tree. This could have made the soil a lot more compact and a lot harder for the water to drain. Another test was taken next to plants where the soil is less compact because the roots of these plants have created air space allowing the drainage for the water to be easier. These two tests were both taken at the same tests meaning it has created a wide range of data creating an error since one test had an advantage from the compacted soil and the other test had a disadvantage. The r2 value for this location 0.76 meaning there was high correlation and this was also the highest between every location.

The last graph was put together to show the overall correlation for all the locations combined. This made it easier to compare the data if there was high correlation not just for each location but for every location that was tested. The r2 value for this graph is 0.58 and it means that there is good correlation.

Overall, there was correlation between soil percolation and water turbidity and Ice Pond had the highest soil percolation with also the least turbid. In the experiment, there were a few things to modify to improve the data collection. The major change should be is the method the soil percolation is tested. As the data was being collected, there were many roots blocking where the

problems with the roots and it would also improve the precision of the data. Another

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During this experiment, there were some errors causing the data to be not precise. The first one and major one is the location we put the cans. Originally it was planned that the cans would be 1 meter away from the pond. Since there were a lot of roots, bushes, etc. some cans were placed

with the other data points. This then lead to the results not being as accurate as possible. Another error is the amount of water used to test the soil percolation. On the first trial, the water was estimated to 20 mL instead of measuring it in a measuring cup for the last three. This is because

experiments can be tested to see if there are any other material that affects the turbidity of the

A C K N O W L E D G E M E N T

I would like to thank my science teacher, Ms. Svatek for all of her support throughout the project and for helping us manage our time efficiently. I also owe thanks to the rest of the middle school science teachers, Mr. Ewins for teaching us how to use a compass and Ms. Larocca and Ms. Schulteis for helping to plan out both of our trips to Drumlin Farm. In addition to the science teachers the naturalists at Drumlin Farm showed us where to go and the safest way to get around the pond, without harming the ecosystem. Finally, I would like to thank my partner Michael

this far without his positive attitude and hard work.

The first person I would like to acknowledge is my partner Lily Druker from helping out getting materials, organizing the trip to Drumlin Farm and testing the experiment. Next, I would like to thank the naturalist who was at each location. They have helped us find the locations and where

e as accurate. I would also like to thank the teachers who took their time to come with us onto the field trip. They kept track of time and told us where we can find our next location. The last person is my teacher Mrs.Svatek, She has helped us tremendously by reviewing our lab report, helping out on our poster board, getting the materials and lastly organizing the field trip.

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W O R KS C I T E D

#

L ily Druker : #

Ashman, M. R., and G. Puri. Essential Soil Science: A Clear and Concise Introduction to

Soil Science. Oxford: Blackwell Science, 2002. Print.

EPA. "5.5 Turbidity." Home. EPA, 6 Mar. 2012. Web. 09 Mar. 2014.

<http://water.epa.gov/>.

Lenntech. "Turbidity." Turbidity. Lenntech, 2012. Web. 18 Mar. 2014.

<http://www.lenntech.com/>.

"Turbidity and Sedimentation." Turbidity and Sedimentation. N.p., n.d. Web. 08 Mar.

2014. <http://www.nerrs.noaa.gov/>.

Plant & Soil Sciences ELibraryPRO. "Soils - Part 2: Physical Properties of Soil and Soil

Water." Plant and Soil Sciences ELibrary. USDA, n.d. Web. 07 Mar. 2014.

<http://passel.unl.edu/>.

#

Michael Tang:

Ashman, M. R., and G. Puri. Essential Soil Science: A Clear and Concise Introduction to Soil

Science. Oxford: Blackwell Science, 2002. Print.

"Erosion." Wikipedia. Wikimedia Foundation, 15 Apr. 2014. Web. 17 Apr. 2014.

<http://wikipedia.org/wiki/Erosion>.

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Leineriza. "5 Different Soil Types â Know Your Soil Type." GROWTH AS NATURE

INTENDED. AgVerra, 7 Apr. 2007. Web. 16 Apr. 2014. <http://agverra.com/blog/soil-

types/>.

Soil Erosion Site. N.p., May 2007. Erosion . 17 Apr.

2014. <http://soilerosion.net/>.

Rader, Andrew. "Break It Down." Geography4Kids.com: Biosphere: Erosion. N.p., n.d. Web. 15

Apr. 2014.<http://www.geography4kids.com/>

"Turbidity and Sedimentation." Turbidity and Sedimentation. N.p., n.d. Web. 08 Mar. 2014

<http://www.nerrs.noaa.gov/>.

Images:

Open Clips. "Drop Face Liquid Rain Raindrop Water Tear Blue." Drop, Face, Liquid, Rain,

Raindrop. Pixabay, 2013. Web. 01 May 2014.

Open Clips. " Earthworm Worm Cute Happy Inchworm Smile Cartoon."Earthworm, Worm,

Cute, Happy. Pixabay, 2013. Web. 01 May 2014.

Open Clips. " Sun Cool Sunshine Glossy Smile Summer Heat." Sun, Cool, Sunshine, Glossy,

Smile. Pixabay, 2013. Web. 01 May 2014.

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The Effect of Soil Conductivity (!S/cm) on Water Conductivity (!S/cm).

By: Isabel Nowiszewski and Kayla Duran

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TABLE OF CONTENTS

Section Author Page

Abstract

Introduction

Materials and Methods

Results

Discussion

Acknowledgements

Works Cited

Works Cited

Isabel Nowiszewski

Kayla Duran

Isabel Nowiszewski

Kayla Duran

Isabel Nowiszewski

Isabel Nowiszewski & Kayla Duran

Kayla Duran

Isabel Nowiszewski

3 3 4 6 9 10 12 13

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ABSTRACT: After visiting Drumlin Farm in Lincoln, Massachusetts, an experiment was conducted to test whether the conductivity of the soil surrounding a pond had an affect on the conductivity of the pond water. The Ice, Bathtub and Poultry Ponds were tested at four locations at each pond. After arriving at each pond, a north-south-east-west transect was created. Twenty four soil conductivity readings and twenty four water conductivity readings were recorded and later were further analyzed. It was expected that the higher the soil conductivity surrounding the pond, the higher the water conductivity would be. After analyzing the data recorded, it was found that there was a very weak overall correlation between the water and soil conductivity at all three ponds. INTRODUCTION: The conductivity of water and soil are key elements to life without humans even knowing it. Both water and soil are associated with the water cycle. Without the water cycle, there would be no wildlife, no precipitation, and no use of water for cooking and drinking. The water cycle begins from one single water molecule. This is evaporated by the sun and then will form a cloud in the process of condensation. Next, the water molecule precipitates into snow or water and fall onto the ground. The water molecule finds its way to the ocean through pore space in the soil. The process will then start all over again (pmm.nasa.gov). The water that falls from the soil to the water has similar nutrients because it has been through the same cycle. The experiment on conductivity of soil and water will be conducted in Lincoln, Massachusetts, at Drumlin Farm. Drumlin Farm is a Mass Audubon Wildlife Sanctuary, which consists of over three-hundred acres of land, five ponds, seven field spots, and three forests. The three ponds that will be tested are; Bathtub, Ice, and Poultry. Bathtub Pond, which is surrounded with coniferous and deciduous trees, is located right near the compost. Poultry Pond, is covered with algae and is and mostly every part of the pond receives sunlight. Ice Pond, has mostly clear water with some patches of sunlight. There are many components that could affect the conductivity level of soil and water. The amount of total dissolved solids (TDS) can make the level of soil and water conductivity differ for each individual sample because it is based on the amount of salts that will dissolve into positive and negative ions (water.epa.gov). This will produce bonding and could affect conductivity (water.epa.gov). These ions bonding can also cause another factor to make the conductivity level unbalanced. The conductivity level could become unbalanced by the number of positive and negative ions. This will determine the number of ions bonding that happen because positive and negative ions bond (water.epa.gov) . Another way the conductivity level could change is the amount of nutrients. Nutrients, such as nitrate and phosphate are key essentials to water and soil (water.epa.gov). The ions bond creating nutrients. Therefore the soil or water could have an imbalance because of the amount of TDS, which will affect the nutrient supply (water.epa.gov). The proposed experiment is the effect of soil conductivity (!S/cm) on the water conductivity (!S/cm). The objective of this experiment is to determine the connection between the conductivity levels of soil surrounding the pond and the water in the pond.

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The question will be tried to be answered by using a transect and a probe to measure the conductivity level. The independent variable for this experiment is the conductivity level of the soil surrounding the pond (!S/cm). The dependent variable for this experiment is the conductivity level of the water in the pond(!S/cm) . Some important controlled variables for this experiment are, the method used to test the conductivity level, the number of samples taken at each part of the transect, the distance from the pond that the soil will be taken from, and the type of probe that will be used. The hypothesis for this experiment is: If the soil conductivity level is high, then the water conductivity level will also be high because when precipitation occurs, the water will go into the soil’s pore space, and water will flow underground into the nearest pond (water.epa.gov). This experiment will show the similarities of soil and water conductivity. Volunteers at Drumlin Farm, will have a better understanding of why the soil and water conductivity is so similar, and how the nutrients in and outside the pond are very similar. It is important to know the connection of the soil and water because this will help with further research with the water cycle and wildlife growth. MATERIALS AND METHODS: After arriving at Ice Pond, Bathtub Pond and Poultry Pond at Drumlin Farm in Lincoln, MA, a compass was used to find four points on each pond. The north-most, east-most, south-most, and west-most points of the ponds were found. These four points provided a North-South-East-West transect, where the data was collected on each pond. Figure 1 (below) shows the three ponds where the data was collected. Figure 1: Map of Drumlin Farm locations with pond locations circled.

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The north-most point data was collected first at Ice Pond. A Vernier water conductivity probe was connected to a TI-nspire calculator and then was placed into the water half a meter from shore. A reading showed up on the TI-nspire calculator and was recorded. The probe was rinsed off and five more samples were collected in the same place to achieve a total of six water data points. Next, half of a meter was measured from the water’s edge away from the pond. The Vernier soil conductivity probe was placed into the soil half a meter from shore and like the water, five more readings were collected to achieve a total of six soil data points at the northern point of Ice Pond. The same testing procedure was followed at the east, south and west points of Ice Pond. The same procedures were also followed at the Poultry, and Bathtub Ponds for setting up the location of where data was collected and collecting the data. A total of forty data points were collected at each of the three ponds, resulting in a total of 120 data points. Figure 2 (below) shows an example of a North-South-East-West transect on a pond. The soil data was collected near where each of the arrows on figure one are. Figure 2: North South-East West transect on a “pond”

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RESULTS: Table 1: The Effect of Soil Conductivity (!S/cm) on Water Conductivity at Poultry Pond.

Table 2: The Effect of Soil Conductivity (!S/cm) on Water Conductivity at Bathtub Pond

Direction Water cond. Soil cond.

WEST 1 212 20 WEST 2 210 30 WEST 3 212 50 WEST 4 215 60 WEST 5 209 30 WEST 6 211 40

*ERROR: only one direction was tested*

Direction Water cond.

Soil Cond.

NORTH 1 220 30 NORTH 2 222 40 NORTH 3 240 70 NORTH 4 212 80 NORTH 5 216 60 NORTH 6 223 90 SOUTH 1 298 30 SOUTH 2 296 40 SOUTH 3 290 20 SOUTH 4 295 30 SOUTH 5 288 30 SOUTH 6 293 20 EAST 1 252 10 EAST 2 260 60 EAST 3 265 50 EAST 4 268 70 EAST 5 275 90 EAST 6 260 70 WEST 1 240 80 WEST 2 245 40 WEST 3 260 60 WEST 4 252 90 WEST 5 246 70 WEST 6 245 90

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Table 3: The Effect of Soil Conductivity (!S/cm) on Water Conductivity at Ice Pond

Direction Water cond. Soil cond.

NORTH 1 253 40 NORTH 2 275 20 NORTH 3 299 60 NORTH 4 229 20 NORTH 5 252 20 NORTH 6 250 10 SOUTH 1 296 20 SOUTH 2 290 28 SOUTH 3 289 26 SOUTH 4 297 27 SOUTH 5 295 29 SOUTH 6 285 27 EAST 1 252 10 EAST 2 260 60 EAST 3 265 50 EAST 4 268 70 EAST 5 275 90 EAST 6 260 70 WEST 1 284 10 WEST 2 290 30 WEST 3 250 10 WEST 4 248 40 WEST 5 268 30 WEST 6 270 50

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Graph 1: The Effect of Soil Conductivity (!S/cm) on Water Conductivity (!S/cm) at Poultry Pond.

Graph 2: The Effect of Soil Conductivity (!S/cm) on Water Conductivity (!S/cm) at Bathtub Pond.

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Graph 3: The Effect of Soil Conductivity (!S/cm) on Water Conductivity (!S/cm) at Ice Pond.

The experiment was tested at Poultry, Ice, and Bathtub Pond. At each pond soil and water conductivity levels were conducted. At Poultry Pond, the r" value was 0.1959. The trendline was downwards(left to right). For Ice Pond, the r" was 0.4733, and the trendline was increasing (left to right). At Bathtub Pond the r" value was 0.005 but only one direction was collected for the soil and water conductivity. The trendline is small and increasing. For each of the graphs, many points were far away from the trendline. Graph 2 and 3 had many points and about 25% of the points were far from the trendline. Graph 1 had only a couple of points, but none of the points were extremely close or far from the trendline. DISCUSSION: This experiment was conducted to test the relationship between water conductivity in ponds and the soil surrounding the ponds. The hypothesis for this experiment was: If the soil conductivity level is high, then the water conductivity level will also be high because when precipitation occurs, the water will go into the soil’s pore space, and water will flow underground into the nearest pond (water.epa.gov). The hypothesis was not supported overall because at all ponds, the water conductivity did not significantly increase when the soil conductivity did. The soil conductivity and water conductivity did not show a relationship in the results of this experiment. The data could have resulted this way due to many reasons. One of these reasons could be the amount of nutrients such as nitrate or phosphate in the soil or water because the level of nutrients in soil and water affects the conductivity (water.epa.gov). The conductivity changes along with the nutrient levels because nutrients in the soil are due to salt and ion levels which increase the conductivity as the salt and ion levels increase (http://water.epa.gov). The amount of TDS (total dissolved solids) could have had an effect on the nutrient levels of the soil or water, causing an

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imbalance in one of the two, resulting in a minimal to no relationship between the water and soil (http://www.agriculturesolutions.com/). There was very weak correlation in the data at Poultry Pond. The r! value for this pond was 0.1959, showing a minimal relationship between the soil and water conductivity. The reason for these results could be because the TDS and nutrient levels in either the soil or water (water.epa.gov). After the conductivity probe stopped working, the small amount of data collected at Bathtub Pond showed a slight correlation, having a r! value of 0.4733. The reason Bathtub Pond showed a higher correlation than Poultry Pond could be because the amount of data collected, or location of collection. Unlike Ice and Poultry Pond, the data taken from Bathtub Pond was taken from only one point. The pond with the lowest correlation was Ice Pond, which had an r! value of .005, showing close to no correlation at all. Ice Pond could have the lowest correlation because of the salt and ion combination. Salt and ions increase the nutrient and TDS levels of soil (Grolier, 87). There could also be a difference in temperature at the three different ponds, causing the water to have a higher or lower conductivity. Warmer water will have a higher conductivity than colder water (water.usgs.gov/edu/watercycle.html) because heat is a better conductor than cold or ice. Even though there was a very low correlation of the overall data, the precision varied from pond to pond. The data recorded at Ice Pond and Poultry Pond had the lowest precision, resulting in low confidence in the data. The data taken from Bathtub Pond showed slightly higher precision, but still gave low confidence due to the large errors made during the data collection. Due to the fact that water data was only collected at one point at Bathtub Pond because the conductivity probe stopped working, sufficient data was not collected at this pond. Sufficient data was collected at Poultry and Ice Pond. There are many things that could be modified in this experiment. For example, the soil and water samples were only collected within a meter from the water’s edge, so no data was collected from the middle of the ponds or further into the soil. The depth of where the soil and water data was also very minimal because the probes used to collect data could only go so deep into the soil. Another way to expand the data collection would be to collect data during different seasons, to have a variation in the temperature of the water and soil because as the temperature increases in soil or water, so does the conductivity (www.agriculturesolutions.com/). The largest error made during the data collection was at Bathtub Pond. While at the calculator. This error could be eliminated by having a fully charged calculator for each pond or an extra probe in case one breaks or stops working. A future study that could be based off of this data is the effect of the conductivity of the surrounding soil of a pond on the aquatic life of that pond. ACKNOWLEDGEMENTS: We would like to thank our science teacher, Ms. Svatek first because without her this whole experiment wouldn’t be possible. We would also like to thank the three other science teachers for all the hard work they put in organizing the trip and data collection and Drumlin Farm. Other than the science teachers, we would like to thank the teacher

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naturalists at Drumlin Farm who helped us find our way around each habitat. Without Delila Keravuori, Miriam Feldman and Chris Attisani we wouldn’t have been able to complete our data collection because they lent us a water sample when our calculator stopped working. Lastly, we would like to acknowledge Ms. Jamison, Mr. Rossiter and Mr. Sarzana for helping us with our collection at each pond.

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WORKS CITED: "5.9 Conductivity." Home. Environmental Protection Agency (EPA), n.d. Web. 26 Feb.

2014. <http://water.epa.gov/type/rsl/monitoring/vms59.cfm>.

The New Book of Popular Science. Danbury, CT: Grolier, 2006. Print.

Perlman, Howard. "The Water Cycle." The Water Cycle, U.S. Geological Survey (USGS)

Water Science School. U.S.A.GOV, n.d. Web. 10 Mar. 2014.

<http://water.usgs.gov/edu/watercycle.html>.

"The Why and How to Testing the Electrical Conductivity of Soils." The Why and How

to Testing the Electrical Conductivity of Soils. Responsible and Organic, Farm and

Garden Supplies, 28 Feb. 2014. Web. 28 Feb. 2014.

<http://www.agriculturesolutions.com/resources/92--the--why--and--how--to-

-testing--the--electrical--conductivity--of--soils>.

"A Tour of the Water Cycle | Precipitation Education." A Tour of the Water Cycle |

Precipitation Education. NASA SVS, n.d. Web. 13 Mar. 2014.

<http://pmm.nasa.gov/education/videos/tour--water--cycle>.

"Water Cycle -- NASA Science." Water Cycle -- NASA Science. NASA SVS, 15 Apr.

2010. Web. 13 Mar. 2014.

<http://science.nasa.gov/earth--science/oceanography/ocean--earth-

-system/ocean--water--cycle/>.

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WORKS CITED:!"5.9 Conductivity." Home. Environmental Protection Agency (EPA), n.d. Web. 26 Feb.

2014. <http://water.epa.gov/type/rsl/monitoring/vms59.cfm>.!

The New Book of Popular Science. Danbury, CT: Grolier, 2006. Print.!

Perlman, Howard. "The Water Cycle." The Water Cycle, U.S. Geological Survey (USGS)

Water Science School. U.S.A.GOV, n.d. Web. 10 Mar. 2014.

<http://water.usgs.gov/edu/watercycle.html>.!

"Water and Soil Characterization - PH and Electrical Conductivity." Water and Soil

Characterization - PH and Electrical Conductivity. Microbial Life Educational

Resources, 3 Dec. 2013. Web. 17 Apr. 2014.!

"The Why and How to Testing the Electrical Conductivity of Soils." The Why and How

to Testing the Electrical Conductivity of Soils. Responsible and Organic, Farm and

Garden Supplies, 28 Feb. 2014. Web. 28 Feb. 2014.

<http://www.agriculturesolutions.com/resources/92-the-why-and-how-to-testing-

the-electrical-conductivity-of-soils>.!

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The Effect of Soil Density on Water Turbidity

By Max Ellsworth (S81 6) and Josh Kim (S81 9)

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Table of Contents Section Author Pages Abstract - Josh Kim (author 2) - 3 Introduction - Max Ellsworth (author 1) - 3 -4 Materials and Methods - Josh Kim (author 2) - 5 6 Results - Max Ellsworth (author 1) - 7 10 Discussion - Josh Kim (author 2) - 10 11 Acknowledgements - Max Ellsworth (author 1) and Josh Kim (author 2) - 12 Works Cited - Max Ellsworth (author 1) and Josh Kim (author 2) - 13 -14

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A BST R A C T The objective of the experiment was to look for a correlation between soil density and water turbidity from ponds within Drumlin Farm in Lincoln, Massachusetts. Water turbidity and soil samples were collected at three ponds: Bathtub Pond, Poultry Pond, and Ice Pond. Seven soil samples and seven water turbidity tests were performed to have fourteen data points from each pond. A total of forty-two data points were collected. A water turbidity tube was used to find the turbidity of the water from each pond. After the water turbidity was tested, soil samples were collected with a soil auger. Then the soil samples were put in an oven so that waterless soil samples could be used to find the bulk density. It was thought that Bathtub Pond would have the highest water turbidity because it has the least dense soil surrounding the pond. However the results showed that Poultry pond had the greatest water turbidity so the hypothesis was incorrect. The data was not very accurate, overall, with low linear regression values. There did not seem to be a strong correlation between soil density and water turbidity. The density data was

ties. While Ice Pond and Bathtub Pond respectively had the second smallest and third smallest turbidities, the only conclusive soil density was that of Ice Pond, which had the greatest density.!!

IN T R O DU C T I O N Soil density determines many qualities of natural habitats crucial to the life of plants and animals. These qualities include soil structure, water clarity, and irrigation (lenntech.com). Turbidity measurements signify the concentration of suspended particles in a body of water (lenntech.com). By either allowing the movement and/or ground saturation of water, or

flow of soil particles (animalrangeextension.montana.edu). Soil density is measured in grams per cubic centimeter (g/cm^3), and water turbidity is measured in centimeters (soilquality.org). The objective of this experiment is to look for a correlation between soil density and water turbidity.!

As a fully functionaDrumlin Farm, located in a Massachusetts Audubon Wildlife Sanctuary within Lincoln, has a plethora of landscapes and geographical features. Three such features are Bathtub, Ice, and Poultry Ponds. Bathtub, Ice, and Poultry Ponds provide water to the plants and animals of Drumlin Farm, which then in turn help fertilize crops, and keep the overall ecosystem in balance. The turbidity of each pond is a key factor in this balanced system. Excessive levels of turbidity in

levels (lenntech.com). This is due to the greater amount of suspended particles which reflect sunlight through the water, and prevent the light from reaching oxygen-creating plants at the bottom of that body of water (lenntech.com). Possible causes of higher turbidity include waste runoff, erosion, water runoff, Phytoplankton, and currents (lenntech.com). The Drumlin of Drumlin Farm may also provide water runoff to the various ponds.!

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Soil bulk density (g/cm^3) is the measurement of the total mass in every cubic centimeter of soil.

macropores, and the proximity and a hill slope (soilquality.org). (animalrangeextension.montana.edu). Micropores are spaces smaller than 0.08 mm between the sand, rocks, air, water, and organic material in soil, whereas macropores are those larger than 0.08 mm (soilquality.org). While micropores restrict movement, macropores enable such movement of particles and nutrients (soilquality.org). Poorly structured soil can cause excessive water and soil drainage, which is a potential cause for higher turbidity (Soil Quality Indicators). Micropores and macropores are also affected by soil density, which further ties together the relationship between soil density and water turbidity. The repeating process of water saturating into the ground through dirt, and eventually sevaporating is known as the Hydrologic cycle (animalrangeextension.montana.edu). Since soil density plays such a significant role in the health

discoveries which promote agricultural health.!

The purpose of this experiment is to determine if there is a correlation between the bulk density of soil and turbidity of water. All three ponds will each be individually examined for this correlation. Bathtub, Ice, and Poultry Ponds respectively have soil types of clay loam, silt loam, and sandy clay loam. The hypothesis states that if Bathtub pond is tested for its turbidity, then it will have the highest turbidity, because it is surrounded by the least dense soil type (agriinfo.in). The clay loam of Bathtub Pond is known to have a bulk density of 1.1 g/cm^3, which is less than 1.3 g/cm^3 and 1.6 g/cm^3 densities respectively of Ice and Poultry Ponds and its larger macropores will enable water runoff to wash its less compact soil into Bathtub Pond. The less dense soil will raise water turbidity (agriinfo.in). !

ecosystem, and searching for the stem of either a beneficial or harmful development. Through looking at water turbidity and soil density, further inferences can be made regarding land usage improvement, as water quality is a universally important factor in natural growth. Looking to the future, optimization of land usage, especially farmland, is a crucial subject, as global warming and increases in population put a stress upon the food chain

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M A T E RI A LS A ND M E T H O DS !This experiment took place at Drumlin Farm (Lincoln, MA) in three ponds, Ice, Bathtub, and Poultry Pond. To find spots for data collection a site called random.org was used. This site uses atmospheric noise to create random points so it is as random as possible. A compass was used to find these random points on the pond. The angle would be formed on the compass and then the group would walk around the pond until the big red arrow pointed at the middle of the pond.!!To find the water turbidity, a bucket was dipped into the pond. The funnel was placed onto the Jackson turbidity meter (see figure one). The water inside the bucket was poured into the turbidity tube through the funnel.The valve at the bottom of the turbidity tube was opened, and water was drained until the secchi disk could just be observed. Once the secchi disk was in sight, the valve was closed so that the current turbidity level could be recorded. The centimeter mark that the water was at on the turbidity tube was recorded. These steps were repeated a total of seven times so that seven turbidity data points for each pond had been collected. A total of twenty-one water turbidity points were collected at Drumlin Farm. Each of the soil samples were extracted from the ground next to where every water turbidity was collected. A soil auger was pushed into the spot until it was full. Then the auger was pulled back up, and the soil emptied into a ziploc bag. These steps were repeated for every random point. A total of seven soil samples were collected from each pond. Just like the water turbidity, twenty-one soil samples were collected. Overall, fourty-two data points for water turbidity and soil samples were collected from the ponds. These soil samples were later used in the science lab to find the average density for each pond.!!To find the average soil density soil samples were taken out of each bag and put into separate, labeled cupcake tins. The oven was set to forty degrees Celsius and was let to preheat. When the oven was ready, the the cupcake tins with the soil samples was put into the oven. The oven was

or two hours and then retrieved. Then each soil sample was then mashed up, using a Mortar and pestle. This made it so that there were no gaps between the soil and it was all solid. The crushed soil was put into a graduated cylinder and its measurement was recorded. Then the soil was put on a scale and the mass was also recorded. The mass of the filter cup was taken out of the weight on the scale so that only the mass of the soil would be counted. The weight was then divided by the mass of the soil and the result was recorded. These steps were repeated for all of the soil samples.!!!

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Figure 1: Soil Auger

Figure 2: Jackson Turbidity Tube

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R ESU L TS

Table 1: The effect of soil density (g/cm^3) on water turbidity (cm) at Bathtub pond.

Table 2: The effect of soil density (g/cm^3) on water turbidity (cm) at Poultry pond.

Table 3: The effect of soil density (g/cm^3) on water turbidity (cm) at Ice pond.

!"#$%&'& ()*+#!,&-./01234& 56"7#8#!,&-014&9& :;<& =>&?& :;@& =A&3& :;=& <9&B& :;=& A@&>& :;B& =>&A& :;=& =<&=& :;=& =B&

CD)"$.)& :;=& =>&E!$*8$"8&()D#$!#F*& :;?& B&

trial # Density (g/cm^3) Turbidity (cm)

1 0.9 21 2 0.5 31 3 0.7 25 4 0.6 20 5 0.8 27 6 0.7 20

7 0.7 21 Average 0.7 24

Standard Deviation 0.1 4

!"#$%&'& ()*+#!,& 56"7#8#!,&-014&9& :;@& 3A&?& 9;9& 3>&3& 9;3& 3>&B& 9;>& ?>&>& 9;9& ?=&A& 9;9& 3B&=& 9;?& 3A&

CD)"$.)& 9;?& 33&E!$*8$"8&()D#$!#F*& :;?& >&

8

Graph 1: The effect of soil density (g/cm^3) on water turbidity (cm) at Bathtub pond

Graph 2: The effect of soil density (g/cm^3)on water turbidity (cm) at Poultry pond

Graph 3: The effect of soil density (g/cm^3) on water turbidity (cm) at Ice Pond

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Graph 4: The average turbidities of Bathtub, Poultry, and Ice ponds

Graph 5: The average soil density of Bathtub, Poultry, and Ice ponds

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R ESU L TS: W RI T T E N

As seen in table three, Ice pond has the highest average soil density of 1.2 g/cm^3. Bathtub pond (Table 1) and Poultry pond (Table 2) share the lowest average soil density of 0.7 g/cm^3. Although Bathtub and Poultry pond share the least

is 33 cm. Bathtub and Ice pond share a standard soil density deviation of 0.2, whereas Poultry

density deviation is 0.1. Bathtub and Poultry pond both have a water

Examining the r-value at 0.0035. Respectively with values of 0.1569 and 0.309 are Poultry (Graph 2) and Ice

and soil density increases. Unlike the other two ponds, Bathtub poboth the soil density and water turbidity increase. Graph 5 shows that Bathtub pond has a significantly greater average turbidity (75 cm) than Poultry (24 cm) and Ice (33 cm) ponds. Poultry and Ice ponds have overlapping error bars due to their respective standard deviations of 4 and 5, which signifies a lack of a significant difference between their turbidities. Graph 5 shows

standard deviation of 0.1, Ice pond has a significantly greater average bulk density than Bathtub and Poultry ponds. Bathtub and Poultry ponds share the same average soil densities of 0.7 g/cm^3, and respectively have standard deviations of 0.2 and 0.1, which indicates that neither has a significantly greater or smaller average bulk density.

In addition to the numerical data drawn from each pond, qualitative observations were also made during the April 8 visit to Drumlin farm. Both Bathtub and Ice ponds were partially covered in Ice. Poultry pond was tinted in a murky-green hue, possibly from algae. All ponds had patches of

statement that the time was ripe for frog mating. DISC USSI O N

This experiment was conducted to test the correlation between water turbidity and the soil density surrounding it. The hypothesis was if Bathtub Pond is tested for turbidity, then it will have the highest turbidity, because it has the clay loam soil, the least dense soil, surrounding it. The lesser the density of the soil there is, the easier it is for soil particles to be broken up into water, and thus raise turbidity. (http://www.agriinfo.in). This hypothesis was not supported because although Bathtub Pond had the least amount of soil density, it had the lowest water turbidity as well. Bathtub Pond ended up with a soil density average of 0.7g/cm^3 and a water turbidity average of 75 cm. Then Ice Pond came next with a soil density average of 0.7g/cm^3 and a water turbidity average of 33 cm. Poultry pond had the same soil density average as Bathtub Pond but had the most water turbidity of 24 cm. This may be due to the fact that the topographical elements with the rain and hills were not added. Also there were many errors and assumptions throughout the experiment.

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Poultry Pond had the most water turbidity was the road right nearby it. support the observation that Poultry Pond had a high algae content. The algae path through the water, and therefore affect the water turbidity results. (amnh.org, Harrison). If

the water turbidity would be similar to Bathtub Pond since they both had the same soil density average. Another possible reason why Poultry Pond and Ice Pond have a greater turbidity than Bathtub Pond is because Poultry and Ice Ponds are both on the bottom of hills. Whenever it rains, the rain may bring down the particles from the hill, and wash them up into the ponds. This will add more water turbidity making harder to see through. (epa.gov) Bathtub Pond is on flat land so there are no particles coming from hills, which would explain why it has such a low water turbidity. The data set precision, and accuracy when compared to the original hypothesis was subpar. The linear regression in the graphs show that the correlation between the soil density and water turbidity is not significant. Bathtub Pond had the least R squared value of 0.0035, then Poultry Pond with 0.1569, and finally Ice Pond had the most linear regression out of the three ponds with 0.3091. The water turbidity standard deviations were both four for Bathtub and Poultry pond, and five for Ice Pond. The soil samples for Bathtub and Ice Pond both had a standard deviation of 0.2 and Poultry Pond had a standard deviation of 0.1. This data is almost conclusive besides

While this experiment being conducted, a few errors occurred for each pond. During the ending of the first rotation at Ice Pond, the testing was rushed to finish and so this affected the water turbidity points because it was harder to see through the water turbidity tube, when the water was stirred up inside. If there was more time to test, the water turbidity would be more accurate, as more time would allow for calmer collection. On Poultry Pond, it was hard to collect full soil density samples because there were many rocks around the pond so the soil was mostly collected from the top. The last pond, Bathtub Pond, was the most difficult to test because they were so many branches and thorns surrounding the pond. The group tried to get as close as it was possible to get to the random points and collected data from there. For future experiments, other components should be tested to see what affects water turbidity because there is no strong correlation between soil density and water turbidity.

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A C K N O W L E D G E M E N TS This project would not have been possible without the help from others. I would like to thank the Buckingham Browne and Nichols Middle School teachers who supervised data collection at Drumlin farm. I would also like to thank the teacher naturalists of the Audubon Society who answered any questions regarding Drumlin Farm. My mother, Mara Ellsworth, provided me with an oven for baking soil, and bought cupcake tins for storing the soil. This was an essential part of

ly, I would like to thank the science department, and our science teacher, Ms. Svatek, for arranging the visit to Drumlin Farm. This project would not have been possible without the help from others. I would like to thank the Buckingham Browne and Nichols Middle School teachers who supervised data collection at Drumlin farm. I would also like to thank the teacher naturalists of the Audubon Society who answered any questions regarding Drumlin Farm. My mother, Mara Ellsworth, provided me with an oven for baking soil, and bought cupcake tins for storing the soil. This was an essential part of the experiment which

Ms. Svatek, for arranging the visit to Drumlin Farm. -Max Ellsworth, author 1

thank our science teacher, Ms. Svatek for helping us throughout the project. Without her everything would have been much harder to put together. I would also like to thank our teacher

also was a big help by letting us use her oven and bake our soil samples. Last but not least, I would like to thank whoever left a patriots cup at the lost and found for letting us use it as a bucket to fill up our turbidity tube.

-Josh Kim, author 2

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W O R KS C I T E D Author 1:

Blanco, Humberto, and R. Lal. Principles of Soil Conservation and Management. Dordrecht?: Springer, 2008. Print. Brown, Katherine, and Andrew Wherrett. "Bulk Density Measurement." Bulk

Density.Soilquality.org.au, n.d. Web. 27 Feb. 2014. <http://www.soilquality.org.au/factsheets/bulk-density-measurement> HowStuffWorks.com Contributors. "What is loam soil?" 09 March

2011. HowStuffWorks.com. <http://home.howstuffworks.com/what-is-loam-soil.htm> Perlman, Howard. " Turbidity. " Turbidity. USGS, 24 F eb. 2014. Web. 27 F eb. 2014. <http://water.usgs.gov/edu/turbidity.html

" Turbidity. " Turbidity. Lenntech, n.d. Web. 27 Feb. 2014. <http://www.lenntech.com/turbidity.htm> .

> "Silt." National Geographic Education. National Geographic, n.d. Web. 01 Mar. 2014. <http://education.nationalgeographic.com/education/encyclopedia/silt/?ar_a=1>.

Author 2

"Density of Soil: Bulk Density and Particle Density." Density of Soil: Bulk Density and Particle Density. My Agriculture Information Bank, 2011. Web. 12 Mar. 2014.

<http://www.agriinfo.in/?page=topic&superid=4&topicid=271>. Harrison, Ian. "OLogy." OLogy. N.p., n.d. Web. 14 Apr. 2014.

<http://www.amnh.org/ology/features/askascientist/question08.php>. Rybolt, Thomas R. Environmental Experiments about Water. New Jersey: Enslow Publishers, 1993. Print. "Soils - Part 2: Physical Properties of Soil and Soil Water." Plant and Soil Sciences ELibrary. USDA, n.d. Web. 17 Apr. 2014. <http://passel.unl.edu/pages/informationmodule.php?idinformationmodule=1130447 039&topicorder=6>. "True Random Number Service." RANDOM.ORG -. N.p., 1998. Web. 17 Apr. 2014. <http://www.random.org/>. "5.5 Turbidity." Home. EPA, 6 Mar. 2012. Web. 14 Apr. 2014.

<http://water.epa.gov/type/rsl/monitoring/vms55.cfm>.

14

Image citations: "Funnels." A Conversion Funnel. IMGRIND, 12 Apr. 2011. Web. 18 Apr.

2014. <http://www.imgrind.com/how-to-develop-a-conversion-funnel-that-converts/>. Naturalists, n.d. Web. 18 Apr. 2014.

<https://www.acornnaturalists.com/store/SOIL-COLLECTION-TUBE-hand-auger-P2090C215.aspx>.

N.d. H ttp://www.pactogo.com/. Web. 1 May 2014.

<http://www.middlesextimber.co.uk/media/catalog/category/soil.jpg> N.d. H ttp://www.middlesextimber.co.uk. Web. 1 May 2014.

<http://www.middlesextimber.co.uk/media/catalog/category Sancaktar, Errol A. "Tools." Secchi Dipin. N.p., 29 July 2013. Web. 18 Apr. 2014.

<http://www.secchidipin.org/instruct.htm>. "SOIL COLLECTION TUBE (hand Auger)." SOIL COLLECTION TUBE (hand Auger). Acorn "Water." Turbidity. N.p., n.d. Web. 18 Apr. 2014.

<http://www.oftimeandtheriver.org/resources/mid20century/fr1931to1972_06.htm>. /soil.jpg>.