6
Intraspecific Variability in Fertility and Offspring Survival in a Nonhuman Primate: Behavioral Control of Ecological and Social Sources

Jeanne Altmann and Susan C. Alberts

The great variability and complexity of human vital rates (age-specific survival and fertility rates) and of behaviors affecting these rates are topics of major investigation in many disciplines. The extent and nature of such variability for our closest nonhuman relatives are only beginning to be elucidated. Our goal in the present chapter is to investigate fertility and family behavior from the perspective of life histories—the schedules of vital rates—in a natural primate population. We do this by evaluating the potential fitness consequences, magnitude, and sources of variability in life histories, particularly of females, and in the behaviors affecting them.

Before doing so, we pause to place the life histories of both baboons (the focus of this chapter) and humans in a comparative mammalian perspective. Most evolutionary studies of life histories have been comparative within or among orders of mammals or even at higher taxonomic levels, and the answers to questions about life history variability and the behaviors affecting it are often quite different depending on the taxonomic level being investigated—vertebrates, mammals, primates, or a single species such as baboons or humans. Our brief comparative notes below are restricted to mammals. (In addition to the references that follow, the interested reader is referred to chapters in Boyce, 1988; Stearns, 1992; Charnov, 1993; Lee, 1999; many in Kappeler and Pereira, 2003; and references therein.)

INTERSPECIFIC, COMPARATIVE VARIABILITY IN MAMMALIAN LIFE HISTORIES

In studies that take a classical comparative approach, patterns of variability or constancy among species or higher taxonomic levels such as



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Offspring: Human Fertility Behavior in Biodemographic Perspective 6 Intraspecific Variability in Fertility and Offspring Survival in a Nonhuman Primate: Behavioral Control of Ecological and Social Sources Jeanne Altmann and Susan C. Alberts The great variability and complexity of human vital rates (age-specific survival and fertility rates) and of behaviors affecting these rates are topics of major investigation in many disciplines. The extent and nature of such variability for our closest nonhuman relatives are only beginning to be elucidated. Our goal in the present chapter is to investigate fertility and family behavior from the perspective of life histories—the schedules of vital rates—in a natural primate population. We do this by evaluating the potential fitness consequences, magnitude, and sources of variability in life histories, particularly of females, and in the behaviors affecting them. Before doing so, we pause to place the life histories of both baboons (the focus of this chapter) and humans in a comparative mammalian perspective. Most evolutionary studies of life histories have been comparative within or among orders of mammals or even at higher taxonomic levels, and the answers to questions about life history variability and the behaviors affecting it are often quite different depending on the taxonomic level being investigated—vertebrates, mammals, primates, or a single species such as baboons or humans. Our brief comparative notes below are restricted to mammals. (In addition to the references that follow, the interested reader is referred to chapters in Boyce, 1988; Stearns, 1992; Charnov, 1993; Lee, 1999; many in Kappeler and Pereira, 2003; and references therein.) INTERSPECIFIC, COMPARATIVE VARIABILITY IN MAMMALIAN LIFE HISTORIES In studies that take a classical comparative approach, patterns of variability or constancy among species or higher taxonomic levels such as

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Offspring: Human Fertility Behavior in Biodemographic Perspective FIGURE 6-1 Duration of several life history stages as a function of body size in anthropoid primates. SOURCE: Data primarily from compilations in Smuts et al. (1987), updated in Lee (1999) and references therein. genera are analyzed. Consequently, single species such as humans or baboons represent at most a single point in the analyses. From that coarse perspective, several generalities can be made about the life history traits of various mammals. First, these traits covary and cluster along a continuum, such that some species have “fast” life histories—rapid offspring growth rates, early maturation, high rates of reproduction, and short reproductive spans (high adult mortality). At the other extreme are species with “slow” life histories—low rates of offspring growth, late maturation, low rates of reproduction and adult mortality. Second, large-bodied mammals tend to have slow life histories, small-bodied ones fast life histories (see Figure 6-1 for anthropoid primates). Third, although this pattern of a fast-slow continuum can be seen in all orders of mammals, the tendency toward slow or fast life histories also differs greatly among the various orders of mammals—carnivores versus primates, for example. Mammals of the same size in different orders differ fairly consistently in slow or fast life history style, and primates, mainly anthropoid primates, have particularly slow life histories. Finally, another interesting feature of the fast-slow continuum is that many life history traits, such as growth rates and adult mortality rates

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Offspring: Human Fertility Behavior in Biodemographic Perspective (Charnov, 1993), remain strongly related to each other even when the effects of body size are removed; that is, constraints of size are not what lead to the correlation among traits, as was often assumed in many studies prior to the mid-1980s (see historical review in Harvey and Purvis, 1999). Both humans and baboons exhibit slow life histories; those of baboons are basically as expected for a primate of their size, whereas some aspects of human life histories tend to be slower than expected (but see, e.g., Hrdy, 1999, and Hawkes, 2002, regarding human “hyperfertility”). That is, primates in general and anthropoid primates in particular have life histories characteristic of much larger nonprimate mammals. They also have particularly long periods of immaturity. Our human quality-based lifestyle runs deep in our phylogenetic history, and we come from a lineage, a family tree, that has at each branch exaggerated or extended the slow lifestyle—to a considerable extent a trade-off of quantity for quality. What explains these patterns, the differences among mammalian orders and the correlations found among life history variables at higher taxonomic levels? Diverse answers to those questions have been proposed, both historically and currently, and the interested reader is referred to Charnov (1993, 2001), Kozlowski and Weiner (1997), the historical review and perspective provided by Harvey and Purvis (1999), and an application to human life history evolution based on Charnov’s approach in Hawkes (2002) and Hawkes et al. (2003). Most important, however, from the perspective of the current volume and the topic of this chapter—variability within a species, whether humans or baboons—is that good explanations of life history variability and correlations are not necessarily the same for all taxa or at all levels of investigation. The relationship among life history variables within species or populations often is, and is expected to be, different in direction, as well as strength, from that among orders (see, e.g., Lande, 1979; Harvey and Clutton-Brock, 1985; Emerson and Arnold, 1989; Lee et al., 1991; Worthman, this volume, for humans). For example, as a result of ecological sensitivity within, rather than among, species, large body size is often associated with large litters, early maturation, high reproductive rates, and low adult mortality rates, in striking contrast to the relationship of these variables among species of a given mammalian order. Life history theories that apply at one level cannot simply be extrapolated from that level to another—for example, from across mammalian orders or from differences among species within an order to variability within species (see, e.g., Lande, 1979; Emerson and Arnold, 1989; Kozlowski and Weiner, 1997).

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Offspring: Human Fertility Behavior in Biodemographic Perspective BABOON LIFE HISTORIES: LIFE HISTORY PATTERN AND VARIABILITY Comparative studies serve to anchor our perception of human or non-human primate traits to our shared biological history and some basic relationships such as those among body size, phylogeny, and life histories. They leave unanswered, however, questions about current dynamic patterns that are shaping behavior, life history variability, ecological responses, and evolutionary potential within species. These require analyses of lifetimes and of the factors that influence them. Here we present two analyses of life history variability in savannah baboons. First, we use matrix demography models to examine the relative strength of selection on different vital rates. In particular, we examine the sensitivity of fitness to comparable changes in infant survival and adult fertility. Second, we evaluate the variability existing in a natural population and the extent to which behavior, particularly choice of habitat and social environment, affects vital rates for both females and males. Until recently, humans were the only primate species for which the requisite life history data were available for detailed analysis of life history variability (see Blurton-Jones et al., 1999, and Kaplan and Lancaster, this volume, and references in both). However, for a small handful of species, these data are accumulating for at least some life history components, and we provide here one of the first such analyses for the large, sexually dimorphic, predominantly terrestrial and highly social baboon, Papio cynocephalus. Selective omnivores, baboons are widespread throughout Africa and occupy a broad range of habitats from mountain through woodland and savannah to semidesert. The data presented here derive primarily from a study underway for more than three decades of the Amboseli baboon population, which resides in the basin to the north and west of Mount Kilimanjaro. Baboons Baboons live in discrete social groups. Members of a group forage during the day and sleep at night in much closer proximity to each other than to members of other groups, and virtually all social interactions are among members of the group of residence. A female usually spends her whole life in the group into which she was born, whereas a male leaves his natal group around the time he attains full adulthood at 8 years. Although groups are sometimes in close proximity, the boundaries are usually very clear, spatially as well as behaviorally. The amount of time that groups spend in close proximity is of relatively short duration and can be somewhat tense, even in habitats or years in which these encounters are rela-

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Offspring: Human Fertility Behavior in Biodemographic Perspective tively more frequent (e.g., Cheney and Seyfarth, 1977; Shopland and Altmann, 1987). Within groups, adult females form clear dominance hierarchies that are predominantly stable both within and across generations as juvenile daughters assume the “family rank” about a year before menarche. Dominance rank in males, in contrast, is much more highly dependent on size and strength and is highly age dependent and unstable (Alberts et al., in press; Packer, 1979; Packer et al., 2000). The larger African carnivores—leopards, lions, and hyenas—prey on baboons and are a particular a risk at night. In each habitat where they are found, members of a baboon group sleep close together either on cliff edges or high in those trees in their habitat that would be the most difficult for a predator to climb. Of the two major tree species in Amboseli, for example, baboons prefer fever trees, Acacia xanthopholea, to umbrella trees, A. tortilis; fever tree branches are higher off the ground, smoother, and more vertical. For baboons the distribution of sparsely scattered nighttime roosts, as well as of potable water and food resources, affects patterns of encounters between groups, daily travel, and seasonal variability in these patterns. In Amboseli, baboons of the fully wild-foraging groups awaken and descend from their sleeping trees shortly after dawn. For the next 11 to 12 hours, they spend almost 75 percent of their time foraging—feeding or traveling to food—across their short-grassland savannah habitat, approximately 10 percent socializing, and the remainder resting, often in a midday siesta. Baboon infants weigh a little less than 1 kg at birth. In the first few months of life the infant clings to its mother’s ventrum and thereby obtains continuous nipple access and transportation during the 8 to 10 km of daily travel. Gradual nutritional and locomotor independence develops during the next year until the infant’s mother conceives again when the infant is about 18 months old and weighs approximately 3 to 4 kg. Although adult male baboons are approximately double the body mass of adult females, infant and juvenile females are very close in size to their male age peers, and almost all of the sexual dimorphism in body size arises during an adolescent growth spurt in males after females reach menarche between 4 and 5 years of age. Life History Patterns in Amboseli To analyze baboon life histories and life history variability, we used data collected from 1971 to 1999 for approximately 600 individuals living in completely wild-foraging groups of baboons (Alberts and Altmann, 2003). We constructed life tables with 1-year age classes and the corresponding survivorship and fertility entries of a population projection matrix, shown for females in Table 6-1 and males in Table 6-2. The tables also

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Offspring: Human Fertility Behavior in Biodemographic Perspective TABLE 6-1 Per Annum Vital Rates for Wild-Foraging Amboseli Baboon Females (1971-1999) by One-Year Age Classes for Analysis in Projection Matrix Models Female Age Class Entries in Population Projection Matrix Elasticity Age-Specific Birth Rate Survivorship Fertilitya Survival Fertility 1 0.7910 0 0.0972 0 0 2 0.8884 0 0.0972 0 0 3 0.9366 0 0.0972 0 0 4 0.9688 0 0.0972 0 0 5 0.9529 0.1281 0.0906 0.0066 0.0083 6 0.9439 0.2719 0.0778 0.0128 0.3056 7 0.9481 0.2747 0.0661 0.0117 0.3500 8 0.9483 0.2639 0.0558 0.0103 0.3085 9 0.9427 0.2590 0.0466 0.0092 0.3256 10 0.9233 0.2230 0.0395 0.0072 0.2973 11 0.8910 0.1975 0.0338 0.0057 0.2429 12 0.8943 0.2303 0.0281 0.0057 0.2459 13 0.9419 0.2607 0.0226 0.0055 0.3273 14 0.9160 0.2588 0.0177 0.0050 0.3000 15 0.8701 0.2833 0.0129 0.0048 0.3333 16 0.8731 0.3000 0.0086 0.0042 0.3784 17 0.7880 0.2647 0.0055 0.0032 0.3704 18 0.6329 0.2162 0.0035 0.0020 0.3158 19 0.6278 0.2433 0.0022 0.0013 0.3000 20 0.8648 0.1832 0.0016 0.0006 0.4286 21 0.7455 0.2391 0.0009 0.0007 0.0000 22 0.5517 0.3207 0.0003 0.0006 0.7500 23 0.6090 0.1302 0.0001 0.0001 0.0000 24 0.4174 0.2138 0 0.0001 0.5000 25 0.3796 0 0 0 0 26 0.5000 0 0 0 0 27 0 0 0 0 0 a The fertility entries in the third column are the elements in the first row of the Leslie matrix, computed from the age-specific birth rates in the last column along with the person-years-lived entries from the estimated life table. The fertility entries take into account both adult survival in the interval and birth rate to individuals in that interval; it is based on the full cohort that enters an age class, whether they survive the age class or not. Because baboons, like humans, do not have a distinct birth season, our calculations are based on a birth flow model. For details, see Caswell, (2001), Alberts and Altmann (2003). contain age-specific birth rates and elasticities, which will be discussed shortly. As evident in the tables, Amboseli baboons experience high infant mortality, much lower female mortality during the late juvenile and early adult years, and then gradually increasing mortality in the latter portion of

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Offspring: Human Fertility Behavior in Biodemographic Perspective TABLE 6-2 Per Annum Vital Rates for Wild-Fraging Amboseli Baboon Males (1971-1999) by One-Year Age Classes for Analysis in Projection Matrix Models Male Age Class Entries in Population Projection Matrix Elasticity Age-Specific Birth Rateb Survivorship Fertilitya Survival Fertility 1 0.7825 0 0.1066 0 0 2 0.9122 0 0.1066 0 0 3 0.9337 0 0.1066 0 0 4 0.9167 0 0.1066 0 0 5 0.9588 0 0.1066 0 0 6 0.9427 0.3734 0.0948 0.0117 0 7 0.9390 0.7759 0.0743 0.0205 0 8 0.9416 0.7791 0.0570 0.0173 0.0667 9 0.9311 0.7663 0.0428 0.0143 0.5754 10 0.9112 0.7423 0.0313 0.0115 0.8155 11 0.8944 0.7221 0.0222 0.0091 0.6493 12 0.8820 0.7074 0.0151 0.0071 0.8176 13 0.8456 0.6652 0.0099 0.0052 0.5543 14 0.8295 0.6467 0.0060 0.0038 0.4919 15 0.7816 0.5950 0.0034 0.0026 0.3007 16 0.6665 0.4747 0.0020 0.0015 0.3326 17 0.6251 0.4334 0.0012 0.0008 0.0776 18 0.8002 0.6252 0.0005 0.0006 0.0647 19 0.7500 0.5859 0.0001 0.0004 0.0485 20 0.3333 0.2131 0 0.0001 0.0776 21 0 0 0 0 0 a The fertility entry takes into account both adult survival in the interval and birth rate to individuals in that interval; it is based on the full cohort that enters an age class, whether they survive the age class or not. Because baboons, like humans, do not have a distinct birth season our calculations are based on a birth flow model. For details, see Caswell (2001) and Alberts and Altmann (2003). b Our calculation of birth rate (and therefore fertility) for males is based on the proportion of mating attributable to males of that age class (see text and Alberts and Altmann, 2003, especially p. 78 and Appendix 4.1 for reproductive rate terminology). the second decade of life (see also Bronikowski et al., 2002). Only a small proportion of individuals live into their third decade. At all three long-term field sites—Gombe and Mikumi, Tanzania, and Amboseli—maximum recorded longevity is 26 to 27 years (Gombe: Packer et al., 1995, and Bronikowski et al., 2002; Mikumi, estimated: Rhine et al., 2000; Amboseli: Bronikowski et al., 2002, and Alberts and Altmann, 2003). Mortality rates for subadult and adult males are somewhat higher than those for like-aged

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Offspring: Human Fertility Behavior in Biodemographic Perspective females, reflecting a common mammalian sex difference. For the Amboseli baboons, this sex difference probably derives from a combination of intrinsic and extrinsic causes of senescence and mortality, including the mortality risk of dispersal (Alberts and Altmann, 1995). Known-age males of 15 to 18 years look much older and more frail than their female age peers.1 Menarche in baboons is followed by a period of somewhat abnormal sexual cycles and adolescent sub-fertility, followed by several normal cycles, conception, and then a 6-month gestation period; as a result, females produce their first offspring (Table 6-1) approximately 18 months after menarche. A long period of relatively steady birth rates follows until early in the third decade of life for the few females who live that long. These patterns are identifiable from near-daily records of menstruation, probabilistic visual correlates of ovulation, and other aspects of reproduction that are readily observed in baboons (Altmann et al., 1977, and references therein). Interbirth intervals after a surviving offspring are almost 2 years at various sites; if an infant dies, the interval is much shorter as its mother resumes cycling within a month and conceives after only one or two cycles. Estimating male offspring production is more problematic and requires more caution in interpretation. In baboons, male dominance status is highly age related, dominance is a good predictor of mating behavior when a female is fertile, and observed mating behavior is a good predictor of genetic paternity (Altmann et al., 1996; Alberts et al., in press, and references therein). We used age-specific mating behavior to make proportional paternity assignments for males of each age; the total conception rate of males is constrained to and determined by that of females. Male offspring production declines much more rapidly with age than do birth rates of females, and the sex difference in this decline is much greater than that for survival (Tables 6-1 and 6-2). A General Approach to Evaluating the Relative Strength of Selection on Different Vital Rates: Perturbations of Female Life Histories Using Matrix Models If one were to compare two family lineages within a population, one lineage in which investment is successfully directed toward increasing infant survival and another in which it is successfully devoted to increasing birth rates, which would be more effective in enhancing population growth 1   The estimate of person-years lived in the first year of life used to construct the projection matrix entries is 0.8551 years for females, and the net reproduction ratio—the usual NRR known to demographers, but also referred to as the net reproductive rate (Caswell, 2001)—is 1.50. This large an NRR could not have been sustained over evolutionary time and reflects only immediately prevailing conditions.

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Offspring: Human Fertility Behavior in Biodemographic Perspective or lineage fitness? Would enhanced parental care be favored or enhanced mating effort? The answer depends in part on the species’ basic schedule of mortality and birth rates, on the extent and style of fast or slow life history. Focusing the question on anthropoids, given the general pattern of age-specific mortality and fertility found in humans and other large primates (a slow life history), what would be the relative impact on biological fitness of two different behavioral changes, each of which appeared in some individuals, one a behavioral change that produced a small proportional change in infant mortality, the other a behavioral change that produced a small proportional change in birth rates? Demographic matrix models are a useful tool for exploring this question. (For a fuller discussion of these models, see references, below, and Alberts and Altmann, 2003, for an introduction to matrix models in the context of primate life history analysis.) A matrix model is based on age-specific survival and fertility rates (from life tables). The model used is the usual Leslie matrix projection model, with one-year-wide age groups, familiar to demographers. Notation follows Caswell (2001). The model generates two results that are of particular interest for our purposes. The first result, λ, is a measure of the projected population growth rate. This measure equals er, where r is Lotka’s intrinsic rate of natural increase. The measure is also equivalent to the relative fitness of the life history described by the vital rates (Lande, 1982a, 1982b; see also McDonald and Caswell, 1993, and Caswell, 2001). The second result is elasticity (or sensitivity) measures, which provide a simple means to explore effects on λ of variability or small perturbations in the initial vital rates. These analyses are of particular relevance to a consideration of the life history consequences of fertility and parental behavior. Each vital rate (each age-specific mortality or fertility rate) in a matrix model will have a characteristic sensitivity, which is an estimate of the impact on λ of a small change in that vital rate (the slope of the vital rate function at that point) with all others held constant. Sensitivities cannot be compared directly because they are based on different rates. Elasticities are more useful; they are sensitivities that have been scaled so that their sum for both fertility and survival across all age classes is 1; they can be directly compared (see, e.g., Benton and Grant, 1999). A vital rate (in our case fertility or survival in a 1-year interval) with large elasticity is one for which small changes result in a relatively large change in λ compared to the effect on λ of a small change in the other vital rates. During the past two decades, matrix models have been greatly extended and many constraining assumptions have been relaxed (Caswell, 2001, and chapters in Heppel et al., 2000, and references therein). Concurrently these models have increasingly been applied to natural populations in studies of population viability and conservation (e.g., Heppel et al., 1994; Crooks et al., 1997; Mills et al.,

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Offspring: Human Fertility Behavior in Biodemographic Perspective FIGURE 6-2 Proportion of elasticity in the matrix model attributable to immature survival, fertility, and adult survival. NOTE: The greater proportion attributable to immature versus mature survival for males derives solely from the later maturity of males than females. SOURCE: Data from Tables 6-1 and 6-2. See text and Alberts and Altmann (2003) for details. 1999), ecology (e.g., chapters in Heppell et al., 2000), and the evolution of behavior (McDonald, 1993; McDonald and Caswell, 1993). If we return to the two lineages, one that invests in effective infant care versus the other that invests in an effective increase in fertile matings, we can compare—for example, in the Amboseli case—survival elasticities of young infants (age class 1) to fertility elasticities of adults (Table 6-1, Figure 6-2 ). For baboon females in Amboseli, a small increase in an infant’s survival during the first year of life will have a much greater impact on λ—up to two orders of magnitude greater—than a proportional increase in female fertility in any age during adulthood. Specifically, the elasticity of survival for age class 1 is 0.0972, whereas the elasticity of fertility is 0.0128 at its highest, in age class 6, and declines to an order of magnitude less, 0.0013, by age 19. The importance of survival versus fertility is evidenced by the fact that, for Amboseli baboons, survival accounts for 91 percent of the total elasticities and fertility for only 9 percent, for both males and females (Figure 6-2; see also Alberts and Altmann, 2003), a common pattern in long-lived species (discussion in McDonald, 1993, for avian species). The implication of these results for, say, an individual making alternative behavioral or investment decisions is complicated. Interpretation depends partially on whether these are lifetime decisions affecting at once fertility or

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Offspring: Human Fertility Behavior in Biodemographic Perspective offspring survival for all years, flexible year-to-year options, or perhaps age-specific decisions (e.g., by young adult or old females). Interpretation also depends on the mechanisms and costs of each type of change; and on whether a key assumption of sensitivity analysis, independence among vital rates, is violated. One example illustrates some of the potential issues in the case of baboons, although it is applicable to many other species. For an older female, the balance would always seem to favor investment in a current infant’s survival rather than in increased fertility (producing another infant). In contrast, for a young adult female in a particular year, a small increase in fertility that year might seem to balance an increase in survival of that single year’s infant; however, if infant survival is dependent on maternal care, that is, the independence assumption of sensitivity analysis is violated, the mother’s increase in fertility is likely to produce a decrease in the current infant’s survival rather than leaving it unchanged. For wild-foraging baboons, this is the case even if the current infant is in its second year of life. If the current infant is less than a year old, its death is almost assured if its mother dies or is caring for another infant. Moreover, as we shall see in the next section, the calculus may vary by ecological and social conditions (see also Hrdy, 1999; Ellison, 2001; Worthman and Kaplan and Lancaster chapters in this volume, for discussion of this topic in humans). This example highlights several limitations or cautions that apply to interpretation of this simple matrix model and of sensitivity analyses in particular. One is the aggregate approach to the vital rates; that is, age classes are treated as groups of homogeneous individuals. Another is that vital rates are assumed to be independent of each other. Both of these assumptions are surely violated to varying degrees. A particularly important example of lack of independence is the case of male fertility rates; male fertility has been calculated by apportioning total female fertility across male age classes according to observed age-specific patterns of mating. Thus, an increase in fertility for one male age class is necessarily accompanied by a decrease in fertility for another. Another example is the situation in which trade-offs between female survival and reproduction or between future reproduction and survival of current offspring (example above) are significant. A third concern about sensitivity analysis is that infinitesimal, independent changes from one set of initial values may not be predictive of responses to larger and otherwise more realistic changes or for changes from a different set of initial vital rates because the fitness function for a vital rate is often not linear (e.g., Pfister, 1998; see also papers in Heppel et al., 2000). An important complement to sensitivity analysis is direct perturbations of the matrix. Direct perturbation permits manipulation of a matrix to create hypothetical scenarios that are within the range, magnitude, and

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Offspring: Human Fertility Behavior in Biodemographic Perspective FIGURE 6-6 Age of reproductive maturity and reproductive rate (measured as in Figure 6-5) are functions of social status. NOTE: High-ranking females experience higher reproductive rates and their offspring mature at younger ages than do low-ranking females (after controlling for changes in foraging environment and group size). of other adult males in the group. As a consequence, adult males disperse among groups. That is, the costs entailed by living with many other adult males are often avoided or at least mitigated by dispersal to groups with more favorable demographic makeup (Alberts and Altmann, 1995; Altmann, 2000). The relationship between dominance status and mating success in male cercopithecines has a long, controversial, and yet well-documented history. Across species, among baboon populations, and within a single population over time (Amboseli), the relationship accounts for approximately 50 percent of the variance in male mating success but is highly variable (Alberts et al., in press). In most species and populations, male dominance status is strongly negatively associated with age (Alberts et al., in press; Packer et al., 2000). Males who stay in a large group or a group in which they are not of high rank sometimes use coalitions and other social means of enhancing fertility (Alberts et al., in press; Noë and Sluijter, 1990, 1995; Packer, 1977). Some older males who had previously been top-ranking and the father of many offspring also stay in groups in which

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Offspring: Human Fertility Behavior in Biodemographic Perspective FIGURE 6-7 Daughters’ social status as predicted by that of their mothers. NOTE: For maternal birth ranks 1 through 10 (left side of the figure), this effect is clear and strong (double that expected for a completely heritable trait). No effect occurs beyond rank 10 because group fission occurs beyond this size; females of different matrilines retain the predicted rank relative to each other in the fission products, but at the time of fission the new smaller groups have had 10 or fewer adult females in the wild-foraging groups (three fission events). their fertility is low. They often provide care and protection for their likely offspring and are thought to reduce the likelihood of infanticide by other males (most recently reviewed in van Schaik and Janson, 2000, and Palombit, 2003), potentially gaining a few matings through female choice rather than dominance status (e.g., Strum, 1982; Smuts, 1985) but also potentially choosing enhancement of offspring survival over greater mating opportunities. In summary, by altering their home range and their social environments through dispersal (males) or group fission (females), both males and females use behavior to change their physical and social environments. In the process, they often mitigate the effects of low social status, in ways that enhance fitness and sometimes in ways that particularly enhance offspring survival and quality (see Figure 6-8).

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Offspring: Human Fertility Behavior in Biodemographic Perspective FIGURE 6-8 Overview of behaviors affecting fertility and offspring survival by fully wild-foraging baboons in Amboseli over three decades. NOTE: The baboons shifted home range when the habitat in their previous range degenerated. Offspring then experienced higher rates of survival and matured at younger ages, and females reproduced more often if their offspring survived. As a result, immediate experienced density (group size and number of adult females per group) increased and reproductive rate then declined as a result of socially constrained reproduction. Group fission followed, removing the density and social constraints. Covariance of Life History Components We started with elasticity analyses that assumed independence among life history components. Violations of this assumption may sometimes be significant, and future analyses will need to explore the dependences. From a broad evolutionary perspective, strong linkages among life history variables in the form of life-history “invariants,” are central to Charnov’s comparative (interspecific) approach to the evolution of life histories (e.g. Charnov and Berrigan, 1993; Charnov, 2001, applications to human evolution in Hawkes, 2002, and references therein). Some of the same correlations may pertain at the level of intraspecific variability as well. However, life history correlations are usually weaker or even in the opposite direction in populations or species than at higher taxonomic levels (see Harvey and Clutton-Brock, 1985; Emerson and Arnold, 1989; Kozlowski and Weiner, 1997; Worthman, this volume). Within a population, some life-history components may be positively correlated because of shared underlying processes (discussed with particular focus on humans in Hrdy, 1999, and Ellison, 2001, and references in both). Under those conditions, behavioral changes will result in several rates increasing or decreasing together. This was seen for infant survival and early maturity in the Amboseli analyses. In other instances, individuals face trade-offs. For instance, producing another infant may inflict higher mortality risk on the mother herself or on her current infant (e.g., Altmann et al., 1988, for baboons). For the Amboseli baboons, we find that these trade-offs seem to be ecologically contingent;

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Offspring: Human Fertility Behavior in Biodemographic Perspective they are evident only in the most stringent ecological habitats or years (Altmann et al., 1988). Not only might vital rates be correlated within individuals, but the actions of one individual can affect reproduction and offspring survival of another. The most obvious instance is the effect of either parent’s behavior on the successful reproduction of the other, particularly in socially monogamous or polyandrous species. The phenomenon is more general, however, as in the case of alloparental care by siblings, grandparents, or other, perhaps more distant, relatives in which one individual may enhance the reproduction of another at a cost to its own reproduction. Enhanced fitness through the actions of others has been postulated for the evolution of alloparental care among some primate species and more specifically as an explanation for humans having “faster” reproductive rates than expected for their body size and otherwise slow life history components (see particularly Hrdy, 1999; Ross and McLarnon, 2000; Hawkes, 2002, and references therein). Covariance and other constraints, within and among individuals, are even more complicated for males. If males cannot appreciably affect total offspring production—that is, if offspring production is determined solely or even primarily by females— increased paternity in one age class will be offset by decreased paternity at other ages, and realistic perturbation analyses for males will need to take this trade-off into account. The analyses presented here provide clear evidence of behavior that enhances fertility, offspring survival, and offspring quality. Changes in reproductive rates were most pervasive but not of greatest magnitude. Changes in foraging environment affected each parameter but most greatly affected offspring survival. In addition, daughters of low-status females matured later. The matrix model perturbation results raised the possibility that female baboons faced with alternatives might benefit from biasing decisions in favor of offspring survival and quality rather than enhanced fertility. The extent to which baboons are actually faced with such behavioral and life history trade-offs and behave as predicted is not yet clear. Both the simple models themselves and departures from their assumptions, such as population substructure, covariance, and stochastic variability, serve to guide future models and empirical investigations. Furthermore, that the social and environmental factors to which the baboons respond covary and feed back on each other is obvious (Figure 6-8) and is of necessity a topic of future theoretical and empirical investigation. Natural populations of nonhuman primates are relatively small and therefore present challenges to investigations of complexity and change over time, challenges that compound those already inherent in study of species with slow life histories.

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Offspring: Human Fertility Behavior in Biodemographic Perspective CONCLUSIONS Over a three-decade period, encompassing at least part of the lives of six generations of baboons and just surpassing the full lifetime of the longest living of the animals, individuals experienced great diversity of environmental and social conditions. These included normal wet and dry seasons; years of abundance and others of drought; many close relatives for some individuals or at certain times and few for others; habitat degeneration in the original home area and availability of not-too-distant areas with rich, new opportunities; groups with many competitors or with few. Groups of individuals, and also individuals acting somewhat independently, altered the physical and social conditions in which they lived and thereby considerably changed, through their own behavior, their own reproductive lives and the opportunities provided to their offspring. Environmental variability has been proposed as the critical environmental context of human evolution (e.g., Potts, 1998). We suggest that adaptation to variable and changing environments is likely to have been an important feature of primate evolution more broadly. Success at responding to environments that change on various temporal and spatial scales and with varying degrees of predictability may be a recurrent theme for the most enduring and widespread primate lineages that we see today and for those likely to persist into the future. Because differences in survival of immature young will have the greatest impact on population growth and individual fitness for species with life histories characteristic of human and nonhuman primates, understanding fertility, parental behavior, offspring behavior, and the mechanisms producing variability in each must of necessity hold a central place in understanding primate adaptation and human origins. For nonhuman primates as for humans, pregnancy, parturition, and offspring rearing occur within a complex ecological and social context. Few would question that the context of human fertility and parental care behaviors is highly variable and that humans both adjust their behavior to context and are often the agents of altering that context (e.g. Hrdy, 1999; Ellison, 2001; Worthman this volume; and references in each of these). That such variability and agency may also be significant in the lives and evolutionary history of our nonhuman primate relatives has not received comparable status. The opportunity to begin to do so offers considerable potential both for understanding primate behavioral ecology and evolution and for providing a window into human origins and diversity. Together, the present analyses provide just one piece in beginning to elucidate the conditions, extent, mechanisms, and individual variability in richness of behavioral complexity related to fertility and offspring care in

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Offspring: Human Fertility Behavior in Biodemographic Perspective natural primate societies. Future research will benefit from the use of more complex matrix demography models—for example, ones that incorporate temporal heterogeneity and covariance among life history components (Caswell, 2001). Studies of physiological mechanisms, ontogenetic effects, the effect of life history trade-offs on observed behavior (see above), and heritable differences in fertility and parental behaviors will also be essential to the agenda of elucidating ecological and evolutionary perspectives on fertility and parental care behaviors in nonhuman primates. The origin of both an absolutely and a relatively long period between birth and maturation in humans is seen among other large anthropoids. That this period of immaturity historically held and currently holds great opportunities for evolution is unsurprising. Increased links between studies of human and nonhuman primates, and of mechanisms and behavioral ecology, are essential to enhancing the research agenda of each. ACKNOWLEDGMENTS We thank the Office of the President of the Republic of Kenya and the Kenya Wildlife Service for permission to work in Amboseli over the years. We also thank the Institute of Primate Research of the National Museums of Kenya for institutional sponsorship in Kenya and the wardens and staff of Amboseli National Park and the local communities of the Amboseli/ Longido region for cooperation and hospitality. Particular appreciation goes to the Amboseli fieldworkers who contributed to the data over the years, especially R.S. Mututua, S.N. Sayialel, J.K. Warutere, P.M. Muruthi, and A. Samuels; to K.O. Pinc for database programming in the creation of BABASE and to the series of assistants who organized BABASE entry and extraction of BABASE data—D. Shimizu, S.L. Combes, A. Mosser, and J.M. Zayas. S.A. Altmann, R.A. Bulatao, K. Hawkes, H. Kaplan, J.W. Lynch, K. Wachter, and an anonymous reviewer provided valuable comments on the manuscript. We gratefully acknowledge financial support from the National Science Foundation (IBN-9985910 and its predecessors) and the Chicago Zoological Society. REFERENCES Alberts, S.C. 1999 Paternal kin discrimination in wild baboons. Proceedings of the Royal Society of London-Biological Sciences 266:1501-1506. Alberts, S.C., and J. Altmann 1995 Balancing costs and opportunities: Dispersal in male baboons. American Naturalist 145:279-306.

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