The Cambrian Information - Explosion Evidence for Intelligent Design

First, it seeks to explain the origin ofthe novel biological form and the information necessary to produce it that emerges after the origin of the first life.. Debate now exists about th

20 The Cambrian Information Explosion

Evidence for Intelligent Design

Stephen C Meyer

introduction

In his book The Philosophy of Biology, Elliott Sober (2000) notes that many

evolutionary biologists regard the design hypothesis as inherently untestableand, therefore, unscientific in principle simply because it no longer com-mands scientific assent He notes that while logically unbeatable versions

of the design hypothesis have been formulated (involving, for example, a

“trickster God” who creates a world that appears to be undesigned), designhypotheses in general need not assume an untestable character A designhypothesis could, he argues, be formulated as a fully scientific “inference tothe best explanation.” He notes that scientists often evaluate the explana-tory power of a “hypothesis by testing it against one or more competinghypotheses” (44) Thus, he argues that William Paley’s design hypothesiswas manifestly testable but was rejected precisely because it could not ex-plain the relevant evidence of contemporary biology as well as the fullynaturalistic theory of Charles Darwin Sober then casts his lot with mod-ern neo-Darwinism on evidential grounds But the possibility remains, heargues, “that there is some other version of the design hypothesis that bothdisagrees with the hypothesis of evolution and also is a more likely expla-nation of what we observe No one, to my knowledge, has developed such

a version of the design hypothesis But this does not mean that no one everwill” (46)

In recent essays (Meyer 1998, 2003), I have advanced a design hypothesis

of the kind that Sober acknowledges as a scientific possibility Specifically, Ihave argued that the hypothesis of Intelligent Design can be successfully for-mulated as “an inference to the best explanation” for the origin of the infor-mation necessary to produce the first life Such a design hypothesis stands,

not as a competitor to biological evolutionary theory (i.e., neo-Darwinism), but instead as a competitor to chemical evolutionary theories of how life first

arose from nonliving chemicals

371

In order to make this argument, I show that considerations of causal equacy (Hodge 1977, 239; Lipton 1991, 32–88) typically determine which

ad-among a group of competing explanations qualify as best I then argue against

the causal adequacy of each of the main categories of naturalistic tion – chance, necessity, and their combination – for the origin of biologicalinformation Further, in order to avoid formulating a purely negative “argu-

explana-ment from ignorance,” I also argue for the positive adequacy of intelligent

agency as a cause of information I note, in the words of the informationtheorist Henry Quastler, that the “creation of new information is habituallyassociated with conscious activity” (1964, 16) Thus, I conclude that Intelli-gent Design stands as the best – most causally adequate – explanation forthe origin of the information necessary to produce the first life

In this volume, Professors Dembski and Bradley amplify the two plementary aspects of this argument – Dembski, by suggesting that livingsystems possess a reliable positive indicator of the activity of an intelligentcause, namely, “complex specified information”; Bradley, by challenging thecausal adequacy of naturalistic explanations for the origin of the informa-tion necessary to the first life Jointly, these two chapters provide both anegative case against the adequacy of naturalistic theories and a positivecase for the causal adequacy of Intelligent Design, thereby supporting Intel-ligent Design as the best explanation for the information necessary to thefirst life

com-thesisThis chapter extends this line of reasoning by formulating another, moreradical design hypothesis Rather than positing Intelligent Design solely as

an explanation for the origin of the information necessary to the first life,this chapter will offer Intelligent (or purposive) Design as an explanationfor the information necessary to produce the novel animal body plans thatarise during the history of life This design hypothesis thus competes directlywith neo-Darwinism in two respects First, it seeks to explain the origin ofthe novel biological form (and the information necessary to produce it)

that emerges after the origin of the first life Second, it posits the action of a

purposive intelligence, not just a purposeless or undirected process, in thehistory of life

Many scientists now openly acknowledge the fundamental difficulties ing chemical evolutionary theories of the origin of life, including the prob-lem of explaining the origin of biological information from nonliving chem-istry Nevertheless, many assume that theories of biological evolution do notsuffer from a similar information problem While many scientists recognizethat invoking natural selection at the pre-biotic level remains theoreticallyproblematic (since natural selection presumably acts only on self-replicatingorganisms), neo-Darwinists assume that natural selection acting on random

fac-mutations within already living organisms can generate the informationneeded to produce fundamentally new organisms from preexisting forms.

I will dispute this claim I will argue that explaining the origin of novel logical information is not a problem confined to origin-of-life research, butrather one that afflicts specifically biological theories of evolution as well

bio-In order to this make this case, I will examine a paradigm example

of a discrete increase in biological information during the history of life:the Cambrian explosion I will then compare the explanatory power ofthree competing models – neo-Darwinism, self-organization, and IntelligentDesign – with respect to the origin of the information that arises during theCambrian

the cambrian explosionThe “Cambrian explosion” refers to the geologically sudden appearance ofmany new animal body plans about 530 million years ago At this time, at leastnineteen and perhaps as many as thirty-five phyla (of forty total phyla) madetheir first appearance on Earth within a narrow five-million-year window ofgeologic time (Meyer et al 2003; Bowring et al 1993) Phyla constitute thehighest categories in the animal kingdom, with each phylum exhibiting aunique architecture, blueprint, or structural body plan Familiar examples

of basic animal body plans are mollusks (squids and shellfish), arthropods(crustaceans, insects, and trilobites), and chordates, the phylum to whichall vertebrates belong

An especially dramatic feature of the Cambrian explosion was the firstappearance of invertebrate phyla with mineralized exoskeletons, including

members of the phyla Mollusca, Echinodermata, and Arthropoda Many

well-preserved animals with soft tissues also first appeared, including

represen-tatives of Ctenophora, Annelida, Onycophora, Phoronida, and Priapulida Fossil

discoveries from the Lower Cambrian Yuanshan Formation in China have

also shown the presence of animals from the phylum Chordata, including two fish fossils, Myllokunmingia fengjiaoa and Haikouichthys ercaicunensis, sug-

gesting an earlier appearance for vertebrates than previously thought (Shu

et al 1999)

To say that the fauna of the Cambrian period appeared in a geologicallysudden manner also implies the absence of clear transitional intermediateforms connecting Cambrian animals with simpler pre-Cambrian forms Andindeed, in almost all cases, the Cambrian animals have no clear morpholog-ical antecedents Debate now exists about the extent to which this pattern ofevidence can be reconciled with the theory of universal common descent.This essay will not address that question but will instead analyze whether the

neo-Darwinian mechanism of natural selection acting on random mutations

can generate the information necessary to produce the animals that arise

in the Cambrian

defining biological informationBefore proceeding, I must define the term “information” as used in biol-ogy In classical Shannon information theory, the amount of information

in a system is inversely related to the probability of the arrangement ofconstituents in a system or the characters along a communication channel(Shannon 1948) The more improbable (or complex) the arrangement,the more Shannon information, or information-carrying capacity, a string

or system possesses

Since the 1960s, mathematical biologists have realized that Shannon’stheory could be applied to the analysis of DNA and proteins to measuretheir information-carrying capacity Since DNA contains the assembly in-structions for building proteins, the information-processing system in thecell represents a kind of communication channel (Yockey 1992, 110) Fur-ther, DNA conveys information via specifically arranged sequences of fourdifferent chemicals – called nucleotide bases – that function as alphabetic

or digital characters in a linear array Since each of the four bases has aroughly equiprobable chance of occurring at each site along the spine ofthe DNA molecule, biologists can calculate the probability, and thus the

information-carrying capacity, of any particular sequence n bases long.

The ease with which information theory applies to molecular biology hascreated confusion about the type of information that DNA and proteinspossess Sequences of nucleotide bases in DNA, or amino acids in a protein,are highly improbable and thus have a large information-carrying capac-ity But, like meaningful sentences or lines of computer code, genes and

proteins are also specified with respect to function Just as the meaning of a

sentence depends upon the specific arrangement of the letters in the tence, so too does the function of a gene sequence depend upon the specificarrangement of the nucleotide bases in the gene Thus, as Sarkar points out,

sen-molecular biologists beginning with Francis Crick have equated information

not only with complexity but also with “specificity,” where “specificity” or

“specified” has meant “necessary to function” (1996, 191)

Similarly, this chapter poses a question, not about the origin of Shannoninformation – mere complexity of arrangement – but about the origin ofthe “specified complexity” or “complex specified information” (CSI) thatcharacterizes living systems and their biomolecular components

the cambrian information explosionThe Cambrian explosion represents a remarkable jump in the specified com-plexity or CSI of the biological world For over three billion years, the bio-logical realm included little more than bacteria and algae Then, beginningabout 570 mya, the first complex multicellular organisms appeared in therock strata, including sponges, cnidarians, and the peculiar Ediacaran biota.Forty million years later, the Cambrian explosion occurred The emergence

of the Ediacaran biota (570 mya), and then to a much greater extent theCambrian explosion (530 mya), represented steep climbs up the biologicalcomplexity gradient.

One way to measure the increase in CSI that appears with the Cambriananimals is to assess the number of new cell types that emerge (Valentine

1995, 91–3) Studies of modern animals suggest that the sponges that peared in the late Precambrian, for example, would have required five celltypes, whereas the more complex animals that appeared in the Cambrian

ap-(such as representatives of Arthropoda) would have required fifty or more

cell types Functionally more complex animals require more cell types toperform their more diverse functions New cell types require many new andspecialized proteins New proteins, in turn, require new genetic information.Thus an increase in the number of cell types implies (at minimum) a consid-erable increase in the amount of specified genetic information Molecularbiologists have recently estimated that a minimally complex single-celledorganism would require between 318 and 562 kilobase pairs of DNA to pro-duce the proteins necessary to maintain life (Koonin 2001) More complexsingle cells might require upward of a million base pairs Yet to build theproteins necessary to sustain a complex arthropod such as a trilobite wouldrequire orders of magnitude more coding instructions The genome size of

the modern fruitfly Drosophila melanogaster (an arthropod) is approximately

120 million base pairs (Gerhart and Kirschner 1997, 121) Transitions from

a single cell to colonies of cells to complex animals represent significant(and, in principle, measurable) increases in CSI

Building a new animal from a single-celled organism requires a vastamount of new genetic information It also requires a way of arranginggene products – proteins – into higher levels of organization New proteinsare required to service new cell types But new proteins must be organizedinto new systems within the cell; new cell types must be organized intonew tissues, organs, and body parts (M ¨uller and Newman 2003) These, inturn, must be organized to form body plans New animals, therefore, em-body hierarchically organized systems of lower-level parts within a functionalwhole Such hierarchical organization itself represents a type of information,since body plans comprise both highly improbable and functionally spec-ified arrangements of lower-level parts The specified complexity of newbody plans requires explanation in any account of the Cambrian explosion.Can neo-Darwinism explain the discontinuous increase in CSI that ap-pears in the Cambrian explosion – either in the form of new genetic infor-mation or in the form of hierarchically organized systems of parts? We willnow examine the two parts of this question

novel genes and proteinsMany scientists and mathematicians have questioned the ability of muta-tion and selection to generate information in the form of novel genes and

proteins Such skepticism often derives from consideration of the extremeimprobability (and specificity) of functional genes and proteins.

A typical gene contains over one thousand precisely arranged bases For

any specific arrangement of four nucleotide bases of length n, there is a

cor-responding number of possible arrangements of bases, 4n For any protein,there are 20npossible arrangements of protein-forming amino acids A gene

999 bases in length represents one of 4999possible nucleotide sequences; aprotein of 333 amino acids is one of 20333possibilities

Since the 1960s, biologists have generally thought functional proteins to

be rare among the set of possible amino acid sequences (of correspondinglength) Some have used an analogy with human language to illustrate whythis should be the case Denton, for example, has shown that meaningfulwords and sentences are extremely rare among the set of possible combina-tions of English letters, especially as sequence length grows (The ratio ofmeaningful 12-letter words to 12-letter sequences is 1/1014; the ratio of 100-letter sentences to possible 100-letter strings is roughly 1/10100.) Further,

Denton shows that most meaningful sentences are highly isolated from one

another in the space of possible combinations, so that random substitutions

of letters will, after a very few changes, inevitably degrade meaning Apartfrom a few closely clustered sentences accessible by random substitution,the overwhelming majority of meaningful sentences lie, probabilisticallyspeaking, beyond the reach of random search

Denton and others have argued that similar constraints apply to genesand proteins (1986, 301–24) They have questioned whether an undirectedsearch via mutation/selection would have a reasonable chance of locat-ing new islands of function – representing fundamentally new genes orproteins – within the time available (Schuetzenberger 1967; Løvtrup 1979;Berlinski 1996) Some have also argued that alterations in sequencing wouldlikely result in loss of protein function before fundamentally new functioncould arise Nevertheless, neither the sensitivity of genes and proteins tofunctional loss as a result of sequence change, nor the extent to which func-tional proteins are isolated within sequence space, has been fully known.Recently, experiments in molecular biology have shed light on these ques-tions A variety of “mutagenesis” techniques have shown that proteins (andthus the genes that produce them) are indeed highly specified relative to bi-ological function (Bowie and Sauer 1989; Reidhaar-Olson and Sauer 1990;Taylor et al 2001) Mutagenesis research tests the sensitivity of proteins (and,

by implication, DNA) to functional loss as a result of alterations in ing Studies of protein mutations have long shown that amino acid residues

sequenc-at many active site positions cannot vary without functional loss (Perutzand Lehmann 1968) More recent protein studies (including mutagene-sis experiments) have shown that functional requirements place significantconstraints on sequencing even at nonactive site positions (Bowie and Sauer1989; Reidhaar-Olson and Sauer 1990; Chothia, Gelfland, and Kister 1998;

Axe 2000; Taylor et al 2001) In particular, Axe (2000) has shown that tiple as opposed to single amino acid substitutions inevitably result in loss

mul-of protein function, even when these changes occur at sites that allow ation when altered in isolation Cumulatively, these constraints imply thatproteins are highly sensitive to functional loss as a result of alterations insequencing, and that functional proteins represent highly isolated andimprobable arrangements of amino acids – arrangements that are farmore improbable, in fact, than would be likely to arise by chance, evengiven our multibillion-year-old universe (Kauffman 1995, 44; Dembski 1998,175–223)

vari-Of course, neo-Darwinists do not envision a completely random searchthrough the space of possible nucleotide sequences They see natural selec-tion acting to preserve small advantageous variations in genetic sequencesand their corresponding protein products Richard Dawkins (1996), for ex-ample, likens an organism to a high mountain peak He compares climbingthe sheer precipice up the front side of the mountain to building a neworganism by chance He acknowledges that this approach up “Mount Im-probable” will not succeed Nevertheless, he suggests that there is a gradualslope up the backside of the mountain that could be climbed in small in-cremental steps In his analogy, the backside climb up “Mount Improbable”

corresponds to the process of natural selection acting on random changes in

the genetic text What chance alone cannot accomplish blindly or in oneleap, selection (acting on mutations) can accomplish through the cumula-tive effect of many slight successive steps

Yet the extreme specificity and complexity of proteins presents a difficultynot only for the chance origin of specified biological information (i.e., forrandom mutations acting alone), but also for selection and mutation acting

in concert Indeed, mutagenesis experiments cast doubt on each of the twoscenarios by which neo-Darwinists envision new information arising from themutation/selection mechanism For neo-Darwinists, new functional geneseither arise from noncoding sections in the genome or from preexistinggenes Both scenarios are problematic

In the first scenario, neo-Darwinists envision new genetic informationarising from those sections of the genetic text that can presumably vary freelywithout consequence to the organism According to this scenario, noncod-ing sections of the genome, or duplicated sections of coding regions, canexperience a protracted period of “neutral evolution” during which alter-ations in nucleotide sequences have no discernible effect on the function ofthe organism Eventually, however, a new gene sequence will arise that cancode for a novel protein At that point, natural selection can favor the newgene and its functional protein product, thus securing the preservation andheritability of both

This scenario has the advantage of allowing the genome to varythrough many generations, as mutations “search” the space of possible base

sequences The scenario has an overriding problem, however: the size ofthe combinatorial space and the extreme rarity and isolation of the func-tional sequences within that space of possibilities Since natural selection

can do nothing to help generate new functional sequences, but rather can

only preserve such sequences once they have arisen, chance alone – randomvariation – must do the work of information generation – that is, of findingthe exceedingly rare functional sequences within a combinatorial universe

of possibilities Yet the probability of randomly assembling (or “finding,”

in the previous sense) a functional sequence is vanishingly small even on

a scale of billions of years Robert Sauer’s mutagenesis experiments implythat the probability of attaining (at random) the correct sequencing for ashort protein 100 amino acids long is about 1 in 1065(Reidhaar-Olson andSauer 1990; Behe 1992, 65–9) More recent mutagenesis research suggeststhat Sauer’s methods imply probability measures that are, if anything, toooptimistic (Axe 2000)

Other considerations imply additional improbabilities First, newCambrian animals would require proteins much longer than 100 residues toperform necessary specialized functions Susumu Ohno (1996) has notedthat Cambrian animals would have required complex proteins such aslysyl oxidase in order to support their stout body structures Lysyl oxi-dase molecules in extant organisms comprise over 400 amino acids Thesemolecules represent highly complex (nonrepetitive) and tightly specifiedarrangements of matter Reasonable extrapolation from mutagenesis exper-iments done on shorter protein molecules suggests that the probability ofproducing functionally sequenced proteins of this length at random is farsmaller than 1 in 10150– the point at which, according to Dembski’s calcula-tion of the universal probability bound, appeals to chance become absurd,given the time and other probabilistic resources of the entire universe (1998,175–223) Second, the Cambrian explosion took far less time (5× 106years)than the duration of the universe (2× 1010years) assumed by Dembski inhis calculation Third, DNA mutation rates are far too low to generate thenovel genes and proteins necessary to building the Cambrian animals, giventhe duration of the explosion As Susumo Ohno has explained:

Assuming a spontaneous mutation rate to be a generous 10–9 per base pair peryear it still takes 10 million years to undergo 1% change in DNA base sequences.

It follows that 6–10 million years in the evolutionary time scale is but a blink of aneye The Cambrian explosion within the time span of 6–10 million years can’t

possibly be explained by mutational divergence of individual gene functions (1996,8475)

The selection/mutation mechanism faces another probabilistic obstacle.The animals that arise in the Cambrian exhibit structures that would have

required many new types of cells, each of which would have required many

novel proteins to perform their specialized functions Further, new cell types

require systems of proteins that must, as a condition of function, act in close

coordination with one another The unit of selection in such systems ascends

to the system as a whole Natural selection selects for functional advantage.But new cell types require whole systems of proteins to perform their dis-tinctive functions In such cases, natural selection cannot contribute to the

process of information generation until after the information necessary to build the requisite system of proteins has arisen Thus random variations

must, again, do the work of information generation – and now not simplyfor one protein, but for many proteins arising at nearly the same time Yetthe odds of this occurring by chance are far smaller than the odds of thechance origin of a single gene or protein

As Richard Dawkins has acknowledged, “we can accept a certain amount

of luck in our explanations, but not too much” (1986, 139) The neutraltheory of evolution, which, by its own logic, prevents natural selection fromplaying a role in generating genetic information until after the fact, relies

on entirely “too much luck.” The sensitivity of proteins to functional loss asthe result of random changes in sequencing, the need for long proteins to

build new cell types and animals, the need for whole new systems of proteins

to service new cell types, the brevity of the Cambrian explosion relative tomutation rates – all suggest the immense improbability (and implausibility)

of any scenario for the origin of Cambrian genetic information that reliesupon chance alone unassisted by natural selection

Yet the neutral theory requires novel genes and proteins to arise –

es-sentially – by random mutation alone Adaptive advantage accrues after the

generation of new functional genes and proteins Thus, natural selection

cannot play a role until new information-bearing molecules have

indepen-dently arisen Thus the neutral theory envisions the need to scale the steep

face of a Dawkins-style precipice on which there is no gradually sloping

back-side – a situation that, by Dawkins’ own logic, is probabilistically untenable

In the second scenario, neo-Darwinists envision novel genes and teins arising by numerous successive mutations in the preexisting genetictext that codes for proteins To adapt Dawkins’s metaphor, this scenario en-visions gradually climbing down one functional peak and then ascendinganother Yet mutagenesis experiments again suggest a difficulty Recent ex-periments performed by Douglas Axe at Cambridge University show that,even when exploring a region of sequence space populated by proteins of

pro-a single fold pro-and function, most multiple-position chpro-anges quickly lepro-ad to

loss of function (Axe 2000) Yet to turn one protein into another with a

completely novel structure and function requires specified changes at many

more sites Given this reality, the probability of escaping total functionalloss during a random search for the changes needed to produce a newfunction is vanishingly small – and this probability diminishes exponentiallywith each additional requisite change Thus, Axe’s results imply that, in allprobability, random searches for novel proteins (through sequence space)will result in functional loss long before any novel functional protein willemerge

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sen-Francisco Blanco at the European Molecular Biology Laboratory hascome to a similar conclusion Using directed mutagenesis, his team hasfound that the sequence space between two natural protein domains is notpopulated by folded or functional conformations (i.e., biologically-relevantproteins) Instead, mutant sequences “lack a well defined three-dimensionalstructure.” They conclude:

[B]oth the hydrophobic core residues and the surface residues are important indetermining the structure of the proteins, and suggest that the appearance of a

completely new fold from an existing one is unlikely to occur by evolution through a

route of folded intermediate sequences [emphasis added].(Blanco, Angrand, and Serrano

1999, 741)

Thus, although this second neo-Darwinian scenario has the advantage ofstarting with functional genes and proteins, it also has a lethal disadvantage:any process of random mutation or rearrangement in the genome would

in all probability generate nonfunctional intermediate sequences beforefundamentally new functional genes or proteins would arise (Figure 20.1).Clearly, nonfunctional intermediate sequences confer no survival advantage

on their host organisms Yet natural selection favors only functional

advan-tage It cannot select or favor nucleotide sequences or polypeptide chainsthat do not yet perform biological functions, and still less will it favor se-quences that efface or destroy preexisting function

Evolving genes and proteins will almost inevitably range through a ries of nonfunctional intermediate sequences that natural selection will notfavor or preserve but will, in all probability, eliminate (Blanco et al 1999;Axe, 2000) When this happens, selection-driven evolution will cease At thispoint, neutral evolution of the genome (unhinged from selective pressure)may ensue, but, as we have seen, such a process must overcome immenseprobabilistic hurdles, even granting cosmic time

se-Thus, whether one envisions the evolutionary process beginning with

a noncoding region of the genome or a preexisting functional gene, the

functional specificity and complexity of proteins impose very stringent itations on the efficacy of mutation and selection In the first case, functionmust arise first, before natural selection can act to favor a novel variation.

lim-In the second case, function must be continuously maintained in order toprevent deleterious (or lethal) consequences to the organism and to allowfurther evolution Yet the complexity and functional specificity of proteinsimplies that both these conditions will be extremely difficult to meet There-fore, the neo-Darwinian mechanism appears to be inadequate to generatethe new information present in the novel genes and proteins that arise withthe Cambrian animals

novel body plansThe problems with the neo-Darwinian mechanism run deeper still In order

to explain the origin of the Cambrian animals, one must account not onlyfor new proteins and cell types, but also for the origin of new body plans.Within the past decade, developmental biology has dramatically advancedour understanding of how body plans are built during ontogeny In theprocess, it has also uncovered a profound difficulty for neo-Darwinism.Significant morphological change in organisms requires attention to tim-ing Mutations in genes that are expressed late in the development of anorganism will not affect the body plan Mutations expressed early in de-velopment, however, could conceivably produce significant morphologicalchange (Arthur 1997, 21) Thus, events expressed early in the develop-ment of organisms have the only realistic chance of producing large-scalemacroevolutionary change (Thomson 1992) As John and Miklos explain,

“macroevolutionary change” requires changes in “very early embryogenesis”(1988, 309)

Yet recent studies in developmental biology make clear that mutationsexpressed early in development typically have deleterious (or, at best, neu-tral) effects (Arthur 1997, 21), including mutations in crucially important

“master regulator” or hox genes For example, when early-acting bodyplan molecules, or morphogens such as bicoid (which helps to set up the

anterior–posterior head-to-tail axis in Drosophila), are perturbed,

develop-ment shuts down (Nusslein-Volhard and Wieschaus 1980; Lawrence andStruhl 1996) The resulting embryos die Moreover, there is a good reasonfor this If an engineer modifies the length of the piston rods in an internalcombustion engine without modifying the crankshaft accordingly, the en-gine won’t start Similarly, processes of development are tightly integratedspatially and temporally in such a way that changes early in development willrequire a host of other coordinated changes in separate but functionally in-terrelated developmental processes downstream Thus, as Stuart Kuaffmanexplains, “A mutation disrupting formation of a spinal column and cord ismore likely to be lethal than one affecting the number of fingers .” (1995,

200)