## 1. Origins of the Concept of Genetic Drift



Although Charles Darwin invoked "chance" in various ways
in the *Origin of Species* (Beatty 1984), he seems not to have
included a concept of drift in his account. He does note in passing
that



> 
> 
> [v]ariations neither useful nor injurious would not be affected by
> natural selection, and would be left either a fluctuating element, as
> perhaps we see in certain polymorphic species, or would ultimately
> become fixed, owing to the nature of the organism and the nature of
> the conditions. (Darwin 1872: 63; see similar claims on p. 120 and p.
> 176)
> 
> 
> 



As the reader will see, this is tantalizingly similar to contemporary
conceptions of drift. But Darwin does not develop the idea further; in
particular, he does not tell us why the distributions of such
variations would be fluctuating over time or how it is that they would
ultimately become fixed. The first serious (and mathematical)
treatments of drift are usually traced to two of the founders of
population genetics, Sewall Wright and R.A. Fisher, although neither
claimed to have developed the ideas behind drift (Beatty 1992). Wright
(1951) credits John Gulick (1873) with the genesis of the idea whereas
Fisher (1922b) first discussed the idea as derived from the work of
A.C. and A.L. Hagedoorn (1921), although Wright (1931a) cites the
Hagedoorns too. It is unclear who first uses the term
"drift" in this context; it appears as early as Wright
(1929). So, let us briefly examine Gulick and the Hagedoorns in order
to understand the origins of the term "drift".



Gulick (1873) points out that with natural selection, one can assume
that where different forms are found, different external conditions
will also be found (with the different forms having adapted over the
course of generations to the different external conditions). However,
there seem to be cases (e.g., among snails) where the external
conditions are very similar, yet the organismic forms are very
different. He notes that these species tend to occupy very small
areas, even though there is reason to believe it is not because they
lack the ability to migrate further. He then postulates a scenario:
Suppose some members of a species migrate to a new area where they are
free from competition and largely separated from the original
population. New variations will arise in the new population, but
unless they are "decidedly malformed", they will persist.
The new population will thus come to differentiate itself from the
original population (e.g., with new shades of color or with variations
of shape), perhaps rapidly if there is a "preexisting tendency
to rapid variation".



Some points to note here that become relevant in later discussions of
drift: 1) Drift is described in contrast to natural selection. 2) The
variations increasing in the population are those that are neutral, or
at least not severely deleterious. (Note that 1 and 2 are also present
in the quote from Darwin above). 3) Drift is associated with small
populations (although it is not fully clear why). 4) Drift is
associated with the founding of a new population in a new area. 5)
Changes in the population are the result of movements of organisms and
their tendency to produce new variations, both of which are physical
processes and not purely mathematical constructs (something that
becomes an issue in later debates). 6) The changes described are of
organisms in a population.



Hagedoorn and Hagedoorn (1921) similarly point out that some traits of
organisms are "trivial", i.e., "cannot possibly be
accounted for as useful", such as "the shape and
arrangement of small hairs on the seeds of some cereals" (p.
107). They likewise maintain that such traits, which can be stable
("pure", i.e., fixed) within a species, cannot be the
product of natural selection; instead, the Hagedoorns assert, they
must be "due to some process which accompanies selection"
(p. 108). The Hagedoorns then proceed to describe several ways in
which variability in a population can be reduced: a new population is
founded which lacks some of the variability of the original
population; a population is split in half (with the variability in the
daughter populations differing from each other and from the original);
and "random sampling" where even though the size of the
population remains relatively constant from year to year, only a small
fraction successfully reproduce. On this last point, they state,



> 
> 
> The group of organisms chosen by fate to become the parents of the
> next generation is usually, but always occasionally, considerably
> smaller than the number of individuals of their species. (1921:
> 120)
> 
> 
> 



Thus, the Hagedoorns endorse points 1-5 above, while describing
two additional processes besides #4 (the founding of a new
population), namely the splitting of a population and the random
sampling of parents. They further explain the relevance of #3 (small
populations): "the smaller the group, the more limited its
potential variability, the sooner it will be pure altogether"
(p. 123). And finally, they maintain that drift can produce fixation
("purity"), or the complete loss of variation within a
population, even in the absence of selection. Fisher (1922b) reads the
Hagedoorns as claiming that "random survival is a more important
factor in limiting the variability of species than preferential
survival" (p. 321), a claim that he challenged by attempting to
show that such a process would be too slow to overcome the rate of
mutation (and thus the introduction of new variability--but he
seems to say otherwise in 1922a).



An essay published by Wright in 1931 provides what is perhaps one of
the earliest *explicit* characterizations of drift:



> 
> 
> It has seemed to me that another factor should be much more important
> in keeping the system of gene frequencies from settling into
> equilibrium. This is the effect of *random sampling* in a
> breeding population of limited size. The gene frequencies of one
> generation may be expected to differ a little from those of the
> preceding *merely by chance*. In the course of generations this
> may bring about important changes, although the farther the
> *drift* from the theoretical equilibrium, the greater will be
> the pressure toward return. (Wright 1931b: 205; emphasis added)
> 
> 
> 



The paper from which this quote is taken was meant to be a summary of
a longer paper, also published in 1931 (Wright 1986: 88). In the
longer paper (1931a), Wright specifies that the random sampling is of
*gametes*. (Gametes are cells that fuse together during
fertilization, such as an egg and a sperm). So, even though Wright
(1931a) notes that the Hagedoorns had "urged the importance of
such random fixation as a factor in evolution", and states that
Fisher (1922b) had analyzed the issue, has he changed the subject to
be random sampling of *gametes* rather than of
"parents" (i.e., organisms)? In short, no: Wright (1932
and elsewhere) makes it clear that he considers drift to encompass
both random sampling of gametes and random sampling of organisms. In
other words, he has *expanded* the phenomena that the concept
of drift is meant to cover from that discussed by Gulick, the
Hagedoorns, and Fisher. But Wright's 1932 paper also emphasized
what would become a persistent confusion between drift and inbreeding;
both inbreeding and drift are more significant in small populations,
so it can become easy to conflate them. But you can have random
sampling of parents (say, through a population split) without
inbreeding, and inbreeding without random sampling of parents. That
alone shows that drift and inbreeding are not the same. So, not all of
the expansions of drift were productive ones.



It should be noted that while Wright and Fisher had numerous
back-and-forth discussions and disagreements about each other's
claims concerning the role of drift in evolution (Provine 1986,
Skipper 2002), they did not seem to disagree about what drift
*was*. Wright (1948) considered the following to be an
"acceptable statement" of his view from Fisher and E.B.
Ford:



> 
> 
> Great evolutionary importance has been attached by Sewall Wright
> (1931, 1932, 1935, 1940) to the fact that small shifts in the
> gene-ratios of all segregating factors will occur from generation to
> generation owing to the errors of random sampling in the process by
> which the gametes available in any one generation are chosen to
> constitute the next. Such chance deviations will, of course, be
> greater the smaller the isolated populations concerned. (Fisher and
> Ford 1947)
> 
> 
> 



On the other hand, Wright's later incorporation of fluctuations
in mutation rate, fluctuations in migration, and fluctuations in
selection (see, e.g., Wright 1949) as types of drift was challenged by
Cain and Currey, who asserted that "the worker on actual
examples must classify processes according to their biological
significance" and that such lumping together would produce
confusion and prevent proper analysis of actual situations (Cain &
Currey 1963: 59). They thus urged the use of the term "sampling
drift", which Wright adopted in the fourth volume of his 1978
magnum opus, *Evolution and the Genetics of Populations*.



In short, drift's founders exhibit a diversity of views about
drift, which John Beatty helpfully describes as follows:



> 
> 
> drift is a heterogeneous category of evolutionary causes and effects,
> whose overall significance relative to other modes of evolution
> (especially evolution by natural selection) has been greatly disputed.
> (Beatty 1992: 273)
> 
> 
> 



Potential causes invoked in the discussion above include sampling of
gametes, sampling of parents, founding of new populations, splitting
of populations, each of which is intensified when populations are
small, while potential effects mentioned include fluctuations of gene
frequencies from one generation to the next, loss of variants from a
population, and fixation of a (possibly non-adapted) type in a
population. Are these causes and effects *all* drift? With that
sort of confusing heterogeneity, there is little surprise that the
concept has drawn philosophical attention. But at least we have our
starting point for philosophical discussion (see Beatty 1992 and
Plutynski 2007 for additional historical overview).


## 2. What Is Drift, and Can It Be Distinguished from Natural Selection?



Philosophers have taken a variety of approaches to characterizing
drift and distinguishing it from natural selection, including a causal
process approach that derives from the history just presented,
approaches that are mathematically derived, and other sorts of
approaches. These are discussed in turn.


### 2.1 A Historically-Derived Account of Drift: The Causal Process Account



Reflecting on the historical uses of the term "drift",
Beatty states that



> 
> 
> what most of the phenomena so designated [as drift] have in common is
> one or another biological form of random or indiscriminate sampling,
> and consequent sampling error. (Beatty 1992: 273; see also Plutynski
> et al. 2016 on the modern synthesis authors' agreement on this
> point)
> 
> 
> 



Let's begin with indiscriminate sampling. Beatty states that
parent sampling is



> 
> 
> *the process of determining which organisms of one generation will
> be parents of the next, and how many offspring each parent will
> have* (1984: 188; italics in original)
> 
> 
> 



Beatty maintains that this parent sampling can be discriminate, that
is, with regard to physical differences, or indiscriminate, that is,
without regard to physical differences (1984: 189). Discriminate
parent sampling is generally considered natural selection;
indiscriminate parent sampling is random drift. Beatty characterizes
gamete sampling similarly, as



> 
> 
> *the process of determining which of the two genetically different
> types of gametes produced by a heterozygotic parent is actually
> contributed to each of its offspring* (1984: 189; italics in
> original)
> 
> 
> 



He continues:



> 
> 
> This sort of sampling might be indiscriminate in the sense that any
> physical difference between the two types of gametes produced by a
> heterozygote might be irrelevant to whether one or the other is
> actually contributed to any particular offspring. (1984: 189)
> 
> 
> 



And again, the indiscriminate form of sampling is drift while
discriminate gamete sampling would be selection.



Several illustrations of indiscriminate sampling are common in the
literature, but some are more helpful than others. One is a
hypothetical scenario in which two genetically and phenotypically
identical twins are walking together; one is struck by lightning
whereas the other lives to reproduce. (The example seems to have its
origins in Scriven 1959 and Mills and Beatty 1979, although these
authors were making a point about fitness, not about drift). This is
an unfortunate illustration in part because it is too easy to get
caught up in the question of whether the twins are *really*
genetically and physically identical, but, more importantly, it is
misleading because in fact, drift *requires* heritable
variation, just as selection does. The lightning example is also
problematic because it makes drift seem exceptional and catastrophic,
whereas it is generally considered to be pervasive (i.e., occurring in
all populations) and not necessarily due to catastrophic or unusual
events. Others (e.g., Matthen and Ariew 2002; Walsh, Lewens, and Ariew
2002) use a series of coin tosses as an illustration of drift, but
this could be challenged because it encourages binary thinking,
instead of allowing for multiple variants with multiple outcomes, and
because it is unclear what the "population" of coin flips
amounts to.



A better illustration of drift has its origins in Theodosius
Dobzhansky's (1937) discussion of Dubinin and Romaschoff's
(1932) model, which asks us to imagine an urn filled with different
colored balls. If the balls are drawn from the urn without respect to
color, e.g., by a person drawing balls while blindfolded, then the
balls are being indiscriminately sampled (unlike discriminate
sampling, where someone deliberately tries to pick balls of a certain
color). If a large sample of balls is taken, we expect the frequencies
of colored balls in the sample drawn from the urn to be very close to
the frequencies in the urn. If only a small sample of colored balls is
drawn from the urn, then our sample may very well have different
proportions of colored balls than the urn does. Multiple samplings
taken over time, which would correspond to multiple generations, would
tend to exhibit a pattern of fluctuating frequencies (recall the quote
from Darwin above). The illustration thus models the population, its
variants with their physical differences, and gives a clear
understanding of the possible outcomes. It is also easily
extrapolatable to, e.g., colorblind predators (Hodge 1987) and other
indiscriminate sampling agents. It does, however, have some
limitations; for example, it lacks an analogue for reproduction, since
the balls do not produce offspring, multiple or otherwise.



Although the characterization of drift and selection in terms of
indiscriminate and discriminate sampling seems straightforward, with
Beatty's explication of indiscriminate sampling an important
clarification of what the Hagedoorns, Fisher, and Wright seem to have
meant by "random" sampling, Beatty (1984) raises a problem
for the conceptual distinction between natural selection and random
drift. The problem is as follows: For every population of organisms in
a given environment, with a certain distribution of types and
associated fitnesses, there is a range of possible outcomes of natural
selection, with some more likely than others. It is, of course, more
likely that the fitter organisms will have greater reproductive
success in the next generation than the less fit, but it is also
possible that they will not. (Darwin repeatedly emphasized this chance
element of natural selection). So, what do we say about the outcomes
where the less fit outreproduce the more fit? Beatty states:



> 
> 
> To the extent that those outcomes are *less* representative of
> the physical abilities of those organisms to survive and reproduce in
> the environment in question, any evolutionary change that results will
> be *more* a matter of random drift,
> 
> 
> 



concluding that it is



> 
> 
> conceptually difficult to distinguish natural selection from random
> drift, especially where *improbable results of natural
> selection* are concerned (Beatty 1984: 196; emphasis in
> original)
> 
> 
> 



As will be discussed further below, much of the twentieth century was
marked by debates among biologists about the relative importance of
drift and selection in evolution. Were those debates at least in part
the result of conceptual unclarity? Millstein (2002) argues that we
need not accept this inadvertent consequence of Beatty's
argument, and that selection can, in fact, be distinguished from
drift. In order to do this, three extensions should be made to
Beatty's account. First, similar to Hodge (1987), Millstein
suggests that a proper distinction between drift and selection relies
on causation, specifically, that drift processes are indiscriminate
sampling processes in which any heritable physical differences between
entities (organisms, gametes, etc.) are *causally*
*irrelevant* to differences in reproductive success, whereas
natural selection processes are discriminate sampling processes in
which any heritable physical differences between entities (organisms,
gametes, etc.) are *causally relevant* to differences in
reproductive success. These more precise characterizations of
"indiscriminate sampling" and "discriminate
sampling" are intended to replace the metaphorical
"sampling" talk, retaining the term "sampling"
as a useful shorthand only. Second, we should be careful to
distinguish the *process* of drift from the *outcomes*
that drift produces, and the *process* of selection from the
*outcomes* that selection produces. (Of course, the importance
of distinguishing process from outcome is not a novel insight; what is
novel here is its application to the problem of distinguishing drift
from selection. The distinction has sometimes been rendered as
"process vs. product" rather than "process vs.
outcome" in the philosophical literature, but given the
teleological and other misleading connotations of
"product", the term "outcome" is preferable
and "product" should be avoided). Third, we should
characterize drift and selection as processes rather than outcomes (as
in the first of the three points). If we do these three things, then
drift and selection are conceptually distinct and the problem Beatty
raises is dissolved; discriminate sampling processes where unlikely
outcomes obtain are still selection processes. On this view, it is
further acknowledged that it is possible for drift and selection to
produce the same outcomes, which helps explain the persistence of
biologists' debates over the relative importance of drift and
selection without making them seem trivial (see Millstein 2002 for
additional discussion of Beatty's arguments).



And what are these drift processes? They are the same physical
indiscriminate sampling processes that Gulick, the Hagedoorns, Wright,
and Fisher (and later, Kimura, who will be discussed further below)
sought to characterize: the sampling of gametes in the formation of
zygotes, the sampling of parents, the founding of new populations, and
the splitting of populations. (Note that this is not intended to be an
exhaustive list). The outcomes are likewise those mentioned by
drift's founders: fluctuations of gene frequencies from one
generation to the next, loss of variants from a population, and
fixation of a type in a population. (Again, this is not an exhaustive
list). Each of these outcomes is affected by population size, as any
indiscriminate sampling process is; smaller populations undergoing
drift tend to experience greater fluctuations in gene frequencies, a
faster loss of variants from the population, and faster fixation of
types in a population. Thus, the Beatty/Hodge/Millstein account of
drift--the Causal Process Account of Drift--is one that is
grounded in the historical development of the term and in biological
practice, with the philosopher's role being one of clarification
and elaboration. Christopher Stephens (2004), Robert Northcott (2010),
and Chris Haufe (2013) also seem to endorse the bare bones view of
drift as a sampling process, if not the Causal Process Account of
Drift in all of its details.


### 2.2 Reactions to and Varieties of Sampling-Based Accounts of Drift



However, the Causal Process Account of Drift has not gone
unchallenged. Robert Brandon (2005) argues that it "does not map
well onto the ways biologists differentiate drift from
selection" (2005: 156), that selection and drift are the same
process (i.e., sampling), and that the large majority of biological
cases are not cases of indiscriminate sampling. He maintains that
"Drift is any deviation from the expected levels of reproduction
due to sampling error" whereas "Selection is differential
reproduction that is due to (and in accord with) expected differences
in reproductive success" (2005: 168-9). These definitions
include both process *and* outcome. Millstein (2005) responds
to each of these challenges and defends her view over his. For the
purposes of this essay, it is important to note, as Millstein (2005)
acknowledges, that Brandon is certainly correct in his descriptive
claim that many biologists incorporate both process and outcome in
their definitions of drift (see Millstein, Skipper, and Dietrich
(2009) for examples). Indeed, the plurality of definitions of drift
offered by contemporary biologists--some process-oriented, some
outcome-oriented, some both, and some alternating within the same
work--gives rise to the need for philosophical analysis, even if
the result, in the end, is to accept that pluralism. The Causal
Process Account of Drift is making a prescriptive claim on the grounds
of 1) increased clarity, 2) the ability to conceptually differentiate
biologically very different phenomena, such as selection in a
fluctuating environment from fluctuating gene frequencies due to
indiscriminate sampling, which have the same outcomes, while 3)
maintaining a grounding in biological practice and (some) biological
usage.



Jessica Pfeifer (2005) weighs in on the disagreement between Millstein
and Brandon, arguing that it is reasonable to think that the source of
probabilities in natural selection are at least partly a result of
abstracting from or ignoring certain features of the environment and
that, if this view is adopted, it is not conceptually confused to
treat selection and drift as causally distinct. On Pfeifer's
view, drift is caused by the distribution of ignored factors, whereas
selection for the trait in question is caused by those features that
are not ignored.



Peter Gildenhuys (2009) argues that the term "drift" is
used to refer to causal influences over a population that have three
features: they are non-interactive, non-pervasive, and indiscriminate
(NINPICs). Thus, he endorses drift as indiscriminate sampling; the
other modifications he makes to the view seem to stem from thinking
that the Causal Process Account precludes drift and selection from
co-occurring and from thinking the view needs to account for location
(e.g., an organism being in the wrong place at the wrong time) as an
irrelevant causal factor. In any case, he acknowledges that his
account and the Causal Process Account probably agree in practice over
what sorts of things should be characterized as constituting drift.
Larry Shapiro and Elliott Sober (2007) also endorse the view that
selection and drift are distinct processes, but Sober, at least, has
backed off this view in a recent paper co-authored with Hayley
Clatterbuck and Richard Lewontin (Clatterbuck, Sober, and Lewontin
2013). Like Gildenhuys, they seem to suggest that if selection and
drift are distinct processes that they cannot co-occur, and they seem
to think that the mere introduction of finite population size
introduces drift.



To be clear, however, there can be indiscriminate sampling processes
and discriminate sampling processes occurring in the same population,
even with respect to the same trait. For example, in a study of over
900 populations, biologist Maxime Lamotte acknowledged that camouflage
gave appropriately colored *Cepaea nemoralis* land snails a
selective advantage in their respective environment while
simultaneously maintaining that foundings of new populations are
"of considerable importance because of the chance variations in
the composition of the first colonizers" (Lamotte 1959: 80); the
variations he refers to are variations in the colors of the snail
colonizers (Millstein 2009). Moreover, since the Causal Process
Account requires that variations be heritable, the non-heritable
locations of organisms are simply irrelevant for the purposes of
deciding on drift vs. selection; for example, the founders of a new
population may all hail from the geographic edge of the original
population, but they can still be an indiscriminate sample of the
whole. Finally, historically, at least (as discussed above), small
population size has always been associated with drift, but it was
never the main phenomenon to be represented. Thus, the variant
sampling accounts of drift should be evaluated in light of these
considerations.


### 2.3 Mathematical Approaches to Drift



Walsh, Lewens, and Ariew (2002) provide a good entree into
understanding a mathematical approach to drift. They begin by
acknowledging the historical uses of the term drift, identifying four:
1) a "Sewall Wright Effect", 2) a "Hagedoorn
Effect", 3) "Indiscriminate Sampling", and 4)
"The Finiteness of Natural Populations" (with some of
their characterizations not fully accurate; e.g., with the first, they
conflate Sewall Wright's Shifting Balance Model where drift
plays a role with drift itself). They suggest that these phenomena are
"disparate" although they acknowledge, citing Beatty
(1984), that the first three can be understood in terms of sampling.
But the fourth form, they assert, cannot. They describe the fourth
phenomenon as follows:



> 
> 
> The Hardy-Weinberg Law says that in infinite populations (of diploid
> organisms) there is no change in gene frequencies when there is no
> variation in gene fitnesses. But natural populations are finite in
> size; often they are small. In finite populations there will always be
> some non-negligible chance that trait frequencies will diverge from
> expectation. (Walsh, Lewens, and Ariew 2002: 456)
> 
> 
> 



With respect to this understanding of drift as the Hardy-Weinberg Law
conjoined with a finite population, Walsh, Lewens, and Ariew maintain
that "there is no larger population literally being
sampled" (2002: 459). Instead:



> 
> 
> ...in these cases what happens is that the distribution of
> fitnesses in the population yields a prediction concerning the way in
> which a population will change. Drift is manifested as a difference
> from the outcome predicted by the fitnesses in the population. The law
> of large numbers tells us that the likelihood of significant
> divergence from these predictions is an inverse function of the size
> of the population. The small size of a population increases the
> chances of error. (Walsh, Lewens, and Ariew 2002: 459)
> 
> 
> 



Walsh, Lewens, and Ariew then state that this is the common feature
that the four types of drift they outline all share; thus drift, on
their view, is when a series of births, survivals, deaths, and
reproductions diverges from the outcome predicted by differences in
fitness. Note that, using the terminology introduced in the previous
section, this is a purely outcome-oriented
("outcome-only") definition of drift. Whatever type of
process (if any) might have produced the outcome plays no role in the
definition. Matthen (2010) defends a similar characterization of
drift: "Departures from expected values are what population
geneticists call 'drift'" (Matthen 2010: 3).



However, notice that the fourth drift "phenomenon" that
Walsh, Lewens, and Ariew identify isn't really a phenomenon.
Rather, it refers to a model from population genetics, the
Hardy-Weinberg model, and predictions based on that model. It is true
that as a consequence of the model, there would be no deviation from
fitness expectations with an idealized infinite population (if we make
some philosophical assumptions about what happens in infinity; Sober
(1984) raises questions about these assumptions), but that there would
likely be such deviations with a finite population. But this is a
purely mathematical approach. The purely mathematical approach
doesn't ask what phenomena the model is supposed to be modeling
and why it is that finite populations are of interest. There is also
no explanation of why a Hardy-Weinberg model with an assumption of
finite population size should count as drift; perhaps this is because
of a philosophical tradition of referring to this as drift (e.g., some
parts of Sober 1984 read that way), or perhaps it is because of the
previously-noted longstanding association between drift and small
population sizes. In contrast, on the Causal Process Account of Drift,
drift would occur even in infinite populations as long as there is
indiscriminate sampling; drift-like outcomes (deviation from fitness
expectations) are not required.



Millstein, Skipper, and Dietrich (2009) challenge the outcome-only
approach to defining drift and the purely mathematical approach that
it is based on. Thus, there seem to be some meta-disagreements between
the process-only and outcome-only approaches to drift; should our
definitions of drift look to the history of biology or should they
look to mathematics? Should we glean our understandings of drift from
the phenomena that biologists have sought to understand (the phenomena
that they developed models for) or from the models alone? If from the
models alone, are we inadvertently drawing on the measure or
operationalization of drift rather than drift itself (Plutynski 2007)?
Differing answers to these questions seem to be at the heart of the
differing definitions of drift.



If one doesn't interpret the model purely mathematically, but
instead considers what phenomenon the Hardy-Weinberg Principle
with-finite-populations is seeking to model, then there is indeed a
larger population being sampled. The equation models the changes from
one generation to the next; the original generation is the population
that is being sampled, and the next generation is the
"sample". That sample may or may not be representative of
the original population, e.g., a heterozygote *Aa* of the
original generation may or may not have offspring in the proportions
25% *AA*, 50% *Aa*, and 25% *aa*.



The mathematical-oriented outcome-only definition of drift is often
associated with the so-called "statisticalist" approach to
evolutionary theory, but since it is simply a definition of drift and
not a metaphysical thesis it need not be. For example, a
non-statisticalist could consistently hold that natural selection is
causal (and thus, evolution would not be purely statistical, as it is
on the statisticalist interpretation), but that drift occurs when and
only when there is a deviation of the actual outcome from fitness
expectation. Indeed, Frederic Bouchard and Alexander
Rosenberg (2004) seem to hold such a view. The intersection between
issues of drift and the debates over statisticalism will be discussed
further below.


### 2.4 Other Accounts of Drift



Other accounts of drift are not so easily classified. For example,
Timothy Shanahan (1992) argues that conceptually, random drift and
natural selection are the ends of a continuum. However, to reach this
conclusion, Shanahan must reject heritability as a necessary condition
for natural selection. As evolutionary biologist John Endler has
argued, this has the effect of trivializing natural selection to the
claim that "there are differences among different
phenotypes" (Endler 1986: 13).



Grant Ramsey (2013) develops a concept he calls
"driftability", which locates drift in individual
organisms rather than in a population. Ramsey points out that the
possible lives that an organism can lead is a large and heterogeneous
set; thus, the actual life that any particular organism leads will
probably not be a representative sample (which he seems to equate to
an average) of the set. Differences within the set of will lead to
different evolutionary outcomes; this intra-organismic heterogeneity
within the set of possible lives of an organism is driftability.



Peter Godfrey-Smith (2009) characterizes drift as changes where two
parameters, the smoothness of fitness landscapes and dependence of
reproductive character on fitness differences, are low. (However, when
he needs to explicate why drift has special importance in small
populations and why it can be mathematically described in particular
ways, he appeals to indiscriminate sampling. Perhaps, then,
indiscriminate sampling is at the core of Godfrey-Smith's view
of drift).



Again, these accounts, which seem to deviate significantly from
biological usage and practice, raise meta-philosophical issues about
how we ought to go about characterizing a scientific concept like
"drift". How far can the definition of a term deviate from
scientific usage and practice and still be considered to be a
definition of the same thing?



One could also be a pluralist about drift, arguing that there is
reason to accept more than one definition of drift, although it is
unclear if anyone has actually endorsed this position. Marshall Abrams
seems to come the closest, stating:



> 
> 
> If random drift is anything, it is not one thing...The term
> applies to many effects on populations or organisms which are said to
> be due to "chance," and to factors which are thought to
> help to produce such effects. (2007: 673)
> 
> 
> 


## 3. Intersection of Genetic Drift with Statisticalist-Causalist Debates



Recent debates about random drift are often entangled with debates
over the purported purely statistical (non-causal) nature of
evolutionary biology, but the issues are separable. There are issues
concerning random drift that do not involve questions of
statisticalism (as this article seeks to document), and there are
issues concerning statisticalism that do not involve random drift
(e.g., much of the literature focuses on natural selection rather than
random drift). The statisticalist claim, generally traced to a pair of
papers by Walsh, Lewens, and Ariew (2002) and Matthen and Ariew
(2002), is essentially that evolution is a population-level
phenomenon, and that although there are causes at the level of
individual organisms (births, deaths, etc.), there are no causes at
the population level, only a statistical summary of the individual
events. Note that it is widely acknowledged that the models in
evolutionary theory are statistical ones, so the distinctive
statisticalist claim is that evolutionary biology is *purely*
statistical. There are at least three alternatives to the
statisticalist claim; one challenges the claim that evolutionary
biology is a population-level phenomenon, arguing that it is
constituted by causes at the level of individual organisms (e.g.,
Bouchard and Rosenberg 2004), a second defends the view that there are
population-level causes (e.g., Millstein 2006; Shapiro and Sober
2007), while a third argues for causes at both levels (Pence
2017).



It was already noted above (see
 section 2.3)
 that the outcome-only definition of drift is often adopted by
statisticalists, but not exclusively so; it can also be endorsed by a
causalist who, e.g., believes that natural selection is a causal
process but that drift is simply deviation from selective
expectations. Perhaps surprisingly, it would also be possible for
someone to endorse a version of the Causal Process Account of Drift
and yet still accept the basic statisticalist premise--if one
thought that drift should be understood in terms of indiscriminate
sampling, and also thought that indiscriminate sampling should be
understood in terms of causes at the level of individual organisms,
then the evolutionary changes wrought by drift would just be be the
statistical summation of individual level causes. In short, it would
be a mistake to infer one's position on the statisticalist
debate from one's definition of drift, although such slippage is
common and the issues are in truth often entangled.



What, then, are the statisticalist issues that random drift is
entangled with? The concerns raised by Walsh, Lewens, and Ariew (2002)
and Matthen and Ariew (2002) have their origins in claims made by
Sober (1984) in his classic *The Nature of Selection*. Sober
characterizes evolutionary theory as a theory of forces, with its
zero-force state described by the Hardy-Weinberg equation of
population genetics (see the
 population genetics entry
 for an explanation of the equation); in such a state, there is no
selection, no mutation, no migration, no meiotic drive, random mating,
and infinite population size. Thus, the Hardy-Weinberg equation is an
idealized model that never obtains in the real world. It is a bit
difficult to see where drift fits into the equation, which is no doubt
the source of much of the confusion over how to define drift. In his
1984 book, Sober alternatively characterizes drift in terms of random
sampling (the process, which occurs, Sober explains, during gamete
formation and the founding of new populations) and sampling error (the
outcome, i.e., the deviation from fitness expectations). From the
point of view of process, at least some types of sampling could be
understood to be part of the Mendelian process. The Mendelian process
includes the "process wherein organism produce gametes and
gametes produce organisms" (Sober 1984: 35), which Sober says is
not treated as a force, but rather as the background against which
evolutionary forces are described. But Sober does not take this route.
Instead, Sober contrasts drift as sampling error (again, the
outcome--presumably introduced when one relaxes Hardy-Weinberg
assumptions to allow for finite populations) with selection, mutation,
and migration; all are forces, Sober asserts, but drift is a different
sort of force. It is not "deterministic" and it does not
have a definite direction (although it does have a magnitude,
determined by the population size). That is, given trait frequencies
and fitness values, Sober suggests, selection predicts a specific
outcome for the next generation in a specific direction (and is in
this sense "deterministic"), whereas drift could yield an
increase any of the types present in the population (and is in this
sense directionless). Moreover, Sober states, you cannot say *how
much* drift has contributed a change relative to the change
introduced by selection; to do so would be as impossible as trying to
say, when flipping a fair coin ten times and obtaining six heads, how
much of the result was due to the fairness of the coin and how much
was due to the fact that it was tossed ten times. He thus concludes
that "if drift is an evolutionary force, it is a force of a
different color" (1984: 117); he calls it a force, he says,
mainly to indicate its causal role.



These metaphysical claims about drift (and selection and other
evolutionary processes--but it is just drift that interests us
here) set the stage for the statisticalists' challenge. Matthen
and Ariew (2002) challenge the claim that there is a defensible sense
in which drift is a force. Aside from the fact that it does not have a
predictable or constant direction (as Sober readily acknowledges),
they point to a case of two similar populations subject to the same
selective pressures, one in which the trait \(T\) becomes fixed and
the other in which the alternative trait \(T'\) becomes
fixed. What explains the outcome in the two cases? Exactly the same
thing, Matthen and Ariew assert, just as exactly the same coin setup
explains two heads and four heads in two series of ten coin tosses.
Thus, they seem to suggest, there is no additional cause or force,
"drift". Walsh, Lewens, and Ariew (2002) similarly attack
Sober's claim that drift is a force; following Rosenberg (1994),
they assert that "the events that are labelled
'drift' events, like lightning strikes, etc. are no
different in kind from selection events" (Walsh, Lewens, and
Ariew 2002: 457)--and thus, drift is not a distinct sort of
force. Moreover, they argue, drift is best interpreted statistically
as statistical error (see argument in
 section 2.3),
 and so again, it is not a force.



To be clear, there is a historical component to the
statisticalists' claims; on their view, Darwin's
evolutionary theory was causal, but with the introduction of
population genetics, evolution became purely statistical. (It is
sometimes unclear whether the statisticalists are making claims about
models/theories or whether they are making ontological claims, or
whether they think that the latter can be inferred from the former).
Hodge (2016; see also Plutynski et al. 2016) challenges this
historical claim by arguing that in fact Darwin--although he
liked to think that his epistemological and nomological ideals were in
descent from Newton's--never understood natural selection
to be a lawful force along with gravitation or inertia. Hodge further
argues that biologists today compare and contrast natural selection
with artificial selection and with drift in ways directly descending
from Darwin's view of natural selection as a causal process.



A number of other philosophers have sought to challenge the
statisticalists' claim that drift is not a force. For example,
Stephens (2004) defends the claim that drift is both a force and a
cause. He asserts that if we understand drift properly as a process of
indiscriminate sampling (instead of as an outcome, as the
statisticalists do), we can see that it is a force, but that in a
population of a given size it always has the *same* force,
regardless of whether there is a large or a small deviation from
expectation. (It may be that Sober's inadvertent vagueness in
his 1984 book on the process/outcome question contributed to the
confusion, since the statisticalists were responding to Sober). He
clarifies that, "because drift is a probabilistic cause, the
*same* causal force can have two *different*
outcomes" (Stephens 2004: 557; emphasis in original). Stephens
further defends the claim that drift can be understood as a force or a
cause by arguing (*contra* Matthen and Ariew) that drift does
have a direction, namely, eliminating heterozygosity; that it can
"make a difference" by affecting the probability of
evolutionary change (more in small populations, less in large); and
that we can cogently speak of the relative importance of drift in an
ensemble of populations or in a population, albeit not at the level of
individuals (see Walsh 2007 for a response to Stephens 2004, 2010 and
Gildenhuys 2014 for a response to his response).



Brandon (2006), however, argues that "eliminating
heterozygosity" is not sufficient to show that drift is
directional, given that (as Stephens would readily acknowledge) if
there were two alleles at a locus, beginning at equal frequencies, we
could not predict which of the two alleles would go to fixation, only
that one of them would; Brandon likens this to saying that "a
20-Newton force is acting on object *A*", (2006: 325),
which, he seems to imply, is not a directional claim. Moreover, he
argues, drift is not a separate process from selection. Thus, drift,
on Brandon's view, is not a force (but it is a law; more on that
below). Joshua Filler (2009) responds to Brandon by defending a more
elaborated account of what a force is (in part drawing on Bigelow et
al. 1988); on that elaborated account, drift's direction can be
seen as less specific than selection, mutation, and migration, but it
gives some directional information. Thus, Filler argues, it can be
seen as less "forcelike" than selection, mutation, and
migration, but it is still a force. Charles Pence (2017), however,
worries that Filler's modifications to our understanding of
"force" may be *ad hoc*, so he offers an
alternative defense of the claim that drift is a force. First, Pence
argues, we already countenance forces that have stochastically
specified directions, such as Brownian motion, and drift is analogous.
Second, we can create an evolutionary thought experiment where drift
is absent, showing that it is not constitutive of all evolving
systems; this is intended to respond to Brandon's claim that
drift is not separable. Importantly, however, Pence points out that
there are essential questions that the entire debate has yet to
address: "what exactly the use of 'forces' is to do
for us, and when explanations utilizing a force metaphor are useful or
perspicuous" (Pence 2017: 1975).



On the other hand, Kenneth Reisman and Patrick Forber (2005) separate
the question of whether drift is a force from the question of whether
drift is a cause, arguing only for the latter while not taking a stand
on the former. In a related paper, they rely on Woodward's
(2003) manipulability account of causation and a 1957 study of drift
by Dobzhansky and Pavlovsky to argue that



> 
> 
> decreasing the number of founding members in replicate populations
> produces an increase in the variability of evolutionary outcomes
> across those replicate populations. (Forber and Reisman 2007: 617)
> 
> 
> 



In other words, they argue that the conditions of the study can be
seen to satisfy the conditions of the manipulability account, showing
that drift ought to be understood as a (population-level) cause.
Shapiro and Sober (2007) state that they endorse Reisman and
Forber's arguments as well as the view of drift as a process.
However, it's unclear whether Shapiro and Sober (or Reisman and
Forber) actually do endorse the view of drift as a process. That is,
it's unclear why population size as a causal factor should count
as a process.



This is because it's a bit unclear if drift is actually what is
being manipulated in Dobzhansky and Pavlovsky's (1957)
experiments, or if it is just population size--and population
size does not seem to be a process. Perhaps Reisman and Forber have
simply shown that population size is a causal factor of evolutionary
change in populations undergoing drift. They also seem to be taking
Woodward's account very literally, in that they seem to think
that the "variable" that has to be manipulated must be a
variable in a mathematical model; otherwise, one could (at least in
principle) manipulate the sampling process by manipulating the
population rather than simply the population size; Clatterbuck's
(2015) account, discussed in
 section 5,
 gives an example of this. (Population size is a variable in
mathematical models of drift, whereas sampling, as discussed above, is
implicit). One could also conceivably manipulate the environment so
that sampling was discriminate rather than indiscriminate or to change
the nature of the indiscriminate sampling.



Pierrick Bourrat (2018) offers an alternative response to Reisman and
Forber; he implies that Reisman and Forber (2005) have overlooked
Woodward's criterion of *invariance* when they invoke the
manipulability account in support of drift as a population-level
cause. Invariance in an intervention, Bourrat states,
"measures the extent to which a relationship between two
variables satisfying the manipulation condition remains stable or
unchanged as various other changes are made in the background of this
relationship" (2018: 162), and, again invoking Woodward, he
asserts that causal relationships that are more invariant provide
better explanations. But, Bourrat argues, causal explanations in terms
of individual-level variables are more invariant under intervention
than causal explanations in terms of population-level variables, and
thus should be preferred for that reason. In other words, similar to
Bouchard and Rosenberg (2004) who are briefly mentioned above, Bourrat
defends a causalist position, but at the level of individuals rather
than at the level of populations. However, Bourrat does concede that
it is reasonable to conceive of drift and natural selection as
population-level causes when they depend on indeterministic events, as
well as for some cases of frequency-dependent selection. Moreover,
Bourrat does not discuss Clatterbuck's (2015) alternative and
arguably superior understanding of the relevant manipulation for
drift; had he done so, it is not clear that his claim for the
superiority of individual-level causal explanations with respect to
drift would follow. Again, though, these are disagreements within the
causalist camp.



Other challenges to the statisticalists' claims about drift as a
cause neither endorse the view of drift as a force nor drift as a
distinct process. For example, Brandon and Ramsey (2007) see drift and
selection as "copossible" outcomes of the same process.
But because there *is* a causal process--albeit only one
rather than two--the statisticalists' claims are not
upheld. Abrams (2007) likewise seems loathe to adopt
"force" talk about drift, at least in a strong realist
sense. He argues that "both selection and drift are aspects of a
probability distribution over future frequencies of genotypes or
phenotypes in a population" (2007: 667). Yet selection and drift
can be distinguished:



> 
> 
> Selection is the aspect of the distribution controlled by differences
> in fitness, while drift is the aspect of such a distribution
> controlled by population size (apart any from effects of population
> size on fitness). (2007: 667)
> 
> 
> 



This makes it sound as though Abrams is adopting a view of drift akin
to that of Reisman and Forber, with its focus on population size, and
indeed Abrams does elaborate on the causal role of population size,
but (as noted above) his views on drift are more accurately pluralist
ones.



More generally, Pence (2017) suggests one way of categorizing the
different causalist approaches (although not all of these have
explicitly addressed drift):



> 
> 
> At the very least, we need to distinguish between (1) the force
> interpretation, as discussed here; (2) the causal process approach
> (elaborated most notably by Millstein 2002, 2006, 2013); (3) the
> causal mechanism approach, first deployed for natural selection by
> Barros (2008) and building on the work of Machamer et al. (2000); (4)
> the manipulationist approach, discussed by Reisman and Forber (2005),
> Forber and Reisman (2007), and Shapiro and Sober (2007), building on
> the work of Woodward and Hitchcock (2003); and (5) the counterfactual
> approach, deployed for natural selection by Glennan (2009) and Huneman
> (2012) and utilizing a notion of counterfactual causal dependence or
> "relevance". (Pence 2017: 1983)
> 
> 
> 


## 4. Detecting Drift Empirically



Throughout the 20th and 21st centuries,
biologists have struggled to detect drift empirically. In particular,
they have experienced challenges in differentiating cases of drift
from cases of selection. The Causal Process Account of Drift in
particular can help to make sense of why this is so, as will be
discussed below. Drift and selection may be different sorts of causal
processes (indiscriminate and discriminate sampling, respectively),
but they can produce similar outcomes. Biologists have thus struggled
to identify distinctive outcomes for drift and selection, only to find
underdetermination re-emerge after biologists modified or added to
their assumptions about the relevant processes (for a clear
characterization of this, see Dietrich and Skipper 2007). Relatedly,
biologists have also disagreed over the relative prevalence of drift
and selection (Beatty 1995, 1997); as noted above, these disagreements
were there almost from the outset with Fisher's response to the
Hagedoorns.


### 4.1 Classic Studies



The disagreements over the prevalence of drift and selection began
almost immediately after Wright and Fisher incorporated drift into
their evolutionary models (see Provine 1986 for an extended discussion
of their disagreements, to which this discussion is very much
indebted). Wright (1931a, 1932), drawing on his experience with animal
breeding, developed the Shifting Balance Theory (SBT), which consisted
of three phases; these have been understood either as empirical claims
about actual conditions (Provine 1986) or descriptions of the ideal
conditions for evolution (Skipper 2002). Skipper provides a clear
description of the SBT as Wright would eventually formulate it (see
Hodge 2011 for discussion of early formulations):



> 
> 
> In the first phase, random genetic drift causes gene frequencies to
> change and pull subpopulations semi-isolated within the global
> population into adaptive valleys because random fluctuations in gene
> frequencies are almost always maladaptive. In phase two, mass
> selection will then act within subpopulations and increase their
> fitness, dragging them from adaptive valleys to adaptive peaks. In the
> third phase, selection between subpopulations, which Wright called
> interdemic selection, driven by differential dispersion (migration of
> organisms from more fit subpopulations to less fit subpopulations)
> would then enable the global population to be raised to its optimal
> peak. (Skipper 2002: 345)
> 
> 
> 



Drift, then, on Wright's view, plays an essential role in the
evolutionary process. Fisher, by contrast, thought that mass selection
on large populations was the predominant and most effective mode of
evolution, leaving very little role for drift given the large
population sizes. (This disagreement about the relative role of drift
in evolution is one of several things that Wright and Fisher disagreed
about; e.g., as is clear from the above, they also disagreed about
population structure and effective population size. See Skipper 2002,
2009 and Plutynski 2005 for analyses of contemporary biologists who
continue to argue the Wright-Fisher debate).



Another, related issue arose concerning the character of the traits
that were said to be subject to random drift. Wright's early
writings, in particular, emphasized the nonadaptive character of the
traits undergoing drift and produced by drift (as can be see in
Skipper's characterization of Wright's SBT above). But a
number of potential confusions arise here (Provine 1986; Millstein
2009): First, "nonadaptive" does not necessary mean
"maladaptive"; it can also mean "neutral".
Second, "nonadaptive" can refer either to the lack of
adaptive differences between organisms or species, or it can refer to
the lack of adaptation to the environment (but authors are not always
clear about which meaning is intended). So, one's views on the
prevalence of drift can be--and historically often have
been--tied to one's beliefs about the prevalence of
adaptive traits (in either sense) in populations. Strictly speaking,
however, there is no necessary connection between nonadaptive traits
and drift; there can be indiscriminate sampling on organisms that are
adapted to their environment and which differ in fitness, and the
outcomes of that indiscriminate sampling can pull the population in an
adaptive direction *or* a nonadaptive one. Thus, the proper
contrast between selection and drift does not map onto
"adaptive" and "nonadaptive", but rather to
"adaptive" and "possibly nonadaptive" (but
also "possibly adaptive").



These theoretical considerations were soon followed by field
examinations of drift (there were also laboratory studies, but these
were less contentious). Two sets of studies of natural populations are
particularly notable. One set, referred to in the introduction to this
essay, is composed of the studies of the polymorphic land snail,
*Cepaea nemoralis*; these studies, and debates over the
prevalence of drift, began in the 1930s and became quite heated in
"The Great Snail Debate" of the 1950s and 1960s (Millstein
2008, 2009 gives more extensive discussion, from which the following
is drawn; the moniker "The Great Snail Debate" is due to
Provine 1986). Early researchers, most famously Arthur J. Cain and
Philip M. Sheppard (1950, 1954), sought to demonstrate the adaptedness
of the color and banding morphs of the snails as well as the sizes of
the populations in which they lived. But these were challenging to
determine; adaptedness was primarily studied indirectly, by seeking
correlations between variants and their backgrounds (presuming
camouflage and selection by predator), and population sizes varied
considerably. And any correlations found were statistical ones, with
lots of "noise". This left the door open for drift; Maxime
Lamotte (1959) argued that by examining the populations as a whole,
one found greater variation among the small populations than among the
large. This was a distinctive signature for drift, but such outcomes
are hard to find and require a very special set of circumstances to
obtain (large numbers of populations of varying sizes that are easy to
count). However, Lamotte's study is not the only classic
evolutionary study to exploit this unique drift outcome;
Cavalli-Sforza's studies of blood groups in humans did so as
well (Richardson 2006). Notably, this was not drift as an
*alternative* to selection (Cain and Sheppard had suggested
that selection precluded much of a role for drift), but rather, an
argument for a substantial role for drift *in addition to* a
substantial role for selection.



Another important set of studies is of the polymorphic Scarlet Tiger
Moth, *Panaxia dominula* (see Provine 1986 for extended
discussion, to which the following is indebted). Fisher and Ford
deliberately chose *P. dominula* because of its small
population sizes, figuring that if they could make the case for
selection against drift in its worst case, they could make a decisive
case against Wright, who they saw as advocating a form of nonadaptive
evolution. But rather than trying to make a case *for*
selection, as Cain and Sheppard did, Fisher and Ford (1947) tried to
make a case *against* drift by arguing that the fluctuations of
gene frequencies across generations were too large to be accounted for
by drift and that the size of the fluctuations did not differ between
the small and the large populations, as you would expect if they were
undergoing drift. Therefore, they concluded, the populations were
undergoing selection. Wright's (1948) reply challenged both the
logic of this conclusion (disproving drift does not prove selection)
as well as their characterization of his views, but more
significantly, he pointed out that Fisher and Ford had not included
data on population sizes for the years in which the gene frequency
fluctuations were statistically significant, so, in fact, it was
possible that the populations had been undergone constrictions in
those years, in which case drift *would* have been able to
produce the observed fluctuations. He also pointed out that
fluctuations in selection or migration (which he very problematically
suggested could be part of an expanded understanding of drift) could
have produced the same outcomes.



In short, the *P. dominula* studies turned on a slightly
different but related proposed unique outcome for drift, that of
fluctuations over time rather than variation at a time as for *C.
nemoralis*, in both cases comparing small populations to large (as
well as considering the capability of populations to produce large
fluctuations), but with *P. dominula*, drawing definitive
conclusions ran into difficulty from lack of data concerning the key
variable of population size. There is also the recognition that
fluctuating selection can produce the same outcome of fluctuations of
gene frequencies across generations as drift can, making it difficult
to resolve the empirical case. Finally, note that biologists have
continued to study both *C. nemoralis* and *P.
dominula*, with the result that additional processes have been
identified that further complicate the empirical analyses (Millstein
2008; Skipper 2009).


### 4.2 Studies of Drift and Molecular Evolution



As Dietrich (1994) has documented, early work in molecular evolution
was focused almost exclusively on selection, something that changed
with the advent of the neutral theory of molecular evolution and the
work of Motoo Kimura, Jack King, and Thomas Jukes. Dietrich
writes:



> 
> 
> The basis of its challenge was Kimura's proposal that most
> changes detected at the molecular level were not acted upon by natural
> selection; they were neutral, and the mechanism of their change was
> random genetic drift. (1994: 22)
> 
> 
> 



To be clear, however, both selection and drift play an essential role
in the neutral theory; on Kimura's view, selection will quickly
eliminate the large number of deleterious mutants and fix the small
number of advantageous ones, leaving the remaining mutant alleles as
neutral, whereupon they undergo a process of drift (Dietrich 2006).
Drift would eventually cause the neutral (and nearly neutral) mutants
to either go to fixation or be lost (although they would be
polymorphic in the meantime), so that observed molecular differences
would be



> 
> 
> the outcomes of a random process of mutation, which Kimura understood
> as produced largely from DNA replication error, processes of
> directional selection, and processes of random drift produced by
> gamete sampling. (Dietrich 2006: 670)
> 
> 
> 



Many of the debates about the neutral theory contrasted this approach
(the "neutralist" approach) to evolution with a more
selectionist (or sometimes, "panselectionist") approach,
causing many to refer to a "neutralist-selectionist
controversy".



The advocates of the neutral theory initially proposed it as an
unrealistic simple model only to have subsequent data on the
prevalence of neutral alleles convince them of its realism. That led
to more explicit testing of the neutral theory and debates over the
molecular clock (Dietrich 2006). To focus on the first of these,
Dietrich (2006) suggests that although the neutral theory promised to
generate numerous quantitative testable predictions--and
did--testing it has in fact proved difficult. Is this because of
the difficulty in identifying outcomes that are unique to drift?
Perhaps so. For example, the neutral theory predicted a certain
measure of heterozygosity, but when Francisco Ayala and colleagues
failed to observe that predicted outcome in a study of natural
populations of *Drosophila*, Jack King responded by saying that
many of the assumptions made by the model could be the source of the
discrepancy. In other words, as has been well-discussed in the
philosophy of science, there are no "crucial experiments"
between two theories because theories are always tested together with
their assumptions, any one of which can be given up rather than
rejecting the theory. Debates over the so-called "molecular
clock" can also be understood in terms of the search for
distinctive outcomes for drift. At first, it was thought that only
drift could make sense of an apparent constant rate of
evolution--that only drift would produce such an
outcome--yet this time it is the selectionists who modified their
assumptions such that their models would also predict a molecular
clock outcome (Dietrich and Skipper 2007).



Subsequently, Tomoko Ohta began to argue for a more significant role
for weakly selected mutants (Ohta 1973). Essentially, Ohta's
definition of "nearly neutral" includes mutants that are
less neutral than Kimura's "nearly neutral" mutants,
and larger amounts of them as well (Dietrich and Millstein 2008).
Later refinements included both slightly deleterious and slightly
advantageous mutants. This changes the processes that one would expect
to be acting. With the (strictly) neutral theory, only drift would act
on the neutral mutants. With the nearly neutral theory, the nearly
neutral mutations (whether advantageous or deleterious) would subject
to very weak selection (discriminate sampling) *and* to drift
in the form of indiscriminate gamete sampling (Dietrich and Millstein
2008). Because the selection is weak, it would be swamped by the
effects of drift, but both processes would still be occurring. Ohta
believed that the nearly neutral theory could better account for the
results found by Ayala and his colleagues (with its large number of
relatively rare alleles), and also, that it could better explain some
features of the molecular clock (Dietrich and Millstein 2008).
However, it has proven much more difficult to find unique outcomes for
the nearly neutral theory than the neutral theory. This makes the
nearly neutral theory more difficult to test for and less useful as a
null hypothesis as compared to the neutral theory, even as it might
account for the available data better.


### 4.3 Recent Empirical Issues Concerning Drift



Hayley Clatterbuck, Elliott Sober, and Richard Lewontin (2013) argue
that it doesn't make sense to talk of drift
"dominating" selection or being "stronger
than" selection. (Among many such claims, this would challenge
Dietrich and Millstein's (2008) claim, discussed in the previous
section, that the best way to understand the nearly neutral theory is
as weak selection dominated by drift). Clatterbuck, Sober, and
Lewontin take selection and drift to be a population-level process or
processes (they don't take a stand on whether there is a one
process or two, but they are clearly "causalists" rather
than "statisticalists"), but they raise concerns for the
way that biologists have understood the value \(Ns\), which is the
effective size of the population multiplied by the selection
coefficient. After some initial controversies over how to interpret
this value, most biologists eventually came to the view that



> 
> 
> selection "dominates" drift when \(Ns\) is much greater
> than some specified number and that drift "dominates"
> selection when \(Ns\) is much less than that number,
> 
> 
> 



with proposed numbers including 1/4, 1/2, and 1; in between values are
thought to be where the two causes are more or less equal
(Clatterbuck, Sober, and Lewontin 2013). Clatterbuck, Sober, and
Lewontin point out that on the standard picture, the values of
*N* and *s* do not predict one gene frequency outcome;
rather, they predict a probability distribution of possible gene
frequency outcomes. But, they argue, you can change this distribution
by changing *N* or by changing *s*, with values
"chosen so that the first change makes more of a difference, or
less, or the same, as you please"; thus, it is "arbitrary
to focus on comparisons that give drift the upper hand, or that do the
same for selection" (Clatterbuck, Sober, and Lewontin 2013:
538). Here, the suggestion seems to be that *N* represents the
drift cause and that *s* represents the selection
cause--although it's not clear why drift-as-cause should be
equated with population-size-as-a-cause--with the conclusion that
the causes are not separable. To say that they are separable would,
Clatterbuck, Sober, and Lewontin say, would be akin to asking whether
the result of four heads of a fair coin tossed ten times is due to the
fairness of the coin or the number of tosses. They also suggest that
it is impossible to have a population that is not undergoing drift,
since even in an infinite population there could be deviation from
selective expectations (again, making it hard to separate the causes).
Finally, they argue that it doesn't make sense to say that with
identical setups that producing differing outcomes, that selection
dominates in some (when the favored allele increases in frequency) and
drift in others (when the favored allele decreases in frequency).



Robert Brandon and Lenore Fleming (2014) point out, however, that
Clatterbuck, Sober, and Lewontin's analysis of a seemingly
empirical question is not based on an empirical discovery, but rather,
a conceptual analysis, and that as a conceptual analysis, it is not
fully consistent; that is, they do not consistently treat drift as a
causal process, but sometimes treat it as an outcome (as in the last
point described in the previous paragraph). Brandon and Fleming cite
several recent empirical studies where biologists seek to provide
evidence that drift dominates selection, not relying on the simple
\(Ns\) to come to that conclusion, and point out that there are other
methods for testing the relative strengths of drift and selection,
such as the McDonald-Kreitman (MK) test. In Brandon and
Fleming's view, "drift is not a process. It is, however, a
predictable result of a process, namely probabilistic sampling"
(2014: 581). It is somewhat unclear, however, how on their view the
drift outcome (which outcome?) is "swamping" or
"overriding" the selective outcome (presumably by the
outcome being the cause of some further, as yet unidentified,
outcome). Further elaboration on this point would be useful.



It has also been suggested, most notably by John Gillespie (2000a,b,
2001), that many purported instances of genetic drift are in fact due
to "genetic draft." Genetic draft is a process of linked
selection (a hitchhiking process) where it is a matter of chance which
of two neutral alleles (in a two-locus model) happens to be linked to
a site that undergoes an advantageous mutation, and where the timing
of these mutations, followed by a rapid selective "sweep"
to fixation, is random. As Skipper (2006) discusses, one of the
interesting properties of genetic draft is that it can produce an
outcome similar to that which one would expect from genetic drift in
small populations, namely, a reduction in genetic variation (thus the
similar name). Gillespie argues that draft is less sensitive to
population size than drift, which leads him to claim that draft is a
more significant cause of evolution than drift (Skipper 2006). Thus,
draft introduces yet another relative significance debate (Beatty
1995, 1997) to add to the others discussed in this article: drift vs.
selection, Wright's SBT vs. Fisher's mass selection,
neutralist vs. nearly neutralist vs. selectionist molecular evolution.
However, it is worth noting that while draft can produce one of the
same outcomes that drift can (reduction in heterozygosity), it would
not give rise to fluctuating gene frequencies from one generation to
the next. So, not all drifty outcomes can be accounted for by
draft.



William Provine (2014) has taken the reduction of drift's role a
step further, calling random genetic drift a "fallacy" and
arguing that no such phenomenon exists in nature, period. Provine
notes that for both Fisher and Wright (and even Kimura), drift was
deeply intertwined with inbreeding, to the extent that one was
sometimes confused for the other, which seems warranted--or, at
least, that the relationship between the two was never fully clarified
(see, e.g., Wright 1931a). Provine defines random drift as
"fortuitous extinction of genes" at a genic locus on a
chromosome. According to Provine,



> 
> 
> Wright believed that random sampling of gametes in Mendelism produced
> "random genetic drift" at every locus [on every
> chromosome] in small populations, and also that inbreeding led to
> rampant "random genetic drift" in small populations
> (Provine 2014: 54).
> 
> 
> 



Here, Provine treats drift as an outcome, and as that outcome seems
physically unlikely or even impossible due to gene linkage, there is,
on his view, no drift. Wright did assert that



> 
> 
> [j]ust because the direction of drift is accidental, the result is a
> kaleidoscopic shifting of the average characters of the population
> through predominant types which practically are never repeated,
> (1931b: 207; see also Wright 1930: 354)
> 
> 
> 



but that makes drift sound like a cause, not an outcome, and it does
not explicitly state that the "shifting" occurs at every
locus on every chromosome. But even if he did, Wright could certainly
have been mistaken about the effects of drift without being mistaken
about the phenomenon itself; notably, Provine does not deny the
existence of the random (i.e., indiscriminate) sampling of gametes,
although he does object to the seeming reification of the term
"gene pool" and the neglect of the relevance of
chromosomes, points that are well-taken.


## 5. Drift as Models, Drift as a Law



As noted above, the phenomenon of drift is represented in mathematical
models of population genetics. The standard mathematical model of
drift found in textbooks is the Wright-Fisher model, the core of which
is the binomial distribution, and it is the model that philosophers of
biology typically appeal to. In the Wright-Fisher model--an
idealized model, as all models are--there are assumed to be
\(N\) diploid adults in a population, mating randomly, with an
allele \(A\) that has a frequency of \(p\_0\) and an alternate
allele at the same locus. The model further assumes that adults
produce an infinite number of gametes having the same allele
frequency. \(2N\) gametes are drawn from the "gamete pool"
at random to constitute the \(N\) diploid individuals of the next
generation. (See Ishida and Rosales 2020 for important clarifications
on the historical development of the Wright-Fisher model).



However, as Millstein, Skipper, and Dietrich (2009) point out, the
Wright-Fisher model is *quite* idealized, since, of course,



> 
> 
> populations do not reproduce by calling in their local statistician
> and asking her to pick exactly \(2N\) gametes at random (with
> replacement) and toss them into the next generation (Gillespie 2004:
> 49)
> 
> 
> 



--but there are more realistic alternatives. John
Gillespie's model, for example, similarly assumes a diploid
population of \(N\) members and a two-allele locus, with
frequencies \(p\) and \(q = (1 - p)\); it also similarly assumes
random mating. Where it differs from the Wright-Fisher model is that
each of the \(2Np A\) gametes constitutes the next generation with a
*random number* of offspring gametes. There is no restriction
on the distribution of the numbers of offspring nor on the total
number of offspring gametes. Thus, unlike the Wright-Fisher model,
Gillespie's model is not tied to *binomial* sampling,
although sampling more generally is still being modeled. Millstein,
Skipper, and Dietrich suggest that the philosophical significance of
such alternative models (including others such as the Moran model, the
Cannings model, or the coalescent) is that we need to be careful about
drawing conclusions about drift from any one particular mathematical
model, always keeping in mind Giere's (1988) point that models
are built as representations of specific aspects of physical
systems.



Clatterbuck (2015) similarly reminds the philosophical community that
it is a mistake to just focus on the Wright-Fisher model, highlighting
the Eldon-Wakeley model in particular. She emphasizes that
different drift models are not predictively equivalent, so that
details of the causal network (represented by the differing
assumptions of the different models) underlying a population can be
seen to change the outcomes of drift. This challenges
statisticalists' assumptions that drift is purely mathematical.
Relatedly, she argues that broadening our conception of drift to
include alternative models reveals novel ways of intervening on drift
that strengthen the causal argument against its statisticalism. For
example, by intervening



> 
> 
> on the population in such a way as to increase the probability that
> individuals have a far greater number of offspring (relative to the
> population size) than allowed by the Wright-Fisher model
> 
> 
> 



we would increase the probability of a neutral allele increasing in
frequency (2015: 3501). This is an improvement over Reisman and
Forber's manipulationist arguments (discussed above), since it
is more clearly the drift (the sampling process) that is being
manipulated rather than just population size.



But perhaps drift is more than just a model (or a set of models);
perhaps it is a scientific law of evolutionary biology. Or so Brandon
(2006) argues, dubbing a "Principle of Drift" analogous to
the Principle of Inertia in that both are intended to be
"zero-force" laws. According to the Principle of
Drift,


1. "A population at equilibrium will tend to drift from that
equilibrium unless acted on by an evolutionary force"



and


2. "A population on evolutionary trajectory *t*, caused by
some net evolutionary force *F*, will tend to depart from the
extrapolated path predicted based on *F* alone (in either
direction or magnitude or both) even if no other evolutionary force
intervenes, unless *F* continues to act" (Brandon 2006:
328).



On this view, drift--and thus change--is the default state
of evolutionary systems, challenging Sober's view (discussed
previously), that the Hardy-Weinberg Principle characterizes the
zero-force state in evolutionary biology. In defending the Principle
of Drift, Brandon challenges those who would argue that there are no
laws of biology (e.g., Beatty 1995; see cites within), although
Brandon (1990) had already done so by defending a Principle of
Selection (see also the related work by McShea and Brandon 2010, in
which drift is characterized as a special case of what they dub the
"Zero-Force Evolutionary Law", or ZFEL).


## 6. Conclusions



Philosophical discussions of random genetic drift have been lively and
fruitful. But as they are still relatively recent, there are many
issues yet to be explored or explored fully. Although much energy has
been diverted toward debating statisticalism, there are many debates
over drift that biologists are engaged in that philosophers could
profitably weigh in on, both historical and contemporary. With respect
to the last two sections of this article in particular (empirical
issues concerning drift and models of drift), we may have only begun
to scratch the surface.