One possible difference between proximate and ultimate explanations might be the following. Ultimate explanations, those concerned with natural selection, make very broad generalisations that apply to many different types of populations. In contrast, proximate explanations give us very deep explanations, but are limited in scope, applying to the some particular target (such as eas or ants). Sober has remarked on the breadth that explanations in evolutionary theory have:
One salient fact about much of evolutionary theory, as opposed to other areas in biology like molecular biology or biochemistry, is that the prop- erties investigated are supervenient. eories of predator / prey inter- actions, diversity / stability models, and the origins and maintenance of sexuality, to name only a few examples, pay very little attention to the physical mechanisms whereby organisms are able to have the prop- erties in question. Even a race of robots or organisms from another planet whose mechanism of heredity is based on a structure other than DNA would potentially fall within the scope of these theories. […] Evolutionary biology frequently arrives at models of great generality by abstracting away from physical details. Fitness is one of the central conceptual tools in this explanatory strategy. (Sober, , p )
As Sober notes, this generality is in part due to supervenience of tness. Because tness can be realised in many different ways, we can construct very broad general- isations at the level of tness, and they remain invariant across many populations. is resembles the car accelerator discussed previously. e relation between the accelerator and the car speed was realised in different ways in cars with different engines. A mechanic, however, wants a deeper, more reliable set of generalisations. So it is with evolutionary theory – once we pick a particular population and want to track very accurately what is going, we typically have to enrich our model with particular details about that population.
Contrast this with nding out how eas jump. is is a very narrow explanatory project in comparison to what Sober had in mind. But it is one that that we expect to give us a deep explanatory generalisation about eas. Is it always the case that proximate explanations will be like this? I think not.
ere are two ways that a proximate explanations might have a very broad scope. e rst is, in some ways, trivial. It is a contingent fact that many proximate mech- anisms are shared by all (or many) organisms. A model of gene transcription applies across an extremely broad scope because this transcription is highly conserved across all biological organisms. Many multicellular organisms share highly conserved de- velopmental pathways that lay out the body plans of animals as diverse as ies and mice (Carroll, , p ). So one way we can give broad explanations in functional biology is by appealing to the shared basis of all biological organisms. Notice that these types of generalisation do not make a trade-off between depth and breadth. e arenotmultiply realised – they each work in the same way. e deep details of
gene transcription hold equally well across all organisms. So these explanations are both deep and broad.
e second way that proximate explanations can be made broad relies, like ulti- mate explanations, on multiple realisation. For example, it turns out that the path integration, or “dead reckoning” that ants use is found across a broad range of ani- mals: mole rats, hamsters, crabs, bees, and spiders (Vickerstaff and Di Paolo, ). us some of the generalisations about path integration may apply to a wider scope (for example, the way that it can accumulate error). But the particular way that certain components of the mechanism are realised differs amongst these organisms. For instance, the pedometer discussed in the previous section is the way that ants keep track of the distance travelled. But this is not the case for bees. Instead, bees calculate the distance travelled by optic ow. is is the speed at which the things move across the visual eld whilst the bee moves. So a particular component in a larger mechanism is realised in a completely different way. It would be sensitive to different interventions; putting stilts on a bee would make no difference to its ability to nd its way back to the hive.
Other such generalisation are possible, at even more abstract levels. For ex- ample, although vertebrates have a variety of mechanisms for getting around – - legged, -legged, hopping, running and walking, it turns out that metabolics of lo- comotion on land is independent of animal shape or limb number (Roberts, ). e energetic costs can be predicted from just a few parameters: the force gener- ated by the foot against the ground, and the foot contact time with the ground. According to Roberts, this indicates that common solutions have been found to the problem of economic movement. Part of this solution is the use of muscles and tendons as springs to store energy that would otherwise be lost, and convert it to kinetic energy. ough the data provides an independent veri cation of this gener- alisation, underlying it is a set of constraints for solving the same problem, though they have been realised in different ways.
ese kinds of generalizations are not about populations, and do not rely on the multiple realization of tness as the basis of their generalisation. But they do rely on the multiple realization of certain components within systems described by the generalisation. is is what makes the scope of these generalisations broader. It also, as we noted before, introduces a trade-off against the depth of the explanations. For any particular realisation may have a different set of underlying dependencies that interact in a different way. e level at which we describe the system is going to be an important factor in being able to apply these generalisations broadly.
ere are a number of reasons that explain why we should expect broad gen- eralisations about mechanisms in biology. As with generalisations in evolutionary biology, it may be the case that these generalisations only hold at a particular level, for they may be realised differently. ere are certain physical constraints on the world, and also certain principles of good design that are applicable to biological systems. (Dennett, ) call these “forced moves” and “good tricks”. Consider the problem of transporting uid – such as blood or sap – within an organism. e branched structures that transport uids often approximate a constraint known as
“Murrays law”, where the sum of cubes of the radii at any level of branching will be equal. Many of the various types of branching structures have independently evolved, so the basis of explanatory breadth is very different from the generalisation we can make about gene transcription switches or body plans. e reason is that:
[…] animals have repeatedly evolved a complex branching hierarchy of vessels approximating a globally optimal system that minimizes the costs of the construction and maintenance of the uid transport system. (LaBarbera, )
Consider this with respect to Sober’s comment about “organisms from another planet or a race of robots” who would fall under the scope of evolutionary the- ory. If these organisms or robots had some sort of uid transport system, then we might expect them to fall under “Murrays law” as well.
In sum, very broad generalisations are possible within proximate, or mechanistic explanation too.
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Summary
In this chapter I have put some weight behind Seeley’s comment that there are two issues that should concern us in understanding transitions in biological organisation. First, ultimate explanations that rely on natural selection assume variation is present in the population. But they do not explain it. For this we need to look at some sort of proximate explanation, for this will tell us what underlies the pheno- typic variance in a population. In the rst instance we have looked at proximate explanations of individual organism traits, but as Seeley pointed out, this kind of proximate explanation applies to the integrative organisation of groups. e dif- ferent ways that individuals can organise themselves will explain tness differences between groups.
Second, the idea that explanations in evolutionary biology have broad scope and explanations in functional biology have narrow scope is overstated. Very general proximate explanations can be given. is may be simply due to contingently shared mechanisms, or to engineering constraints.
Both of these issues are important. For if proximate explanations play a role in understanding natural selection, and they can be given across a broad scope, then perhaps these kinds of explanations can be applied across different levels of organ- isation.
ere are some interesting interactions between these types of explanatory pat- terns and the issues of transitions. One interaction in particular may explain an over-emphasis on ultimate explanations, sometimes to the detriment of proximate explanations (a point noted above by West-Eberhard). Notice that the scope of ulti- mate explanations is increased by (as Sober puts it), “abstracting away from physical details”. So removing details relevant for proximate explanations is the very thing
that makes ultimate explanations more general. A broad generalisation in evolu- tionary biology removes the very details that might play a role in another type of generalisation – one that involves the physical details that have already been ab- stracted away. is sheds some light on the problem of integrating evolutionary and developmental biology. A theory of variation depends on the proximate details that evolutionary biology, in search of generality, idealizes away.
I’ll make one last comment that connects these explanatory patterns to transi- tions in biological organisation. I distinguished these two patterns by their differing target of manipulation, which is either at the individual-level or at the population- level. But what counts as an individual is, in part, what is at question during a transition. Choosing to treat some new level as an individual, or simply part of a structured population has implications for one’s account of what makes a transition possible. I’ll return to this issue in the second part of the thesis, where I argue in length that the proximate issue ofgenerating bene t has an important role to play, though it has usually plays second- ddle to the problem of cooperation.