TEKS Support |
This unit contains activities that support the following knowledge and skills elements of the TEKS.
(1) (A) |
X |
(4) (A) |
X |
(1) (B) |
X |
(4) (B) |
|
(1) (C) |
X |
||
(2) (A) |
X |
(8) (A) |
|
(2) (B) |
(8) (B) |
||
(2) (C) |
(8) (C) |
||
(2) (D) |
|||
(3) (A) |
X |
(9) (A) |
|
(3) (B) |
X |
(9) (B) |
|
(3) (C) |
X |
The mathematical prerequisites for this unit are
The mathematical topics included or taught in this unit are
The equipment list for this unit is
To the Teacher |
Teaching mathematical modeling, generally, will change your processes within the classroom. You tend to become a storyteller and guide, rather than a lecturer. It is great fun to set the stage and observe how the students decide to play their parts.
In many ways, teaching modeling is similar to the guide of a white-water rapids expedition. You know where the white water is, you know that you want your group to be excited about trying out some of the rapids, yet you steer the canoes away from the dangerous areas. You will be needed to assist the students in deciding which course to take and which to ignore. Through discussion and questioning, you can lead the students to an exciting and rewarding journey along the river of mathematical knowledge. At the same time, you will want to allow them the freedom to make decisions as to the forks to take.
Two of the lessons are listed as optional. In particular, Activity 3, an interim report, may be omitted if time is short for the unit. This lesson is designed to have students consolidate what they have learned in relation to the modeling process as well as the steps taken to analyze the migration model. If this lesson is omitted, you should summarize these ideas in a lecture format, since the ideas will be used in the analysis of the net-growth model and as tools in the final report.
If all lessons are used, the unit should take approximately two to three weeks.
Note: It may help to read the student Unit Summary and Key Concepts to familiarize yourself with the flow of this unit.
Overview |
This unit is designed to reinforce the mathematical modeling process, as well as to give students a different point of reference for exponential functions. It is up to you to decide what areas of mathematics you want to emphasize. Throughout these pages, multiple avenues are suggested so that you have enough flexibility to design the unit in the best interest of the students in your class.
There are parts of the unit that should be done by every student or group of students. Other parts may be de-emphasized, depending on the avenue you decide to take. To summarize the necessary elements for students in a concise way, the following list is provided:
It is assumed that the students have worked with exponential functions and exponents in previous courses. However, most introductory algebra courses do not formally work with the recursive relationship of the exponential, e.g., the idea of successive multiplication by a value and that it is possible to find the growth rate by finding the slope of the recursive graph.
The simulation is important for two reasons. First, it gives students a hands-on experience of how a population can grow over time. Second, students realize that many predictions are done using simulation and that variability can be large when there are few trials. When they see predictions stated in papers or on television, they should be inquisitive about how they were done.
This assignment ties the process of modeling to wildlife and environmental issues and any other issues that are relevant in the students lives and communities. It is clear that not all students, perhaps even very few, have an interest in the moose population in a New York state park. Yet, it is also clear that the modeling process is used in many other areas to help argue for or against a particular path of action.
The first time through this unit, you will probably want to use the existing materials to get a clear sense of the process. It will also allow you to have students use the Unit Project to gather more information involving areas you might want to use in the future. However, after you have worked through the unit, you may want to select an example that would be of more interest to your students. With some modification, you could apply the same process to a variety of populations and growth patterns. Remember that the moose example is just one vehicle to emphasize the modeling process and characteristics of relative short-term population growth as an exponential function.
Following is a listing of elements of the unit with suggested ways to use the materials. Please keep in mind that these are just suggestions and that you should feel free to experiment.
Additional Resources on the Modeling Process |
Discuss your expectations for the unit. Set up the reasons to study modeling. Discuss the unit, the modeling process, and the idea that various groups may be affected differently by a decision. A helpful resource that discusses the modeling process is A First Course in Mathematical Modeling by Frank R. Giordano and Maurice D. Weir published by Brooks/Cole, Monterey, CA, 1985. See Chapter 2, pages 2940. Another source is the textbook series Mathematics: Modeling Our World developed by COMAP and distributed by SouthWestern Publishing, Inc. In particular, Course 3, Unit 7, Modeling Your World, is a detailed trip though mathematical modeling.
Teacher Notes |
Unit ProjectTracking Wildlife and Other Issues |
![]() |
|
Materials needed |
Newspapers, television, Internet Notebooks |
Students may decide to select an environmental or wildlife situation related to the unit or any other situation of particular interest related to community or world issues. Guide them to look for coverage of decisions with conflicting points of view or decisions that have been made based on some type of predictions.
When introducing the assignment, make sure the students understand what you want for log entries. You may want to have them report about their particular entries daily, weekly, or at the end of the unit. You may also want to have the entries turned in each week so that you can read them. Whatever you decide, be sure the students are aware of your expectations. If you decide that a unit-ending project is desirable, be sure to let the students know what you want the project to encompass, how you will assess it, and a time line. As an alternative to a long-term assignment, this can also be given as a weeklong or two-day assignment.
This project is designed to encourage students to look outside the classroom and into the world. Opportunities for such vision are abundant. Any time a projection is necessary or there are differing points of view or information is needed, analysis through modeling is appropriate. In todays world, there is rarely a time when all groups agree on what needs to be done, and, when they do, they rarely agree on the way to get it done.
These are the types of situations to look for in the student papers (or reports). Do they understand that the power of mathematics is in helping all of us deal with such issues?
You might want to have an oral report or a written report from each student, or you may want to use group reports in addition to or instead of individual reports. This decision will depend somewhat on the manner in which you have students report throughout the unit. Several options are described below.
If students maintain their own files of articles and logs, they can report to the class on the articles and events that they find throughout the unit. The teacher, or student, might then lead a discussion relating the work to ideas developed in solving the moose problem.
If you have students turn in the articles regularly during the unit, you can compile and distribute a list of some of the most pertinent topics. Then have the students discuss in their groups how these topics are related to the moose problem and/or the modeling process. Each group will then report to the class on its findings.
You or your students can create a bulletin board of selected items. Students could then pick out an item of interest and write a brief paper about how the chosen topic relates to the moose problem and/or modeling.
For a more directed approach, lead a discussion of topics the students have found that relate either to the moose problem or to the modeling process. Draw attention to the overall problem of making decisions. Ask the students to write summaries of what they have done in the unit and how this might relate to other topics, which affect their lives. The students could read the Unit Summary to assist them in recalling the processes they went through.
Activity 1Whats the Moose Problem? |
![]() |
|
This activity sets the context for the unit. The students have an opportunity to discuss and refine the central question of the unit. If you have decided to use a context other than the moose situation, this is where it should be introduced and examined.
In their groups, ask students to read the situation described and consider the questions they might ask and information needed. Lead a class discussion of their results. Guide the students into focusing on the question of whether it is desirable to add moose to the park. The decision should therefore focus on what the results will be if they do or do not add 100. When this discussion has taken place, look at the Refining the Questions section of the activity. You may want to use the overhead of it (Transparency 2) or discuss it, asking the students to write down the questions.
Allow students time to develop their answer. A class discussion should help the students come to agreement that questions similar to the second and third questions on the transparency are a reasonable first step:
How many moose will be in the park if no additional moose are moved there?
and,
How many moose will be in the park if 100 additional moose are moved there?
After discussing the need for further refinement, lead the students to the final two questions on the transparency:
How many moose will be in the park, at the end of 20 years, if no additional moose are moved there?
and,
How many moose will be in the park, at the end of 20 years, if 100 additional moose are moved there?
Spend as much time as is necessary to develop its ideas. Asking good questions is the key to successful modeling.
Homework 1More Moose Questions |
![]() |
|
This piece is designed to give students a deeper appreciation of the various factors involved in the decision. Question 4 of the assignment asks students to think about others who have an interest in the outcome of the moose decision, since various interest groups may use the information in entirely different ways.
Materials needed |
Activity 1 Transparency 2 |
Homework 1Which Facts Matter? |
![]() |
|
Have students read the Moose Fact Sheet. Note that Question 2 of this assignment asks them to revisit the final, refined questions in Activity 1 with these new facts in mind.
Activity 2Your Moose Model Begins |
![]() |
|
This activity is designed to meet two goals. The first is to give the students practice in the techniques of mathematical modeling. When they get to the second part of the unit, they will have tools they can use to explore a different model for population growth. They will examine the techniques of using tables, graphs, and equations to help find patterns for prediction. The second goal is to find relationships between a recursive and a closed-form description of events.
Students set up a first model, using incoming migration as the only factor that affects the moose population. A new modeling diagram is introduced, and the students review the representation of information through recursive and closed-form expressions for linear growth. Students will arrive at an answer to the key question by using graphical, analytical, and numerical representations of the model.
The first part of this activity emphasizes the questions students will be answering throughout this unit and reviews the modeling process. The discussion develops the assumptions that the students will formulate for the first model.
Diagram 1 in this section represents the changing population as a flow is introduced to help the students describe their model. This type of diagram will continue to be used.
The materials lead the students through the modeling process using the assumption for the first modelmigration only. In the section How Many Moose in 2013? the students are led through the development of a linear model for growth, using the process described. The resulting rate of migration will set the stage for results in subsequent questions. The groups are then asked to project the results to the year 2013.
The work in this section illustrates another way to arrive at the resulting change and population in the year 2013. The concept of recursive thinking is described and the connection between closed and recursive forms of a linear equation is examined.
Homework 3Moose Populations: Analytic Representations |
![]() |
|
This work asks the students to link the tabular and graphical representations for the results on Case A and Case B (not adding or adding 100 moose). Case B is a good example of a piecewise-defined linear function. Additional work on this type of definition could be used, depending on your students.
Materials needed |
Activity 2 Homework 3 Transparencies 3 through 7 Graph paper |
This work is designed to reinforce the ideas of rate of change, graphical representations, and piecewise-defined functions. The recursive graphs (Questions 1 and 3) focus on the process of adding moose from year to year, thus lie along the same line since the process does not change. Transparencies 6 and 7 are included for discussion of these questions during the next class period. They assume a migration rate of 2 moose per year. If your class has chosen a different rate, be sure to discuss how that difference would affect each of the graphs.
The assumptions listed on Model OneMigration can be developed through a class discussion of Activity 1s exploration. If you choose this discussion option, use Model OneMigration as a summary reference.
You may need to explain the modeling diagrams. Discussion might take the following format.
Emphasize that an early step in the modeling process is to simplify the problem. This allows an understanding of the phenomena and an easier development of the initial model. In this particular problem, since the interest is in the moose population over a twenty-year period, assume that the population in the park continues to increase in the same way that it has over the past few years. Namely, migration into the park is the only factor affecting population growth.
In an ideal situation, the students arrive at the following facts and assumptions through group and class discussion. If discussion is not working, these factors should be given to the students, using the student pages for this lesson. Following are the facts known initially.
The following assumptions are made to simplify the model.
Activity 2 may work best using small groups, with help from you as needed. As students work, remind them of the processes they are using and the questions they are trying to answer. They will need to use these same techniques again when they revise their models in later lessons. When everyone is finished, discuss the results. You may want to have each group make a short presentation of its work. Transparencies 4 and 5 are provided to assist in the discussions.
Discuss the idea that the steepest line touching both blocks of data connects the lowest estimation in 1988 to the highest estimation in 1993. Similarly, discuss the fact that the flattest line goes from the lowest estimate for 1993 to a high point in 1988. (Avoid emphasis on the equations of these lines for now.) Use Conclusion #2 to explore the idea of the "x-intercept" and the implication of the fact that "some" moose were seen in the park in 1980.
Review the modeling diagram on Transparency 3 as a representation of inflow. Allow the class to decide on a value to use for the rate of moose migration per year. Have them use their value to answer the remaining questions. Then have the class agree on the year to use as "the initial year"the last year having zero moose.
Allow the students to complete the tables and questions. Be sure they reflect the "rate" and "initial year" assumptions made in the first part of this activity. As a class, have the students discuss their results. Although the closed form is traditionally used, the recursive definition is a more natural first description in the context of this problem. It is important that the students review both of these forms, since they will be using them to develop the concept of an exponential model later in this unit.
Note the additional assumptions required in adding the 100 moose:
Activity 3Interim Report to the Commissioner |
![]() |
![]() |
|
This activity gives students an opportunity to summarize their work by preparing brief oral reports in which they discuss the concepts and assumptions of their models. Homework 4 introduces the possibility that population growth is occurring by means other than migration.
Materials needed |
Activity 3 Homework 4 Graph paper Blank transparencies and transparency pens Grid Transparency 9 |
Small groups are suggested for this assignment. Students may need help organizing and developing their thoughts. After distributing this assignment, give them a day to work on these reports in their groups. As they are discussing what they should include, go around to the groups and guide them in formulating their work. They should include the factors they considered and assumptions they made to arrive at their model. Have available materials that students could use to display their information. These materials might include chalk, blank transparencies and pens for an overhead projector, graph paper, and blank graph grid transparencies (Transparency 9). Encourage students to discuss not only their model, but also limitations of their model. This is a two-day assignment. It may take a full day, as well as time outside class, for students to prepare their reports. Encourage discussion and thoughtfulness. The reports are not necessarily as important as the process of preparation. Reports should be brief, but as thorough as time allows, so organization is important.
When the presentations have been made, hand out Homework 4 for students to consider. Discuss the modeling process with the students. Due to the new information, they will now have to revise their models, make new assumptions, and consider other factors. This will set up the next iteration of the modeling process.
Activity 4A Life-and-Death Situation |
![]() |
|
In this activity, students realize that the migration model is insufficient. The students will revisit the problem, revise the assumptions that were made, and continue the modeling process. They will be introduced to the idea that the herds current population is dependent upon its previous population. They will deal with a number of growth-type models, and will use a simulation game to gather data on the moose population in Adirondack State Park.
Using independent/small-group and large-group discussions, the students begin analyzing the new information and realize the necessity for a new model. Complexity slowly increases to include factors such as deaths, emigration, and births into a net growth model.
Activity 5Net-Growth Moose Model |
![]() |
|
Working in small groups, students will use a simulation game to generate data. They will plot these data to help them begin to understand the nature of the growth in the moose population.
This activity is designed to give the students an idea of what is involved in simulation. It should also allow them to realize that population is quite variable when populations are small, and, more importantly, when there are few females in the herd. The activity will probably take about a day and a half to graph, discuss, and complete. Students may have to do some of the simulation at home.
Students should have fun doing this, when they understand the process. Student pairs are probably best for this activityone to generate the random numbers and read the survival chart, and one to record. A detailed description of how to run this simulation is given below, and Transparency 15 may be used to guide the class. Reserve some time in class to help students find the rand key on their calculators. It is crucial that each student pair use its own calculator.
Distribute all of Activity 5 , and use Transparency 16 to go through the process for one years worth of data with the entire class, to ensure there is a consistent method of recording the data on the sheets. Afterwards display Transparency 17 and have the students begin their own simulations. After completing a year or two of simulations, students in each pair could work individually. By splitting up the work, they have a reasonable chance of completing six to eight years worth of simulation.
It might help the process for each pair to post its herds population on the board or butcher paper, or on Transparency 17. This would maintain group productivity and let the students see all the possible variations in this simulation.
The "Survival" table showing the assumed birth and survival rates is, in fact, based on our best guesses. You may want to stress that the data in this table were generated by "informed guesswork." In such cases, the modeler is responsible for defending the assumptions as reasonable. It should be stressed that the probabilities listed are for survival to the next year, not the probability that a given moose will survive to that age. For example, you assume that a 10-year-old moose will have a 93% chance to reach age 11, whereas the probability of an infant living until age 11 would be closer to 35% (the product of its annual survival probabilities).
Be sure your calculator is in floating-point mode for the following calculations.
Have the students plot their individual data on the butcher paper so that all students can see their results. Ask them to record their data in the table as well. With just 8 years of data, it may not be clear of the variability. Ask the students how they might go about using this combined data for predicting the number of moose in the park in the year 2013. One way could certainly be averaging the data at each year. Another might be taking the largest or smallest values at each year, depending on whether it is desirable to over-estimate or under-estimate the total population. This discussion will lead into Homework 4.
Homework 5Simulation of the Moose Model |
![]() |
|
Students will use a computer or calculator program to generate a more complete picture of the growth model.
Materials needed |
Activity 4 Homework 5 Calculator/Computer Simulation program for the selected technology A large sheet of "butcher paper," with axes set up for years 19802015 (horizontal) and population from 0 to 200 (vertical) A large sheet of "butcher paper," with a table set up for years 19802015 and a column for population. Transparencies 1, 2, 10, 11, 12, 13, 14, 15, 16, and 17 |
Distribute the first page of Activity 4. It is designed to start students thinking about how populations change. A number of factors were considered and assumptions were made in Model One that affect the model for the number of moose in the park, including (among other things) flooding, wildfires, new roadways, disease, a change in predators, illegal hunting, and environmental changes in Vermont, New York, and Canada. Certainly, no single model will include all of them. As the students consider these factors, remind them that they are really making their second pass through the modeling process. This is a good time to review the modeling process (see Transparency 1), and the central problem (Transparency 2). The students are reviewing the properties of objects and deciding which properties to model. Students will probably consider the types of change (birth, death, and so on) in a variety of orders. Do not insist on following the order presented in the reading. However, students should realize, with the additional assumption of moose deaths, that the population will reach equilibrium (level off) if no births occur.
After this discussion, hand out the remainder of the activity and asked students to read through it. The section called Summarizing the Net-Growth Model could be used as a shortened reading if you use a large-group discussion of the previous pages of the reading.
Transparencies 10, 11, and 12 illustrate some of the types of change students may have examined in answering the last question. 13 and 14 represent the convention for indicating dependence of one quantity on another using the feedback arrows. However, do not force assumptions. For example, students may want to allow migration to be included in their models. The effect of this decision may then be explored during the student simulation exercise, Using Simulation in Your Model, by having different models implemented by different groups.
The point of the opening discussion is to see the variation in probabilistic outcomes for a small number of trials with small initial herd sizes, in order to motivate the following computer activity. Your students may quickly realize that the number of females is really the driving factor in the growth of their herds population. If a herd is unfortunate enough to lose some of the females at first, or if all the newborns happen to be males, the herd could even decline in population at the start. You want the students to understand that simulations are often used not only to predict outcomes, but also to yield some understanding of the range of possible or likely outcomes.
Hand out the first page of Homework 5 and put Transparency 18 on the overhead. Each shows the plot of ten simulations, with each simulation covering 20 years. Each path represents a separate herd. The graph shows two properties that you should discuss with your students.
First, there is a very wide range of growth rates in this graph; in fact, one herd even decreased in population! Your class results will probably vary as well. Ask the group to explain what happened to its herd to cause either a high or a low birth rate.
Second, there is not a smooth growth in the individual herds from year to year. Many of the paths seem to "bounce around." The point is that, if the herd is small enough, it is quite possible for all the offspring to be male (or female) in any given year. That would certainly affect the growth of the herd. If there were a hundred moose in the herdwith maybe 30 offspringit is much more likely that there would be a more balanced distribution of males and females. The following computer activity assumes that there are 100 additional moose.
Random behavior is a complex topic. Expose your students to these ideas. However, this may be their first exposure to these ideas, so do not insist on mastery or deep understanding at this time.
Computer ActivityUsing the Computer Program |
Now distribute the other two pages of Homework 5, the breakdown of the moose population and the Tally Sheet. The second part of this homeworkthe computer simulationshould be fun for the students. With more computers, collection of these data will go faster. If you are running short on time, you can use the data provided in Transparencies 19 and 20, and move directly to the "averaging" task described below. If you select this option, distribute copies of the data from 20. If there is no time for averaging in class, it may be assigned as part of homework. The results are provided on Transparencies 21 and 22.
Run the program "moose127.exe" (or moose simulation if using Windows). The population provided is 127 moose, beginning in the year 1993. If you have Windows, and want to have a little more flexibility, you can install the simulation program by running the "setup" program from Windows. The setup program will install the appropriate software on you hard disk and create an icon that you can click to run the program.
The listings of moose127.txt and moose27.txt are included in the disk, and may be modified to suit the students curiosity. In order to modify these, you will need to load the moose.txt file, change the data lines, and/or beginning year, and compile moose.txt to moose.exe. This is possible only if you have QBasic™ (or some compatible software) on your system.
Collect the students simulation data on Transparency 17. Then have students help you average the results, year by year, and record the yearly averages in their own notes. Program listings and detailed directions are included in the Appendix to this lesson. If the disk is bad, or you want to alter the program, it is a QuickBasic™ program. You can enter the program and modify it to suit your interests.
The program is a "run-time" version and is provided in this form for both MACTM and DOSTM environments. There is also a version for the TI82TM, but it runs much more slowly.
The data collected will be used for the students Final Report to the Commissioner in Activity 6.
Activity 6Final Report to the Commissioner |
![]() |
|
It is suggested that the less teacher direction on this activity, the better.
Group workpreferably small groupsis suggested for this activity. The teacher should be available to guide, suggest, and prod the students in the direction of solid mathematical justification.
Various suggestions and a possible sequence of analysis are described below. Students should arrive at a specific destination, but they do not necessarily have to travel the same road to get there.
Resist the temptation to be too directive. However, students should all explore varied simulation dataeither those generated by the class or those that are providedto understand the value of pooling the data by averaging and to plot the growth of "average" herds. Sufficient guidance should be provided so that they investigate representations of the growth, with the goal of writing its mathematical description (equation) in some form. Some students will be able to discover both the recursive and closed-form equations; others will find only the recursive form, and others will not find either on their own. Each student should be prepared to understand the results of all reports, though, and learn from them.
As you know, conservationists proposed augmenting the Adirondack State Park moose herd by an additional 100 moose. The results of 10 simulations are plotted on Transparency 19.
It would be best for the students to have the opportunity to generate such a plot with their own data from Activity 4. You may want to have your students use the sample data from the simulation listed in Transparency 20 in the interests of saving time and ensuring common results. All "answers" in this activity are based on these sample data; results from student simulations should be similar, but not exactly the same. In any case, students should notice that there is much less variability in the possible outcomes, and there is a distinct pattern to the data, as compared to their work with smaller herds. The goal of this activity is to discover and describe this pattern.
Have students plot their data to form a graph like that in Transparency 19. To discuss the simulation results as a single function, students need to combine the results of the simulations into one list. One way to do this is to calculate the average population for each year. Have them do this for their data and make a new graph of average herd size versus year. Results for the data from Transparency 20 are included in Transparencies 21 and 22.
With 100 extra moose added, it becomes very clear from the graph that the growth in population with respect to time is not a linear relationship. On the other hand, it is also very clear that there is some well-defined relationship here, since the growth seems to proceed in a very predictable fashion.
Another relationship to investigate is current population versus previous population. The ordered pairs to be plotted are (P1, P2), (P2, P3), (P3, P4)...(P19, P20).
Plotting these points gives some indication of how populations change from one year to the next. A blank grid is provided as Transparency 23 and in the student pages. The graph in Transparency 24 shows the relationship of current populations with those of the previous year. The relationship shown by the graph is obviously linear. In fact, if one calculates the regression line, one finds that Pcurrent = 1.127 Pprevious 1.7.
We strongly suggest that you do not ask your students to find the regression line, because the constant term "1.7" will unnecessarily confuse the discussion. Instead, ask the students to hold a ruler up to the graph and observe that the y-intercept is very close to zero. This gives the students the right to assert that the form of the current population is the previous population times some number, or Pcurrent = K * Pprevious. In other words, a linear relationship exists between current and previous population. The slope of this relationship is the ratio of successive populations. This may therefore be computed either by calculating the slope of a line sketched through the graph (using (0, 0) and a point near the right end of the data) or by calculating the ratios between the successive populations. If time permits, do both. A blank table and a blank graph are provided for this work.
Have the students compute this ratio for all adjacent data points. They should find that the ratio is indeed fairly constant for your data (usually between 1.12 and 1.13). A histogram of these ratios will make the point quite clearly.
Note that the column for the difference between successive populations will likely lead to no useful relationships. It is included here to verify that the growth is not linear.
Unit Assessment |
The following list of learning outcomes was created for the Wildlife unit. The outcomes are arranged in two different levels: the lower-level skills, describing the more straightforward, technical skills; and the higher-level skills, related to interpretation, critical attitude, and argumentation. (Some of the skills mentioned are not learned explicitly in this unit, but are based on former units.)
The student should be able to:
The student should be able to:
Unit Summary |
How you use this unit wrap-up will depend on what you decided to do with the Unit Project. You may decide at this point to display and discuss the information the students came up with in their research. The following suggestions are written with that plan in mind.
Any time there is a projection or there are differing points of view or information is needed, analysis through modeling is appropriate. In todays world, there is rarely a time when all groups agree on what should be done, and, when they do, rarely on the way to get it done. These are the types of situations to look for in the students Unit Project papers (or reports). Do they understand that the power of mathematics is in helping all of us deal with such issues?
Final reporting and summary discussion may take place in any of several ways. You might want to have an oral report or a written report from each student, or you may want to use group reports. This decision will depend somewhat on the manner in which you have had students reporting throughout the unit. Several options are described below.
If students have maintained their own files of articles and logs, they can report to the class on the articles and events they have found throughout the unit. The teacher, or student, would then lead a discussion relating the work to ideas developed in solving the moose problem.
If you have had students turn in the articles regularly during the unit, you could hand out a list of some of the most pertinent topics. Then have the students discuss in their groups how these topics are related to the moose problem and/or the modeling process. Each group would then report to the class on its findings.
You or your students could create a bulletin board of selected items. Students could then pick out an item of interest and write a brief paper about how the chosen topic relates to the moose problem and/or modeling.
For a more directed approach, lead a discussion of topics the students have found that relate either to the moose problem or to the modeling process. Draw attention to the overall problem of making decisions. Ask the students to write a summary of what they have done in the unit and how this might relate to other topics that affect their lives.
The students could use the Unit Summary to assist them in recalling the processes they went through. The Unit Assessment materials deal with modeling and modeling diagrams, exponential functions, randomness, and other topics from the mathematics of this unit. You may want to extend the topics to address the societal issues that are important for students to recognize and how mathematics can help answer some of the unanswered questions when it comes to decisions.
Annotated Student Materials |
|
During this unit, you will be doing some of the work of a wildlife manager. Wildlife managers try to understand the natural world so they can help environmental systems to survive. To do that, they have to observe and record population data for a variety of species. As they track changes in wildlife populations over time, they use the data they collect to try to make predictions about future populations. In some cases, they must decide if control of populations by humans is wise and necessary.
Your task will be to use mathematical modeling to solve problems related to predicting the population of moose in a park in New York. You will be using what you learn to advise the commissioner of the New York Environmental Conservation Department. On to the moose!
|
![]() |
|
Adirondack State Park (ASP) is a six-million-acre wilderness area in upstate New York. Prior to 1980, the last moose recorded in the park was shot in 1861. After 1980, however, some moose were spotted there. In 1988, it was estimated that 1520 moose were in the park. In 1993, it was estimated that there were 2530 moose.
The New York State Environmental Conservation Department (ECD) conducted a public opinion survey. A majority of the people surveyed favored a "gradual increase in the moose population as the animals migrate from nearby New England states and Canada and expand their numbers through natural reproduction." Conservationists suggested moving 100 moose into the park over a three-year period. The ECD determined that this would cost $1.3 million, and the commissioner of the EDC had the task of making a recommendation to the governor about this situation.
Imagine that you are going to advise the EDC commissioner. Before you can do that, you need some specific questions answered. Pose one such question about the data above.
Answers will vary. Someone must decide whether to add moose. Also, the students may be more specific as to the exact number of moose projected. Some may even want to find out why it even makes sense to survey the people.
What additional information will the commissioner need?
Answers will varyhow many moose will there be if the commissioner addsor does not addmoose? Who is affected by the moose population? Is it good or bad to have more moose?
Here is one problem you may have posed in this activity:
Should the ECD recommend moving 100 moose into the park, or should it recommend that nature take its course? |
You will use the mathematical modeling process to simulate what would happen in each case. This will help the commissioner arrive at a decision.
The first step in the modeling process is to state a problem to be solved. The problem we have defined can be restated more specifically:
How many moose will be in the park if no additional moose are moved there? How many moose will be in the park if 100 additional moose are moved there? |
These two questions might even be too broad. You may also need to specify a reasonable time period.
The conservationists who suggested moving 100 additional moose into the park used a 20-year time frame for their projections. Since the life span of a moose is 1523 years, it is reasonable to see what happens to the population during one generation. Therefore, we shall further refine the problem by asking the following questions:
How many moose will be in the park at the end of 20 years if no moose are moved there? How many moose will be in the park at the end of 20 years if 100 moose are moved there? |
Note that the conservationists suggested moving 100 moose to the park over a three-year period. A simplifying assumption can be made that this move occurs all at once, at the beginning of the 20-year period. You may want to return to this assumption and modify it in the future.
|
![]() |
|
The moose scenario is based on a short article in The New York Times from April 7, 1993. Below are some of the questions the article did not answer. As you answer them, think about whether mathematical modeling can help you to answer these types of questions.
Answers will varythey may have surveyed conservation groups, groups interested in tourism, lumber industry groups, farmers, and homeowners in the areas that may be affected.
Answers will vary"Do you favor adding moose for $1.3 million?" "Do you see additional moose to be important to your industry?"
Answers will varymore moose improve the possibility that the population will continue to grow; larger population of wildlife; its nice to be able to go into the woods and see moose.
Answers will varyhunters, loggers, farmers in the area, and wildlife biologists, among others.
No. Although the answers to the questions above are important, the questions generally cannot be answered by a simple mathematical model.
|
![]() |
|
The second part of the modeling process is to make assumptions that assist you in solving the problem. Having additional facts about the situation may help. Here are some facts about moose:
Since so many factors are involved in this problem, it may be necessary to make additional simplifying assumptions later in the modeling process.
|
![]() |
|
You are now ready to develop a model to assist you in solving the problem. Recall that the two questions we chose to focus on are
How many moose will be in the park at the end of 20 years if no moose are moved there? How many moose will be in the park at the end of 20 years if 100 moose are moved there? |
For simplicity, we shall refer to the two parts of the problem as Case A (move no moose) and Case B (move 100 moose).
Mathematical modeling can yield different solutions to the same problem, depending on the assumptions you make and the factors you consider. It is helpful to start with a simple model; that is, make assumptions that allow you to arrive at a solution and understand the problem. This may not be the best solution; however, it affords you some understanding of the problem that you can use in a more refined model. This process of making assumptions and refining the model continues until you arrive at a solution with which you are satisfied.
Review the facts from Activity 2. List assumptions that you think would be helpful (and reasonable) in answering the questions in Cases A and B above.
In 1988, there were 1520 moose in the park. By 1993, there were 2530 moose. If there are only 2530 moose, with 6 million acres of land in the park, the chance that a moose can get a date on a Saturday night may be slim. The moose may never get together to mate! Therefore, assume that no moose births will occur for Case A. For simplification purposes, in your initial model you can also assume that there are no deaths in the 20-year period.

Figure 1
The modeling diagram may help you picture your initial model. The rectangle represents the moose currently in the park. Refer to this as the "stock" of moose. You might think of this stock as similar to a tank or barrel that can fill up and/or drain out. The arrow represents the migration into the park. Refer to this as the "flow" of moose. You might think of this as similar to flow through a pipeline. The ring is like a "valve" that allows you to adjust the flow of moose into the park. In Case A, you would twist the ring so that the flow would remain open, and migration would occur at a constant rate.
Your goal is to find out how many moose are in the stock 20 years after the New York Times articlethat is, in the year 2013. To do this, you need to know the number of moose migrating each year. You know that moose were spotted in the park after 1980. Figure 2 illustrates the estimated information. The bar-like parts represent the range of estimated values: 1988, 1520; and 1993, 2530.
Keep in mind that you assume that the population grows only by means of migration and that the number of moose coming into the park is the same each year. This type of growth (constant number each year) may be represented by a line. In this case, the slope of the line represents the rate of growth of population with respect to time. The steeper the line, the faster the growth.
= 1,6

Figure 2
One moose per year from 1988 (20) to 1993 (25).
Three moose per year from 1988 (15) to 1993 (30).
Answers should vary from 1 to 3.
Moose are migrating in at a constant rate of _____ moose per year.
With this migration rate as your slope, use your straightedge to draw a line that extends through the two sets of data. Now use this line to estimate the moose population in the year 2013. Explain your method clearly.
If no moose are added, the number of moose in the park in 2013 will be: ______
Answers should vary from around 45 (using one moose per year) to 90 moose (using three moose per year).
Extend the line to estimate (to the nearest year), the last year that the population in the park was 0. The initial year: _____.
Answers should vary from around 1968 to 1983. For purposes of future discussion, try to eliminate those prior to 1980, since moose were actually first seen in the park in the early 1980s. This reinforces the idea that the model may need to be adjusted to fit the particular context.
Another way to describe this migration is by using a table. Table 1 is designed to pair the current years population with the previous years population. Verify the results of your graph by filling in the table of values to represent the number of moose in the park each year. Use your conclusions from Activity 3 to assist you in filling out the chart. Circle your initial year.
Table 1
Year |
Previous Population |
Current Population |
1980 |
||
1981 |
||
1982 |
||
1983 |
||
1984 |
||
1985 |
||
1986 |
||
1987 |
||
1988 |
||
1989 |
||
1990 |
||
1991 |
||
1992 |
||
1993 |
||
1994 |
||
1995 |
||
1996 |
||
1997 |
||
1998 |
||
1999 |
||
2000 |
||
2001 |
||
2002 |
||
2003 |
||
2004 |
||
2005 |
||
2006 |
||
2007 |
||
2008 |
||
2009 |
||
2010 |
||
2011 |
||
2012 |
||
2013 |
Answers should varydepending on the estimate by students of the growth rate. A growth rate of two moose per year, starting in 1982, would have (0,0) in 1982, (0,2) in 1983, (2,4) in 1983, and so on.
Answers should varyto find the population for the first year, add the moose migrating into the park to the population in the initial year; to find the population for the next (second) year, add the moose migrating into the park to the first years population; and so on.
Answer: The number of years since their initial year. Population = (migration rate) × (number of years since the initial year).
Answers should varysomething like, the recursive is in terms of the year before, and the closed is in terms of the total years since the initial year. Both use the number of migrations per year.
Recursive: writing the "next few years" populations. Closed: predicting a population for a distant year.
Answers should vary from around 45 (using one moose per year) to 90 moose (using three moose per year).
|
![]() |
|
Previously, you used a recursive expression to represent the current population, based on the previous population. This yearly change can be thought of as displacement of moose, and may be recursively represented as follows:
Pcurrent = Pprevious + new moose |
where P represents moose population. |
A recursive representation requires an initial value. Why?
In your model, the initial value is 0 moose. You can restate the recursive representation as:
Pinitial = 0 Pcurrent = Pprevious + new moose |
A closed representation may be used to represent the population at any time, in terms of the migration rate (moose per year), the elapsed time (years), and the initial population. The closed form equation is:
Ptime = (migration rate ´ time) + Pinitial |
where time represents the number of years since your initial year. |
Pinitial is still 0 in this closed-form expression:
P(t) = (migration rate) t + Pinitial
Table 2
Year |
Previous Population |
Current Population |
1980 |
0 |
0 |
1981 |
0 |
Pprevious + new moose = 2 |
1982 |
0 |
0 |
1983 |
0 |
2 |
1984 |
2 |
4 |
1985 |
4 |
... |
1986 |
6 |
|
1987 |
||
1988 |
||
1989 |
||
1990 |
||
1991 |
||
1992 |
18 |
20 |
1993 |
Pcurrent = 20 |
Pprevious + new moose + 100 = 122 |
1994 |
122 |
124 |
1995 |
124 |
... |
1996 |
126 |
|
1997 |
||
1998 |
||
1999 |
||
2000 |
||
2001 |
||
|
2002 |
||
2003 |
||
2004 |
||
2005 |
||
2006 |
||
2007 |
||
2008 |
||
2009 |
||
2010 |
154 |
156 |
2011 |
156 |
158 |
2012 |
158 |
160 |
2013 |
160 |
162 |
Fill in the recursive chart in Table 2 to represent the results of moving 100 moose into the park in 1993.
Answers should varythis chart is filled in using two moose per year; once again, it depends on the students assumptions of initial year and migration.
= 8, 12, 15, 16
Answers should vary from around 145 (using one moose per year) to 190 moose (using three moose per year).
Sample graph:

This graph is recursive and results from using a migration of two moose per year. Student answers will vary, but the pattern should be similar: The slope should be 1 in all cases, and tells you nothing additional; the intercept gives you the starting value, thus, the migration rate. Note that this is a different interpretation from a time series graph, in that the slope is not the rate of change in population. Rather, it represents the rate of change in successive years. Since the quotient Current/Previous is always 2/2 (or whatever the student uses as the migration rate), this quotient is one.
Sample graph:

The graph above represents an assumption of growth of two moose and an initial year of 1982.
|
![]() |
|
You have scheduled a meeting with the commissioner to present your findings to date. You plan to include (as all modelers should) an explanation of the methods you used to arrive at your results, the model that you used, and the factors that you did not include in your model. The commissioner has decided to see you, but has limited time.
Prepare an oral presentation (using whatever presentation materials you have available) for this meeting.
See teachers notes for description of expectations.
|
![]() |
|
You have finished modeling the problemor so you thinkwhen some new twists occur. The conservationist group, which has been advocating that 100 moose be moved to the park, has just issued a report. According to their projections, the addition of 100 moose to the park will result in a moose population of around 1,300 in the year 2013. Your model does not come close to the conservationists number, but it was the best model you could construct given the limited information you originally had. Also, the ECD receives information that some baby moose have been sighted in the park.
|
![]() |
|
You have convinced the commissioner to give your department additional funds to study the problem more deeply. Reconsider your initial assumptions, which led to the migration model. In a short-term situation, an assumption of no moose deaths makes sense. However, your model represents 20 years. The expected life span of a moose is 1523 years. Some moose migrating into the park at the beginning of the 20-year period may already be aged. Accordingly, it is reasonable to consider deaths as a factor in your model, along with migration. Still assuming there are no births, a revised modeling diagram reflecting this would be:
Death is represented by a flow out of the moose stock. This model may be represented recursively as:
Pinitial = 0 Pcurrent = Pinitial + immigration death. |

Figure 3
This model assumes that every moose that migrates into the park will stay there until it dies. Repeat your work from Activity 2, Table 1, and Homework 2 using this new model. Write a short paragraph summarizing your findings. However, some moose may migrate into the park (immigration), but later leave the park (emigration). Redrawing the above modeling diagram to reflect immigration, emigration, and deaths as flows into or out of the stock of moose, it might look like:

Figure 4
Write a recursive representation of your modeling diagram.
Pinitial = 0 |
Modify your model to reflect any other considerations you believe are important.
In Model 1, you assumed that the moose population grows only through migration. It seemed reasonable to ignore births as a factor, given the large size of the park and the relatively small number of moose. However, the sighting of some baby moose in the park in 1993 indicates that moose might have given birth in the park. You therefore need to introduce births into your model.
The modeling diagram reflecting this situation could be as follows:

Figure 5
Assume that the moose population in the park remains sparse enough that the moose do not feel crowded. Migration therefore remains constant. However, with more moose in the park, they are more likely to meet and mate, so births will probably occur. Similarly, with more moose, some are likely to be old or ill, and deaths will probably occur. Therefore, the numbers of births and deaths depend upon the number of moose in the park. You can indicate this relationship with a thin, curved-arrow connector to form a feedback loop.

Figure 6
The recursive representation of the modeling diagram as refined is:
Pinitial = 0 Pcurrent = Pprevious + births + immigration (deaths + emigration) |
To simplify this model, call all the changes to the population the "net growth," and rewrite the recursive representation:
net growth = births + immigration (deaths + emigration).
Therefore, the model in recursive form is:
Pinitial = 0 Pcurrent = Pprevious + net growth |
For purposes of this new model, assume that the immigration and emigration are roughly the same number of moose. Net growth would include only births and deaths. Both factors may be expressed in terms of the previous years population. That is, both deaths and births are based on how many moose are in the park.

Figure 7
Combining births and deaths into net growth results in this final diagram:

Figure 8
One further refinement to the model is necessary, however. Since 1993 was the first year that moose calves were detected in the park, this seems to be a good place to start the growth model. Since it was estimated that between 25 and 30 moose were in the park, use 27 in the model. Therefore, set the initial year to 1993 and the initial population to 27 moose.
There has been a major change in the park: the introduction of females, and the observation of births to those females.
Deaths
In your first model, you assumed that deaths simply did not occur. It seemed like a reasonable assumption at the time, since there are no natural predators in the park and you had data suggesting that most of the moose wandering into the park were very young. On the other hand, you have seen that linear growth would take such a long time to increase the population that deaths by old age would have to be considered in the relevant time period.
Births
Since you have concluded that migrations (producing linear growth) are insufficient for large increases in population, your model must include another factor. You must include births. (There have been two sightings of moose cows with calves in the park, so it is reasonable to assume that births will continue to occur within its boundaries.)
Age/Gender
Notice that, in a simpler model (which ignored both births and deaths), the age and gender of the moose were irrelevant. This is no longer the case. Therefore, age and gender information should be included in your model.
Migrations
Although the migrations were a necessary condition for establishing the herd, you have calculated that the migrations happen at a rate of approximately 23 per year. In searching for the effect that might cause the herd to grow to 1,300 in 20 years, 2 or 3 migrations per year will play a very small part. For convenience, your next model will ignore the effects of continuing immigrations/ emigrations into and out of the area.
The consolidated modeling diagram looks as shown in Diagram 8. Remember, the feedback arrow represents the fact that the amount of growth in the population depends, in some way, on the current population. The "two-way" arrow on the flow indicates that net growth can be either positive or negative.

Figure 9
|
![]() |
|
You will now begin a simulation of the moose population in Adirondack State Park. Keep in mind what you are trying to accomplish. You are running the simulation to collect data in order to see if there is a pattern to the growth in the population. You know the approximate initial population.
Table 3. 1993 Herd
Age |
Females |
Males |
0 1 |
1 |
1 |
1 2 |
0 |
0 |
2 3 |
0 |
1 |
3 4 |
2 |
3 |
4 5 |
1 |
4 |
5 6 |
1 |
2 |
6 7 |
0 |
3 |
7 8 |
0 |
2 |
|
8 9 |
0 |
4 |
9 10 |
0 |
2 |
Totals |
5 |
22 |
Assume that there are 22 males and five females in the population. You can change this assumption and try a different make-up later. Using Table 3, together with the Simulation Checklist, Table 4, and the worksheets, run the simulation for an eight-year period.
Note: See Teachers Notes for a detailed discussion of this activity, as well as a more detailed discussion of running the game.
Table 4. Survival Table
Female |
Male |
||
Age |
Survival % |
Birth % |
Survival % |
0 1 |
75% |
0% |
75% |
1 2 |
90% |
0% |
90% |
2 3 |
80% |
90% |
95% |
3 4 |
95% |
90% |
95% |
4 5 |
95% |
90% |
95% |
5 6 |
95% |
85% |
95% |
6 7 |
95% |
80% |
95% |
7 8 |
95% |
75% |
95% |
8 9 |
95% |
70% |
95% |
9 10 |
95% |
60% |
95% |
10 11 |
93% |
50% |
93% |
11 12 |
90% |
40% |
90% |
12 13 |
85% |
30% |
85% |
13 14 |
80% |
0% |
80% |
14 15 |
80% |
0% |
80% |
15 16 |
80% |
0% |
80% |
16 17 |
80% |
0% |
80% |
17 18 |
80% |
0% |
80% |
18 19 |
80% |
0% |
80% |
19 20 |
80% |
0% |
80% |
Table 5
|
Year 1 |
Year 2 |
Year 3 |
Year 4 |
|||||||
Age |
Female |
Male |
Female |
Male |
Female |
Male |
Female |
Male |
||
0 1 |
| |
| |
|
|
||||||
|
1 2 |
|
|
||||||||
2 3 |
| |
|
|
|||||||
3 4 |
| | |
| | | |
|
|
||||||
4 5 |
| |
| | | | |
|
|
||||||
5 6 |
| |
| | |
|
|
||||||
6 7 |
| | | |
|
|
|||||||
7 8 |
| | |
|
|
|||||||
8 9 |
| | | | |
|
|
|||||||
9 10 |
| | | |
|
|
|||||||
10 11 |
|
|
||||||||
11 12 |
|
|
||||||||
12 13 |
|
|
||||||||
13 14 |
|
|
||||||||
14 15 |
|
|
||||||||
15 16 |
|
|
||||||||
16 17 |
|
|
||||||||
17 18 |
|
|
||||||||
18 19 |
|
|
||||||||
19 20 |
|
|
||||||||
Gender |
|
|
||||||||
Total |
|
|
|
|
||||||
The assumption of 27 moose5 females and 22 maleswas used to fill in year 1.
Table 5-a
|
Year 5 |
Year 6 |
Year 7 |
Year 8 |
|||||
Age |
Female |
Male |
Female |
Male |
Female |
Male |
Female |
Male |
0 1 |
||||||||
1 2 |
||||||||
2 3 |
||||||||
3 4 |
||||||||
4 5 |
||||||||
5 6 |
||||||||
6 7 |
||||||||
7 8 |
||||||||
8 9 |
||||||||
9 10 |
||||||||
10 11 |
||||||||
11 12 |
||||||||
12 13 |
||||||||
13 14 |
||||||||
14 15 |
||||||||
15 16 |
||||||||
16 17 |
||||||||
17 18 |
||||||||
18 19 |
||||||||
19 20 |
||||||||
Gender |
||||||||
Total |
|
|
|
|
||||