Download Unit 13 Evolution Teacher Guide

Unit 13 Evolution Teacher Guide
Investigation 2
Adaptation
Introduction
In this investigation, students use a computer simulation of sheep and grass to study how
the genetic makeup of populations is affected by selection pressures. They experiment
with a single variable trait to observe genetic drift under various conditions, and they
introduce a mutation and see if it becomes common in the population.
Students will gain experience with both inquiry skills and content, including:
 Conceptualizing species in terms of population rather than individuals.
 Using and collecting evidence from a computer simulation.
 Observing the effects of selection pressures in a simulation.
 Experimenting with the spread of adaptations and mutations in a population.
 Developing descriptions, explanations, predictions, and models using evidence.
 Using technology to gather data and make accurate measurements.
 Developing explanations based on scientific information and evidence, including
computer models.
 Applying and adapting a variety of appropriate strategies to solve problems.
 Representing, analyzing, and generalizing a variety of patterns with tables,
graphs, words, and, when possible, symbolic rules.
 Using a basic understanding of probability to make and test conjectures
about the results of experiments and simulations.
Discussion guide
Additional teacher background
There are several closely related models in the two investigations for unit 13. The models
in Investigation 2 focus on the genetic makeup of a population and how it changes in
response to selection pressures. The principal concepts of Investigation 2 are as follows:
 A population has a range of genetic traits – not all individuals are the same.
 In sexual reproduction, the offspring get genetic material from both parents, and
combine it in a new and unique way.
 Individuals can change their behavior, but not the genetic material they pass on.
 Selection pressure exists if the probability that individuals will reproduce
successfully is different for different traits. Over time, this changes the proportion
of a given trait in the population, in the direction of traits that are more likely to
be successful for reproduction (genetic drift).
 Thus, evolution is a two-step process:
o random mixing of parents’ genes in offspring
o selection against some traits
 There are often many selection pressures, and they may operate in opposing
directions.
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


The range of traits remains available in the gene pool, even if there’s strong
selection against some of them.
New traits can arise from mutations, which disappear if unfavorable, and can
spread throughout the population if favorable.
Evolution and adaptation happen at the population level, not the individual level.
Evolution and adaptation happen over generations, not within an individual
lifetime.
How the computer model works
In this investigation, instead of taking data with sensors, students run experiments and
collect data with a computer model., written in NetLogo, a language for modeling
complex systems. (For further information, go to http://ccl.northwestern.edu/netlogo/)
The investigation uses several different models that all have the same rules but highlight
slightly different features. The rules are as follows:
 The SETUP button creates an equal number of male and female sheep in a field of
grass.
 The sheep move around and use up energy as they move. They take 12 steps per
year.
 If they cross a green patch, they gain some energy and turn the patch from green
to brown – that is, they “eat the grass”.
 If the sheep run out of energy, they die.
 The sheep live for six years and then die.
 From age 3 to age 6, each female randomly picks one male from the flock once a
year and and mates with him to have one baby. The baby’s traits come from both
its parents.
 The grass grows back in an adjustable amount of time.
 The graph shows the relative amount of grass and the total sheep population.
 SETUP sets up the model, GO-ONCE runs it for one year, and GO-FOREVER
runs it continuously. The model stops if the GO buttons are clicked on again. It
also stops if all of the sheep die.
 Each sheep has a TEETH variable, which can be 0.8 (worse), 1.0 (average), or 1.2
(better). The higher the value, the greater the energy it gets from eating grass, if
the SELECTION? switch is on. This is an example of a variable trait.
 In Trial 3 (Mutation), sheep can also inherit the color blue. This is an example of
a mutation. If the SELECTION? switch is on, the blue sheep get twice as much
energy from the grass as white sheep.
 Each sheep inherits traits from its parents, according to Mendelian genetics,
which is explained below.
Genetics
This model uses Mendelian genetics, but students don’t need to learn how this works in
detail. Darwin wrote The Origin of Species without any knowledge of genetics, and the
central ideas of evolution do not depend on it. Students should understand that babies
inherit a trait by receiving different genetic material from each parent and combining it in
a unique way. They tend to be like their parents, but not exactly. If a parent has better
teeth, a baby is more likely to have better teeth. Also, a trait can remain present in the
gene pool but hidden (that is, unexpressed) for one or more generations.
If you plan to talk about Mendelian genetics, here is the exact mechanism: every sheep
has two chromosomes, each with a teeth gene that can be dominant (T) or recessive (t).
The baby receives one chromosome, randomly chosen, from each parent. If both parents
contribute T, then the baby is TT; if one contributes T and the other t, the baby is Tt; and
so forth.
Male
T
t
Female T TT tT
t tT tt
The trait is codominant in this model; that is, the value of TEETH is as follows:
TT
tT
Tt
TEETH = 1.2
TEETH = 1.0
TEETH = 0.8
At the beginning, 1/4 of the sheep will have TEETH = 1.2; 1/2 will have TEETH = 1.0;
and 1/4 will have TEETH = 0.8.
If SELECTION? = OFF, the trait is not expressed. The value of TEETH will have no
effect on how much energy sheep get from grass. However, the student will probably
notice that the average value of TEETH fluctuates even without any selection pressure.
This random process, called genetic drift, is quite pronounced when there are only a few
hundred animals. This is one reason why small populations of endangered species are so
fragile. A small inbred gene pool can lead to the loss of favorable genes and the
preponderance of unfavorable ones. A larger gene pool is more robust and adaptable.
If SELECTION? = ON, the trait is expressed. The larger the value of TEETH, the more
energy sheep get from grass. After a time, especially if GRASS-REGROWTH-RATE is
low (try 40) and many sheep die of starvation, TT will predominate in the population and
the average TEETH will approach 1.2.
On the other hand, if the farmer removes the sheep with better teeth (perhaps because
they are bigger and worth more), the herd may adapt by moving toward smaller teeth.
Such conflicting pressures are common in nature and lead to a stable genetic distribution
in the long run.
One of the most important ideas of evolution is that populations evolve, not individuals.
The population changes because an animal with a favorable trail is more likely to
reproduce and pass the trait on to its babies, and not because the animal changes during
its lifetime. This may be very confusing to students, partly because humans do learn and
change during their lifetimes. But for evolution, what matters is the genes we are born
with and whether we pass those genes on to the next generation.
There are two fundamental features of living systems that make evolution possible. Both
are illustrated in this model. The first feature is that populations are not all genetically
identical. This is called genetic variation. Some traits have a range with many
intermediate values, such as height, weight, and skin color. Populations can adapt to
changing conditions (and back again), just using the variations that are already in the
gene pool. The example of this in the model is the TEETH variable.
A second possibility is that mutations may add new traits that didn’t exist in the
population before. The example of this in the model is having blue wool. This trait is
arbitrarily linked to much better teeth. There’s no good biological reasoning for this! It’s
just a way to make the spread of the mutation visible in the model.
The blue/much-better-teeth trait is recessive, so the inheritance chart looks like this:
Male
C
Female C CC
(white)
c cC
(white)
c
cC
(white)
cc
(blue)
The second process that makes evolution possible is called natural selection. Genetic
information is passed on from parents to offspring, who tend to be genetically like their
parents. If an individual with a certain trait is more likely to survive and have offspring
than an individual without that trait, then there is a selection pressure for that trait. The
trait becomes more common in the population over many generations. This could be true
of a variable trait, like TEETH, or a single mutation, like blue wool.
Together, genetic variation and natural selection lead to the evolution of organisms over
many generations. For all animals with sexual reproduction, the genes get scrambled
around in each new generation, and mutations may be added as well. Natural selection
leads to favorable traits becoming more common over many generations.
The cartoon at the beginning of this investigation illustrates a variety of beak shapes that
birds have evolved to find food in different niches. For more about this, see
http://www.nhm.org/birds/guide/pg009.html.
Usually, selection is complex in nature. There may be conflicting pressures both for and
against a trait. In the model, this is demonstrated using the TEETH variable in Trial 2. If
TEETH has a high value, sheep get more energy from grass and are less likely to starve
to death. But they are more likely to be removed by the farmer, which favors a low value
of TEETH. Students can turn these two effects on and off and observe the results.
Another example of conflicting selection pressures is in Trial 3. Blue sheep get much
more energy from grass, which favors them. But if females refuse to breed with blue
males, the blue gene is selected against. Once again, students can turn these two effects
on and off.
A further step, which is not explored in this model, is the origin of species. If a single
population is isolated into two groups, the two groups may evolve differently, due to
different environmental pressures or chance mutations. If they reach a point where they
won’t breed with one other, they remain different and two species come to exist instead
of one.
Question 6 in the Analysis – how giraffes got long necks – is a good discussion question
for testing students’ understanding of natural selection. One common misconception is
that animals can change their genetic makeup by their behavior. But a baby inherits its
parents’ original genetic makeup, which is unchanged by what the animal learns during
its lifetime. So the first (Lamarckian) theory in question 6 is not the way nature works.
A second misconception is that the whole population gradually gets longer necks. While
this is true, the more accurate statement is that girafffes with longer necks are more likely
to survive and reproduce, so that over many generations, giraffes with longer necks
become become a larger proportion of the population. This process requires both genetic
variation and natural selection, working together.
Suggested Timeline
The amount of time you spend on introductory discussions, experiments with the
simulation, and analysis, will determine your overall timeline. The following represents a
possible timeline.
 One class period - "Setting Up" discussion
 One class period - Trial I: Better teeth
 One class period - Trial II: Conflicting selection pressures
 One-half to one class period – Trial III: Mutation
 One class period - Analysis and "Wrap Up" discussion
Additional days can be used for Further Investigations.