Cladisticules-Teacher’s Guide
I. Objectives.
The Cladisticules exercise is designed to introduce students (advanced high
school or beginning university-level) to the following concepts in
phylogeny/evolution:
Characters
Character states
Parsimony
Homology
Homoplasy
Cladograms
Ingroup and outgroup
Rooting
Evolutionary polarity
Synapomorphy
Symplesiomorphy
Monophyly
In addition, this exercise allows students to conduct their own simple cladistic
analysis on a set of imaginary organisms (Cladisticules).
II. Suggestions for teaching the Cladisticules exercise.
For optimal impact, we suggest first introducing the concept of shared ancestry
and the way that the distribution of homologous characters (homologies) in
different organisms can allow us to infer shared ancestry at different levels (more
or less inclusive groups). An example that is often useful for this purpose is to
discuss the unique characters that unite the group Mammals (e.g. hair,
milk)…they are useful for grouping all mammals, but if you wanted to uncover
sub-groups within the mammals, you’d need to look at other unique characters
that distinguish the various groups. The character hair, for instance, would not
be useful for distinguishing the primates from the bats, but the character of flight
would be.
We have found that one effective technique for presenting the material is to
distribute (or present) the Cladisticules exercise in increments. First, provide
page 1 (the figure with all the cladisticules ingroup and outgroup), and have the
students identify potential homologies (characters) that vary among the
creatures shown (the variants being character states within a character). Page
2 identifies some of these characters, so it should not be shown until students
have had a chance to work through the exercise of character selection on their
own. Once these characters have been identified, have the students fill out the
data matrix on page 3 (the completed matrix on page 4 is provided solely for
teacher reference).
After the students have filled out the data matrix, we suggest introducing the
principle of parsimony, that is, the simplest or shortest explanation for the
character data is most likely the correct one. This principle is widely used among
biologists as a model of how evolution proceeds. In phylogenetic analyses we
generally utilize traits that are evolving slowly relative to the age of the group in
question so it is reasonable to assume that changes are minimal. In phylogenetic
studies, parsimony relates to the number of times a character changes from one
state to another for all the taxa on an entire tree. The tree arrangement that
minimizes the total number of character state changes is the most parsimonious
tree. Thus parsimony does not rely on an assumption that evolution must
proceed according to the absolutely shortest route, instead it assumes that nonhomologous change in one character should only inferred if necessary to fit the
overall pattern displayed by all characters (see below for an illustration using the
cladisticules).
it is appropriate at this point to introduce the concept of the outgroup versus the
ingroup, and the idea of rooting. We feel that it is important to emphasize that
the outgroup is not essential to the process of constructing a cladogram: an
outgroup is only used to root the tree (it is perfectly acceptable for many
purposes to have an unrooted tree as well). But if we have a good idea of one or
more appropriate outgroups (that is, organisms that we know are
phylogenetically outside of the group that we want to study), then including
outgroups in our analysis is a good idea because ii allows us to root our tree -that is, it allows us to hypothesize where the bottom of the tree is and to see the
direction or evolutionary polarity of the changes in character states, from
primitive to derived, on the cladogram. Shared derived characters are called
synapomorphies, and shared primitive characters are called
symplesiomorphies. The distinction is important, since only synapomorphies
can be used to define monophyletic taxonomic groups (i.e., groups that contain
all and only descendants of a common ancestor).
For simple data sets, the parsimony principle can be implemented using set
theory. Each character state can be viewed as a set of those organisms
possessing that state. For simplicity, we'll use the character state considered to
be evolutionarily derived (apomorphic) using outgroup comparison as discussed
above. By convention, the inferred plesiomorphic state is coded '0' and the
apomorphic state is coded '1' (as in the solution to the data matrix, page 4).
Building a tree is equivalent to adding together the sets that are proper subsets
of each other. The Venn diagram on page 5 (top), again, can either be provided
to the students or used only by the teacher. In our experience presenting this
exercise, it is usually most effective to not distribute the Venn diagram to the
students, but instead work through the first two or so groupings on a chalk board
(working from most inclusive to least inclusive characters, drawing a set
boundary around the organisms sharing state '1' in each character), and then
allow some time for students to complete Venn diagrams on their own, going
back over the correct Venn diagram with the entire class after students have had
the opportunity to work on the problem individually. Teacher’s note: the
numbers on the diagram (along edge of boxes) represent the characters that
group the cladisticules (names inside of boxes) at various levels.
How to deal with character conflict? Character #7 unites a group (April, Tanya,
and Jane) that is in conflict with the rest of the groupings (this is equivalent to an
improper subset in set theory), shown on the bottom of page 5. This is an
example of a homoplastic character (homoplasy) -- a character that we initially
thought to be a homology, that after our analysis is found to not be a homology
(in this case, it could be a convergent similarity due to gender, since it unites the
females). It is important to point out that while we try to pick characters that we
believe to be homologous, we can only identify non-homologous characters
(homoplasies) after our analysis is done (in light of all the evidence gained from
the other characters).
Once the Venn diagram is completed, have the students attempt to construct a
cladogram from it (again, we would suggest withholding the final cladogram on
page 7), and then work through the problem together. We show the process on
page 6. In producing the final tree, keep in mind that branches can be freely
rotated at a node, so the trees on pages 6 and 7 are identical. Be sure to point
out to students the power of this sort of evolutionary inference: we can not only
reconstruct the branching order (relative recency of common ancestry) but also
infer the order of character change.
Note that this set-theory approach to building trees would not work for large,
complicated data sets, and indeed is not the exact approach that current
computer algorithms work to build trees. However, it does illustrate the
conceptual framework behind phylogenetic reconstruction accurately, and is the
easiest approach for beginners to grasp intuitively. Students should be
encouraged to look into the subject further, since the whole area of computerassisted phylogenetic analysis is rapidly developing and being applied to many
exciting topics in biology including biogeography, community ecology, behavior,
development, public health, and medicine.