Causes of Eutrophication and its Effects of on Aquatic Ecosystems. Eutrophication can occur when inorganic nutrients are introduced into an aquatic

Size: px

Start display at page:

Download "Causes of Eutrophication and its Effects of on Aquatic Ecosystems. Eutrophication can occur when inorganic nutrients are introduced into an aquatic"

Annice Stewart
6 years ago
Views:

1 Rachel Nash BIOL 271 Prof. Wagner T.A. Emily Bernhardt Eutrophication Lab Report 4/2/2008 Abstract Causes of Eutrophication and its Effects of on Aquatic Ecosystems Eutrophication can occur when inorganic nutrients are introduced into an aquatic ecosystem. This study was conducted in order to better understand how run-off containing agricultural fertilizers can cause eutrophication. Using a system of aquariums, terrestrial and aquatic plants, and fertilizer, we measured the dissolved oxygen saturation, temperature, ph, optical density, nitrate/ nitrite, phosphate, and ammonia/ammonium of tanks subjected to fertilizer and control tanks over an experimental period of 49 days. We statistically analyzed the data and discovered that the algal density, optical density, and dissolved oxygen concentration of fertilized tanks suggested that eutrophication occurred. Because the effects of eutrophication can have a negative effect on aquatic ecosystems, and fertilizers are widely used in the United States to boost crop growth, eutrophication is a serious ecological as well as socio-economic challenge. Introduction Overproduction of organic matter in bodies of water is called eutrophication. (Ricklefs, 2007). This process commonly occurs when limiting nutrients such as phosphorus and nitrogen are introduced into aquatic systems. Phosphorus and nitrogen from agricultural fertilizers often accumulate in soils and are then leached into nearby water sources, causing eutrophication (Stephanou et. al., 2000; Torrent et. al., 2007). Eutrophication is characterized by increases in phytoplankton and algae biomass as well as changes in species and composition of macrophytes. These changes can lead to numerous problems such as decreases in water translucence and 1

2 saturated oxygen caused by the death and decomposition of plants, subsequent fish kills, and loss of aquatic biodiversity. Additionally, blooms of algae known as red or brown tides carry toxins that are absorbed into animal tissues, such as shellfish, and may harm humans if ingested. Cyanobacteria also release neurotoxins that poison livestock and threaten humans (Carpenter et. al., 1998). The process of reversing eutophication is difficult due to the challenges in tracking pollution to its sources as well as the magnitude of the affected areas. However, though phosphorus has no documented negative effects on humans or animals, nitrate pollution is toxic at high concentrations, and can harm infants as well as cattle if levels reach 45 mg/l (Carpenter et. al., 1998). Because of this and other negative effects associated with eutrophication, numerous papers exist concerning the assessment and management of eutrophic aquatic ecosystems. One such paper describes rating eutrophic levels based on concentrations of nitrate, as nitrogen is the most limiting nutrient for phytoplankton growth (Stefanous et. al., 2000). In this study we observed the process of eutrophication in a system of aquariums by treating the submerged macrophyte of a species of Elodea that is common to temperate low-land streams and lakes, with fertilizer run-off applied to potted corn plants (Madsen and Baattrup- Pedersen, 1995). Our group conducted this experiment in order to better understand the effects of fertilizer input and eutrophication on aquatic systems. We hypothesized that eutrophication would occur in tanks treated with fertilizer and that no significant evidence of eutrophication would occur in our control tanks. Based on our hypothesis we predicted that inputs of fertilizer should increase the growth of the Elodea plants in our experimental tanks, while the plants in our control tanks should have a significantly lower increase in growth. Additionally we predicted that nitrogen, phosphorus, and ammonia concentrations as well as optical density of treated tanks 2

3 should exceed that of our control tanks, while the oxygen saturation of water from our control tanks should surpass that of our experimental tanks. Methods Our experiment involved creating a hypothesis, setting up a system of plastic tanks to test our hypothesis, testing the water chemistry of the aquarium water throughout the experiment, and taking final measurements at the end of our experiment. In order to test the effects of fertilizer addition and eutrophication on water quality, we first obtained two plastic aquariums filled with 3 liters of reverse osmosis water and another 3 liters of tap water, and added 300 mg of aquarium salt to each. Next we labeled one tank as our control tank and another as our fertilizer, or experimental, tank. We took two sprigs of Elodea, weighed them, and added one to each tank. After this we planted one germinated corn seed each in two plastic pots of soil. We took initial measurements of the water from both tanks including dissolved oxygen saturation, temperature, ph, optical density, nitrate/ nitrite, and ammonia/ammonium. After taking these measurements we placed the pots on top of the aquariums as shown in Figure 1. Tanks Plastic Pots Fertilizer Control Elodea Sprigs Figure 1: Diagram of aquarium set-up 3

4 Throughout the experiment we watered the corn on top of our experimental tank with water mixed with fertilizer, and watered the control corn with plain reverse osmosis water, allowing the water to drain out of the pots and through holes in the tops of the aquariums. After twenty-eight days we repeated our initial measurements with the addition of a phosphate measurement, and also measured the corn height and Elodea mass. On day forty-nine of our experiment we took final measurements of the chemical and physical aspects of the water and weighed the Elodea along with the aboveground portion of the corn. We also estimated the amount of algal growth in each tank. We completed our three sets of measurements using a variety of materials. Through colorimetric tests using a spectrophotometer we measured phosphate and ammonia/ammonium. The reagents included a Nutrafin Phosphate Test and a Nutrafin Ammonia Test Kit made by Hagen from Montreal, Canada. We also used Quick Dip Nitrate/Nitrite Test Strips made by Jungle Laboratories Corp. from Cibolo, Texas, USA. In order to measure optical density we ran samples of water from each tank through a spectrophotometer. We measured dissolved oxygen, ph, and temperature using specialized digital meters specific to each variable. Results Control Fertilized Mean Variance Observations Pooled Variance Hypothesized Mean Difference 0 df 22 t Stat P(T<=t) one-tail 2.94E-08 t Critical one-tail P(T<=t) two-tail 5.89E-08 t Critical two-tail Figure 2: Results of two-tailed t-test assuming equal variance of the fresh biomass (g) of corn plants grown with and without fertilizer (α = 0.05). 4

5 Figure 2 shows the results of a two-tailed t-test assuming equal variance of the fresh biomass in grams of the corn plants grown with and without fertilizer added, where alpha equals The mean mass of the fertilized corn is grams while that of the control corn is 1.44 grams. With a degree of freedom of 22, P is equal to 5.89E-08, suggesting that the difference between the corn grown with and without fertilizer is statistically significant. Control Fertilized Mean Variance 8.07E Observations Pooled Variance Hypothesized Mean Difference 0 df 22 t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail Figure 3: Results of two-tailed t-test assuming equal variance of optical density (abs) of water within tanks with and without potential fertilizer inputs (α = 0.05). Figure 3 demonstrates the results of a two-tailed t-test assuming equal variance comparing the optical densities (abs) of tank water with and without fertilizer inputs. At a degree of freedom of 22 where alpha equals 0.05, P equals Thus we conclude that the difference between the optical densities (abs) of tanks treated with fertilizer run-off and those not treated with fertilizer run-off is statistically significant. 5

Figure 4: Comparative bar graph of average nutrientt

average concentrations of phosphate, ammonium,

the experimental fertilized tanks and the control

Though these values are not statistically

with a t-test, the bar graph of figure 4 shows the

any of the other nutrients, especially when measured

67 mg/l in our control The second most common

which is relatively constant between our fertilized

02 mg/ /L differencee between the higher 0.

6 Figure 4: Comparative bar graph of average nutrientt concentrations (mg/l) of water within tanks with and without potential fertilizer inputs. Figure 4 illustrates a comparison between the average concentrations of phosphate, ammonium, nitrate, and nitrite measured in mg/l found in both the experimental fertilized tanks and the control tanks. Though these values are not statistically significant when individual compounds are compared with a t-test, the bar graph of figure 4 shows the differences between the average values of the four compounds when compared to one another. As shown, nitrate has the highest concentration of any of the other nutrients, especially when measured in tanks with fertilizer input, reaching a peak average concentration off 4.17 mg/l while only reaching 1.67 mg/l in our control tanks. The second most common compound found in the water samples is phosphate, which is relatively constant between our fertilized and control groups, showing only a 0.02 mg/ /L differencee between the higher 0.82 mg/l of fertilized tanks and the mg/l of non- an fertilized tanks. Ammonium is the third highest compound measured in our tank water, having average concentratio n of.2 mg/l for fertilized tanks andd a.1 mg/l for tanks not experiencing 6

7 fertilized run-off. Nitrite, is the least common nutrient found in our aquarium systems having an average concentration in fertilized tanks of 0.1 mg/l, and an average concentration in our control tanks of 0.06 mg/l. Control Fertilized Mean Variance Observations Pooled Variance Hypothesized Mean Difference 0 df 22 t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail Figure 5: Results of two-tailed t-test assuming equal variance of changes in Elodea wet biomass (g) due to growth between plants within tanks with and without potential fertilizer inputs (α = 0.05). Figure five reveals the results of a two-tailed t-test assuming equal variance of changes in Elodea biomass as measure in grams between those plants grown in tanks with and without fertilizer inputs. With a degree of freedom of 22 and alpha equal to 0.05, P equals approximately Thus we accept our null hypothesis that no statistically significant difference exists between the changes in plant growth of the Elodea plants growing in water subject to input of fertilizers and those growing in our control tanks. Algal Category Control Tanks Fertilized Tanks 1 67% 17% 2 33% 58% 3 0% 25% Figure 6: Table of percent of control and fertilized tanks at each algal category. The table shown in Figure 6 shows the percent of control and fertilized tanks described by each algal category, where category 1 describes high abundance, 2 describes middle 7

8 abundance, and 3 describes high abundance. 67% of the control tanks fit the lowest algal category, and the other 33% were estimated at a category 2 algal abundance. None of the control tanks had enough algal growth to fit the high abundance category. 17% of the fertilized tanks were at a level 1 algal abundance, 58% at a level two algal abundance, and 25% had high enough algal growth to be placed in the category 3 of high abundance. Control Fertilized Mean Variance Observations Pooled Variance Hypothesized Mean Difference 0 df 22 t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail Figure 7: Results of two-tailed t-test assuming equal variance of dissolved oxygen concentration (mg/l) of water within tanks with and without potential fertilizer inputs (α = 0.05). Figure 7 shows the results of a two-tailed t-test assuming equal variance of dissolved oxygen concentrations measured in mg/l of water samples taken from control and fertilized tanks. At a degree of freedom of 22 and with alpha equal to 0.05, P equals As P is less than 0.05, we reject the null hypothesis, and support the hypothesis that the difference between the dissolved oxygen concentrations (mg/l) of tanks with and without fertilization run-off is statistically significant. The mean oxygen concentration for the fertilized tanks is mg/l while the average oxygen concentration for the control tanks is mg/l. 8

9 Discussion The results of our experiment support our hypothesis that eutrophication should occur in tanks treated with fertilizer, and that no significant evidence of eutrophication should occur in our control tanks. Corn grown with fertilizer had a statistically higher biomass (g) than corn grown without fertilizer, suggesting that nitrogen and phosphorus are limiting factors of corn growth, as shown by the results displayed in Figure 2, where P is 5.89E-08. The results shown in Figure 3, where P equals 0.025, support our prediction that the optical density (abs) of the water in control tanks is lower than that in fertilized tanks. This shows that more algae, fungi, bacteria, or plant growth took place in the fertilized tanks than in the control tanks. However, our prediction that fertilizer should cause the elodea in the experimental group to grow more than those in the control tanks was not statistically accurate, as revealed by the values in Figure 5 where P equals Instead, 25% of the fertilized tanks were characterized by high algal density, 58% of had a middle algal density, 67% of the control tanks had a low algal density, and none of the control tanks had a high algal density (Figure 6). Because the majority of the control tanks had low algal growth, and none of them experienced high algal growth, while one quarter of the fertilized tanks had a high abundance of algae, and the majority had at least a middle level algal abundance, we concluded that algae played a major role in the eutrophication process through raising the optical density (abs) of the water. As predicted, average nitrogen, phosphorus, and ammonia concentrations were higher in those tanks subjected to inputs of fertilizer than in the control tanks. However, none of these values are statistically significant. Instead, Figure 4 shows that nitrate and phosphorus are the nutrients used least by the aquatic life, suggesting that in the fertilized tanks, they were the least limiting nutrients. This is also supported by the P-value of Figure 5. In testing the differences in 9

10 the growth of the Elodea in fertilized and unfertilized tanks, P equals 0.45, meaning there is no statistically significant difference. This means that the fertilizer did not influence the growth of the Elodea, though future studies could reveal whether it influenced algal growth to a statistically significant level. The t-test results shown in Figure 7 reveal the final piece of evidence in suggesting that eutrophication occurred in the fertilized tanks. In documented cases of eutrophication, dissolved oxygen concentration (mg/l) in water is low (McKee et. al., 2003). The dissolved oxygen concentration (mg/l) of the water in the control tanks was significantly higher than that of the tank water that had potential fertilizer inputs, as shown in Figure 7 where P equals The ecological implications of eutrophication are various when decreases in dissolved oxygen (mg/l) are considered on a broad scale. Other studies have found that anoxia can occur in aquatic ecosystems with intense eutrophication, causing mass fish death, as well as the death of many other aquatic organisms. Reversing the process of eutrophication involves removing the sources of inorganic nutrients such as those that are used on a wide scale in the United States for agricultural purposes. The socio-economical and even political issues related to eutrophic aquatic environments are complex, and difficult to manage, making this study one of great ecological importance for the future of ecology. Further studies are needed to test methods of decreasing agricultural and urban run-off of inorganic nutrients in order to begin to remedy the negative ecological impacts of eutrophication. 10

11 References Carpenter SR et. al. (1998) Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications. 8: Madsen TV, Baattrup-Pedersen A (1995) Regulation of growth and photosynthetic performance in Elodea canadensis in response to inorganic nitrogen. Functional Ecology. 9: McKee D et. al. (2003) Response of freshwater microcosm communities to nutrients, fish, and elevated temperatures during winter and summer. Limnology and Oceanography. 48: Ricklefs RE (2007) The economy of nature, 5 th edn. W.H. Freeman and Co. New York Stefanou P et. al. (2000) Nutrient scaling for assessing eutrophication: the development of a simulated normal distribution. Ecological Applications. 10: Torrent J et. al. (2007) Agriculture as a source of phosphorus for eutrophication in southern Europe. British Society of Soil Science. 23:

EUTROPHICATION. Student Lab Workbook

EUTROPHICATION. Student Lab Workbook EUTROPHICATION Student Lab Workbook THE SCIENTIFIC METHOD 1. Research Background literature research about a topic of interest 2. Identification of a problem Determine a problem (with regards to the topic)