## 1. History




 The debate over adaptationism is often
traced back to a 1979 paper by Stephen Gould and Richard Lewontin,
called "The Spandrels of San Marco and the Panglossian Paradigm:
A Critique of the Adaptationist Programme," or simply the
"Spandrels" paper. This paper is important but, in
fact, this debate traces back to the nineteenth century, with elements
of adaptationism or pluralism as currently understood being present in
the work of Henry Bates, William Bateson, Charles Darwin, Ernst
Haeckel, Herbert Spencer, Alfred Wallace, and August Weissman, among
others (see Mayr 1982 and Ruse 2003 for some of the historical
background).




 In the early twentieth century, views that
we now call adaptationism and pluralism were enunciated by biologists.
Among them were two of the then (and now) most influential evolutionary
biologists: Ronald Fisher and Sewall Wright. The central idea of
Fisher's important 1930 book "The Genetical Theory of
Natural Selection" is that natural selection is the only
important influence on trait evolution. This is the central text of
adaptationism; indeed, it has an honored place in the minds of most
evolutionary biologists, no matter what their position on adaptationism
(compare Grafen 2003 and Kimura 1983). Issued again in 1958 in a
revised edition and in 1999 in a variorum edition, this book has
garnered over 8,400 journal citations; over 7,600 have occurred
since 1975 (Web of Science, June 2010).




 Sewall Wright's pluralist view
of evolution was presented in several places, with his 1931 paper
"Evolution in Mendelian Populations" and the 1977 book
"Evolution and the Genetics of Populations, Volume 3 Experimental
Results and Evolutionary Deductions" being the best known. The
paper has received over 3,400 citations; over 3,000 have occurred since
1975, while the book has received over 800 citations since 1977 (Web of
Science, June 2010).




 These works by Fisher and Wright are
canonical contributions to the field of evolutionary biology. They were
based partially on prior claims and counterclaims about the influence
of natural selection and of non-selective forces on trait evolution,
especially in species such as land snails that have easily
distinguishable trait variation (see Millstein 2007a). In turn, these
works stimulated continuing claims and counterclaims. The mid-1970s
explosion of citations reflects the fact that the number of biologists
studying ecology and evolution increased markedly as compared to the
early 1960s and that evolutionary biology gained separate departmental
status at many universities; these changes were in part caused by the
increased societal awareness and concern at that time about pollution
and the impact of humans on the environment. There were two central but
mainly disjunct scientific developments that energized the
proliferation and refinement of adaptationist and of pluralist views
during this period. The first was the extensive development of
"strategic" claims in evolutionary ecology, which in the
case of a given trait, say, the allocation of energy to male and to
female offspring (e.g., Hamilton 1967; see also Charnov 1982), provides
an explanation as to why the observed trait is locally optimal. Such a
claim invokes only natural selection as an important causal explanation
of the trait. The second development was the neutral theory in
population genetics, which posits that natural selection plays little
or no role in determining DNA and protein sequence variation in natural
populations (e.g., Kimura 1968, 1983). The former development generated
little initial controversy, while the latter development immediately
generated lasting controversy (see Dietrich 1994).




 It is this combination of social,
institutional, and scientific developments that formed the background
to Gould and Lewontin's 1979 paper, which can be best understood
as an important but not singular event in a long-standing debate in
evolutionary biology. It is neither the beginning of the debate over
adaptationism nor something much narrower, e.g., little more than
"the attempted intellectual lynching" of sociobiology, cf.,
Queller (1995); see also Pigliucci and Kaplan (2000). Such claims are
at best historically incorrect.


## 2. Different Flavors of Adaptationism




 Recent work in the philosophy of biology
(Orzack and Sober 1994a, Sober 1996, Amundson 1988, 1990, Godfrey-Smith
2001) has helped uncover three "flavors" of adaptationism;
these reflect differences in beliefs among current professional
developers and users of evolutionary arguments. They represent
commitments about the state of nature, about the way to do science, and
about what is important to study.




 The first flavor, "empirical"
adaptationism, is the view that natural selection is ubiquitous, free
from constraints, and provides a sufficient explanation for the
evolution of most traits, which are "locally" optimal, that
is, the observed trait is superior to any alternative that does not
require "redefining" the organism (Orzack and Sober 1994a).
This is a claim about the realized influence of natural selection on
the evolution of traits as compared to other evolutionary
influences.




 The second flavor,
"explanatory" adaptationism, is the view that explaining
traits as adaptations resulting from natural selection is the central
goal of evolutionary biology. This is a claim about the greater
importance of some kinds of explanations. Opinions differ as to whether
this is a scientific claim or an aesthetic claim (see below).




 The third flavor,
"methodological" adaptationism, is the view that looking
first for adaptation via natural selection is the most efficient
approach when trying to understand the evolution of any given
trait. This could be true even if adaptations are rare (although
a substantial majority of biologists believe that adaptations are
common). The belief that adaptations are common is quite
different from the claim that only natural selection need be invoked in
order to explain these adaptations.




 The flavors of adaptationism are logically
independent. The truth of one claim does not necessarily imply the
truth of the other claims. For example, it could be true that most
traits are adaptations that can be explained by invoking no more than
natural selection (the first flavor) but still be false that it is most
fruitful to look first for adaptation (the third flavor). In fact,
realized intellectual stances are more circumscribed in that most
adaptationists are advocates of empirical, explanatory, and
methodological adaptationism (e.g., Charnov 1982, Dawkins 1976, Maynard
Smith 1978). In addition, there are many biologists who are advocates
of explanatory and methodological adaptationism, but who explicitly
reject empirical adaptationism (e.g., Mayr 1983). On the other hand,
some biologists reject all three flavors of adaptationism (e.g.,
Carroll 2005, Wagner *et al*. 2000, West-Eberhard 2003). There are many
instances of competing adaptationist and pluralist explanations of the
same biology. For example, Cain and Sheppard (1954) and Lamotte (1959)
famously present competing explanations of morphological traits in land
snails; Ackermann and Cheverud (2004) test adaptationist and
pluralist explanations of the diversification of morphological
evolution of humans and their ancestors; Millstein (2007b)
illustrates the differences between adaptationism and pluralism by
presenting the same biology (of a heat-shock protein) from both
perspectives.




 Distinguishing among the flavors of
adaptationism was an important advance in our biological and
philosophical understanding. These flavors of adaptationism differ in
their practical implications for evolutionary biology. We now
discuss each in detail.


### 2.1 Empirical Adaptationism




 Godfrey-Smith (2001, page
336) defined empirical adaptationism as follows: "Natural
selection is a powerful and ubiquitous force, and there are few
constraints on the biological variation that fuels it. To a large
degree, it is possible to predict and explain the outcome of
evolutionary processes by attending only to the role played by
selection. No other evolutionary factor has this degree of causal
importance."




 This definition captures two
important beliefs of adaptationists. The first is that natural
selection governs all important aspects of trait evolution and that
other evolutionary influences will be of little consequence at least
over the long term. The second is that the order in nature is a
consequence of natural selection. Parker and Maynard Smith (1990) is an
important example of this approach.




 Empirical adaptationism is typically regarded as descriptive of the
evolution of directly observable traits such as leg length (e.g.,
Vella 2008). A dizzying variety of traits has been analyzed from the
perspective of empirical adaptationism; many specific examples can be
found in Hardy (2002), Stephens *et al*. (2007), and Westneat
and Fox (2010). Many proponents of empirical adaptationism concede
that important aspects of the evolution of DNA and protein sequences
are little influenced by natural selection.




 The important methodological
implication of empirical adaptationism stems from the causal power that
it assigns to natural selection: an apparent discrepancy between data
and the predictions of an optimality model should be resolved by
rejection of that model and development of a new model. This is
justified by an appeal to our "always" imperfect knowledge
of nature (e.g. see Cain 1989). This contrasts with the pluralist
perspective: such a discrepancy might well provide evidence against
natural selection.




 Many views counter to empirical
adaptationism have been enunciated. Some dispense with natural
selection entirely (or nearly so), such as in the study of molecular
evolution, where there are neutral evolutionary explanations for many
features of the genome (e.g., Lynch 2007b). Some retain natural
selection within populations as an important evolutionary force but
endorse the importance of other forces (e.g., Crespi 2000, Goodwin
2001, Carroll 2005), while others go further and invoke natural
selection among populations or species along with natural selection
within populations (Gould 2002, Jablonski 2008).


### 2.2 Explanatory Adaptationism




 Godfrey-Smith (2001, page 336) defined
explanatory adaptationism in this way: "The apparent design of
organisms, and the relations of adaptedness between organisms and their
environments, are the *big questions*, the amazing facts in
biology. Explaining these phenomena is the core intellectual mission of
evolutionary theory. Natural selection is the key to solving these
problems; selection is the *big answer*. Because it answers the
biggest questions, selection has unique explanatory importance among
evolutionary factors."




 Explanatory adaptationism is viewed
by its proponents (e.g., Dawkins 1976, Dennett 1995, and Griffiths
2009) as important because it organizes research to understand how
natural selection underlies the world around us. To this extent, it can
be viewed as an untestable aesthetic claim, instead of as a scientific
claim. At minimum, it is a claim as to the proper goal of science as a
manifestation of human reason and enlightenment. Amundson (1988, 1990)
claims that explanatory adaptationism is a stance about the natural
world and the products of scientific inquiry, instead of being a view
about biology or how best to do science. However, explanatory
adaptationism may have normative implications for evolutionary
biologists, if adopting it is necessary in order to construct sensible
explanations in developmental biology and physiology (Griffiths
2009). Viewed as an aesthetic claim, explanatory adaptationism
has no practical implications for science, but it does have
implications for the public debate about the relevance of biology to
our image of humanity. In particular, Dennett and Dawkins argue
that this perspective counters the natural theological argument from
design and vindicates a secular humanist perspective.




 Biologists not advocating explanatory
adaptationism view the central mission of evolutionary biology
differently. For example, many systematists believe that
describing the history of life is the central mission of evolutionary
biology; in doing so, one might be agnostic about the evolutionary
forces influencing this history (see Hull 1988 and Felsenstein 2004 for
further details).


### 2.3 Methodological Adaptationism




 Godfrey-Smith (2001, page 337) defined
methodological adaptationism in this way: "The best way for scientists
to approach biological systems is to look for features of adaptation
and good design. Adaptation is a good 'organizing concept'
for evolutionary research."




 This is a claim about the efficiency of
tools. No matter how incorrect it may ultimately be to invoke natural
selection as a sufficient explanation for a trait, it is the most
direct way possible to find the true causal explanation of a trait.
Methodological adaptationism differs markedly from empirical
adaptationism in that the former acknowledges the possibility that
natural selection may ultimately prove not to have the most influence
on a given trait's evolution. In addition, a methodological
adaptationist can accept that an apparent discrepancy between data and
the predictions of a model of natural selection may be resolved by
concluding that the trait is little influenced by natural selection,
instead of by concluding that the model is incorrect.




 One potential argument against
methodological adaptationism is that a mixture of distinct approaches
is superior at advancing knowledge as compared to a single approach
(Kitcher 1993). Allowing for a division of cognitive labor could be a
good thing; perhaps evolutionary biology benefits from an array of
methodological strategies with differing degrees of risk. This
contrasts with the view that multiple approaches with conflicting
assumptions are a hindrance.




 Views counter to methodological
adaptationism range from strong views that deny that adaptation is a
good guiding concept to weaker views that privilege different
explanations. For example, Gould and Lewontin's (1979)
argument for considering constraint-based "Bauplan"
explanations before or along side selective explanations is an example
of methodological anti-adaptationism.


## 3. Testing and Standards of Evidence




 An important part of the
adaptationism debate concerns the testing of adaptive and non-adaptive
hypotheses. The belief that scientific practice in evolutionary
biology does not adhere to the proper standards of evidence motivates
many of the critiques of adaptationism. This concern has been taken
seriously by some evolutionary biologists; for example, Rose and Lauder
(1996) claimed that a central task of contemporary evolutionary biology
is to articulate a "post-Spandrels adaptationism," a task
that involves improving testing methods by including comparative and
molecular data, conducting careful long-term studies in both the
laboratory and the wild, and incorporating a more comprehensive
understanding of development and constraint.




 We now discuss testing of
adaptationism itself and the associated implications for testing
evolutionary hypotheses generally, and the sort of epistemic
difficulties that must be overcome. We highlight how the debate
has led to increased understanding of the importance of phylogenetic
methods, of the viability of optimality models as tools for testing
adaptive hypotheses, and of whether constraint hypotheses are rivals to
adaptive hypotheses or provide the backdrop against which we test
hypotheses about the evolutionary process.


### 3.1 Testing adaptationism




 Orzack and Sober (1994a, 1994b, 1996,
2001) (see also Orzack 2008) proposed an approach for testing
empirical adaptationism. In their view, the truth of empirical
adaptationism is a possible outcome of testing of optimality models, as
opposed to being something that is decided a priori.




 Their proposal, the "Adaptationism Project", involves
assembling specific kinds of analyses of traits in order to assess the
relative frequency and importance of natural selection across the
biological realm. In order to contribute to the ensemble test, an
analysis must include an assessment of the quantitative fit of the
optimality model and of the within-population heterogeneity of fit to
the predictions (see below and Orzack and Sober 1994a for why these
assessments are required). At present, there are very few trait
analyses that contain these elements; after an extensive literature
review, Orzack and Sober identified only Brockmann and Dawkins (1979),
Brockmann *et al*. (1979), Orzack and Parker (1990), and
Orzack *et al*. (1991) as analyses that contain the required
assessments.




 Of course, to conduct an ensemble test,
important methodological difficulties must be confronted, including how
to choose populations and species to analyze, and how many cases are
necessary to provide an adequate test. The name "Adaptationism
Project" is an acknowledgement of a parallel to the "Human
Genome Project"; both are carried out by a consortium of
investigators and require advance organization of the process by which
knowledge is gathered (instead of just occurring willy-nilly).
This is an ambitious project but one that is achievable, cf., the
"Genome 10K" project, which is also an effort to create an
unprecedented data ensemble (Genome 10K 2009).




 Ensemble tests have a long
precedent in biology and evolutionary biology, although none appear to
have been prospectively organized. For example, we have the ensemble
conclusion that "almost all" speciation occurs via
geographical isolation (Mayr 1963) or that the genetic code is
"nearly" universal (Crick 1968). Either or both of these
claims could be true but the present empirical knowledge that generated
either one is not even remotely close to being based on a sample of
organisms that could be taken to be representative of all species.




 Empirical adaptationism is both
a claim about the relative frequency of natural selection across
evolutionary histories and about the power of natural selection to
overcome constraints and contingency. Orzack and Sober's
(1994a,b) ensemble test of the truth of empirical adaptationism is
structured in the following way for any given trait, T. In order to
contribute to the ensemble test, the analysis of the trait must allow
the investigator to confirm one of the following hypotheses about the
power of natural selection:



> 
> (U) Natural selection played some role in the evolution of T. (U
> denotes ubiquitous since
> this proposition applies to most traits.)
> 
> 
> 
> 
> (I) Natural selection was an important cause of the evolution of T.
> (I denotes important.)
> 
> 
> 
> 
> (O) Natural selection is a sufficient explanation of the evolution
> of T, and T is locally 
> optimal. (O denotes optimal.)
> 
> 
> 




 Orzack and Sober claimed that
empirical adaptationism is a generalization of (O), namely that natural
selection is a sufficient explanation for most (nonmolecular) traits
and those traits are locally optimal.




 Orzack and Sober provided a specific
protocol to assess whether O is true for a particular trait. It
involves comparing the predictive accuracy of a "censored"
evolutionary model, one that invokes only natural selection, and an
alternative "uncensored" model that invokes additional
evolutionary influences such as genetic drift (random trait change
caused by population number being finite), or constraints caused by the
way the trait is determined genetically or developmentally. If
the censored model is quantitatively accurate and there is no
within-population heterogeneity of fit to predictions and the
uncensored model fails in either regard, then one can infer that
natural selection is a sufficient explanation for trait T.
Optimality models embody proposition (O) in that natural selection is
assumed to be the only important influence on the focal trait's
evolution; the result is assumed to be the evolution of a trait that
maximizes individual fitness. Of course, an optimality model, like any
evolutionary model, must include background assumptions and constraints
that anchor the "local" analysis of the focal trait.
However, given these assumptions, natural selection is assumed to act
without constraint on the trait.




 There is some controversy over the
protocol for testing whether natural selection is a sufficient
explanation of a trait. Brandon and Rausher (1996) objected that
local optimality is a distinct claim and so tests for the importance of
natural selection should not use optimality models, whose use they
equate to "theft", which they believe means that such
models are generically incompatible with universal aspects of the
biology of organisms. They also take issue with how the
predictive accuracy of censored and uncensored models should be
assessed. Godfrey-Smith (2001) makes the observation that the
censored and uncensored test models typically have different
complexity. More complex models usually fit the data better, but
risk obscuring the underlying trend or comprising predictive
accuracy--there may be a problem of over-fitting lurking here
(see, e.g., Gauch 2003 for an overview of the curve-fitting
problem).




 Extending this framework to molecular
traits, where completely neutral evolution is a plausible explanation,
requires expanding the set of hypotheses about natural selection.
It now should include:



> 
> 
> (N) Natural selection played no role in evolution of T. (N
> denotes neutral.)
> 
> 




Some argue that N is rarely, if ever, true (e.g., Gillespie 1991),
whereas others argue otherwise (e.g., Kimura 1983, Lynch 2007a).
An ensemble test involving molecular traits would help resolve this
controversy. In addition, the notion of optimality at the
molecular level must be made precise. A molecular trait needs to have
an identified phenotypic consequence. The endeavor to identify such a
consequence will likely always involve a combination of very detailed
molecular, biochemical, and phenotypic analyses. However, despite the
difficulty of the needed analyses, there are claims as to the
optimality of various molecular traits. A canonical example is the
claim that triosephosphate isomerase, an enzyme involved in glycolysis
in animals, fungi, plants, and some bacteria, is catalytically
"perfect" (Albery and Knowles 1976); this is a claim that
hypothesis O is true. For molecular traits, the assessment of the
influence of natural selection, i.e., distinguishing between hypothesis
N and hypotheses U and I, is facilitated by the degeneracy of the
genetic code and the existence of non-coding regions in the genome. We
expect heterogeneity of the realized influence of natural selection
among sites in the genome, and differences in evolutionary rates
between sites where a DNA base change alters the protein sequence and
those sites that it does not (see examples in Graur and Li 2000,
Kreitman and Akashi 1995, Nielsen 2005, and Yang 2006).


### 3.2 Testing adaptive hypotheses




 The debate over
adaptationism contains claims and counterclaims about what hypotheses
should be included in an analysis of the adaptiveness of a trait.
This is crucial because assessments of evidentiary support depend on
what hypotheses we consider (see Sober 1990, Earman 1992). We
must consider all the relevant hypotheses in order to provide good
evidence for a hypothesis (Stanford 2006, Forber 2010). One
common pluralist complaint is that adaptationists neglect this standard
of evidence. Such an inclusive standard is essential because many
different evolutionary trajectories can lead to the same outcome.
As Gould and Lewontin (1979) wrote, "One must not confuse the
fact that a structure is used in some way...with the primary
evolutionary reason for its existence and conformation". In
addition, subtle differences in evolutionary history may lead to
different evolutionary outcomes (Beatty and Desjardins 2009). Thus, we
cannot conclude that natural selection played an important role in the
evolution of some trait just because we have a plausible adaptive
hypothesis in mind. Indeed, finding suitable evidence for an
adaptive (or non-adaptive) hypothesis is difficult because we lack good
epistemic access to evolutionary history. This lack of access is
a premise of Gould and Lewontin's critique, and it motivates
their call to evaluate testing methods in evolutionary biology,
especially those methods that consider only adaptive hypotheses with no
regard for non-adaptive rivals. Biologists have continued to develop
new testing methods that do this (see, e.g., Rose and Lauder 1996,
Hansen *et al*. 2008).




 This aspect of the adaptationism debate is
connected with a general epistemological issue in philosophy of
science: underdetermination of theory by evidence. Evolutionary
hypotheses are typically underdetermined by available evidence.
In principle, rival hypotheses make different commitments about the
nature of evolutionary history, but in practice these hypotheses are
empirically indistinguishable given the available evidence.
Philosophers argue about the consequences of this underdetermination
for our understanding of biological science (Turner 2005, Stanford
2006). Yet, there is agreement that the problem of underdetermination
should be addressed by developing and using tests that discriminate
between rival hypotheses.




 Evidentiary relations depend on what
hypotheses we compare, and so good testing methods should include all
rival hypotheses. If we fail to include a relevant rival, say,
one that emphasizes developmental constraint, then we may not have
found sufficient evidence for the adaptive hypothesis. Failing to
contrast adaptive and non-adaptive explanations weakens any
adaptationist analysis (Forber 2009).




 Evolutionary hypotheses make a
variety of commitments about development, ecology, genetics, and
history. As a result, an adaptive hypothesis makes contact with
evolutionary history only in conjunction with a number of auxiliary
hypotheses. The most convincing case for an adaptive hypothesis will
include a variety of evidence, especially independent data that confirm
the different facets of an evolutionary hypothesis (Lloyd 1988).
Sober's (2008) analysis of a testing protocol for evolutionary
hypotheses makes clear the role of auxiliary hypotheses and assesses
the evidentiary import of different observed outcomes. He provides an
analysis of whether and how fit between an optimality model and the
observed population mean favors natural selection over genetic
drift.


### 3.3 Common ancestry and adaptation




 The adaptationism debate has helped clarify the importance of
comparative methods for testing adaptive hypotheses.




 The relatedness among species due to common
ancestry can reduce the amount of seemingly independent evidence one
has for or against any evolutionary hypothesis. Species with a recent
common ancestor may have inherited the same trait from the ancestor, as
opposed to evolving it independently of one another. Comparative
methods help one assess the extent to which a set of related species
provide independent evidence for or against a given evolutionary
hypothesis (Harvey and Pagel 1991). The general awareness of the need
to use such methods stems primarily from the initially narrower debate
that took place within systematics in the 1960s and 1970s over how to
create classifications of organisms that are "scientific"
and as such, are transparent recipes that are accessible to others,
instead of being "private" and non-scientific. This debate
generated tremendous controversy (Hull 1988) and it spurred on the
development of methods to statistically correct for dependence among
species' trait values when assessing an adaptive hypothesis
(Felsenstein 1985, Harvey and Pagel 1991). In addition, it became more
widely understood that a claim that one trait evolved in response to
another is enormously strengthened by phylogenetic confirmation; the
history of trait acquisition must be consistent with the hypothesis
(see Maddison 1990 and references therein).




 These developments are salutary in
that they show biologists how to better test adaptive hypotheses and
have clarified the phylogenetic assumptions that are necessary to test
adaptive hypotheses (Sober and Orzack 2003). As such, they are a
methodological improvement that has generally gained a positive
reception among philosophers of biology (e.g., Sterelny and Griffiths
1999). Many biologists agree, but controversy continues. Some
acknowledge the potential importance of comparative methods but point
to limitations that may reduce their usefulness (Reeve and Sherman
2001, Leroi *et al*. 1994). As such, these critiques are consistent with
methodological adaptationism. Others view any allusion to potential
non-adaptive influences on trait evolution to be mistaken; in their
view, the importance of phylogenetic methods is that they help reveal
complete history of natural selection on the trait (Grafen 1989). As
such, this is a critique consistent with the espousal of empirical
adaptationism.


## 4. Do optimality models describe evolution?




 Claims and counterclaims about the use of
optimality models for understanding evolution are a central part of the
debate over adaptationism, although some believe that there is no
necessary connection between optimality modeling and adaptationism
(Potochnik 2009). While many biologists believe that optimality
models are useful, whether evolution by natural selection tends to
produce optimal traits is controversial (see, e.g., Dupre
1987).




 Optimality models put the contingencies of
history and developmental and genetic constraints in to the background
so as to focus on natural selection. Much work in evolutionary
game theory embodies this approach. Most game-theoretic models are used
to describe the evolution by natural selection of strategic behavior to
a local optimum called an evolutionarily stable strategy (Maynard Smith
1982) (but see Orzack and Hines 2005 and Huttegger 2010 among
others). This approach has the assumption that there is direct
selection on the trait under analysis. This is often justified on the
grounds that there exists a "good fit" between the trait
and its current function (Maynard Smith 1978) or that natural selection
is ubiquitous in nature (Mayr 1983). The Spandrels paper targeted
these general arguments for optimality models.




 Biologists have discovered many ways in
which the genetic details of trait determination and/or ecological
details of the population can prevent the evolution of optima. For
example, interaction between loci (linkage or pleiotropy) can prevent
the optimal phenotype from being fixed in a population, and thereby
prevent the maximization of mean fitness (Moran 1964). Such a deviation
from the state of highest fitness is called genetic load. The standard
adaptationist response is that genetic and ecological constraints are
eliminated over evolutionary time by the introduction of new genetic
variation via mutation (Parker and Maynard Smith 1990).




 While this controversy has been divisive
(Schwartz 2002), there are prospects for a synthesis. First,
Eshel and Feldman (2001) distinguished between "short-term
evolution", the evolutionary dynamics of a fixed set of
genotypes, and "long-term evolution", bouts of short-term
evolution interspersed with introductions of new genetic
variation. They noted (page 162) that "long-term evolution
proceeds by an infinite sequence of transitions from one fixed set of
genotypes to another fixed set of genotypes, with each of these sets
subject to short-term evolution..." Optima are often
not accessible in the short-term due to constraints on available
variation. However, genetic variation may be introduced over the long
term so that the population eventually reaches an optimum. The
substantive point is that we now understand how apparent short-term
impediments to optimality can be resolved over the long term. Mutations
must appear at the right time and the ecology must remain stable over
the long term; whether these conditions are met frequently enough in
nature to justify the optimality approach is an empirical issue (see
also Hammerstein 1996). The second prospect for synthesis is
Wilkins and Godfrey Smith's (2009) proposal that the truth of
empirical adaptationism, and the concomitant application of optimality
models, depends on the intended "grain" of resolution of
the evolutionary analysis. At a fine grain of resolution, when there
are few peaks in the adaptive landscape, most observed populations may
be on or near these peaks. Adaptationism is appropriate at this
resolution. If we "zoom out" and look at a grand landscape
over large regions of morphospace, the situation changes. At a
very coarse grain of resolution, much of morphospace is empty and
constraints often explain why certain regions remain unexplored by
biological evolution. Adaptationism is inappropriate at this
resolution.




 Finally, the focus on optimality modeling
in connection to adaptationism has led to a precise statement of how
the nature of fit between data and the predictions of an optimality
model influence the degree of evidentiary support for the adaptive
hypothesis (Orzack and Sober 1994a, b). Qualitative agreement by
itself is not sufficient to accept the hypothesis of local optimality.
Instead, quantitative agreement and an assessment of nature of possible
between-individual heterogeneity of fit to model predictions are
required in order to have evidence for optimality; without both of
these test components, acceptance of the hypothesis of optimality is
not warranted (see above).


## 5. Are constraint hypotheses genuine rivals to adaptive hypotheses?




 One issue in the debate over
adaptationism and optimality models concerns whether constraint
hypotheses count as genuine alternatives to adaptive hypotheses.
Gould and Lewontin (1979) view constraint hypotheses as competing with
adaptive hypotheses as explanations of traits. Advocates of optimality
models (e.g., Maynard Smith 1978, Roughgarden 1998) take the set of
evolutionary constraints to be a background commitment of any
optimality model. The constraint set may include developmental
and genetic constraints on variation and transmission, but it is
natural selection that drives evolution and so explains the trait given
those constraints. Advocates of optimality models treat
constraints as presupposed by adaptive hypotheses. A concern of
many critics of adaptationism is that this treatment of constraints
undervalues their role in explaining evolutionary form and novelty.




 Developmental processes may limit the spectrum of evolutionary
trajectories available to a lineage. Maynard Smith *et
al*. (1985, page 266) defined a developmental constraint as
"a bias on the production of variant phenotypes or a limitation
on phenotypic variability caused by the structure, character,
composition, or dynamics of the developmental system." More
recently, the definition of constraint has become more nuanced (see,
e.g., Wagner and Altenberg 1996, Winther 2001).




 Part of the controversy over
constraints can be resolved by distinguishing between "constraint
on adaptation" and "constraint on form" (Amundson
1994). In the former, certain trajectories are less likely
because they require populations to leave local optima or
"peaks" in the adaptive landscape. In this case,
natural selection limits the potential evolutionary trajectories.
In the latter case, certain trajectories are unavailable due to the
structure of the current developmental system.




 Advocates of optimality models often argue
that building and testing such models provides the best way to identify
and discover evolutionary constraints, and that these constraints can
then be used to build better optimality models (Amundson 1994, Seger
and Stubblefield 1996). Many biologists that analyze the
evolution of development or "evo-devo" use a different set
of molecular and morphological investigative techniques to uncover
robust and important developmental constraints (see, e.g., Muller
and Newman 2003, Kirschner and Gerhart 2005). They object that
the concept of optimality is a poor tool for answering their research
questions. The recognition of two kinds of constraints resolves
this dispute. We see then that optimality modeling usually
entails the incorporation of or the discovery of constraints on
adaptation, whereas studies of evolution and development investigates
constraints on form. A full understanding of evolutionary history
requires a synthesis of these approaches.




 Developmental and genetic constraint
hypotheses do not invoke causal processes in the same way that adaptive
hypotheses do. Can such different hypotheses compete with one another?
This aspect of the adaptationism debate connects biology to an
important puzzle about the nature of causation and explanation.
If explanation amounts to identifying causes, then constraints must be
causes to explain evolutionary outcomes. But how can impediments
have a causal influence on the evolutionary trajectory of a
lineage? One possible answer is that they don't have any
causal influence--they are merely the background against which
natural selection operates. Such a view treats causes as part of
a process, or involving some kind of energy transfer (Dowe 2008).
This view of causation vindicates the adaptationist view that the
constraint set is presupposed by any respectable adaptive
hypothesis. For adaptationists, new constraints simply mean that
we need to build new models. Testing is then just a matter of
comparing different adaptive hypotheses that have different
constraints. The other possible answer is that constraints
do have a causal influence on evolution because they prevent
evolutionary trajectories from attaining some outcomes. This view
is consistent with counterfactual and interventionist approaches to
causation, such as the comprehensive one defended by Woodward (2003),
and vindicates the approach of treating constraints as genuine
alternatives to adaptive hypotheses.




 Linking this debate to
philosophical ideas about causation can help us evaluate whether
evolutionary constraints count as genuine alternatives.
Constraints are defined as *biases or limitations* on the
production of variation. From the perspective of causation, this
is a heterogeneous combination. Constraints that bias a lineage
towards certain evolutionary trajectories look like productive
probabilistic causes, and avoid certain conceptual entanglements that
face boundaries or limitations. Innovations in the developmental makeup
of an organism can make new changes and subsequent evolutionary
trajectories more likely, a hallmark of a causal factor. This helps
clarify the importance of evolutionary innovation. Innovations that
produce biases may be crucial to explaining major evolutionary
transitions, such as the emergence of multicellularity (Sterelny 2008).
When certain changes make new evolutionary outcomes more likely
they are part of the explanation of those new outcomes. Such
biases count as probabilistic causal influences since they change the
probability of a lineage taking certain evolutionary trajectories
(Hitchcock 2008).




 Whether boundaries count as causes, and
thereby explain evolutionary outcomes, is more problematic. A
prevailing view within evolutionary biology is that constraints must
count as causal influences, whatever our account of causation (whether
it be by prevention or by omission, see Woodward 2003 for discussion).
Gould and Lewontin (1979) adopted this position. Sansom (2003) argued
that the debate over the evolutionary importance of constraint amounts
to an issue about the relative causal contributions of constraint and
natural selection to evolutionary outcomes. The causal
contribution of constraint can be assessed by using comparative data in
order to compare evolutionary outcomes of lineages with and without the
constraint of interest. If there is a difference, then the
constraint has an identifiable causal influence, all other things being
equal. Pigliucci and Kaplan (2000, 2006) proposed a test protocol
based on transition matrices in which probabilities of evolutionary
change are specified under natural selection and under one or more
competing constraint hypotheses, so as to test natural selection
against constraint. More philosophical analysis is required to assess
the viability of this approach.




 Whatever the position on whether
constraints count as causes, the lesson to be taken from this part of
the adaptationism debate is that it is essential to precisely specify
the rival evolutionary hypotheses. There are many examples of such
precise specification in the biological literature. For example, Frank
(1985) and Stubblefield and Seger (1990) analyzed the influence on sex
ratio optima of different constraints on the information available to
parents; Lloyd (2005) described the evidentiary support for
explanations of the evolution of the female orgasm. Lloyd's
analysis supports Symons' (1979) proposal that the female orgasm
exists because of a developmental constraint in combination with strong
selection for the male orgasm. If males fail to achieve orgasm
then no reproduction occurs. The tissue responsible for the male
orgasm appears early in human development, long before sexual
dimorphism occurs, and this tissue is found in both male and female
sexual organs. This example contains competing hypotheses that have
commitments about boundaries and about natural selection. The
Symons constraint explanation invokes a feature of development and
indirect selection on a different trait, whereas the adaptive
hypothesis does not incorporate the developmental constraint and
instead, posits a direct role for selection.




 There is room for reconciliation
here. As adaptationists point out, any evolutionary hypothesis
must assume some constraints, so the accusation that optimality models
fail to include constraints is incorrect. But pluralists are
right to argue that in some cases constraints may play a significant
role in the evolution of some trait, and that the correct evolutionary
explanation may not even include natural selection for the trait.




 Constraints are often understood as
biases or limitations on potential evolutionary trajectories. How do we
identify potential trajectories? This will depend on how biology
provides counterfactual information. We cannot appeal solely to
realized evolutionary history, since not all potential trajectories
have occurred. Evo-devo research on novelty provides one of the
best strategies for exploring potential evolutionary trajectories
(Wagner 2000, 2001a,2001b, Muller and Wagner 2003, Calcott 2009).
As the causal mechanisms underlying development are better understood,
we will gain a better grasp on the nature of constraints and how they
explain evolutionary outcomes.


## 6. Concluding Remarks




 Why should biologists and philosophers care
about the debate over adaptationism? This debate has been and will
continue to be important to biologists because it helps clarify how to
do better evolutionary biology. Despite this, a minority of
currently-active biologists contribute to the debate about
adaptationism, and many ignore it or disparage it. For a variety of
reasons, many of the important points that have arisen from the debate,
such as how to structure empirical tests of adaptive hypotheses and
optimality models, go unheeded. For example, claims for local
optimality continue to appear that lack a specification of even a
single alternative hypothesis to the adaptive hypothesis. This lack
inevitably leaves ambiguous the status of the adaptive hypothesis. In
addition, standards for rejection of the (only) adaptive hypothesis
continue to be rarely delineated if at all.




 The debate over adaptationism will continue
to be important to philosophers of biology because much will be gained
by a more informed understanding of the use of hypotheses about natural
selection by biologists. In the 1970s and 1980s, there was a general
tendency to misunderstand the conceptual commitments of users of
optimality models. More recently, there has been a growing
understanding of the variety of conceptual commitments held by users of
such models, especially that the use and development of an optimality
model need not bind the user to a blind acceptance of the claim that
natural selection is all powerful.