primate life histories

ARTICLES

Primate Life HistoriesCAROLINE ROSS

The link between body size and life-history characteristics has led to alarge number of studies that have in-

vestigated the nature of these relation-ships.3-8 Life-history characteristics of-ten scale with body weight in apredictable way so that body size infor-mation can be used to predict the lifehistories of species that cannot beobserved directly because they are ex-tinct or difficult to study. Despite this,descriptions of scaling relationshipsdo not tell us why life histories vary.They do not explain variation in bodysize, the form of the scaling relation-ship, or life history variation that isnot predicted by body size variation.Theoretical modeling, comparativestudies limited to primates, and intra-specific work that concentrates on thevariation of life histories within a spe-cies or population have all been usedto try and understand life history varia-tion. This review attempts to draw

these studies together to give an over-view of work on primate life histories.

COMPARATIVE LIFE HISTORIESAND ALLOMETRY

A large animal usually takes longerto grow to maturity than does a smallanimal. This simple observation mayat first seem to be intuitively easy toexplain. Few of us are surprised tohear that a small bushbaby can growto maturity in less than a year, whereasa large orangutan female will not startbreeding until she is more than 10years old. One might expect that alarge animal could take in more foodthan a small one and that a large babycould eat more and hence grow faster.This is in fact true. Orangutan infantsgrow at a rate of about 15 grams/daywhereas dwarf bushbabies grow only0.9 grams/day. But although the oran-gutan is 230 times heavier at birththan the bushbaby, it does not grow230 times as fast. In addition, thebushbaby has a head start on theorangutan: it is 12% of its adult size atbirth whereas the orangutan baby isonly 5% of its adult weight. This, to-gether with the bushbaby’s proportion-ately higher growth rate, means that itpulls ahead and reaches its adult sizelong before the orangutan does.

This example illustrates the allome-tric relationship between many life-

An animal’s life history can be summarized by key variables that account for its lifecourse from conception to death. Biological parameters that are of interest relate toreproductive effort and developmental rates (e.g., gestation length, neonatal weight,prenatal and postnatal growth rates, weaning age, and weaning weight) and the rateof reproduction (e.g., age at first and last reproduction, interbirth interval, the numberof offspring per litter, birth rate, and the intrinsic rate of natural increase [rmax]). Therather obvious fact that such variables differ from species to species and fromindividual to individual has been the subject of much interest since the late 1960s,following the observation that species seem to be arranged in a spectrum thatranges from small animals that breed rapidly and develop early, have many youngper litter, and have short lives, to large animals that breed slowly and develop late,have few young per litter, and have long lives.1,2

Caroline Ross is a member of the Ecologyand Evolutionary Biology Research Groupand a lecturer at Roehampton Institute Lon-don. She has carried out research intoprimate life histories using a comparativeperspective and is presently concentratingon the relationship between life historiesand patterns of infant care in primates andother mammals. She has also carried outfield work in India, looking at the social struc-ture and ecology of Hanuman langurs. She iscurrently collaborating with Dr. Mike Lawes ofNatal University on a research project lookingat the socioecology of blue monkeys (Cerco-pithecus mitis) at Cape Vidal, SouthAfrica.

Key Words: allometry; comparative analyses;ecology; mortality

54 Evolutionary Anthropology

history variables and body size. Mostlife-history variables are correlatedwith body size so that, within a giventaxon, knowledge of the size of ananimal can lead to fairly accurate pre-dictions of its life-history characteris-tics. The relationship with body size israrely a simple isometric one in whichlife-history characters vary in directproportion to body size, so that, forexample, an increase in body size (W)by 30% will correspond to an increasein the parameter (P) of 30%; i.e., P 5kW (where k is a constant). Rather, themore usual situation is that the param-eter will vary in an allometric fashionwith body size, so that the equationrelating the parameter (P) to body size(W) is of the form P 5 aWb, where aand b are constants. If this formula islogarithmically transformed, it de-scribes a straight line with a slope of bthat intercepts the Y axis at c. This isthe type of relationship that is foundfor the life-history parameters dis-cussed for the bushbaby and orangu-tan example. Larger primates do in-deed have higher growth rates andlarger neonates than do smaller pri-mates. However, the increases are notdirectly proportional to their bodyweight but are proportional to W0.75

and W0.85, respectively (Fig. 1).Many studies have examined the

nature of allometric relationships, bothin general3,4 and for primates specifi-cally.5-8 Such studies have tried to findthe value of the allometric exponents(the slope of the log-log plot) and toexplain the observed relationships withbody size. A primary aim of suchstudies has been accurate determina-tion of the allometric exponent, butthis is difficult for two reasons.9,10

First, it is not always clear whichstatistical method should be used todetermine the position of the best fitline through the data. Second, the bestfit line may be unduly influenced byspecies-rich taxa, in which case amethod to correct this bias must bechosen. Because these questions havebeen widely discussed,9-11 I will notdeal with them at length here. How-ever, anyone who is planning to under-take or understand allometric analy-ses should examine this problembefore embarking on their work.

The calculation of allometric rela-tionships has shown that scaling lawsseem to be remarkably constant across

a wide range of animals.3,4 In manycases the slopes of lines are very simi-lar, although their elevation may vary,giving ‘‘grade differences’’ betweengroups (Fig. 1). Once the allometriesof some variables have been calcu-lated, those of many others may bepredicted, for the allometric scaling ofone variable may well be linked to thatof another. For example, if the allome-tric exponent of growth rate in mam-mals scales to W0.75 (as it does) we canpredict (correctly) that age at maturityshould scale to W0.25. However, thisdoes not tell us the ultimate reasonsfor these relationships. The change inthe ratio of surface area to volumewith size, changes in foraging effi-ciency with size, and other ‘‘designconstraints’’ on physiology have allbeen suggested as playing a part inproducing allometric relationships. Asyet, however, the precise way in whichorganisms and environments interactto produce scaling ‘‘laws’’ has yet to beresolved.

PRIMATE LIFE HISTORIESCOMPARED WITH THOSE OF

OTHER MAMMALSAllometric relationships for many

primate life-history characters aresimilar to those of other mammals.This is true of the values of the slopesfor the logged values of neonatalweight, gestation length,5,12 weaningweight,13 and longevity,14 among oth-ers. Despite having a similar slopevalue, the intercept values for theselines are different, so that primatesgenerally have longer gestation lengthsand larger neonates, and live longerthan do other mammals of the sameweight.5,12,15 However, they are similarto other mammals in that they weantheir infants when they are at about athird of adult body weight.13

Primates differ from other mam-mals in the form of their relationshipbetween age at first reproduction andbody weight. A typical primate has alater age at first reproduction thandoes an ‘‘average’’ mammal of the samesize (Fig. 2).8,16,17 The late maturationof primates is linked to their slowpostnatal growth as compared to othermammals6,17-19 and gives rise to theirlow rate of population increase.8,20 Thelate maturation and concomitantly ex-tended infancy and adolescence of pri-

mates has been the subject of muchdiscussion, not least because humanshave evolved one of the longest prere-productive periods of any mammalianspecies.

Primates also differ in having ahigher allometric exponent for femaleage at first reproduction (AR) againstbody weight (Fig. 2) than do othermammals. This means that as sizeincreases, the difference between an‘‘average’’ mammal’s AR and an ‘‘aver-age’’ primate’s AR is greater at largerbody sizes. The difference in the scal-ing of AR has been noted by Char-nov,20 who links primate’s life-historydifferences to their unusual form ofbasic growth function (relating bodyweight (W) to growth rate): DW/dT 5AW0.75. The value of the constant A isapproximately 1 for most mammals,but for primates it is 0.42. This sug-gests that primates differ from othermammals in having very low produc-tion rates, so that they take longer togrow both themselves and their in-fants than do other mammals. Thismay also account for the slow breed-ing rate of primates.20,21

Why are primates different? Al-though Charnov and Berrigan’s21 ap-proach suggests that primates differ intheir production rate, it does not ex-plain why primates should have low Avalues. Although Charnov and Berri-gan21 suggest that the large brain ofprimates may lead to low values of Abecause of the high energetic de-mands of large brains, they point outthat snakes and lizards also have low Avalues but do not have large brains.

Alternatively, Janson and vanSchaik22 postulate that the low growthrate of primate species may be causedby a negative association between mor-tality rates and growth rates. Theyargue that primates may be increasingtheir chances of reaching reproductiveage if the disadvantage of delayingmaturity (i.e. increasing the time takento grow to reproductive age and hencehaving a long prereproductive phasein which death is possible) is out-weighed by an advantage of low mor-tality rates when growth rates are low.Janson and van Schaik’s models reston the assumption that juveniles aremore susceptible to food shortagesand are more likely to starve than areadults, partly because their small sizeand lack of experience leads to their

ARTICLES Evolutionary Anthropology 55

having a low feeding efficiency (theypresent some data to support thistheory). An additional problem for ju-veniles is their susceptibility to preda-tion which means that they cannotescape from competition over food bysimply keeping away from adults, butmust stay near the center of groups

and thus compete for food with largeranimals. If juveniles are susceptible tostarvation, a fast-growing juvenilewould be particularly at risk becauseof its increased food demands. Thispredicts that animals who feed onfood that is easy to find and process(such as folivores with unseasonal food

supplies) should have faster growthrates that species who have to copewith more difficult feeding problems(e.g. insectivores or frugivores withseasonal patchy food supplies). If Jan-son and van Schaik are correct a largebrain size may be correlated with de-layed maturation because a large brain

Figure 1. (a): Log10 Neonatal weight (N) versusLog10 body weight (W) for 81 primate species.Data are logarithmically transformed to give alinear relationship so that log10N 5 0.85 log10W20.63.17 The best fit lines illustrate the majoraxes for primate species (- - - - - -) and mammalspecies (-----), indicating that primates havelarger neonates than do other mammals ofthe same adult body size.5,12,17 (b): Log10 litterpostnatal growth rate versus Log10 body weight(grams) for primate subfamilies. The slope ofthe line is difficult to determine because of thegrade differences found within primates, but isprobably about 0.75.6,17,23 Symbols showingsubfamilies for figure 1b. T Lemurinae (includ-ing genera Lemur, Varecia); R Cheirogal-inae (Cheirogaleus, Microcebus); X Lorisinae(Arctocebus, Loris, Nycticebus, Perodicticus); NGalaginae (Galago); S Callitrichinae (Callithrix,Cebuella, Saguinus); V Callimiconinae (Cal-limico); 1 Aotinae (Aotus); 3 Cebinae(Saimiri); ¢ Cercopithecinae (Cercopithecus,Erythrocebus, Macaca, Mandrillus, Micopithe-cus, Papio); M Hylobatinae (Hylobates); QPonginae (Pan); U Hominae (Homo).

56 Evolutionary Anthropology ARTICLES

size is needed by animals that processfood in a complex way. Such animalswould also be expected to show lowforaging efficiencies in juveniles (whohave not learned the complex skillsneeded to feed) and hence be selectedto have a low maturation rate in orderto keep their food demands low. De-spite this there is no strong evidencethat growth rates, or any other lifehistory parameters, are correlated withdiet within the primate group8,17,23 al-though inclusion of more detailed di-etary data on seasonality and the prob-ability of food shortage might give adifferent picture.

Hence the ecological approach ofJanson and van Schaik suggests thatprimates could be selected to have lowA values because their ecologies selectfor a slow growth rate. Although Jan-son and van Schaik’s hypothesis maynot explain the whole story it doessuggest further avenues of research. Itmay be that other, less well studied,mammalian orders also have life his-tory allometries that are similar toprimates, or at least different from atypical mammal, if so these may shedsome light on this problem.

MODELS OF LIFE-HISTORYEVOLUTION: EXPLAINING

VARIATIONWhy do life histories vary, and why

are changes in some variables linkedto changes in other variables? Theseare the questions that models of life-history evolution seek to answer. Al-

though the details of such models dif-fer, they all assume that trade-offsbetween fitness components are impor-tant (Box 1). The theory of r and Kselection was the first comprehensivedescription of life histories, but itsexplanatory powers are limited by thelack of detailed consideration of mor-tality patterns.24,25 For this and otherreasons (discussed at length byStearns25), use of the traditional classi-fication of species into fast, r-selectedversus slow, K-selected is unlikely tolead to a better understanding of life-history evolution. More recent modelsemphasize the effect that age-specificmortality patterns would have on life-history evolution and on the relation-ship among mortality rates, growthrates, and reproductive rates (Box1).20,25,26 Such models appear to havegreater explanatory and predictivepower than does the r and K selectionmodel, with both theory20,21,25 andcomparative analyses26 suggesting thatmortality patterns are correlated withlife-history variables.

A comparative analysis of mammalsby Promislow and Harvey26 suggeststhat in mammals both high juvenilemortality and high adult mortality arelinked to an early age at first reproduc-tion when the affects of body weightare held constant. In addition, highjuvenile mortality rates are linked toshort gestation lengths, small young,large litters, high birth rates, and earlyweaning ages. If juvenile mortality ishigh, breeding early will decrease thechance that individuals will die before

reaching maturity and will favor moth-ers that produce large numbers ofsmall offspring. These are the resultspredicted by models of life-history evo-lution that incorporate age-specificmortality.20,25 However, the relation-ship between mortality and life historyis complicated by interactions be-tween juvenile and adult mortalityrates. If the effects of body weight arenot removed, an increase in juvenilemortality relative to adult mortalityresults in an early age at maturity,suggesting that relatively high juvenilemortality leads to early maturationand small adult body size. However, ifthe effects of body size are held con-stant, the relationship is reversed sothat for animals of a given size, rela-tively high juvenile mortality results indelayed maturation. It seems likelythat this relationship is the result ofbalancing the advantages of early ma-turity against the advantages of de-layed maturity that are found if older,larger mothers are more successful atraising their young.

LIFE HISTORIES AND PRIMATEECOLOGY

Age-specific mortality rate data areunfortunately available for only a fewprimate populations, making directtests of most life-history models impos-sible. For this reason, many studiesthat have tried to understand the evo-lution of primate life histories haverelied on the use of ecological vari-ables as substitutes for mortality data.Studies that try to relate life historiesto ecology generally assume that cer-tain types of ecology are likely to belinked to certain types of mortalitypatterns, i.e. that there is a relation-ship:

ecology G mortality pattern G life history.

The problem with such assumptionsis that the nature of the relationshipbetween ecology and mortality is rarelyunderstood. Despite this, the searchfor links between ecology and life his-tories may well be a productive one ina single taxon in which species have asimilar body design and physiology(such as the primates or arthropods).Such groups are likely to respond in asimilar way to their environment, sothat even if the influence of their ecol-ogy on mortality pattern is unknown,

Figure 2. Log10 female age at first reproduction versus Log10 body weight for primate species. Thebest fit lines illustrate the major axes for primate species (__) and mammals (- - - - - -), showing thedifferent elevations and slopes for the two groups.8,16


it is a least likely to be similar fromone species to another.

In primate studies it is generallyassumed that highly variable, unpre-dictable environments will lead to highlevels of mortality among individualsat all ages, but particularly amonginfants and juveniles. Such assump-tions are not supported (or, indeed,refuted) by direct evidence that usesmortality data from primate species.Hence, any link between ecology andlife-history characteristics in primatesdoes not necessarily support any onemodel of life-history evolution overanother. This may well beg the ques-tion of why we bother to look for suchlinks. One reason is that an indicationthat the life histories of some speciesin similar environments are similarmay indicate one or more likely expla-nations for a link that can then beinvestigated in more detail once mor-tality patterns are better understood.

Several ecological variables, includ-ing habitat, climate, and geographicalrange, have been suggested as mea-sures of environmental predictabil-ity.8,27-29 In most of these studies, theinfluences of body mass were firstexcluded from the analyses, as ecologyand body size are often closely linked.By excluding the influence of bodysize and by restricting analyses toclosely related species, it is hoped thatthe way in which ecology affects mor-tality patterns will be similar in allspecies, and hence, that links betweenecology and life-history parameterswill reflect variation in mortality pat-terns.

Using simple measures of habitattype, I have found that rates of popula-tion increase, as measured by the in-trinsic rate of natural increase (Box 2),varied with habitat type.8,29 When pri-mates were divided into five habitatgroups, species living in open, unpre-dictable habitats were found to havehigher rmax values relative to body sizethan did those in more predictablehabitats29 (Fig. 3). A similar patternwas found when the two most impor-tant components of rmax, birth rate andfemale age at first reproduction, arelooked at. Primates living in the moreunpredictable habitats have higherbirth rates and an earlier age at firstreproduction than do species living inmore stable and predictable habitats.However, the same study found no

Box 1: Trade-offs, mortality and life history evolution

. . . the average number of any animal or plant depends only indirectly on thenumber of its eggs or seeds.

In looking at Nature, it is always necessary to keep the foregoing consider-ations in mind—never to forget that every single organic being may be said to bestriving to the utmost to increase in numbers; that each lives by a struggle atsome period in its life; that heavy destruction inevitably falls either on the youngor old, during each generation or at recurrent intervals.

Darwin (1872, p. 49)49

Darwin’s theory of natural selection predicts that any heritable character thatincreases an organism’s contribution to forthcoming generations will be se-lected. This has often been taken to mean that selection will operate to increasefecundity to the maximum possible within the constraints of genetic variabilityand the environment.50 However, as Darwin noted, the production of largernumbers of young does not always lead to increased representation in futuregenerations. Modern evolutionary theory tends to explain this phenomenon interms of trade-offs. Models of life-history evolution realistically assume that anorganism’s fitness is limited by its finite resources and time for reproduction.This means that individuals must make ‘‘choices’’ when they use resources, andmay trade the advantages of one option for those of another. For example,animals may have either many small infants or a few large infants; the limitedresources they have for reproduction means that they cannot have infinitenumbers of large infants. Similarly, trade-offs may be made between invest-ments in young and investments in survival ability. If investing less than themaximum possible in one reproductive attempt increases a parent’s possibilityof survival, a lowering of reproductive effort per attempt may be advantageous.The balance of investment between reproductive effort and survival effort maychange through an animal’s lifetime as the probability of death and fecunditychange with age.

In many situations, individuals of a certain age are capable of producing moreyoung than are individuals of another age. In most mammals, fecundity initiallyrises with age and then falls off as the animal approaches the end of its life. Theinitial rise is caused by a variety of factors that may include the increase in bodysize with maturity or the attainment of a high rank in a social group that givesincreased access to food and mates. If there is a trade-off between survival andfecundity, it is not difficult to imagine that, in certain circumstances, it will beadvantageous to delay the age at first reproduction until an age at whichfecundity is high.

Variation in mortality rates due to environmental causes (extrinsic mortality)may influence the costs and benefits of different trade-offs in crucial ways. Forexample, if juvenile extrinsic mortality rates are high, animals are unlikely to beable to trade the disadvantages of delayed reproduction for the advantages ofincreased fecundity at a later age. Those that risk such a strategy are likely to diebefore they reach the age at which they can start to reproduce. Variation in adultmortality rates will also affect the potential advantages of trade-offs. Lowextrinsic adult mortality is more likely than high extrinsic adult mortality to lead toa trade-off of decreased fecundity against increased probability of adult survival.

Finding correlations between mortality rates and other life-history parametersmay be complicated by the fact that mortality is both extrinsic (due to outsideforces) and intrinsic (due to the very trade-offs discussed).26 Hence, an animalthat allocates a large amount of resources to reproduction may have a highmortality rate because extrinsic mortality is selecting for a high reproductiveeffort or because reproductive effort results in a high mortality rate, or both.Separating these causes of mortality needs a detailed knowledge of both thenatural history of a species and the way in which its mortality patterns vary withenvironment and alternative reproductive strategies.


link between growth rates, either pre-natal or postnatal, and any environ-mental measure. I originally inter-preted this result as indicating thatforest species were K-selected; that is,that their life histories were an adapta-tion to living in a predictable environ-ment with the need to be highly com-petitive.8,29 However, as Promislow andHarvey26 noted, an alternative andprobably better explanation is thatforest species have low mortality ratesfor their body size, a characteristicthat is associated with a low age at firstreproduction in mammals.

The broad correlations between re-productive rates and habitat type mayin part be a result of the fact that sometaxa of primates are more likely than

others to be found in unpredictablehabitats. For example, many of theOld World monkeys live in highly vari-able habitats and tend to have a rela-tively high rmax, whereas the apes aregenerally restricted to tropical forestsand have a relatively low rmax.28 Simi-larly, among New World monkeys thecallitrichids tend to be found in sec-ondary forest and edge habitats, andalso have a relatively high rmax ascompared to that of cebids.30 However,there are indications that life-historyvariation in primates is influenced bymore than phylogeny. Studies that con-centrate on closely related species havealso shown that habitat type appearsto be related to life-history strategy.

The eight species of continental

Asian macaques can be divided intotwo ecological groups. The first group(‘‘forest’’ macaques) is restricted to pri-mary broadleaf evergreen forests,whereas the second group (‘‘opportu-nistic’’ macaques) is found in a varietyof habitats, including highland areas,forest edges, and towns.31 Species thatare similar ecologically are not de-scended from a common ancestor andthere is no obvious link between phy-logeny and habitat type.31 In severalcases, species from the forest groupare broadly sympatric with opportunis-tic species. For example, in SoutheastAsia the opportunistic long-tailed ma-caque is found sympatrically with thelarger evergreen forest-living pig-tailedmacaque (Fig. 4). Similarly, in SouthIndia, the bonnet macaque is a wide-spread opportunistic species, inhabit-ing many forest types, villages, andtemple sites, whereas the lion-tailedmacaque is restricted to broadleaf ev-ergreen forest. These two types of ma-caques differ in their life histories.Forest macaques have longer inter-birth intervals, a later age at first repro-duction, and, hence, a lower rmax thando opportunistic species in the samearea.32

Explaining this pattern is not easybecause very few data are available onthe mortality patterns of wild ma-caques and none at all on forest spe-cies. However, the pattern may beconsistent with some age-specific mod-els of life-history evolution. Birth ratedifferences can be explained if speciesrestricted to primary broadleaf ever-green forest have lower mortality rates,perhaps because they are subject tolower predation rates or have a moreconstant food supply than do thosefound in secondary and deciduous for-est. Lower mortality rates after repro-ductive age would be predicted to leadto slower reproduction if a decrease infitness due to an increase in interbirthinterval was counteracted by an in-crease in fitness due to increasedchances of survival of mother andoffspring and consequent slowing ofreproductive rate.

Delayed maturity in forest habitatscan be explained if the advantages ofearly maturation are outweighed bythe advantages of increased survival ofoffspring born to older mothers. Oneindication that age-specific fecunditymight affect the life histories of ma-

Box 2: The intrinsic rate of natural increase, rmax

The value of rmax is a theoretical figure that can be taken as an indication of aspecies’ potential for ‘‘filling up’’ an available habitat; i.e., it is a measure of thespecies’ maximum rate of population growth that is possible when resources arenot limiting. The equation generally used for calculating rmax is based on theassumptions that the birth rate is constant, at least for the first few litters, andthat no mortality occurs until individuals have reached the age of last reproduc-tion.

The calculation of rmax using this method requires knowledge of only threeparameters: the earliest age at first reproduction in females (a); the maximumbirth rate of female offspring (i.e., the number of female offspring born per year)(b); and the maximum age at last reproduction (w). From these, rmax (r in theequation below) can be found by iteratively solving Cole’s50 equation:

l 5 e2r 1 be2ra 2 be2r(w 1 1).

It should be realized that the value of rmax differs from that of r, the latter beingan empirical value that is a measure of a population’s actual growth rate. Thatvalue will therefore include the effects of mortality before the age at lastreproduction is reached, the effects of variation in the birth rate with age, and theeffects of immigration and emigration on the population under study. Hayssen51

has argued that the value of r is more relevant than is rmax for studies on theinteraction between life histories and evolution. Her argument is that theassumptions that are made before rmax is calculated frequently are not valid fornatural populations, and that rmax is therefore not a suitable measure of apopulation’s capacity for growth. The assumption of 100% survival to age at lastreproduction is a serious objection to the use of rmax. However, the lack of dataon age-specific mortality rates and their effect on a population’s growth meansthat it is virtually impossible to remedy this situation and either estimate a valuefor r or measure it in natural populations. It is partly the simplicity of itscalculation that has led to general use of rmax instead of r.

Another advantage of using rmax is that it is a value that can be comparedbetween species without the confounding effects of local environmental influ-ence. Values of r for wild populations are rarely reported. Furthermore, evenwhen r values are available, their relevance to the evolutionary potential of thepopulation is often obscured by the fact that r can easily be altered by short-termclimatic changes or by human interference.


caques comes from a nonforest spe-cies, the Japanese macaque. This spe-cies lives in an extremely seasonalclimate and only about 40% of femalessurvive to reproductive age. However,there is little evidence that the speciesis capable of supporting an rmax ashigh as that of related species in sea-sonal climates. Even under captiveconditions, the r max of the Japanesemacaque is lower than that of otherspecies of opportunistic macaque be-cause females rarely start breedinguntil they are five years old.33,34 Thebest explanation for this late reproduc-tion suggests that delaying reproduc-tion increases the survival rate ofmothers and their offspring. Studiesof free-ranging animals suggest thatthe harsh conditions experienced bythe Japanese macaques do not allowmothers under a certain weight to rearinfants successfully,34 a situation thatis combined with strictly seasonalbreeding. Between the ages of fourand five years, a female’s weight in-creases from about 5.8 to 7 Kg. Four-year-old females are rarely largeenough to breed successfully and thosethat attempt to do so run a very highrisk of losing both their infant andtheir own lives.

Studies of other groups of relatedspecies also show a link between ecol-ogy and life-history strategy that maybe explained by age-specific models oflife-history evolution. For example,Rowell and Richards28 compared thematuration and breeding rates of cap-tive African monkeys and concludedthat open grassland species are faster-developing and faster-breeding thanforest species. This result was backedup by later work on wild popula-tions.35-37 Once again, this work isdifficult to interpret without detailedknowledge of mortality rates, andagain data is scarce, particularly forforest species. However, rapid develop-ment to maturity would be predictedto evolve in conditions where mortal-ity rates of infants, juveniles, andadults are high. This might be thecase, for example, if predation ratesare higher for open-country animals(although this may be questionable38).

How do Primates Achieve theBest Possible Life History?

Numerous lines of evidence suggestthat life-history variation is adaptive,with variation in mortality patternsbeing the vital link between environ-

ment and life-history traits. If this isthe case, animals need to have mecha-nisms that enable them to changetheir life histories to meet environmen-tal challenges. Such changes may oc-cur directly through the effect of natu-ral selection on genes that determinedevelopmental and breeding rates.Many reproductive traits have beenshown to be partly genetically deter-mined and hence responsive to selec-tion, provided genetic variability ismaintained in some way as, for ex-ample, balancing selection or environ-mental variability. For example, evi-dence from olive baboons has shownthat age at first reproduction is a highlyheritable trait in a captive populationin a uniform environment.39 Similarly,work on humans has shown that ageat menarche has a high heritability.40

But variation in life-history param-eters cannot be explained purely bygenetic variation. Many studies sug-gest that environmental effects are alsoimportant. If animals of a given geno-type can respond to different environ-ments in different ways, they may alsohave the ability to respond adaptivelyto environmental change. Physiologi-cal adaptation may play a part inproducing different responses and,hence, the optimum life-history forindividuals. (See Stearns’25 chapter 3for an excellent in-depth discussion of‘‘norms of reaction,’’ or the ways inwhich life-history variation may beproduced by an interaction betweengenotype and environment.) Adaptiveresponses might be seen when femalesdo not have access to adequate re-sources and respond by delaying repro-duction, thus trading low fecundity atan early age for increased fecundity ata later age. Age at first reproductionmay also be delayed if females whobreed late have better survival pros-pects than do those who breed at anearly age. Similarly, correlations be-tween birth rate and resource availabil-ity are to be expected if females tradefecundity costs for their own survivalbenefits or those of future offspring.

Some evidence that female primatesdo respond in this way to resourceavailability comes from work that re-lates reproductive parameters to fac-tors that affect access to resources.Studies have shown that animals hav-ing limited access to resources arelikely to delay reproduction as com-

Figure 3. The intrinsic rate of natural increase (rm) is related to habitat type in primate species.8,29

The figure shows habitat type and mean relative rm for 72 primate species (as in Ross29), whererelative rm 5 observed log10rm-expected log10rm. Habitat groups: 1, species restricted to orpreferring primary forest; 2, forest species not restricted to primary forest; 3, species restricted to orpreferring secondary and edge forest; 4, woodland species; 5, species found in highly seasonalhabitats.


pared to others having better accessand thus the ability to breed success-fully at an younger age (e.g., vervets41).Factors that relate to resource acquisi-tion, such as high rank for a female orher mother, have also been linked to

early maturation in primates species(such as savannah baboons42 and Japa-nese macaques43). Other studies haveshown a facultative response to in-creased food supplies, with better fedanimals having higher birth rates and

decreased ages at first reproduction ascompared with their unprovisionedconspecifics.44 These studies suggestthat although primate individuals tendto have a life history that is partlydetermined by their population’sevolved characteristics, these can beadjusted by a more immediate re-sponse to proximate cues.

Birth Rates and Infant CareFor primates that are selected, for

whatever reason, to increase their ratesof reproduction, there may be rela-tively few options available. Animalsthat are selected to have high rates ofreproduction are being selected to putresources into producing many in-fants and raising them rapidly. A pri-mate mother selected to increase herrmax can achieve this either by startingto breed at an earlier age or by increas-ing her birth rate. (Increasing the ageat last reproduction also increases thermax, but this influence is small com-pared to that of decreasing age at firstreproduction or increasing the birthrate). Because primates are a groupthat produce few infants, an increasein reproductive rate cannot easily beachieved by simply increasing thenumber of young that are produced.The successful raising of any morethan two infants per litter is just not anoption for an animal with only twonipples who must feed her infantsfrequently. Females who start to repro-duce at an early age may increase boththeir rmax and their total reproductivelifespan, but such early breeding mayimpose costs if females are not fullygrown or socially adept. In such situa-tions, increasing the growth rates ofher young and hence decreasing herinterbirth intervals may be the onlyway a female primate can producemore offspring. Recent work has shedsome light on one way that femaleprimates can increase their birth rate.

Numerous primate species exhibitsome kind of nonmaternal care.Among such species, care may be pro-vided by nulliparous females, juve-niles of both sexes, or adult males(usually the father or one of severalpossible fathers).45,46 In most casesthere are one or more reasons why anindividual might want to care for aninfant; most of these individuals areeither the infant’s relatives or are gain-

Figure 4. The a) long-tailed macaque (Macaca fascicularis) and b) pig-tailed macaque(Macaca nemstrina) are both found in in Southeast Asia, but the former is found in a range ofhabitats whereas the latter is restricted to evergreen forest. Photographs by DJ Chivers and JGFleagle.

a

b


ing social benefits from their caringbehavior. However, only mothers ofsome species allow others to care fortheir infants. Their willingness to giveup their infant to another is presum-ably related to the balance of the costs(the carer might harm or neglect theinfant) and benefits of relinquishingcare to another. Recent work hasshown that the best explanation forthis variation in maternal care behav-ior is that giving away infants allowsmothers to divert resources from somecaregiving activities to supplying theiroffspring with the resources they needto grow rapidly (Fig. 5).23,47,48 Infantsof species with nonmaternal care havehigh growth rates and are weanedearlier relative to body size than arespecies with a slower relative growthrate.

Interestingly, high infant growthrates do not appear to be correlatedwith other features of the animals’environment, such as diet, climate, orhabitat.23 Hence, it seems that earlyweaning is primarily a result of nonma-ternal care, which allows mothers toincrease their birth rate by decreasingthe time between births, and thus toincrease their rmax . Despite the appar-ent advantages of nonmaternal care, itwill not always be possible for moth-ers to find others to assume that care.Caregivers may not be available ortrustworthy, which possibly can leadto a lack of direct correlation betweenecology and growth rate. Selection for

rapid growth may also select for evolu-tion of either paternal or nonmaternalfemale care and hence for particulartypes of social living. Consequently,life history variation apparently is in-fluenced by maternal behavior and theavailability of nonmaternal caregiv-ers. This suggests that links betweensocial structure and life-history param-eters may be important in primates.

UNANSWERED QUESTIONSIt is clear that a complete under-

standing of the evolution of primatelife-histories is hampered by our lackof detailed knowledge of mortality pat-terns in most species. We have mortal-ity data for only a few species andcomplete life tables for even fewer.The data that are available come al-most entirely from Old World mon-keys, usually living in managed colo-nies or in relatively open-countryhabitats. Data from forest-living ani-mals and other taxa are almost nonex-istent. To answer many of the ques-tions that are raised by this study,more data from other groups must beobtained. This can be done only bylong-term studies. In particular, anunderstanding of the causes of bothintrinsic and extrinsic mortality willlead to a more complete understand-ing of the nature of trade-offs in life-history evolution.

The link between growth rates andallocare suggests that another impor-

tant area of research may be the in-vestigation of links among behavior,social structure, and life-history evolu-tion. Social structure may influencemortality patterns: for example, infantmortality may be related to maternalrank or the chances of infanticide, andthus affect other life-history variables.Much of the work done on the life-history characteristics of primates hasled to predictions that could be testedusing other taxa, something that israrely done by primatologists. We needto expand our horizons to look atother mammalian groups and to com-pare primates with other animals.Such an approach is particularly im-portant if we are to understandwhether or not primates really aredifferent from other mammals and, ifso, why?

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