Jennifer Clark

Sue Dorlack

Oxygen Production and Depletion by Phytoplankton in Light and Dark Conditions of Area Ponds

 

 

Abstract

Phytoplankton are organisms that utilize photosynthetic and respiratory functions to obtain energy and reproduce. To observe this phenomenon and test the significance of these processes, we measured physical and chemical factors of area ponds during the day and night. Our results exhibit significant variations in oxygen and pH, while exhibiting little significance of temperature or chlorophyll variations. Oxygen concentrations were significantly (P = 0.004) higher during the day which corresponds to the photosynthetic processes of phytoplankton activity.

Keywords: phytoplankton, photosynthesis, respiration, photoautotroph.

Introduction

The purpose of this experiment is to observe the photosynthetic and respiratory processes of phytoplankton, and to identify significant variations of oxygen in area ponds in light and dark conditions. Such variations in oxygen concentrations qualify the presence and activity of phytoplankton populations. Further observations of data gathered can lead to determination of pond characteristics, such as high phytoplankton blooms possibly resulting from high nutrient content (geese feces &/or foliage debris). Our results will indicate higher oxygen levels during the day due to phytoplankton photosynthetic activity, and lower oxygen levels at night due to phytoplankton respiratory activity. The other measurements, such as pH, will corroborate the oxygen measurements.
Photosynthesis is the process in plants that transforms energy from sunlight to chemical energy which plants can use to grow. Plants make organic substances and release oxygen from CO2 and water when energy from the sun is absorbed in the chlorophyll pigments of plants. The basic reaction is:

6 CO2 + 12 H2O + light energy >> C6H12O6 + 6O2 + 6H2O

Phytoplankton are single celled aquatic plants that float in surface waters. Most phytoplankton are photoautotrophs, although some have complex nutritional requirements and require organic substrates They use light energy to make sugar, oxygen, and, water molecules. In dark conditions plants and phytoplankton respire, consuming oxygen. They are the primary source of energy for all aquatic food chains on earth (Berman-Frank & Dubinsky, 1999). Phytoplankton come from many classes of algae and bacteria, motile flagellates and ciliates. Microalgal cells can range in size from less than 1 mm to greater than 1 000 Ám, and in some cases can multiply to more than one million cells per liter during a high peak bloom (Martin, 2000). Because phytoplankton are one celled they cannot develop specialized organs. They can only adapt to changes in their environment through intracellular mechanisms. This means that they should be able to adapt quickly to their environment to maximize their survival. Their sensitivity to environmental conditions makes them excellent indicators of environmental trends. (Aldridge, 1997).

Microscopic algae generally go through yearly cycles of rapid growth and decay. The growth period is characterized by a burst of growth and multiplication, during which time each plant may multiply into thousands or millions. This growth burst is referred to as blooming and it goes on season after season in all types of aquatic environments. Phytoplankton diversity depends upon a number of factors, the major ones being temperature, light intensity, and nutrient levels (Martin, 2000).

The climate has been unseasonably warm, leaves are falling from the trees, and there are high numbers of geese in this area. The combination of these factors may contribute to high levels of phytoplankton activity in area ponds, even after their optimum seasonal bloom. To quantify and qualify such an observation this survey would need to be repeated during peek summer months, but for a basic understanding of phytoplankton activity, our data should allow for an adequate identification of phytoplankton activity at less than optimum conditions.

 

Materials and Methods

In order to test our hypothesis successfully, several controls were utilized. First, we determined that data needed to be collected during dark and light hours of the day. This was done to test the effects of photosynthesis and respiration of photoautrophs' ability to alter dissolved oxygen levels in water. Secondly, we determined that we needed a variety of locations for gathering our data. By doing so, we eliminated any possibility of bias and made each site unique. Next, we decided to take the night and day samples from the same sites to insure the integrity of our data. By collecting our data from the same sources (during the night and day), we decreased the likelihood of any unexpected variables from having any effect on our data. Finally, we decided that all the night samples were to be taken during the same night and all day samples be taken during the same day. By doing this, we also decreased the likelihood of any altered water conditions to effect our data.

The first part of our experiment involved collecting data at night. On October 26th, between the hours of 5:00 a.m. and 7:00 a.m. (before sunrise), we visited 8 different ponds within a 12 mile radius of Alverno College. The ponds we visited were 116th and Grange Rd., Awe's in Franklin (private property), Whitnal Park (two ponds), 86th and Grange Rd. (Jeremiah Curtain Quarry), Scout Lake Park, Wilson Park, and Jackson Park. At each site we measured the dissolved oxygen levels and temperatures by utilizing the YSI Model 85. (The YSI is an instrument that measures dissolved oxygen, conductivity, salinity, and temperature). In addition, we collected one water sample in a glass container at each site. (A total of 8 samples were taken during the night). The samples were placed in a dark cooler to prevent any change from occurring in the water conditions. Immediately after all the night samples were gathered, we returned to Alverno to test the pH and absorbance of each. We used a pH meter and spectrophotometer to obtain this data.

The second part of our experiment involved using the same procedures to collect our day samples as we did when collecting our night samples. We collected 16 samples throughout the entire experiment. The following table reflects the data we gathered during the entire experiment.

 

Figure1

Dissolved Oxygen (mg/L)

pH (log value)

Temperature (C˚)

Absorbance (560 nm)

Site

Night

Day

Night

Day

Night

Day

Night

Day

1

10.3

19.8

.892

.897

15.4

11.2

.025

.03

2

8.4

10.43

.872

.873

14.8

13.5

.01

.02

3

9.3

19.5

.885

.898

15

12

.04

.058

4

15.1

14.8

.887

.895

14.4

13

0

.022

5

12.3

19.3

.877

.894

15.3

15.5

.03

.035

6

15.3

19.3

.876

.886

15.6

16.9

.012

.05

7

12.2

17

.871

.883

15.6

13.4

.037

.06

8

9.1

11.22

.877

.887

15.3

13.7

.2

.17

Avg.

11.5

16.419

.879

.889

15.175

13.65

.044

.057

 

Results:

The data gathered shows that the average of dissolved oxygen levels increased to an average of 16.419 mg/L during the day and decreased at night to an average of 11.5 mg/L. (See figure 2). According to a T-test run on the individual oxygen levels (to determine if the data reflected any significant differences), the value of .004 was obtained.

The data also shows that the average pH levels increased during the day (.889) and decreased at night to .879. (See figure 3). A T-test was run on the individual pH levels and produced a value of .0004.

The average temperature shows a decrease during the day (13.65C˚) and an increase during the night (15.175C˚). (See figure 2). A T-test reflected the value of .02.

The data also shows that average absorbance increased during the day to .057 and decreased to .044 during the night. (See figure 3). A T-test run on the individual absorbances produced a value of .076.

A correlation test was run between the dissolved oxygen levels and the pH levels from the data collected at night. The value of 0.056 was given. Likewise, a correlation test was run between the dissolved oxygen levels and pH levels from the data collected during the day. The result was the value of 0.668.

Figure 2

 

 

Figure 3

 

 

 

 

 

 

 

Discussion

The data and results support our hypothesis, that photosynthetic activity will exhibit significant variations in oxygen concentration in the day, photosynthesis versus the night, respiration. Statistical analysis of oxygen averages show a significant increase in oxygen concentration during the day. This is further supported by the analysis of pH levels that also show a significant increase in pH, which is typical of chemical properties of water. The more oxygen species, the more basic a solution will be (­ OH basic, ­ H acidic). Correlation between oxygen concentrations and pH values show a midrange, positive relationship. The other variables tested exhibit a control factor, such that there is no significant variation in spectrophotomic analysis of chlorophyll or temperature. If there was a significance of either of these variables the significance of the oxygen results would possibly be attributed to the presence of more phytoplankton at the time at which the second samples were obtained. The same is true for temperature, since it also can affect oxygen concentrations, considering the properties of water. Relative observations of turbidity, it was calm during the time span of testing at both times, show it was not a contributing factor to oxygen levels (Martin, 2000).

Further studies would be needed to qualify whether unseasonable conditions, geese abundance, and foliage debris are contributing factors to phytoplankton activity at such a late time of year. Testing during the summer and winter months would allow for observations at optimum and unfavorable conditions. Carbon and/or nutrient analysis would also be useful in determining limiting factors of phytoplankton activity (Mullineaux, 1999). Other ecological observations could be further analyzed by testing for aquatic herbivore populations such as zooplankton, and their affects on phytoplankton populations (Vanni & Layne, 1996).

 

 

 

 

 

 

References

 

Aldridge, Lisa. 2000. Phytoplankton in Hamilton Harbour. McMaster University Link: www.science.mcmaster.ca/biology/harbour/species/hhphyto/phyto.htm

Berman-Frank, Ilana & Dubinsky, Zvy. 1999. Balanced growth in aquatic plants: myth or reality? Bioscience, Vol. 49 Issue 1.

Martin, Jennifer L. (2000). Protocol for Monitoring Phytoplankton. A REPORT BY THE MARINE BIODIVERSITY MONITORING COMMITTEE (ATLANTIC MARITIME ECOLOGICAL SCIENCE COOPERATIVE, HUNTSMAN MARINE SCIENCE CENTER) TO THE ECOLOGICAL MONITORING AND ASSESSMENT NETWORK OF ENVIRONMENT CANADA, Department of Fisheries & Oceans Biological Station, St. Andrews New Brunswick, Canada E0 G 2X0

Mullineaux, Conrad W. 1999. The plankton and the planet. Science, Vol. 283 Issue 5403.

Vanni, Michael J. & Layne, Craig D. 1996. Nutrient recycling and herbivory as mechanisms in the "top-down" effect of fish on algae in lakes. Ecology: Vol. 78, No.1.

*Introduction & Discussion, J. Clark. M&M & Results, S. Dorlack. Sampling & Data Analysis (lab), BOTH