The following was written in partial fulfillment of the requirements of Dr. Greg Welty's Philosophy: Science and Religion class at Southeastern Baptist Theological Seminary.
The following was prepared as a one-page, single-spaced short response to a question from the readings for this class.
The tension between realism, generality, and precision posited in biology is a function not of those constraints in general, but of the specific constraints on biology and other sciences dealing with what is often described as having “emergent” phenomena. The closer the science is to physical first principles, the less these terms stand in contrast. For example, in chemistry, a realist description of the chemicals in question is actually helpful in dealing precisely with the terms in question. The behavior of the chemicals at large scales can be modeled more effectively precisely because the underlying principles are relatively well understood and the phenomenon describable not merely as a representative abstraction but in terms corresponding to what seem to be the actual characteristics of the system in view. The same is true of much of physics. For example, the idea of general relativity is (as its name suggests) extremely general, covering the behavior of all macroscopic systems at least; is sufficiently precise in its predictions to enable extraordinary feats of timekeeping and geolocation; and is understood by the majority of working physicists to be a true and not merely a useful description of how space-time behaves.
The question arises then: assuming the claim is correct for biology, why is this so? The answer seems to be that biological systems are not subject (at least so far as they are understood so far) to be capable of reduction to the same kinds of general theorems as the more purely physical sciences. Though biological is concerned of physical subjects, those subjects seem not to merely the expression of mechanistic phenomena (though of course this point is debated by some physicalist philosophers and scientists). Rather, their behavior emerges atop the underlying physical system, and then diverges in unpredictable ways from individual subject to individual subject. As a result, descriptions of the trends that occur in a given population may be general, but do not do justice to the behavior of any one member of that population, and so are not precise. Thus, ecologies are functions of aggregate behavior, but that aggregation is something like the “average American family”: it is a description of no individual element within the system, but of the combined output of the whole system. Moreover, under even trivially different conditions (a lightning strike occurring in one place rather than another, for example, and changing the behavior of the animals in that area), the specific outcome of the system might have been meaningfully different—even if still able to be modeled under the same general descriptions.
Indeed, most effective general models of behavior in biological systems are neither realistic nor precise. Attempts to model the function of neurons are often precise, but intentionally non-realist and non-general, not least because in most organisms, neurons are non-generalizable: only the simplest creatures have non-differentiated neurons. But in each of these cases, these are functions of the kind of increasingly complex systems, which are not apparently describable purely in terms of their underlying components. The brain, for example, is composed not just of an extraordinarily large number of neurons, but of a great variety of kinds of neurons as well, and the neurons all have the same basic chemical makeup and the same basic genetic structure, but develop in different ways because of specific driving factors in their environment, signals from chemicals driven by other parts of the body, and so on. Any description of any part of this system will necessarily be subject to the constraints the biologist describes simply because there is no single underlying principle driving the system; rather, it is a complex system where each part informs the others. The same is true (and even more so) of systems made up of biological actors, such as communities and ecologies; it is unsurprisingly also a common feature of systems which include actors with agency (such as economics).