Learning to read the tree of life
Evolution education is entering an exciting time: scientists are working on the Open Tree of Life the first comprehensive tree charting the evolutionary relationships of all named species—and many U.S. classrooms are preparing for state adoption of the Next Generation Science Standards (NGSS), in which evolution and common ancestry are central. However, in order to capitalize on these developments, students will need to become competent in the surprisingly tricky skill of “tree thinking.”
Trees are one of the most powerful metaphors in art and science. For biologists, the “tree of life” stands for both the unity and diversity of life. But are students and non-scientists accurately interpreting its branches? As I’ve discussed here before, misconceptions about the mechanism of natural selection—often referred to as microevolution—are rampant. However, understanding macroevolution—the big picture of biological evolution, including the common ancestry of life and the relationships among groups of living things—may be even more difficult.
Troubles with trees
Science education researchers have been documenting students’ troubles with trees for many years. Textbooks, museum exhibits, and other learning resources are filled with a variety of tree-inspired diagrams that often represent different types of information from each other. Different diagrams may show different levels of taxa (for example, species, genera, or orders). Some may be oriented horizontally and others vertically. And they may or may not include shared traits, shared ancestors, or time. Some researchers have argued that diagrams that are not cladograms—which use a simple branching system to depict clades, or groups that share a common ancestor—are less useful and only serve to confuse. Yet cladograms themselves are notoriously easy to misinterpret.
Common misinterpretations of cladograms result from reading from top to bottom (horizontally oriented cladograms) or from left to right (vertically oriented ones) and inferring either increase in “complexity” (likely reinforced by highly problematic “march of progress” diagrams) or passage of time. Similarly, instead of following the nodes back to a most recent common ancestor, many people focus on the tips (the parts marked with taxa names)—and infer that spatial closeness implies a closer evolutionary relationship.
When describing what is represented in cladograms, students focus on perceived “similarities” rather than ancestry. For the most part, the more recently two taxa shared a common ancestor, the more similarities they will have. But because of confounding factors like convergent evolution (when distantly related taxa evolve similar traits in response to similar environmental pressures) perceived similarity can be highly inaccurate, and is not what is represented in a cladogram. For a full summary of the pitfalls with an abundance of clarifying diagram examples, see evolutionary biologist T. Ryan Gregory’s review article (pdf).
The National Evolutionary Synthesis Center (NESCent) recently held a meeting to address some of the challenges in evolution communication. In response to scientists outlining the misinterpretations of trees, paleontology writer Brian Switek tweeted:
If reading across the tips of a cladogram/phylogeny is misleading, we need new imagery for #evocomm to the public.
This suggestion dovetails well with the expectations for science practices set forward in the NRC’s A Framework for K-12 Science Education (from which the NGSS were developed):
By grade 12, students should be able to: Represent and explain phenomena with multiple types of models—for example, represent molecules with 3-D models or with bond diagrams—and move flexibly between model types when different ones are most useful for different purposes.
Perhaps if students were given a totally different kind of visual model for common ancestry to use alongside the traditional tree metaphor, they could overcome some of the difficulties and learn something about the nature of scientific modeling in the process.
A change of perspective
I met Sonia Stephens a little over a year ago at the NARST (National Association for Research in Science Teaching) annual meeting and was immediately excited by her work. As part of her dissertation in science communication, she had responded to all the conceptual difficulties that trees seem to cause by creating a digital dynamic evolutionary map (DEM).
In her paper in Evolution: Education & Outreach, Sonia explains that the map is essentially a top-down cross-section of a phylogenetic tree. Multiple cross-sections, which animate in sequence, represent different points in time. Taxa appear as dots whose relative spatial distances are determined by phylogenetic relatedness. When reading a cladogram, the intuitive impulse to infer relatedness from spatial distance between branch tips inevitably leads to error. The DEM works with this intuition, rather than against it.
When I asked her about what people would need to understand in order to use the map, she said:
I assumed a basic knowledge of biology, having seen (though not necessarily knowing all the nuances of) phylogenetic trees, and familiarity with at least some terminology, e.g. evolution, genes, species, etc. In order to integrate the DEM into a classroom setting, you’d want to provide more context for these concepts.
The DEM is free to use (under creative commons license CC BY-NC-SA) and Sonia is always interested to hear from possible collaborators.
Another digital innovation on evolutionary tree diagrams, the amazing OneZoom Tree of Life Explorer, will be visualizing the Open Tree of Life. As detailed in an article on the PLOS community pages, OneZoom’s tree breaks the static, paper-bound mold in many ways—and it includes three different fractal shape options, which may prevent some misinterpretation. However, unlike the DEM all versions retain the branching metaphor.
The flexibility of digital visualization has the potential to overcome many of the obstacles to “tree thinking.” I look forward to seeing research evaluating the affordances of these new tools and the development of appropriate educational supports.
Gregory, T. R. (2008). Understanding evolutionary trees. Evolution: Education and Outreach, 1(2), 121-137.
Stephens, S. (2012). From Tree to Map: Using Cognitive Learning Theory to Suggest Alternative Ways to Visualize Macroevolution. Evolution: Education and Outreach, 5(4), 603-618.