Everything that evolves requires two explanations. First, why does a given trait exist compared to many other traits that could exist (ultimate causation)? Second, what are the physical mechanisms that cause the trait to be expressed (proximate causation)?
The question “Why do apple flowers bloom in spring?” nicely illustrates the distinction between ultimate and proximate causation. Apple trees can conceivably flower at any time but those that bloomed too early were nipped by frost and those that bloomed too late failed to develop their fruit. Apple flowers bloom in spring because those that didn’t lost the Darwinian contest. That’s the ultimate explanation.
At the same time, there is a physiological mechanism that causes actual apple flowers to bloom in spring, which furnishes the proximate explanation. I’m not an apple flower expert but in many plant species the timing of flowering is accomplished by sensitivity to day length. This fact is important because sensitivity to day length by itself has little impact on survival and reproduction. Nevertheless, it often evolves as the proximate mechanism because day length provides an accurate cue to the time of year. Temperature is more directly relevant to survival and reproduction but it is also highly variable. Thus, a plant that relies upon temperature as a flowering cue might bloom during a warm spell in early March, only to be nipped by frost when winter resumes its grip. In general, the proximate explanation for a trait need not bear any resemblance to the ultimate explanation, other than to reliably cause the organism to do the right thing with respect to survival and reproduction.
Another important fact about the ultimate-proximate distinction is embodied by the proverb “There are many ways to skin a cat”. All plant species that bloom in spring can be explained in roughly the same way in terms of ultimate causation, but the proximate mechanisms can be different. To pick another example, many species of animals that live in the desert, including insects, reptiles, mammals, and birds, have evolved sandy coloration to avoid being seen. The exteriors of these creatures are made of completely different materials, however, so the proximate mechanisms that produce sandy coloration are different in each case. In our own species, milk became an important resource for adults independently in Europe and Africa several thousand years ago. Both populations evolved the ability to digest lactose as adults but the proximate mechanisms are different. The “many ways to skin a cat” principle can even be demonstrated in the laboratory. Imagine dividing a stock population of fruit flies into a number of isolated populations and selecting for exactly the same trait–wing length–in each one. Longer wings evolve in each case but the particular genes that mutated to result in longer wings are usually different. There are many ways to skin a cat and there are many possible proximate mechanisms for any given trait that is favored by natural or artificial selection.
Lin Ostrom’s work provides two examples of why the ultimate-proximate distinction matters for economic theory and policy. First, after a large number of case studies of groups attempting to manage their commons had been compiled, Lin tried to relate the success of each group to a large number of independent variables that had been coded. To her dismay, she found very few statistically significant correlations. Here is how she describes her experience in a recent article published in the Annual Review of Political Science.
I dreamed of analyzing the rules that we had coded in our meta-analysis to find those that were generally associated with long-term success. I spent weeks and weeks rereading cases, writing them up, redoing statistical analysis, and thinking that I was a dope for not being able to identify regularities in the specific property rights of the successful cases. Finally, the idea dawned on me that I should drop the idea of identifying the specific rules that tended to generate success. Perhaps what I needed to do was move up a level in generality to try and understand some more general institutional regularities among the systems that were sustained over a long period of time. I did not even know what I should call those regularities, but the idea finally flashed that one way of talking about it would be as ―design principles.
In other words, Lin initially attempted to correlate the success of each group with specific proximate mechanisms. Because there are many ways to skin a cat, the proximate mechanisms that work successfully in one group need not operate in other successful groups, resulting in weak correlations in a statistical analysis. When Lin started to focus on design principles, she was studying ultimate causation. The design principles are required for success, no matter how they are implemented, resulting in strong correlations. Of course, studying or advising any particular group would require close attention to both ultimate and proximate causation. Lin learned about the need to distinguish between ultimate and proximate causation the hard way. Evolutionary theory makes the distinction crystal clear at a foundational level.
The second example provided by Lin’s work involves how groups of fishermen successfully manage their commons. The important variable, of course, is the number of fish that are harvested compared to the capacity of the population to regenerate. Fisheries biologists build complicated models to determine optimal harvesting rates and go to a lot of effort to monitor harvesting rates on the water. Yet, Lin discovered that groups of fishermen who successfully manage their commons almost never monitor harvesting rates. The information is difficult to collect, even more difficult to monitor, and the relationship between the harvest rate and regenerative capacity of the stock is influenced by many variables. Instead, the groups of fisherman use simple rules that are easy to monitor, such as the number of boats that are allowed to operate at a given time, the kind of nets that they can use, and so on. They are just like those plants that use a reliable cue such as day length rather than an unreliable cue such as temperature to do the right thing, even though temperature is more directly related to fitness.
The ultimate-proximate distinction is so foundational in evolutionary theory that it would be odd indeed if it did not prove to be equally foundational in our efforts to understand and manage human life.