Introduction to the Biotic Water Quality of a Stream

Transcription

1 Teacher s Guide Introduction to the Biotic Water Quality of a Stream Lesson Description This lesson allows students to learn the Biotic Water Quality Score (BWQS) method for collecting macroinvertebrates. Organisms with a high sensitivity to reduced oxygen levels are given a high numerical value. Organisms that can thrive in low oxygen levels are given a low numerical value. Factors that promote high oxygen content will also promote a diversity of macroinvertebrates. The central idea behind quantification is that macroinvertebrates have a wide range of oxygen requirements. Following student research on assigned benthic, aquatic organisms, the preliminary activity will allow students to perform a dry run to practice the skills needed for the actual BWQS field study. Skills included are: collecting procedures, proper identification of aquatic organisms, using a taxonomic key, data recording and evaluation. The preliminary activity in the classroom consists of showing the students the kick seine net and demonstrating how to use it. A key idea is to put down four meter sticks to show students the size of the area they should be disturbing. Students will learn that kicking is turning over rocks and mixing up the sediment with their feet as well as rubbing the benthic organisms to dislodge them from the bottom of the rocks. After these skills are demonstrated, students in small groups use the sheets from their student packets to identify the various groups of aquatic organisms. Students use a picture and/or taxonomic key to identify each organism and then tally all organisms on the BWQS data sheet. Using MS Excel, students create a spreadsheet with the appropriate biotic values for each organism. Using this spreadsheet they then calculate the BWQS. See for details. Following the procedure, three samples are collected from the stream study site. Each kick seine collection must be scanned carefully to find all the organisms. Usually an attempt is made to collect 100 organisms for the purpose of having a representative sample. Be aware that the larger more motile organisms will be collected first. Teachers will demonstrate how to carefully move debris and search for the less motile macroinvertebrates. Give students the opportunity to use the same techniques to continue the search. With continued supervision and patience the smaller, less motile organisms will be collected. Sometimes students collect far fewer aquatic macroinvertebrates than the expected numbers. In this case, it is easy to express the number of organisms collected as a percentage of 100. In a small population, each organism must be represented in the final BWQS. Find the spreadsheet from the Project Watershed website, with all formulas included, under teacher resources. If you are unable to download the spreadsheet from the website, the BWQS sheet included in this packet will have to be calculated by students. Science Concepts Introduced Sampling procedures Macroinvertebrate identification Determination of species diversity Observation of macroinvertebrates life cycles 1

2 Process Skills Emphasized Collecting benthic organisms Using a taxonomic key Organizing Analyzing data into a spreadsheet using MS Excel to determine the BWQS. Use an MS-Excel spreadsheet to analyze and graph data. Technology Used Internet Word and Excel programs Project Watershed database Aquatic macroinvertebrate picture keys: MST Standards Standard 1 key idea 1 and 3 Standard 4 key idea 6 and 7 Standard 7 key idea 1 Learning Outcomes Students will be able to: Properly use a taxonomic and/or picture key to identify benthic organisms Collect aquatic macroinvertebrates using a kick seine net Enumerate all organisms collected Compute a BWQS based on a collection of macroinvertebrates Graphically represent each group of the organisms that make up the BWQS Use the Project Watershed database to compare BWQS to the chemical and physical properties of a stream. Time Requirements Preparation activity - two class periods (60 80 minutes) Data collection minutes (approximately) at a stream site. Data Analysis - two-class period (60 80 minutes) in the computer lab Instructional Strategies Collection and identification of macroinvertebrates Enumeration of macroinvertebrate on a spreadsheet. Group research, followed by presentations Background Research on Macroinvertebrates Nerbonne (2003) found a possible bias and error in sorting and identifying aquatic insects (macroinvertebrates). In a masters thesis she described students, when sorting insects from debris (kick seine,) selected mostly larger (rather than smaller) insects and insects that moved slowly (compared to insects that moved too fast or not at all). Proper insect identification was also a problem. Nerbonne s study shows the need for adequate training and preparation. She also suggests that sampling groups work in teams for sorting and identifying aquatic macroinvertebrates to verify students sorting and identification efforts. Prior to the field trip, knowledge of the stream site and weather conditions is a necessity for the safety of the students. Even smaller streams can be dangerous with fast, high waters. 2

3 Project Watershed has a permit, and all schools involved are collecting under the Project Watershed umbrella. Project Watershed has a collection license that will support your activities only while collecting with them. The handouts of macroinvertebrates from the Project Watershed site (see teacher resources) that represent the collections for the classroom simulation are in the student packet. The macroinvertebrate collection key is in the teacher packet. This preliminary activity will allow students to become familiar with the collecting equipment, collecting procedures, identification of macroinvertebrates, data recording and the calculation of the BWQS. Preliminary Activity Teachers should have a basic understanding of the aquatic macroinvertebrate life cycles and also be able to identify (or use a key to identify) most of the aquatic insects on the data table. Chemical and physical needs of aquatic organisms are important to know because of the relationship between those parameters and the number and types of aquatic organisms. Students will perform a classroom simulation of the stream collection process before going to the stream for the actual field collection process. Each time they will follow the same procedure as seen in the SUNY ESF Lesson #5 Biological Stream Monitoring: How to Calculate the Biotic Water Quality Score. Collect aquatic macroinvertebrates, properly identify them and input the values into a spreadsheet to determine the BWQS. Stream Data Collection Students must be supervised while in or near the stream performing the collection procedures. Assume that at least 10 different groups of benthic organisms could be identified. Then from their simulation they will be able to separate all similar organisms into separate containers. Once they have scanned the kick seine after three different collections a final tally of each container will be conducted. The students then record the final number of each different type of organism and record the data on the tally sheet. Carefully release all organisms back into the stream. Collect all equipment and prepare to exit the stream site leaving it as clean as when you arrived. Assessment Assessment of this lesson is two fold. First, the preliminary student activity can be assessed by which stream site each group is performing. Teachers have the data answer sheet to check student s results. Each group will receive stream site sheets numbered 1 thru 5. The results should be the same from group to group when using the sample stream site. Second, after data is collected in the field it must be analyzed. Students will analyze each set of data collected to input the BWQS. Students will use the Project Watershed spreadsheet from the teacher resource section on the website to analyze their data. Extensions/Options This same activity can be done using one stream site and comparing the BWQS from season to season. Research the life cycles of aquatic organisms; this will promote understanding of how aquatic ecosystems can change from season to season. Groups of 2 or 3 can research specific organisms and present to the class pictures of juveniles and adults and their ecological role at various stages of their metamorphosis. Project Watershed s database can be used to download the data for graphing the water chemistry at the site where students have collected invertebrates. Compare the chemical and physical properties of all highly sensitive (a high BWQS value) stream collection sites to the same properties of low sensitivity sites (a low BWQS value). Report the similarities and differences in your findings to the class. Analyze the similarities or differences in the BWQS in fall, winter, spring and summer collections. Draw relationships between abiotic (chemical and physical) properties and biotic properties. 3

4 Key Terms abiotic, aquatic organisms, benthic, biotic, chemical and physical parameters, cobbles, diversity, nymph, larva, macroinvertebrates, life cycles, runoff, stream ecosystems, riffles, pools. Prerequisite Knowledge basic understanding of stream ecology use of taxonomic dichotomous keys of macroinvertebrates use of taxonomic dichotomous picture keys of macroinvertebrates Microsoft Word and Excel aquatic life cycles pollution ecology of runoff in streams runoff nonpoint source pollution point source pollution Equipment Needed aquatic kick seine net white board or white background light colored collecting pans and jars (10 12) forceps and plastic spoons (6 8 of each) boots or waders (2 or 3 pairs) taxonomic and picture keys (4 or 5 laminated) References Biological Stream Monitoring: How To Calculate the Biotic Water Quality Score, Lesson 5 on invertebrates monitoring can be downloaded from the SUNY ESF website. Follow these links: K-12 teachers & students 3. K-12 programs and resources 4. Supplemental curriculum materials and other resources 5. Environmental analysis of watersheds See Key from Project Watershed for identification of macroinvertebrates. M.K. Mitchell and W.B. Stapp 1997 Field Manual for Water Quality Monitoring, GREEN/Earth Force, Alexandria, VA. Websites Project Watershed Database: Aquatic Macroinvertebrate picture keys: Work Cited: Caduto, Michael J., 2003 Canaries of the Waters, Sanctuary, Massachusetts Audubon Society, p Nerbonne, Julia Frost and Bruce Vondracek Volunteer Macroinvertebrates Monitoring: Assessing Training Needs Through Examining Error And Biases In Untrained Volunteers, Journal of the North American Benthological Society 22 (1): Handouts 1. Data collection sheets from the Project Watershed website Each Stream Study (1-5) is based on material found on the Project Watershed web site. 3. Spreadsheets for sample collections of the BWQS. 4

5 Sample 1 BWQS Answer Page Total points = 372/40 = 93 Biotic Water Quality Score = Excellent 10 Stonefly nymph x 10 points = Mayfly nymph x 10 points = Caddisfly larva x 10 points = 40 2 Water Penny larva x 10 points = 20 6 Dobsonfly larva x10 points = 60 2 Riffle Beetle larva x 10 points= 20 4 Crayfish x 6 points = 24 2 Gilled Snail x 4 points = 8 5

6 Sample 2 BWQS Answer Page Total points = 174/32 = 54 Biotic Water Quality Score = Good 2 Stonefly nymph x 10 points = 20 3 Fishfly larva x 6 points = 18 1 Caddisfly larva x 10 points= 10 1 Water Penny larva x 10 points = 10 2 Cranefly larva x 8 points = Midgefly larva x 5 points = 70 2 Crayfish x 6 points = 12 4 Aquatic worm x 0 points = 0 6

7 Sample 3 BWQS Answer Page Total points = 108/19 = 56 Biotic Water Quality Score = FAIR 2 Dobsonfly larva x 10 points x 20 2 Stonefly nymph x 10 points = 20 4 Midgefly larva x 5 points = 20 5 Crayfish x 6 points = 30 3 Aquatic worm x 0 points = 0 3 Damselfly nymph x 6 points = 18 7

8 Sample 4 BWQS Answer Page Total points = 129/28 =46 Biotic Water Quality Score = POOR 2 Leech x 2 points = 4 2 Cranefly larva x 8 points = 16 4 Aquatic worm x 4 points = 0 5 Midgefly larva x 5 points = 25 3 Lunged snail x 4 points = Blackfly larva x 6 points = 72 8

9 Sample 5 BWQS Answer Page Total points = 166/47 = 35 Biotic Water Quality Score = POOR 15 Aquatic worm x 0 points = 0 9 Blackfly larva x 6 points = 54 3 Lunged snail x 4 points = Midgefly larva x 5 points = 100 9

10 Sample 6 BWQS Answer Page Total points =322/36 = 89 Biotic Water Quality Score = EXCELLENT 7 Mayfly nymph x 10 points =70 2 Cranefly larva x 8 points = 16 8 Caddisfly larva x 10 points = 80 1 Planarian x 0 points = 0 4 Gilled snail x 4 points =16 10 Stonefly nymph x 10 points = Dobsonfly larva x 10 points = 20 2 Water Penny larva x 10 points = 20 10

11 Student s Guide Introduction to the Biotic Water Quality of a Stream Introduction Aquatic insects are like canaries in the coal mine. They indicate the health of the water. Each aquatic species has certain tolerances to pollution levels. Insects can be affected by changing water chemistry, temperature, dissolved oxygen, substrate and water flow. A clean environment has a diversity and richness of aquatic insects (Caduto, 2003). Pollution of a stream can come from many different sources. Water that passes through a heavily residential area faces runoff from lawn chemicals and fertilizers, sewage treatments outflows, and leaching of septic systems. In a rural area, most of the contamination comes from runoff from farms containing high amounts of nitrogen and phosphorus (Caduto, 2003). All types of runoff have the potential to harm an aquatic ecosystem. If runoff kills algae on rocks, then mayflies that feed on the algae die off. The stoneflies and others that feed on the mayflies soon die off and eventually affect the top predators such as trout. In a coal mine when a canary died, the miners got out of the mine quickly. If the insects and other macroinvertebrates die in our streams, what can we do? Where can we go? Our job is to use macroinvertebrates as indicators of stream health to tell us if there are pollution problems in the stream or watershed. A wide diversity of oxygen sensitive macroinvertebrates in a stream equates to a healthy canary in a coal mine. Learning Outcomes Students will be able to: Properly use a taxonomic and picture key for aquatic macroinvertebrates. Collect aquatic macroinvertebrates using a kick seine net. Graphically represent the Biotic Water Quality Score (BWQS) and compare water quality conditions at the site at various seasons of the year. Skills Required Group work in a cooperative manner Using a taxonomic key (proper macroinvertebrate identification) Proper sampling procedures Data collection and analysis Spreadsheet composition (data entry and analysis) New Terms abiotic, aquatic organisms, benthic, biotic, chemical and physical parameters, cobbles, diversity, nymph, larva, macroinvertebrates, life cycles, runoff, stream ecosystems, riffles, pools. 11

12 Quest We are making a transition from our current biotic monitoring method to a more quantified method for Biotic Water Quality Score (BWQS). Your quest is to find a way to improve the biotic method by using the BWQS. You will include a section in your final report offering suggestions for improvement. All aspects of biotic monitoring are open for suggestions. If something about the process described in the lesson is unclear to you, define the problem and suggest a possible improvement. Suggestions will go to your teacher and to the Project Watershed host site. If you are uncertain what the suggestion for improvement should be, at the very least explain what you are having difficulty understanding. We will make every attempt to help you in your quest. Materials aquatic kick seine net white board or plastic about the size of a kick seine (2 x 3 ) light colored collecting pans and jars (10 12) forceps and plastic spoons (6 8 of each) boots or waders (2 or 3 pairs) taxonomic and picture keys (4 or 5 laminated) data tables Procedure Research on macroinvertebrates 1. Students work in pairs or small groups. 2. Each group will be given a specific aquatic organism. 3. Each group will be responsible for gathering as much information on that organism and presenting it. This can be done using poster board or power point. 4. Presentations should include information for each stage of nymph, larva and the adult. Include: a picture, physical descriptions, changing habitats, scientific name, role in the food web, use as an indicator species and any human uses. Preliminary Lesson 1. In small groups you will each receive a packet containing pictures of benthic organisms from an actual stream sample. 2. Your group task is to correctly identify all presorted organisms. 3. Make sure everyone in the group agrees. Identification is a team effort, not the job of one student (group checks and balances). 4. Record the numbers for each macroinvertebrate next to its name in the spreadsheet. 5. The last step is to calculate the BWQS for that stream site using the values in the spreadsheet. Stream Data Collection You will be collecting macroinvertebrates from a specific section of a stream and determining the BWQS for that section. The BWQS may not be indicative of the entire stream because of many other factors. Discuss with your group why and how these numbers can change from section to section of the stream. 1. In groups, pick a shallow area (1 2 ) in a riffle near the study site. The sample area should have plenty of cobbles (rocks). 2. Samples should be taken as demonstrated by your teacher in class. It is very important samples are gathered as carefully as possible to obtain a representative sample of the macroinvertebrates living in the stream. 3. The collecting group will split into 2 sub-groups. The kickers (2 students) and the collectors (4 or 5 students). Students can switch from time to time. 4. A 3 by 3 area should be sampled (kicked) for 1 minute. 12

13 5. The kick seine should be carefully brought to the stream bank and placed on a white background (for better visibility). 6. Three or four students should check the net for macroinvertebrates. Students should be thorough and take their time. 7. Carefully remove these organisms and place all similar organisms in a container with water. 8. After all macroinvertebrates have been collected, they need to be identified accurately. Every member of the collecting team needs to help. All decisions need to be verified by another member of the team (a system of checks and balances). 9. Record your data on the data sheet. The BWQS can be calculated from the data sheet. Extensions/Options Prepare a presentation of your stream study data at a public forum. Using either poster board or power point, present your sampling methods, data collected and analysis of the water quality. You may hypothesize on why the stream supports this type of diversity and describe why projects like this have an important place in environmental monitoring. Assessment 1. Perform the previous method of sampling using the same organisms in this sample. Compare and contrast the previous method to the BWQS. 2. Explain the importance of Indicator Species. 3. How do the abiotic factors such as temperature and dissolved oxygen (DO) affect the abundance or presence of certain aquatic organisms? 4. How are aquatic organisms that are sensitive to pollution like the canary in a coal mine? 5. Besides temperature and dissolved oxygen, what other (a) chemical factors and (b) physical factors can affect the diversity of aquatic macroinvertebrates? 6. Why might the BWQS change from section to section of the same stream? Handouts Data collection sheets from the Project Watershed website. Packet with spreadsheets and sample collections. 13

14 Investigating a Watershed Using BWQS: Sample 1 (1) 10 collected (1) 10 collected (1) 4 collected (1) 2 collected (1) 6 collected (1) 2 collected (1) 4 collected (1) 2 collected (1) 14

15 Sample 2 (2) 2 collected (2) 3 collected (2) 1 collected (2) 1 collected (2) 2 collected (2) 14 collected (2) 2 collected (2) 4 collected 15

16 Sample 3 (3) 2 collected (3) 2 collected (3) 5 collected (3) 4 collected (3) 3 collected (3) 3 collected 16

17 Sample 4 (4) 2 collected (4) 2 collected (4) 4 collected (4) 5 collected (4) 3 collected (4) 12 collected 17

18 Sample 5 (5) 15 collected (5) 9 collected (5) 3 collected (5) 20 collected 18

19 Sample 6 (6) 7 collected (6) 2 collected (6) 8 collected (6) 1 collected (6) 4 collected (6) 10 collected (6) 2 collected (6) 2 collected 19

20 BIOLOGICAL WATER QUALITY MEASUREMENT A biotic score is based on the tolerance of different benthic organisms to pollutants; some organisms are tolerant and some are sensitive. According to the biotic score method, sensitive organisms are assigned high values and tolerant organisms are assigned low values. The computer average value for a collected sample yields the Biotic Water Quality Score. Procedure: (1) Collect close to 100 organisms. (2) Identify all the organisms using a macroinvertebrate identification key; record the number of each organism identified. (3) Enter the number in the yellow number column. Excel will multiply the number of each organism identified by its BWQS and then divide the product by 10. (4) Excel will calculate the individual organism scores to obtain the percentage of the total = BWQS. Suggested ranges of Biotic Water Quality Scores for streams in New York State: non-impacted (excellent water quality ) slightly impacted (good water quality ) moderately impacted (fair water quality) 0-40 Severely impacted (poor water quality) BIOTIC WATER QUALITY SCORE WORKSHEET AQUATIC NUMBER BIOTIC ORGANISMS COLLECTED VALUE PRODUCT Product/10 (A) (B) A X B A X B / 10 Aquatic worm Beetle Larva (not riffle) Black fly Caddisfly Clam Cranefly Crayfish Damselfly Dobsonfly Dragonfly Fishfly Leech Mayfly Midge Riffle Beetle Scud Snail Sowbug Stonefly Water penny larva TOTAL 0 BWQ SCORE = #DIV/0! Source: Robert Bode, NYS DEC Nov-99 NAME OF STREAM: LOCATION: DATE: 20

21 Teacher s Guide Comparing Current Chemical Water Quality Measurements with Past Measurements At A Stream Site Lesson Description In this lesson, students will compare their most recent water quality measurements with their past measurements at the same stream site. Samples are usually taken during the spring and fall seasons of the year, and to avoid seasonal variations, the spring measurements should be compared only to spring measurements from the past. The same protocol should be followed when comparing the fall measurements to those from the past. Samples collected from the most recent stream surveys can be measured and converted to Q values. (Mitchell and Stapp). The averaged measurements from the same site collected for the same season of the year should also be converted to Q values. The Q values, as illustrated in the aforementioned reference, assign a value between zero and one hundred for each measurement conducted. By using a Q value, the amount of a substance present can be compared to the ideal amount of that substance. The Q value allows us to compare the measured levels of phosphates, nitrates, turbidity and all the other measurements to the ideal values for the stream sample. The use of Q values provides a level playing field, and instead of comparing apples to oranges we can compare, for instance, the ripeness of apples to the ripeness of oranges. The measurement of ripeness for apples and oranges can be assessed by Q values, and this analogy can be applied to any of the water quality measurements for comparison. There are several other methods to evaluate and analyze the water quality data, but they require the use of statistics that may be outside the scope of this investigation or beyond the expertise of the students. Keeping with the data conversion to Q values, our comparisons will be simply how far is our sample or our database average below the ideal amount for each measurement. Any difference in value that is greater than 10 Q values is considered worthy of closer inspection and further investigation. Science Concepts Introduced Compare current data collected from a stream site to accumulated data at that stream site. Evaluation of recently collected data to an on-line database. Process Skills Emphasized Accessing web based information. Downloading data to a spreadsheet. Comparing recently collected data to the database average Preparing a class presentation Technology Used: Computer Analytical software such as MS Excel Internet MST Standards Standard 1: Key idea 1 - Performance indicators 1, 2, 3 Standard 2: Key idea 2 - Performance indicators 1, 2, 3 Standard 3: Key idea 1 - Performance indicator 2 Key idea 6 - Performance indicator 1 Standard 7: Key idea 1 - Performance indicators 1 and 4 Key idea 2 - Performance indicators 1, 2, 3, 4, 5, 6

22 Learning Outcomes Students will be able to: 1. Use a spreadsheet to find the averages for a set of chemical values. 2. Manipulate data in MS Excel. 3. Convert data into graphs in MS Excel 4. Compare and evaluate a recent collection with past collections of data. 5. Communicate group results in a class presentation Time Requirement 4 Class periods or 2 double periods (block) Collection and analysis Comparisons and class presentations Instructional Strategies Learning and communicating through group work Background Input a new column (monthly) in the downloaded database, allowing students to cancel out seasonal differences. Assist groups on the spreadsheet manipulation. If possible, arrange to have a technophile in each group capable of performing, or better yet, teaching the spreadsheet functions to the other group members. If students do not have computer access, the teachers may have to sort the database to obtain average values for comparison. Use the Q values to make the comparisons. Values usually deviate from the number (+ or ) by two or three Q values. A good estimation for a significant number will be a difference of ten or more Q values between chemical measurements. Assessment Q value results will be quantified and compared in a group presentation. A written report will be submitted following the oral report. Both reports will be evaluated to see how students determined the Q values. Extensions/Options 1. Students plot spring/fall variation for each chemical test. 2. Each group graphically displays seasonal variations. 3. Compare two samples from different stream sites from the same stream (collected on the same day). These comparisons should be relatively simple because the same weather and precipitation conditions will be present at both sites. Key Terms Q values, upstream site, downstream site, database, chemical v non-chemical measurements Prerequisite Knowledge 1. All participants will understand how to find optimum results for water chemistry tests using the Q values tables from the references. (Mitchell and Stapp). 2. The water quality chemistry tests include: dissolved oxygen (DO), ph, nitrates, phosphates, total dissolved solids, chlorides, biochemical oxygen demand (BOD). 3. The non-chemical water quality tests include: turbidity, and fecal Coliform Equipment Needed Computer with MS Excel and MS Word Printer Internet Access

23 References M.K. Mitchell and W.B. Stapp 1997 Field Manual for Water Quality Monitoring, GREEN/Earth Force, Alexandria, VA Web sites:

24 Handouts Conversion Graphs for water quality measurements to Q values from Mitchell and Stapp

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26 Student s Guide Comparing Current Chemical Water Quality Measurements with Past Measurements At A Stream Site Introduction Once water quality measurements obtained from a stream study are available, there must be an investigation to see if those measurements are accurate. The most recent stream study will be compared to the averaged test results from the database. If these results are similar in Q value to the samples collected in the past, they will tell us no significant pollution has occurred recently (the last several days) upstream from the collection site. Pollution can enter the watershed in many forms. Project Watershed s nine tests are specific to the most probable types of pollution. If differences between your sample and the average from the database are found in significant numbers, it would signal pollution is entering the watershed somewhere upstream. The water quality chemistry tests include: dissolved oxygen (DO), ph, nitrates, phosphates, total dissolved solids, chlorides, biochemical oxygen demand (BOD). The non-chemical water quality tests include: turbidity, and fecal coliform. Your instructor will present a simple method for comparing test results using Q values (Mitchell and Stapp). Learning Outcomes Students will be able to: Use a spreadsheet to find the averages for a set of chemical values. Manipulate data in MS Excel. Convert data into graphs in MS Excel Compare and evaluate a recent collection with past collections of data. Communicate group results in a class presentation Skills Required Use of computers and software Sort information from the database Compare data from various sites and times Public speaking New Terms Q values, chemical physical and biological parameters. Quest You are an investigator searching for traveling midnight polluter (s) who has been releasing illegal chemicals into our local streams. We know that there have been large amounts of certain chemicals released at various times of the year. The problem is that we only monitor the stream twice a year. Realizing that once the chemicals are released, they can be washed away by the stream flow. We have to almost catch the polluter(s) in the act. Your task is to compare recently collected samples to the Project Watershed database and determine if the polluter(s) has made an illegal release into your stream. Materials A set of data from your most recent stream study Computer with MS Excel and a word processing program Access to the Internet Procedure 1. Download all the water chemistry data at the selected stream site. 2. Sort the data by month to avoid seasonal influences. 3. Compute and evaluate the mean for each of the nine parameters of water quality from the database. 4. Convert each mean to a Q value from the established reference. 5. Convert the current data collected from the recently measured stream site into Q values using the reference (Mitchell and Stapp).

27 6. Compare the Q values for each of the chemical parameters to see if there are what you would consider to be significant differences. 7. Find any deviation between current and past values. Explain the differences and why they would be considered highly significant. 8. Develop an Excel bar graph to show the current and past Q values for visual comparison of the investigation results. 9. Present the results of your investigation to the class. Extension/Options 1. Students plot the monthly values for each of their chemical tests. 2. Identify variations in the spring/fall period. Expect wide variations. 3. Graphically display any seasonal variation. 4. If your stream fails to show expected variations, choose another stream (available on the website) with a larger database. 5. Compare two samples from different stream sites from the same stream collected on the same day. These comparisons should be relatively simple because the same weather and precipitation conditions were present at both sites. Expect minimal variations. References M.K. Mitchell and W.B. Stapp 1997 Field Manual for Water Quality Monitoring, GREEN/Earth Force, Alexandria, VA. Websites: See websites (above) to research why the Q values vary by a significant amount. Assessment Rubric Work effectively by following directions for analysis of water quality parameters using Q values. Demonstrate the ability to gather and process information by downloading the appropriate data. Demonstrate the ability to calculate all parameters into seasonal averages using a spreadsheet for comparison. Generate Q values from the processed data. Demonstrate ability to analyze Q values (present to past). Demonstrate significant differences in Q values and offers a hypothesis for the variations. Present results and interpretation in a clear, concise and informative manner. Handouts

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29 OPTION: BIOLOGICAL WATER QUALITY MEASUREMENT A biotic score is based on the tolerance of different benthic organisms to pollutants ; som organisms are tolerant and some are sensitive. According to the biotic score metho sensitive oranisms are assigned high values and tolerant organisms are assigned lo values. The computer average value for a collected sample yields the Biotic Water Qua Score. Procedure: (1) Collect close to 100 organisms (2) Identify all the organisms using a macro-invertebrate identification ke record the number of each organism identified (3) Enter the number in the yellow number column. Excel will multip the number of each organism identified by its BWQS and then divide the product by 10 (4) Excel willl calculate the individual organism scores to obtain the percentage of the total = BWQ Suggested ranges of Biotic Water Quality Scores for streams in New York State non-impacted (excellent water quality slightly impacted (good water quality moderately impacted (fair water quality 0-40 Severely impacted (poor water quality BIOTIC WATER QUALITY SCORE WORKSHEET AQUATIC NUMBER BIOTIC ORGANISMS COLLECTED VALUE PRODUCT Product/10 (A) (B) A X B A X B / 10 Aquatic worm Beetle Larva (not riffle Black fly Caddisfly Clam Cranefly Crayfish Damselfly Dobsonfly Dragonfly Fishfly Leech Mayfly Midge Riffle Beetle Scud Snail Sowbug Stonefly Water penny larva TOTAL 0 BWQ SCORE = #DIV/0! Source: Robert Bode, NYS DEC Nov-99 NAME OF STREAM: LOCATION: DATE: THE BIOTIC WATER QUALITY SCORE METHOD

30 Teacher s Guide Using A Volunteer Acquired Database Constructed On The Internet, Examine the Relationship between Dissolved Oxygen and Water Temperature Lesson Description The relationship between dissolved oxygen and water temperature is critical for aquatic life in a stream, river or lake. More dissolved oxygen is present in water with a lower temperature compared to water with a higher temperature. The reason for this inverse relationship between dissolved oxygen and temperature is that the solubility of a gas in a liquid is an equilibrium phenomenon. According to La Chatelier's Principle, any reaction reaching equilibrium will seek a new equilibrium when a variable (temperature) influencing that equilibrium is altered. This gas solubility in a liquid relationship can be further clarified if you think about what happens to a cold carbonated beverage; as it is opened and stands around for a while at room temperature. Once warmed to ambient temperature the taste is very flat ; since more of the tangy ; carbon dioxide bubbles have escaped. Boiled water also tastes flat because all of the oxygen gas has been removed by heating. More dissolved oxygen is present in water with a lower temperature compared to water with a higher temperature. Given the two variables of dissolved oxygen and temperature with a possible linear relationship, an analysis of the relationship is possible by plotting both variables on a graph as part of an XY scatter plot. Using MS Excel spreadsheets, it is very easy to do this. Using either Excel or a graphing calculator, calculate the correlation coefficient, conduct a linear regression on the data, and find the given r-squared value along with the "best-fit-line" equation. The correlation coefficient = r is a value between negative 1 and positive 1. The closer the value is to -1 and +1, the better the predictability of the relationship. If r =-1, there is a negative slope and if r = +1 the r-value represents a positive slope or positive relationship. Variables with r-values close to 0 represent no relationship. R squared represents the % change in the dependant variable that can be contributed to the independent variable. If r-squared is 0.88, then 88% of the change in the dependant variable is attributed to a change in the independent variable. Most of the time, multiple variables will affect the given variable as is the case of water temperature and dissolved oxygen. In brief, r squared is the relative predictive power of a model. The value of r squared (r 2 ) is a descriptive measure between 0 and 1. The closer it is to one, the better your model. By "better" we mean a greater ability to predict. A value of r squared equal to one (which only occurs in fairy tales and textbook exercises), would imply that the linear regression provides perfect predictions, and the more the two variables are related. As the r-squared value gets closer to zero, the less the two variables are related and the less reliable the regression equation will be for purpose of making predictions Science Concepts Introduced Making predictions from data previously collected and analyzed for their correlation.

31 Process Skills Emphasized Internet retrieval of a specific database Interpreting data Applying statistics Computer analysis Technology Used Internet MS Excel using the correlation function. MST Standards Standard 2 Key idea 1 Standard 3 Key Idea 6 Standard 4 The Living Environment Key Idea 5 Living Environment 5 Physical Setting/Earth Science 2 & 7 Learning Outcomes Students will be able to: Access the Project Watershed database at < Open a spreadsheet, copy and paste (download) the values to be investigated. Save the original database and make a backup copy. Sort the data by stream, by date, or by location. Find the correlation between water temperature and dissolved oxygen. Generate scatter plot graphs. Prepare a report describing their findings for the dissolved oxygen/water temperature correlation. Time Requirement 2-4 class periods or 2 blocks (dependant upon student skill level using the Internet, spreadsheets and graphing programs). Class period one: accessing and exploring the database at < Class period two: downloading selected data, placing it in a MS Excel spreadsheet, and manipulating the data using the MS Excel correlation, formula and chart functions. Class period three: preparation of a statistical report by student groups with class discussion on the understandings formed and/or anomalies observed. Instructional Strategies Cooperative learning groups Individual learning Statistical inquiry Background When downloading information from the website, it is necessary to select for MS Excel format. Students will need to enter the correlation formula and highlight two columns of variables to determine if a relationship exists. Students will also highlight two columns in order to use the Chart functions to produce a graph of the selected variables. The primary focus of this exercise

32 is to have students examine the variables, dissolved oxygen and water temperature. Once they have learned how to use MS Excel to examine these selected variables, they will be able to use the same procedures to examine any pair of selected variables. The reference section of this lesson contains a number of links to web pages that provide computer directed instruction in the use of spreadsheets, graphing, and finding correlations. Since instruction in spreadsheet use is primarily procedural, it is recommended that a strategy of demonstration followed by guided practice be employed. Because the process of data collection is inherently flawed, students will find that the observed results of their investigation may differ strikingly from their expected results. This provides an excellent opportunity to stress the importance of accuracy and precision whenever data is collected. In addition, it should be emphasized that there are many variables other than water temperature that can affect dissolved oxygen concentration. Because the expected relationship is based upon controlled laboratory measurements, interfering variables such as those found in field collected data are not present. This provides an excellent opportunity for students to consider what other factors could be altering dissolved oxygen concentrations from their expected levels. Assessment 1. Students demonstrate their competence for the learning outcomes as follows: Access the Project Watershed database and download selected data by copying and pasting selected data into a spreadsheet. Prepare a graph(s) from teacher designated sets of data using default formatting. Derive the correlation coefficient of data by using the statistical formula functions for correlation in a spreadsheet. Perform a self-directed search of the Project Watershed data and report on the findings. (Findings must include copies of the data selected, graphs and statistical findings applied to the data.) Put forth conclusions based on their findings and provide possible explanations and/or suggestions for further data collection or analysis to satisfy their search. 2. Student groups will be responsible for developing a report on their findings for presentation to the class. 3. Students take part in a class discussion of their data as well as their interpretations, and conclusions relative to the database and the statistical and graphic tools they used. Rubric for statistical correlation and graphic applications: 100 points with suggested point distribution as follows: 10 points for successfully accessing the online database 10 points for successfully copying and pasting data in a spread sheet 15 points for entering and using the correlation formula in the spread sheet 15 points for producing a scatter plot graph of the variables using the chart menu 20 points for interpreting the statistical correlation in a written report 20 points for interpreting the graph produced in a written report 10 points for the presentation of findings to the class.

33 Extensions/Options Use graphic and statistical techniques to perform additional self-directed searches of the Project Watershed database to examine other sets of paired variables for possible correlation. Student groups use the paired variables for analysis of different streams or seasons. Find variables with the highest correlation. Ultimately, students will gain confidence in using MS Excel spreadsheets as a way to prospect for potential relationships between other paired variables. After investigating the database in this lesson, students should be encouraged to participate in a stream sampling experience. Key Terms Dissolved oxygen, correlation, variable, database, coefficient, r-value, linear regression, best-fit-line and scatter plot. Pre-Requisite Knowledge Skill in computer use is desirable but could be taught by assigning more time for this lesson. Knowledge of the relationship between gas solubility and solvent temperature, presented formally in previous classes, or informally by using a simulation or an analogy. Equipment Needed A computer connected to the Internet. References/Websites Interpretation of graphs and statistical findings: 1. Scatter plot, line graph and/or correlation information: Scatter plot and line graph with excel instructions: 3. Line graphing 4. Correlation Using Excel spreadsheets to find statistical correlation between two sets of data. a. Choose a cell where you want to display the results. b. Enter an equal sign, then correl, and a left parenthesis. ex. =correl( c. Describe the range of values for the first variable: ex. =correl (b2:b85 (This describes the series of values for the first variable in column b from cell number 2 to cell number 85.) d. Next type a comma (,) and then the range for the second value P. ex. = correl (b2:b 85,d2:d85)

34 In this example, you are looking for the correlation between the values for first variable listed in column b, rows 2 through 85 and the values for the second variable listed in column d, rows 2 through 85. When you complete entering the formula, hit return and the numerical value for the correlation should appear. Correlation describes how much one variable is affected by another variable. If the dependent variable increases in proportion to the increase of an independent variable, the relationship is described as a positive correlation. If the dependent variable increases in proportion to the decrease of an independent variable, the relationship is described as a negative relationship. The formula for correlation produces a number from -1 to +1. The number 1 indicates a perfect correlation and sign indicates whether the relationship is positive or negative. To see graphic representations of this, visit the following website <

35 Handouts Project Watershed Correlation Of Two Variables Dissolved Oxygen vs. Water Temperature A. Importing Data: 1.Go to< 2. Click on the database icon 3. Click on Browse Data By Stream. 4. Select the parameters you wish to view in this lesson; they will be dissolved oxygen and water temperature. 5. Click on the stream you would like to study. 6. Finally Click on Submit 7. Copy and paste this information into an Excel Spreadsheet. (You may have to reformat your row and column dimensions to make it look good. Do this by highlighting all columns used, and go to the format menu.) 8. Save and print out this sheet. Highlight all data and make sure you set print area. B. Graphing Your Data: 1.) Highlight all your numerical data. (Make Dissolved Oxygen the X-Variable and water temperature the Y Variable.) 2.) Click on the Chart Wizard in the menu bar. 3.) Choose the XY Scatter Plot as your graph. 4.) Go through the process making sure you have a key, label both axis and also include a title. 5.) Format your graph any other way you wish and create it as a New Sheet 6.) Save and print out this graph. (All you need to do is click on the graph and hit print.) C. Getting the Best-Fit-Line: 1.) While looking at the chart, go to the Chart Wizard drop down menu and choose Add trend line. 2.) Choose Linear (Should be the default). 3.) Click the options tab in this window and select To display the equation and the r 2 value on the chart. 4.) Save the graph and print a copy. Complete the following questions, staple all copies to this sheet and hand in. Make sure your name is on all copies! Directions: Answer the following for your graphs concerning the relationship between dissolved oxygen and water temperature. 1) Best-fit-line equation: 2) What is your r 2 value? 3) What is your r-value (Correlation Coefficient)?

36 4) Explain in words what the correlation coefficient (r) says about the relationship between these two variables. What is/are good r-value(s)? 5) Knowing that the equation of all lines in the form Y = mx+b has a slope of m and a Y-Intercept of b, what is the slope and the Y-Intercept of your best-fit line? 6) Interpret these values. What does the slope say about the rate each changes? What can you say about the Y-Intercept? 7) Knowing an equation that represents a pattern of data allows us to make predictions about one variable when we know the value of the other. Assuming the temperature in your stream is 20 degrees Celsius, what would you predict the dissolved oxygen level to be?

37 Data for Hand held Graphing Calculators If No Internet is Available Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Limestone Creek, Kirkville Rd. Bridge Crossing Date Dissolved O2 (mg/l) Water Temp (C) 5/22/ /23/ /29/ /20/ /9/ /8/ /8/ /24/ /19/ /5/ /24/ /17/ /21/ Limestone Creek, Mill Run Park 6/5/ Limestone Creek, Mill Run Park 10/28/ Limestone Creek, Mill Run Park 5/3/ Limestone Creek, Minoa Shepps Corners Rd--Smith's Market Limestone Creek, Pleasant Street service road by former Manlius STP Limestone Creek, Pleasant Street service road by former Manlius STP Limestone Creek, Pleasant Street service road by former Manlius STP Limestone Creek, Pleasant Street service road by former Manlius STP Limestone Creek, Pleasant Street service road by former Manlius STP Limestone Creek, Rte. 5 Bridge Crossing, Fayetteville/Town Hall Limestone Creek, Rte. 5 Bridge Crossing, Fayetteville/Town Hall 10/23/ /9/ /20/ /10/ /7/ /8/ /15/ /23/