Regularities and Diversity inDevelopmental Pathways:Mother–Infant Relationships inHamadryas Baboons

Marıa Victoria Hernandez-LloredaDepartamento de Metodologıa de las

Ciencias del ComportamientoFacultad de Psicologıa

Universidad Complutense de MadridCampus de Somosaguas

28223 Madrid, SpainE-mail: vhlloreda@psi.ucm.es

Fernando ColmenaresDepartamento de Psicobiologıa

Facultad de PsicologıaUniversidad Complutense de Madrid

Campus de Somosaguas28223 Madrid, Spain

E-mail: colmenares@psi.ucm.es

ABSTRACT: Change, stasis, stability, discontinuity, orderliness, and diversity areall potential characteristics of developmental systems. This study uses multilevelmodeling to characterize the normative developmental pathways of the early socialrelationships of 23 mother–infant pairs embedded in a multilayered colony ofhamadryas baboons (Papio hamadryas hamadryas). The relationships wereassessed by means of 27 behavioral measures that were collected during 100–220 focal sampling sessions per infant, from birth to 380 days of age (25 two-weekage intervals). Seventy four percent of the behavioral measures exhibited an age-related pattern. Infant age, however, was not predictive of the rate of the behaviorsrelating to the management of mother–infant conflicts. This study providesempirical evidence that the development of mother–infant relationships mayinvolve periods of change and stasis, overall orderliness, and diversity as well ascanalization of developmental pathways. We believe that growth curve analysis canbe useful to tackle various hot issues in the study of behavioral development.� 2005 Wiley Periodicals, Inc. Dev Psychobiol 47: 297–317, 2005.

Keywords: developmental pathways; growth curve analysis; change; regularities;diversity; mother–infant relationships; hamadryas baboon

INTRODUCTION

Living systems, whether they consist of cells, organs,

whole organisms, or groups of individual organisms,

undergo changes over their lifetimes. Understanding how

they develop during ontogeny and why they follow the

particular developmental trajectories they do pose a major

challenge in developmental science and in evolutionary

biology (Bateson & Martin, 2000; Bateson, 2001; Gould,

1977; Gottlieb, 1992; Oyama, 2000). Animal behavior

researchers interested in unraveling the principles that

account for the development of an individual’s behavior or

the relationship within a two-partner (or higher order)

social system have struggled to develop conceptual and

quantitative tools capable of capturing, assessing, and

measuring its crucial properties and of testing hypotheses

that provide a meaningful account of the processes that

drive the patterns of stability and change observed during

ontogeny (Bateson, 1983, 2003; Blass, 1986, 1988; Bryk

& Raudenbush, 1987; Butterworth & Bryant, 1990;

Chalmers, 1987; Gottlieb, 1992, 2001; Hall & Oppen-

heim, 1987; Immelmann, Barlow, Petrinovich, & Main,

1981; Lewkowicz & Lickliter, 2002; Michel & Moore,

1995; Oyama, 2000; Oyama, Griffiths, & Gray, 2001;

Turkewitcz, 1992; Willett, 1988).

The conceptual framework adopted here is based on

the developmental systems view, laid down by evolution-

ary biologists (Hoo, 1998; Hood, 1998; Lewontin, 1983;

Oyama, 1982, 2000), psychobiologists and comparative

psychologists (Gottlieb, 1992; Johnston & Gottlieb,

2000), and ethologists (Bateson & Martin, 2000; Bateson,

Received 15 February 2004; Accepted 8 June 2005Correspondence to: F. ColmenaresContract grant sponsor: MEyC (Spain) (postdoctoral fellowship to

FC (1988–1991)Contract grant sponsor: MCyT (Spain) (to FC) (project grants)Contract grant numbers: PB98-0773, BSO2002-00161Published online in Wiley InterScience

(www.interscience.wiley.com). DOI 10.1002/dev.20104

� 2005 Wiley Periodicals, Inc.

2003). This view emphasizes emergence at all levels of

organization as the outcome of constructive interactions

or coactions within and across levels. It also highlights the

hierarchical organization of developmental systems, the

interpenetration of genes, organisms, and their environ-

ments, and the dialectical relation between the multiple

interactants, which are constructed rather than fixed and

inherited separately.

The longitudinal approach to the study of behavioral

development involves repeated measurements on one or

several behaviors for the same sample of individuals over

a number of consecutive points in time (Martin & Bateson,

1993; Sackett, Sameroff, Cairns, & Suomi, 1981; Willett,

1988; Wohlwill, 1973). The resulting data structures are

inherently hierarchical, that is, each occasion of measure-

ment contributes to a subset of observations that are nested

within individuals, and, therefore, statistically dependent.

Conventional statistical methods, including regression

and ANOVA models, have a number of conceptual,

methodological, and statistical limitations and short-

comings (see, e.g., Bryk & Raudenbush, 1987, 1992;

Boyle & Willms, 2001; Hox & Kreft, 1994; Hernandez-

Lloreda, Colmenares, & Martınez-Arias, 2003; Michel,

2001; van der Leeden, 1998; Willett, 1988). The proper

analysis of such developmental data requires statistical

methods that take fully into account the multilevel struct-

ure of longitudinal data and which are flexible regarding

both the handling of unbalanced designs and the modeling

of covariance structures. One of these analysis techniques

is hierarchical linear modeling, variously labeled multi-

level models, random-coefficient models, mixed models,

and covariance components models (Bryk & Raudenbush,

1987, 1992; Goldstein, 2003; Raudenbush, 2001; Snijders

& Bosker, 1999; van der Leeden, 1998; Willett, 1988).

Growth curve analysis allows the estimation of a group’s

average developmental trajectory and each individual’s

developmental trajectory; it therefore allows an esti-

mation of the individual variation around the average

trajectory and the analysis of correlates and predictors of

individual differences in developmental pathways.

One of the circumstances that have contributed to

hinder the advance in our understanding of behavioral

and relationship development as it takes place in freely-

interacting socially-living animals is the paucity of

empirical data available on the ontogenetic trajectories

of known individuals within and across species. Some

taxa, such as, for example, primates, are long-lived

animals (Kappeler, Pereira, & van Schaik, 2003) and

adequate knowledge of an individual’s complete develop-

mental (life) history would ideally require the collection

of longitudinal observations spanning several decades. An

alternative research strategy, which has already proved

fruitful, is to focus on early relationships such as those

involving the mother and her infant, as they are known to

have long-lasting effects on the physiological and

psychological systems that regulate the infant’s beha-

vioral and social competence and on both partners’

biological fitness (Fairbanks, 1996, 2003; Hofer, 1987;

Kraemer, 1992; Maestripieri, 2003; Pryce, Martin, &

Skuse, 1995; Suomi, 1997; Suomi, Novak, & Well, 1996).

Thus, data on the first months of the development of an

infant’s relationship with his or her mother are available

for a number of primate species (e.g., Berman, 1984;

Deputte, 2000; Fairbanks, 1996, 2003; Maestripieri, 1994,

2003; Nash & Wheeler, 1982; Nicolson, 1987; Pereira &

Altmann, 1985).

The main goal of this study was to identify patterns in

the development of two-animal social systems by means

of multi-level modeling, a statistical methodology that, to

our knowledge, has not been previously used in this

context (see Hernandez-Lloreda et al., 2003; Hernandez-

Lloreda, Colmenares, & Martınez-Arias, 2004). The

study was conducted on 23 mother–infant pairs embed-

ded in a large, multilayered colony of hamadryas baboons

(Papio hamadryas hamadryas), and the data were colle-

cted longitudinally during the infants’ first year of life.

Although the findings are expected to contribute to the

knowledge of the natural history of the study species’

behavioral development, on which almost nothing is

known, we were primarily interested in using the data to

come to terms with key developmental issues of wider

theoretical interest. In particular, we wanted to explore the

nature of behavioral development, for example, the occur-

rence of age-related regularities and the extent of diversity

in individual developmental pathways. We believe that

having precise information on these general issues is a

crucial and necessary first step for formulating research

questions that can be specified more clearly and for testing

more refined and focused alternative hypotheses in the

future.

MATERIALS AND METHODS

Subjects and Housing

The subjects of this study were members of the colony of

hamadryas baboons (P. h. hamadryas) housed in the Madrid Zoo,

Spain (for details, see Colmenares & Gomendio, 1988). The

colony was established in June 1972 and was studied continuo-

usly until 2002 (Colmenares, 2004). The colony was housed in a

large compound consisting of an outdoor enclosure measuring

36 m-long, 26 m-wide, and 7 m-deep, and an attached indoor

area. The outdoor enclosure was terraced and contained several

climbing structures, a water-filled moat, and several islands.

Animals were fed once daily and running water was available ad

libitum. Animals could enter and leave the indoor rooms at will.

The social organization and mating system of the Madrid baboon

colony resemble those described for wild hamadryas baboons

298 Hernandez-Lloreda and Colmenares

(e.g., Kummer, 1984): multilevel social structure, one-male

reproductive units with and without ‘‘follower’’ males, harem

defence polygyny, serial polyandry, strong bonding between the

harem-holding males and their females and relatively weak

affiliative relationships among the harem females (Colmenares,

1992, 2004). The observational study reported here was conduc-

ted from August 1986 to February 1989, when the colony

consisted of 48–61 individuals, organized into five one-male

units. The study subjects were 23 infants, including 9 males and

14 females, and their mothers (Fig. 1).

Data Collection

We used focal animal sampling methods (Altmann, 1974),

observing each infant for four to nine 15-min sessions per

2-week periods from birth to 380 days of age (i.e., each subject

was sampled during 100–220 fifteen minute sessions, alto-

gether). Each subject’s data were pooled per 2-week period, that

was considered an ‘‘age interval,’’ so that each subject’s growth

data comprised 25 age intervals or time points. The average

number of infants sampled per age interval was 20 (range¼ 14–

20, mode¼ 18). Each sampling day, focal subjects were chosen

on a rotating schedule. To increase independence, no infant was

sampled more than once in a day. Before starting and after

finishing the focal session, we took instantaneous (point)

samples, recording the identities of all the focal infant’s

neighbors, using the following mutually exclusive four cate-

gories of spatial states: inventral contact, in contact, within 50 cm

and between 50 and 150 cm. In addition, at 5 and at 10 min during

the focal session, point samples of the focal infant’s spatial states

were also recorded, using the categories defined above.

Observations were written directly on check-sheets which

consisted of 60 partitions, each denoting one 15-s interval

sample. Thus, each focal session yielded 60 interval samples and

4 sample points of data.

Behavioral Measures and Data Analysis

The complete behavioral catalogue used in the recording of the

data comprised 4 spatial states and 52 behaviors. Table 1 gives

the list and a brief description of the 27 behavioral measures used

in the analysis presented here (see also Fig. 1). These consist of

behaviors used by each member of the dyad, i.e., the mother and

her infant, to interact with the other and behavioral states that

designate the dyad’s state with respect to spatial measures of

contact and proximity.

This study is based on 673 hr of systematic data collection,

that is, 161,644 interval samples and 11,031 point samples.

Proportion data were transformed by using arcsine square root

of p (Y¼arcsin (Hp), where p was the proportion of time; and

frequency data were square root transformed, i.e., y ¼ffiffiffi

xp

, or,

if the data included zero scores, .5 was added to all values,

y ¼ffiffiffiffiffiffiffiffiffiffiffiffi

x þ :5p

(e.g., Martin & Bateson, 1993).

Multilevel Growth Curve Analysis. We applied two-level

hierarchical linear models (Bryk & Raudenbush, 1987, 1992;

Goldstein, 2003; Snijders & Bosker, 1999; van der Leeden,

1998; Willett, 1988; see also Hernandez-Lloreda et al., 2003).

These entail the specification of a pair of linked statistical

models, one for individual developmental trajectories (level 1 or

within-subject model), and the other for individual differences in

developmental trajectories (level 2 or between-subjects model).

This two-level conceptualization of development implies that

the parameters defined in the first level become the outcome

measures in the second level (Bryk & Raudenbush, 1992;

Snijders & Bosker, 1999; Willett, 1988).

Within-Subject Model. Individual development may be mod-

eled as a polynomial function of infant age. The within-subject,

level-1 model used had the form

Yti ¼ �0i þ �1iðAGEÞti þ �2iðAGEÞ2ti þ . . .þ �piðAGEÞp

ti þ eti

ð1Þ

where Yti, that is, the measurement on the outcome variable for

individual i on occasion t, is a function of a systematic growth

trajectory plus random error, the bs are the coefficients of a

polynomial function of degree p and the etis are random error

terms. The level 1 predictor variable was the infant’s AGE (i.e.,

the age of individual i at time t). The powers bgiTtig represent

transformations of this variable, specifying a linear, quadratic,

cubic, or higher order polynomial development function (Bryk &

Raudenbush, 1992; Bryk, Raudenbush, & Congdon, 1996; van

der Leeden, 1998). In picking the order of the model, authors

generally recommend to maintain a sense of parsimony and

avoid high-order polynomials (Montgomery, Peck, & Vining,

2001; Willett, 1988). High-order polynomial growth models

often contain parameters whose biological or psychological

significance are difficult to assess. Furthermore, when the sample

of subjects is small, simpler models, i.e., low-order polynomials,

FIGURE 1 (a) Mother–infant ventro-ventral contact.

(b) Dorsal transport. (c) Aggressive rejection by mother.

(d) Mother restrains her infant.

Developmental Pathways and Mother–Infant Relationships 299

Table 1. Behavioral Measures and Their Definitions

Behavioral measures related to mother–infant ventro-ventral contact

Time in ventro-ventral contact Percentage of point time samples in which the infant is in ventro-ventral

contact with the mother

Duration of bouts of ventro-ventral contact Average length of consecutive intervals in which the mothers and their

infants are in ventro-ventral contact

Time in ventro-ventral transport Percentage of intervals in which the mother carries her infant ventrally

Infant makes ventro-ventral contact Rate per hour that the infant initiates ventro-ventral contact with the mother

Mother makes ventro-ventral contact Rate per hour that the mother initiates ventral-contact with her infant

Infant breaks ventro-ventral contact Rate per hour that the infant breaks ventro-ventral contact with the mother

Mother breaks ventro-ventral contact Rate per hour that the mother breaks ventro-ventral contact with her infant

Behavioral measures related to mother–infant contact

Time in contact Percentage of point time samples in which the infant is in contact with

the mother

Time in dorsal transport Percentage of intervals in which the mother carries her infant dorsally

Infant makes contact Rate per hour that the infant initiates contact with the mother

Mother makes contact Rate per hour that the mother initiates contact with her infant

Infant breaks contact Rate per hour that the infant breaks contact with the mother

Mother breaks contact Rate per hour that the mother breaks contact with her infant

Behavioral measures related to mother–infant proximity

Time <50 cm Percentage of point time samples that the mother is within 50 cm of the

infant

Time >150 cm Percentage of point time samples that the mother is over 150 cm away

from the infant

Approaches by infant Rate per hour that infant moves from more than 50 cm away from the

mother to less than 50 cm from mother

Approaches by mother Rate per hour that mother moves from more than 50 cm away from her

infant to less than 50 cm from infant

Leaves by infant Rate per hour that infant moves beyond 50 cm away from the mother

Leaves by mother Rate per hour that mother moves beyond 50 cm away from the infant

Behavioral measures related to maternal rejection

Body jerks by mother Rate per hour that mother displays body jerks in response to infant contact

Nonaggressive rejection Rate per hour that mother prevents infant from making or maintaining any

form of contact with her by holding it away, pulling it off, blocking the

chest with an arm, etc.

Aggressive rejection Rate per hour that mother prevents infant from making or maintaining any

form of contact with her by threatening, hitting, biting, etc. the infant

Behavioral measures related to maternal restraint

Mother restrains Percentage of intervals that mother prevents infant from breaking any

form of contact with her or from moving away from her by holding it

by the body hair, the arms or legs, the tail, etc.

Behavioral measures related to infant distress

Body jerks by infant Rate per hour that infant displays body jerks in response to the mother’s

behaviour

Infant tantrums Rate per hour that infant displays behaviors such as violent body spasms,

geckers, screams, squeaks, thrashes on the ground, in response to

maternal rejection

Infant moans Percentage of intervals that infant utters a continuous low vocalization

with fluctuations in volume and pitch, with pursed-lips, in response to

maternal rejection

Mother grooms Percentage of intervals that the mother grooms her infant

Note. The behavioral states ‘‘time in ventral contact,’’ ‘‘time in contact,’’ ‘‘time <50 cm,’’ and ‘‘time >150 cm’’ were mutually exclusive.

300 Hernandez-Lloreda and Colmenares

are more efficient than complex ones because the latter tend to

vary more across samples (Zucchini, 2000). Thus, we chose the

model that provided the best fit, but we stopped at polynomials of

third order.

With the within-subject model described in Equation 1 we

tested the hypothesis that the status of the various behavioral

measures analyzed was a function of the infant’s age.

Between-Subjects Model. A key feature of Equation 1 is the

assumption that the individual growth parameters (i.e. the bs)

vary across subjects. The between-subjects model represents the

observed heterogeneity in individual development trajectories.

A between-subjects model, with simple random variation in the

individual development parameters across the group, could be:

�0i ¼ �00 þ u0i

�1i ¼ �10 þ u1i

..

.

�pi ¼ �p0 þ upi

ð2Þ

where the parameters g00, g10, . . . ,gp0 are known as fixed effects,

and represent the average developmental trajectory over all

individuals. The u0i, u1i, . . . ,upi are random error components

denoting the departures of b0i, b1i, . . . ,bpi from these g00,

g10, . . . ,gp0 coefficients for each individual i. This level 2 model

of simple random variation is called an unconditional model

since no level 2 predictors for any of the b parameters have been

introduced (Bryk & Raudenbush, 1992; van der Leeden, 1998).

More elaborate between-subject models can be developed if one

or several level 2 predictor variables are added to the model to try

to explain part of the variability of the level 1 b coefficients. This

further step in the analysis would take us beyond the scope of this

paper, though. Nevertheless, an analysis of predictor variables

that account for the patterns of inter-individual variation

observed has been presented elsewhere (Hernandez-Lloreda &

Colmenares, 2005).

Proportion of Variance Explained. In a hierarchical linear

model there is more than one level at which the explained

variance must be determined (Snijders & Bosker, 1999). In a

two-level model, the within-unit variance explained (i.e., R12) is a

measure of how well the independent variables in the model

explain the outcome variable, and the between-unit measure

(i.e., R22) is the amount of variance between level 2 units that is

accounted for by the predictors in the model. In the model

presented here, the predictor variable was the infant’s age, thus

R12 represents the proportional reduction of error for predicting

an individual’s outcome at any given point in time by infant age

and R22 denotes the proportional reduction of error for predicting

an individual’s mean over time by infant age. To these measures

of explained variance, only the fixed effects contribute. To

calculate R12 and R2

2 we used Snijders’ and Bosker’s formulae

(Snijders & Bosker, 1999) for models with random intercepts

only. To estimate R12 and R2

2 in models with random slopes we re-

estimate the models as random intercept models with the same

fixed parts (omitting the random slopes). These yield values that

are very close to the values obtained for the random slopes

models (Snijders & Bosker, 1999).

Assumptions. For the level 1 random terms (eti), it is assumed

that they are independent and normally distributed with zero

mean and variance s2. The level 2 random terms are assumed to

have a joint normal distribution with zero mean, variance tqq and

covariance tqq0 for any pair of random effects q and q0. (It is

important to remark that multilevel models are very flexible

regarding the data design and allow modeling of a broad array of

covariance structures, see, for example, Bryk and Raudenbush

(1987, 1992)).

Testing the Assumptions. We checked the tenability of the

assumptions underlying the model by means of analysis of the

residuals (Bryk et al., 1996). As regards the assumptions about

level 1 random effects, homogeneity of variances was tested

using the H statistic (Bryk & Raudenbush, 1992) and normality

was checked by computing separate probability plots for each

i unit (Bryk & Raudenbush, 1992). Normality at level 2 was

checked by using the Mahalanobis Distance measure (Bryk &

Raudenbush, 1992). For each i unit we plotted the observed

distance statistics against the expected order statistics. The

assumptions were met by the data, except in the case of four

behavioral measures, i.e., mother makes ventro-ventral contact,

mother makes contact, body jerks by mother, and infant breaks

ventro-ventral contact, in which the level 1 homogeneity of

variances assumption was violated. We re-analyzed these

behavioral measures by means of a nonlinear (Poisson) model;

however, the results did not differ from those obtained with

hierarchical linear regression modeling. Thus, we have reported

the results of the latter model.

To run the analyses we used the software packages HLM for

Windows, versions 4.01 and 6.0 (Bryk et al., 1996; Raudenbush,

Bryk, Cheong, & Congdon, 2004), and MlwiN version 1.00

(Goldstein et al., 1998) and SPSS version 11.0.

RESULTS

Average Developmental Trajectories

A large proportion of the behavioral measures analyzed

exhibited an age-related pattern (20 of 27, or 74%). We

classified the shape of the 20 average developmental

trajectories identified into five developmental patterns,

DPs (Tab. 2), which could be readily detected by visual

inspection (Fig. 2; see also Appendix 1). These various

DPs were established by examining the timing of the

maximum of the developmental trajectory, which occur-

red either in the beginning (i.e., DPs 1 and 2) or sometime

later but before the end of the infant’s first year of life (i.e.,

DPs 3–5). When a break point was detected, which is

defined here as a change in the sign of the slope (from

positive to negative), we took into account the timing of

such a break point. Application of this criterion yielded

three additional types of curves: left-skewed inverted

J-shaped curve (DP 3), centered inverted U-shaped curve

(DP 4), and right-skewed inverted J-shaped curve (DP 5).

Table 2 shows that the left-skewed inverted J-shaped curve

Developmental Pathways and Mother–Infant Relationships 301

(i.e., DP 3) was the most common shape of developmental

trajectory for the behavioral measures that followed an

age-related pattern (11 of 20, or 55%) and that the second

most common developmental trajectory was the one

classified as DP 1 (5 of 20, or 25%), in which the status of

the behavior was a decreasing function of infant age, that

is, the maximum was reached in the first age interval (i.e.,

at birth) and there was no plateau thereafter (see Tab. 2,

DP2). Appendix 2 shows the final unconditional models

fitted to each of the behavioral measures and presents the

results of the significance tests for the fixed effects of the

models (i.e., mean initial status, mean first-order para-

meter, mean second-order parameter, and mean third-

order parameter).

Developmental Pattern 1 (DP 1). This includes five

behavioral measures that peaked in the very early stages of

the infant’s life and then exhibited a pronounced decline in

their status as a function of infant age (Tab. 2). The overall

values of R12 and R2

2 tend to be fairly high (.41� .22 and

Table 2. Developmental Patterns (DPs), Behavioral Measures, and Proportion of Variance Explained by Infant Age

(First Year of Life)

Developmental pattern Behavioral measure s2 explained

Time in ventro-ventral contact R12¼ .61; R2

2¼ .62

Time in ventro-ventral transport R12¼ .69; R2

2¼ .61

Mother makes ventro-ventral contact R12¼ .33; R2

2¼ .36

Body jerks by mother R12¼ .22; R2

2¼ .27

Mother grooms R12¼ .15; R2

2¼ .05

Duration of bouts of ventro-ventral contact R12¼ .36; R2

2¼ .30

Time in dorsal transport R12¼ .40; R2

2¼ .12

Time in contact R12¼ .96; R2

2¼ .97

Time <50 cm R12¼ .20; R2

2¼ .02

Infant makes ventro-ventral contact R12¼ .31; R2

2¼ .06

Infant makes contact R12¼ .39; R2

2¼ .08

Infant breaks ventro-ventral contact R12¼ .47; R2

2¼ .26

Infant breaks contact R12¼ .36; R2

2¼ .03

Leaves by infant R12¼ .41; R2

2¼ .09

Approaches by infant R12¼ .39; R2

2¼ .15

Mother makes contact R12¼ .21; R2

2¼ .13

Approaches by mother R12¼ .22; R2

2¼ .07

Mother breaks contact R12¼ .09; R2

2¼ .00

Leaves by mother R12¼ .25; R2

2¼ .07

Time >150 cm R12¼ .59; R2

2¼ .61

302 Hernandez-Lloreda and Colmenares

.39� .24, respectively), especially for those measures

denoting the dyad’s overall level of ventro-ventral contact

time (i.e., time in ventro-ventral contact and in ventral

transport). This indicates that the age of the infant

represents a good predictor of the changes in the status of

these behaviors across time. Interestingly, in addition to

the two states of ventral contact already mentioned, this

pattern is followed by three behaviors initiated by the

mother (i.e., mother makes ventro-ventral contact, mother

grooms, and mother displays body jerks).

Developmental Pattern 2 (DP 2). This pattern is

followed by only one behavior pattern which is, in fact,

a behavioral state: the average duration of the bouts of

FIGURE 2 (a) Behavioral measures related to mother–infant ventro-ventral contact. Each panel

describes, for each behavioral measure, the individual (thin lines) and average (thick lines)

developmental trajectories (top graph) and the amount of variance across time (bottom graph). The

curves for the individual trajectories are based on empirical Bayes estimates. Y-axis: rate refers to

hourly rate, time to proportion of either interval or point samples (see Tab. 1), and duration to number

of consecutive interval samples. X-axis: age refers to 2-week age intervals (n¼ 25). N¼ 23 mother–

infant pairs (see ‘‘Materials and Methods’’). (b) Behavioral measures related to mother–infant

contact. (c) Behavioral measures related to mother–infant proximity. (d) Other behavioral measures.

Developmental Pathways and Mother–Infant Relationships 303

ventro-ventral contact between the mother and her infant.

The curve is very similar to the one we have just seen (DP

1) except that the initial decline is followed by a fairly long

period of stasis before it drops again towards the end of the

infant’s first year of age (Tab. 2). The behavioral content of

this measure is very similar to the behavioral states that we

have just described for the previous developmental pattern

because it also provides an index of the time that both

partners spend in ventral contact. R12 and R2

2 are only

moderately high, .36 and .30, respectively (Tab. 2).

Developmental Pattern 3 (DP 3). As already mentioned,

this left-skewed inverted J-shaped curve is the develop-

mental pattern most common in this study. The behavioral

FIGURE 2 (Continued)

304 Hernandez-Lloreda and Colmenares

measures included in this cluster reflect the beginning

of the growth of independence (behavioral states: time in

contact, in dorsal transport, and within 50 cm of the

mother), and the attempts on the part of the infants to take

on a more active role in the regulation of the contact (i.e.,

infant makes/breaks ventro-ventral contact and contact)

and proximity (i.e., infant approaches/leaves) relation-

ships with their mothers (Tab. 2). The fit is better for the

behaviors initiated by the infant (n¼ 6) than for those ini-

tiated by the mother (n¼ 2) (R12: .39� .05 vs. .22� .01).

Developmental Pattern 4 (DP 4). Two behaviors, both

initiated by the mother, are part of this developmental

pattern in which the break point occurs around the age of

6 months (Tab. 2). The inverted U-shaped curve describes

the rate with which the mother moves a step further in the

FIGURE 2 (Continued)

Developmental Pathways and Mother–Infant Relationships 305

process of actively promoting her infant’s growing

independence (i.e., mother breaks contact and mother

leaves her infant). R12 and R2

2 show rather low values,

indicating that, although there was a temporal pattern,

variation in the mother’s behavior over time is poorly

accounted for by infant age (Tab. 2).

Developmental Pattern 5 (DP 5). This developmental

pathway is followed by only one behavioral measure

which can be taken to represent the level of spatial (and, to

some extent, social) independence achieved by the

members of the mother–infant dyad during the infant’s

first year of life (i.e., time both partners were beyond

150 cm of each other). Interestingly, this behavioral

measure peaks towards the end of the third quarter of the

infant’s first year of life and then drops off as if some

degree of recovery of the situation immediately preceding

the peak were realized (Tab. 2).

Behavioral Measures not Showing an Age-RelatedPattern. The status (hourly rate or duration estimation)

over time of the remaining seven behaviors did not exhibit

an age-related pattern of development; their status was

therefore largely unpredictable with regards to the infant’s

age (Fig. 3). These were mostly behaviors used by the

mothers and their infants during situations in which they

were engaged in the management and resolution of their

conflicts. Interestingly, the two traditional categories of

mothering style can be identified in this cluster, restrictive

(i.e., mother restrains infant) versus rejecting (i.e., mother

breaks ventral contact, and aggressive and nonaggressive

rejection by the mother), as well as the intensity of the

infant’s response to his or her mother’s mothering

style (i.e., infant’s body jerks, tantrums, and moans).

Individual Differences inDevelopmental Pathways

The variance of the observations was a function of age

because individuals happened to grow at different rates.

In general, the structure of variances and covariances

among the observations will depend both on the functio-

nal form assumed for the individual growth model and

on the amount of variance and covariance among the

individual growth parameters (Bryk & Raudenbush,

1987). In the majority of the behavioral measures

analyzed, the shape of the developmental function was

mirrored by the pattern of individual variation (Fig. 2a,b,

and d). This occurred either in the first weeks after birth

(Fig. 2a and d) or sometime later (Fig. 2a and b). There

were, however, several behavioral measures for which

there was no such a positive association in the shape of

the two functions (i.e., average status and variance)

(Fig. 2c). Within this category we find four behaviors

relating to approaches and leaves by both partners

whose variation peak took place at the end of the first

year. Interestingly, the amount of variance exhibited by

the behavioral measures approaches and, especially,

leaves by the infant, tended to diminish or even reach a

minimum around the time when the average status had

achieved its maximum (Fig. 2c). Within this category, in

which the average and variation peaks are temporally

dissociated, there was another behavioral measure,

duration of bouts of ventro-ventral contact. This

reached a minimum towards the 4th month of the

infant’s life and remained at such low values for about

3 months (Fig. 2a). Appendix 2 describes the results of the

significance tests for the random effects of the models

fitted. It can be noted that the individual differences in

the various parameters (i.e., initial status, growth rate

FIGURE 2 (Continued)

306 Hernandez-Lloreda and Colmenares

and so on) that define each individual’s developmental

trajectory were generally highly significant.

DISCUSSION

The study of mother–infant relationships, initially driven

by an interest in the contribution of early experiences

to later social development within the framework of

Bowlby’s attachment theory (see Maestripieri, 2003;

Suomi, 1995, for reviews), has been a fashionable topic

in primatology all along (Hinde, 1974, 1983; Hrdy, 1999;

Maestripieri, 2002, 2003; Nash & Wheeler, 1982;

Nicolson, 1987; Pryce et al., 1995). Nevertheless, the

actual number of published accounts of the time course of

development of the relationships between mothers and

infants is rather meagre. The comparisons across studies

are further complicated by five additional factors: the

number of behaviors (and categories) analyzed, the durat-

ion and number of time points covered by the studies,

the size of the sample per time point, the level and type of

quantification, and the demographic and ecological sett-

ing, all of which are highly variable. Baboon (Papio spp.)

studies of mother–infant relationships illustrate this

situation rather nicely (Altmann, 1978, 1980; Altmann

& Samuels, 1992; De Vore, 1963; Nicolson, 1982; Nash,

1978; Rowell, Din, & Omar, 1968; Ransom & Rowell,

1972; Rhine, Norton, & Westlund, 1984; Rhine, Norton,

Wynn, & Wynn, 1985; Wasser & Wasser, 1995; see, also,

Barrett, Dunbar, & Dunbar, 1995; Lycett, Henzi, &

Barrett, 1998). This paper provides empirical information

on the early social relationships of 23 mother–infant

pairs embedded in a multilayered colony of hamadryas

baboons. More specifically, it provides data on the time

course of 27 behavioral measures assessed in 25 two-week

intervals, from birth to 380 days of age (Appendix 1). This

is the first mother–infant relationship study of this kind on

a harem-forming species (see, however, Fletcher, 2001,

for gorillas) and, specifically, on P. h. hamadryas.

FIGURE 3 Behavioral measures that did not conform to an age-related pattern. Legend as for

Figure 2a.

Developmental Pathways and Mother–Infant Relationships 307

Despite the large differences across baboon (and other

primate) studies of mother–infant relationships in the five

parameters forementioned, there seem to be indications

that the general time course of development of some of the

behavioral measures most commonly used to assess

mother–infant relationships may turn out to be strikingly

similar across populations and even across primate

species (Altmann, 1980). This applies to the behavioral

measures mother–infant contact time (Altmann, 1978,

Fig. 1; Altmann, 1980, Fig. 47; Barrett et al., 1995, Fig. 3;

Nicolson, 1982, Fig. 17; Wasser & Wasser, 1995, Fig. 1;

this study: Appendix 1a and b), and the two forms of

infant-carrying, i.e., ventral and dorsal transport, that

some authors have analyzed separately (Rhine et al., 1984,

Fig. 2; this study: Appendix 1a and 1b) and others as a

single combined category (Altmann & Samuels, 1992,

Fig. 2; Nicolson, 1982, Fig. 13; Rhine et al., 1985, Fig. 1).

Lycett et al. (1998, Fig. 3) and Barrett and Henzi (2000,

Fig. 2a) obtain very similar results for time spent on

nipple. An adequate quantitative test of this general

impression remains to be done, though.

Studies of baboon mother–infant relationships that

have taken a quantitative approach (e.g., Altmann &

Samuels, 1992; Lycett et al., 1998; Wasser & Wasser,

1995) have used conventional statistical methods that are

problematic (Hernandez-Lloreda et al., 2003; Michel,

2001). Thus, Altmann and Samuels (1992) and Lycett et al.

(1998) applied multiple linear regression analysis, a

statistical model that ignores the hierarchical nature of

longitudinal data, and raises problems resulting from the

dependence between the (repeated) measurements. When

the assumption of independence of residual error terms is

violated, the estimates obtained are inefficient and the

Type I error rate is much higher than the specified a (Hox

& Kreft, 1994; van der Leeden, 1998). Wasser and Wasser

(1995) used a slopes-as-outcomes approach (e.g., Bryk &

Raudenbush, 1992) to characterize developmental rates

empirically and explain individual differences in terms of

environmental variables. Although this approach is also

based on fitting developmental functions, it is inadequate

to test for differences between individuals in growth

parameters because the error structure assumed by the

linear model differs from the actual error structure (Hox &

Kreft, 1994). (See Hernandez-Lloreda et al. (2003), for an

example, comparing the results obtained by applying

various conventional statistical methods and multilevel

modeling to the study of the development of Ventral

Transport in our study group).

Although multilevel modeling is widely known and

used within educational statistics (Bryk & Raudenbush,

1987, 1992; Boyle & Willms, 2001; Raudenbush, 2001;

Snijders & Bosker, 1999; van der Leeden, 1998; Willett,

1988), its application in animal behavior studies has only

recently started to be explored (Hernandez-Lloreda et al.,

2003, 2004; Hernandez-Lloreda & Colmenares, 2003,

2004, 2005; Michel, 2001). The two-level hierarchical

linear growth modeling used in this paper has shed light on

the nature of relationship development in mother–infant

dyads. A large proportion of the behavioral measures

analyzed were found to have a defined developmental

pathway (Fig. 2; Appendices 1 and 2). The majority of the

behaviors that conformed to an age-related pattern tended

to vanish towards the end of the infant’s first year of life

(Tab. 2), somehow suggesting that they were specific to

that period of the infant’s life span. Whereas the average

status of some behaviors peaked at birth and then declined

more or less steadily with time (i.e., DP 1: 5 behaviors; DP

2: 1 behavior; Tab. 2), the average status of others peaked

at different times, from about the 3rd month (DP 3: 11

behaviors) through the 6th (DP 4: 2 behaviors) to the 9th

(DP 5: 1 behavior). The shape of the five developmental

patterns identified in this study suggests that different

behaviors (or clusters) played a significant role in the

mother–infant relationship at different times. This can be

interpreted as an indication that there are age (or stage)-

specific interactions and roles within the mother–infant

relationship. Interestingly, the behaviors related to the

management of mother–infant conflict (see Fig. 3) did not

follow a defined overall infant age-related pattern,

indicating that both the rate and the timing of occurrence

of these behaviors were dyad-typical and more difficult to

predict by infant age. It is also noteworthy that the

developmental pathways followed by the mothers’

behaviors were more difficult to predict by infant age

than were those followed by the infants’ behaviors (Fig. 2),

suggesting that the development of the infants’ behaviors

was generally more canalized and normative than that of

their mothers’.

Development (and evolution) are processes that are

taken to involve change and stasis, order, and diversity

(e.g., Bateson & Martin, 2000; Gottlieb, 1992; Oyama,

2000). This study provides empirical evidence that the

development of mother–infant relationships involved

periods of varying rates of change, overall orderliness,

and wide diversity in the developmental pathways

followed by both partners’ behaviors. Infant age emerged

as a strong predictor of their trajectories of development.

Although we understand that it is always tempting to

explain this infant age-related consistent patterning as an

indication that behavioral trajectories are controlled by

some sort of internal program that drives the maturation of

the different behaviors during the individual’s ontogeny,

we do believe that there are other alternative views that

can account for this age-related orderliness. For example,

Bramblett and Coelho (1985) studied the development of

eight behaviors in a sample of 96 baboons (Papio spp.)

from birth to 84 months of age, and used stepwise multiple

regression to analyze the relative contribution of age,

308 Hernandez-Lloreda and Colmenares

cohort, gender, and rearing experience (experimentally

controlled: peer-reared vs. mother-reared) to the variation

observed in rates of performance. These authors found

that rearing experience was statistically unimportant and

from this they concluded that ‘‘ . . . genetic control of

maturation shapes behavioral development in baboons

regardless of subtle experiential differences in early or

later life. Behavioral flexibility may have adaptive value,

but it may also be little more than a veneer on a genetically

mediated structure.’’ (p. Bramblett & Coelho, 1985,

p. 270). Leaving aside the fact that such a single-level

approach is statistically inadequate and may thus lead to

misleading conclusions (Hernandez-Lloreda et al., 2003),

and that there is abundant information showing that early

experiences may have profound effects on later social

relationships (e.g., Suomi, 1995, 1997), their findings can

also be interpreted in a very different way. According

to the developmental systems view (e.g., Gottlieb, 1992;

Oyama, 2000; Oyama et al., 2001), espoused in this study,

behavioral traits are constructed during ontogeny rather

than genetically programmed to emerge, and the char-

acteristics of behavioral development, including their

being orderly patterned over time as well as the diversity

of individual pathways that may arise, are the outcome of

the coactions that take place within and across multiple

levels and not the fulfillment of an internally guided plan.

The growth curve analyses presented in this paper have

shown that the performance of the behavioral measures

related to mother–infant interaction changed over the

infant’s first year of life, that such changes were signi-

ficantly predicted by infant age (level 1 predictor), and that

individual differences in development pathways were also

statistically significant. The next logical step will be to

determine which variables (level 2 predictors) may account

for the individual differences reported in this study

(Hernandez-Lloreda et al., 2003; Hernandez-Lloreda &

Colmenares, 2005). It would also be interesting to analyze

data from different populations for which data are

available (see above) by means of three-level hierarchical

linear growth models.

Although the developmental functions identified

suggest that the development of the behaviors analyzed

was a continuous process (Boyle & Willms, 2001), the

curvilinear characteristics of many of the developmental

pathways (Fig. 2) also suggest that developmental

discontinuities might be occurring (e.g., Bateson, 1981),

which can be investigated with a special analysis techni-

que known as piecewise linear growth modeling (see

Hernandez-Lloreda et al., 2004; Hernandez-Lloreda &

Colmenares, 2005).

Although we have described and analyzed separately

the developmental time course of the mothers’ and their

infants’ behaviors, it is assumed all along that each partner

is very likely to affect and, to some extent, shape the

other’s behavior over time. For example, the mothers’ and

infants’ roles in the maintenance of contact and proximity

within the dyad has been a traditional concern in studies of

primate mother–infant relationships (Hinde, 1974, 1983;

Maestripieri, 2002, 2004; Nash & Wheeler, 1982), and we

believe that this should also be approached with modern

statistical techniques such as Multivariate Multilevel

Modeling (e.g., MacCallum & Kim, 2000), which we

are now applying (Hernandez-Lloreda & Colmenares,

2004 and in prep.). This analysis should help to clarify the

contributions of each interactant to the developing system,

and to interpret many characteristics of the developmental

pathways in terms of the conceptual system put forward

by Gottlieb (1976) and Bateson (1983). In this respect, an

examination of the findings from this study regarding the

relation between the timing of the peaks in the average

status of the behaviors of each partner and in the amount

of individual differences across time suggests a number

of hypotheses worth testing in the future. We have the

impression, for example, that the mother’s return to oestrus

after the period of postpartum amenorrhea has an important

impact on her behavior (Esteban & Colmenares, 2001; see

also Berman, Rasmussen, & Suomi, 1994) and that this

might induce a major reorganization of the mother–infant

relationship, including the narrowing of individual differ-

ences (i.e., canalization) for some behaviors (for example,

duration of bouts of ventro-ventral contact, Fig. 2a).

We are well aware that we have partly simplified (and

to some extent distorted) the complexity of the develop-

mental processes that drive these early relationships by

ignoring the fact that the mother–infant dyads are actually

part of a larger system, i.e., the group where they are

embedded. Thus, although extra-dyadic reciprocal influ-

ences have not been considered, this should not be taken

to imply that we regard them as unimportant. The local

characteristics of the social niche and general landscape

where the mother–infant-dyads develop may well be

responsible for the differences within and between species

that have been reported (e.g., Maestripieri, 2001).

NOTES

This work was partly supported by a postdoctoral fellowship

from the MEyC (Spain) to F. Colmenares (1988–1991) and by

project grants PB98-0773 and BSO2002-00161 from the MCyT

(Spain) to F. Colmenares. We would like to thank the students

that participated in the data collection and in the tabulation,

S. Albares, M.J. Blanco, R. Gil, and C. Moratalla, and M.J.

Cepero, M.M. Esteban, V. Gutierrez-Diego, M. Pertegal, and F.

Zaragoza, respectively. We also thank Rosario Martınez-Arias

for statistical advice and Francisco Serradilla for the photo-

graphs included in Figure 1. We are grateful to the staff of the

Madrid Zoo for their cooperation in the maintenance of the

baboon long-term research project.

Developmental Pathways and Mother–Infant Relationships 309

APPENDIX 1a. Rate (hourly rate), time (proportion of either interval or point samples; see Table 1), or duration (number of

consecutive interval samples) of the behavioral measures related to mother-infant ventro-ventral contact, as a function of age.

Means (�SEMs) are given for each infant’s age interval (n¼ 25 two-week age intervals; N¼ 23 mother-infant pairs)

310 Hernandez-Lloreda and Colmenares

APPENDIX 1b. Behavioral measures related to mother-infant contact. Legend as for Appendix 1(a)

Developmental Pathways and Mother–Infant Relationships 311

APPENDIX 1c. Behavioral measures related to mother-infant proximity. Legend as for Appendix 1(a)

APPENDIX 1d. Other behavioral measures. Legend as for Appendix 1(a)

312 Hernandez-Lloreda and Colmenares

APPENDIX 2a. Hierarchical Analysis of the Behavioral Measures Related to Mother–Infant Ventro-Ventral Contact

Fixed effect Estimate t-ratio p Random effect Standard deviation df w2 p

Time in ventro-ventral contactg00 1.0457 18.03 .000 U0 .2513 22 153.00 .000g10 �.0458 �10.87 .000 U1 .0185 22 177.94 .000

eti .2126Mother makes ventro-ventral contact

g00 1.5493 13.08 .000 U0 .4426 22 63.39 .000g10 �.0678 �10.81 .000 U1 .0189 22 35.63 .033

eti .6803Infant breaks ventro-ventral contact

g00 1.5544 4.19 .000 U0 .6734 21 84.84 .000g10 .4933 5.40 .000 U1 .0274 21 49.35 .001g20 �.0547 �7.77 .000 eti .8941g30 .0013 8.12 .000

Time in ventro-ventral transportg00 .5322 18.24 .000 U0 .1019 22 138.90 .000g10 �.0438 �10.38 .000 U1 .0042 22 69.06 .000g20 .0009 6.19 .000 eti .0913

Infant makes ventro-ventral contactg00 .5453 2.78 .011 U0 .4070 22 52.51 .000g10 .4447 7.76 .000 U1 .0273 22 49.26 .001g20 �.0369 �7.24 .000 eti .7738g30 .0007 5.80 .000

Duration of bouts of ventro-ventral contactg00 6.2329 17.46 .000 U0 .996 22 82.52 .000g10 �.7810 �8.19 .000 U1 .086 22 114.22 .000g20 .0593 7.06 .000 eti 1.259g30 �.0015 �7.05 .000

Fixed-effects: g00, mean initial status; g10, mean first-order parameter; g20, mean second-order parameter; g30, mean third-order parameter. Random-

effects: U0, initial status level 2 residuals; U1, first-order parameter level 2 residuals; U2, second-order parameter level 2 residuals; eti, level 1 residual.

APPENDIX 2b. Hierarchical Analysis of the Behavioral Measures Related to Mother–Infant Contact

Fixed effect Estimate t-ratio p Random effect Standard deviation df w2 p

Time in contactg00 .0838 1.936 .065 U0 .1065 22 63.42 .000g10 .1214 10.212 .000 U1 .0040 22 34.16 .047g20 �.0105 �9.984 .000 eti .1610 22g30 .0002 8.865 .000

Infant makes contactg10 1.0268 24.93 .000 U1 .0898 22 75.77 .000g20 �.0769 �16.78 .000 U2 .0033 22 61.54 .000g30 .0016 11.69 .000 eti 1.2575

Infant breaks contactg10 1.1053 19.49 .000 U0 1.2538 22 63.63 .000g20 �.0908 �15.19 .000 U1 .0617 22 102.35 .000g30 .0019 12.60 .000 eti 1.0578

Time in dorsal transportg10 .0628 14.77 .000 U1 .0109 22 80.97 .000g20 �.0049 �11.09 .000 U2 .0005 22 61.06 .000g30 .0001 7.62 .000 eti .1068

Mother makes contactg00 .7358 4.84 .000 U0 .3794 21 57.98 .000g10 .3137 7.63 .000 U1 .0165 21 40.36 .007g20 �.0280 �7.66 .000 eti .5385g30 .0006 6.92 .000

Developmental Pathways and Mother–Infant Relationships 313

APPENDIX 2b. (Continued )

Fixed effect Estimate t-ratio p Random effect Standard deviation df w2 p

Mother breaks contactg00 .9231 6.44 .000 U0 .3769 22 48.76 .001g10 .1432 6.07 .000 U1 .0167 22 39.50 .012g20 �.0054 �6.45 .000 eti .6873

Legend as for Appendix 2(a).

APPENDIX 2c. Hierarchical Analysis of the Behavioral Measures Related to Mother–Infant Proximity

Fixed effect Estimate t-ratio p Random effect Standard deviation df w2 p

Time <50 cmg10 .0832 16.53 .000 U1 .0081 22 40.54 .009g20 �.0062 �10.44 .000 U2 .0004 22 38.57 .016g30 .0001 7.29 .000 eti .1449

Approaches by infantg10 .7637 19.18 .000 U0 .5998 23 62.22 .000g20 �.0484 �10.61 .000 U1 .0444 22 68.09 .000g30 .0008 6.73 .000 eti .9288

Leaves by infantg10 .7215 20.67 .000 U0 .4817 23 46.96 .003g20 �.0464 �11.27 .000 U1 .0376 22 66.27 .000g30 .0008 7.17 .000 eti .8694

Time >150 cmg10 .0233 2.66 .015 U1 .1153 22 61.70 .000g20 .0043 4.45 .000 U2 .0047 22 50.23 .001g30 �.0002 �6.53 .000 eti .2030

Approaches by motherg10 .5348 19.22 .000 U1 .0170 21 57.91 .000g20 �.0396 �11.71 .000 eti .8461g30 .0008 8.36 .000

Leaves by motherg00 .4326 3.52 .002 U0 .3279 22 49.39 .001g10 .2213 11.70 .000 U1 .0277 22 63.23 .000g20 �.0071 �10.49 .000 eti .6220

Legend as for Appendix 2(a).

APPENDIX 2d. Other Behavioral Measures

Fixed effect Estimate t-ratio p Random effect Standard deviation df w2 p

Body jerks by motherg00 1.5906 13.85 .000 U0 .4054 22 97.03 .000g10 �.0624 �4.53 .000 U1 .0212 22 55.40 .000g20 .0011 2.26 .034 eti .4479

Mother groomsg00 .2689 9.19 .000 U0 .1034 17 67.82 .000g10 �.0079 �5.47 .000 U1 .0042 17 35.88 .005

eti .1132

Legend as for Appendix 2(a).

314 Hernandez-Lloreda and Colmenares

REFERENCES

Altmann, J. (1974). Observational study of behavior: Sampling

methods. Behaviour, 49, 227–247.

Altmann, J. (1978). Infant independence in yellow baboons. In

G. M. Burghardt, & M. Bekoff (Eds.), The development of

behavior (pp. 253–277). New York: Garland STPM Press.

Altmann, J. (1980). Baboon mothers and infants. Cambridge,

MA: Harvard University Press.

Altmann, J., & Samuels, A. (1992). Costs of maternal care:

Infant-carrying in baboons. Behavioral Ecology and Socio-

biology, 29, 391–398.

Barrett, L., Dunbar, R. I. M. & Dunbar, P. (1995). Mother–

infant contact as contingent behaviour in gelada baboons.

Animal Behaviour, 49, 805–810.

Barrett, L., & Henzi, S. P. (2000). Are baboon infants Sir Phillip

Sydney’s offspring? Ethology, 106, 645–658.

Bateson, P. P. G. (1981). Discontinuities in development and

changes in the organization of play in cats. In K. G.

Immelmann, W. Barlow, L. Petrinovich, & M. Main (Eds.),

Behavioral development (pp. 281–295). Cambridge: Cam-

bridge University Press.

Bateson, P. P. G. (1983). Genes, environment, and the

development of behaviour. In T. R. Halliday, & P. J. B.

Slater (Eds.), Animal behaviour, genes, environment, and

learning (Vol. 3), (pp. 52–81). Oxford: Blackwell.

Bateson, P. P. G. (2001). Behavioral development and

darwinian evolution. In S. Oyama, P. E. Griffiths, & R. D.

Gray (Eds.), Cycles of contingency. Developmental systems

and evolution (pp. 149–166). London: The MIT Press.

Bateson, P. P. G. (2003). The promise of behavioural biology.

Animal Behaviour, 65, 11–17.

Bateson, P. P. G., & Martin, P. (2000). Design for a life. How

behaviour develops. London: Cape.

Berman, C. M. (1984). Variation in mother–infant relation-

ships: Traditional and non-traditional factors. In M. F. Smith

(Ed.), Female primates (pp. 17–36). New York: Alan R. Liss.

Berman, C. M., Rasmussen, K. L. R., & Suomi, S. J. (1994).

Responses of free-ranging rhesus monkeys to a natural form

of social separation. I. Parallels with mother–infant separa-

tion in captivity. Child Development, 65, 1028–1041.

Blass, E. M. (Ed.). (1986). Handbook of behavioral neurobiol-

ogy. Developmental psychobiology and developmental

neurobiology (Vol. 8). New York: Plenum.

Blass, E. M. (Ed.). (1988). Handbook of behavioral neurobiol-

ogy. Developmental psychobiology and behavioral ecology

(Vol. 9). New York: Plenum.

Boyle, M. H., & Willms, J. D. (2001). Multilevel modelling of

hierarchical data in developmental studies. Journal of Child

Psychology and Psychiatry, 42, 141–162.

Bramblett, C. A., & Coelho, A. M. (1985). Age changes

in affinitive behaviors of baboons. American Journal of

Primatology, 9, 259–271.

Bryk, A. S., & Raudenbush, S. W. (1987). Application of

hierarchical linear models to assessing change. Psychological

Bulletin, 101, 147–158.

Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear

models: Applications and data analysis methods. London: Sage.

Bryk, A. S., Raudenbush, S. W., & Congdon, J. R. (1996).

HLM: Hierarchical linear and nonlinear modeling with the

HLM/2L and HLM/3L programs. Chicago: Scientific Soft-

ware international.

Butterworth, G., & Bryant, P. (Eds.). (1990). Causes of

development: Interdisciplinary perspectives. New York:

Harvester Wheatsheaf.

Chalmers, N. R. (1987). Developmental pathways of behaviour.

Animal Behaviour, 35, 659–674.

Colmenares, F. (1992). Clans and harems in a colony of

hamadryas and hybrid baboons: Male kinship, familiarity

and the formation of brother teams. Behaviour, 121, 61–94.

Colmenares, F. (2004). Kinship and its impact on social

behavior in multileveled societies. In B. Chapais, & C.

Berman (Eds.), Kinship and behavior in primates (pp. 242–

270). Oxford: Oxford University Press.

Colmenares, F., & Gomendio, M. (1988). Changes in female

reproductive condition following male take-overs in a colony

of hamadryas and hybrid baboons. Folia Primatologica, 50,

157–174.

De Vore, I. (1963). Mother–infant relations in free-ranging

baboons. In H. L. Rheingold (Ed.), Maternal behavior in

Mammals (pp. 305–335). New York: Wiley.

Deputte, B.(2000). Primate socialization revisited: Theoretical

and practical issues in social ontogeny. Advances in the

Study of Behavior, 29, 99–157.

Esteban, M. M., & Colmenares, F. (2001). The effect of the

mother’s first postpartum oestrus on the mother–infant

relationship in a non-seasonally breeding species, the

hamadryas baboon (Papio hamadryas). Folia Primatologica,

72, 353.

Fairbanks, L. A. (1996). Individual differences in maternal

style. Causes and consequences for mothers and offspring.

Advances in the Study of Behavior, 25, 579–611.

Fairbanks, L. A. (2003). Parenting. In D. Maestripieri (Ed.),

Primate psychology (pp. 144–170). Cambridge: Harvard

University Press.

Fletcher, A. (2001). Development of infant independence from

the mother in wild mountain gorillas. In M. M. Robbins, P.

Sicotte, & K. Stewart (Eds.), Mountain gorillas (pp. 153–182).

Cambridge: Cambridge University Press.

Goldstein, H. (2003). Multilevel statistical models ( 3rd ed.)

London: Hodder Arnold.

Goldstein, H., Rasbash, J., Plewis, I., Draper, D., Browne, W.,

Yang, M., Woodhouse, G., & Healy, M. (1998). A user’s

guide to MlwiN. London: Multilevel models Project,

Institute of education, University of London.

Gottlieb, G. (1976). Conceptions of prenatal development:

Behavioral embriology. Psychological Review, 83, 215–234.

Gottlieb, G. (1992). Individual development and evolution: The

genesis of novel behavior. Oxford: Oxford University Press.

Gottlieb, G. (2001). A developmental psychobiological systems

view: Early formulation and current status. In S. Oyama, P. E.

Griffiths, & R. D. Gray (Eds.), Cycles of contingency.

Developmental systems and evolution (pp. 41–54). London:

The MIT Press.

Gould, S. J. (1977). Ontogeny and phylogeny. Cambridge:

Harvard University Press.

Developmental Pathways and Mother–Infant Relationships 315

Hall, W. G., & Oppenheim, R. W. (1987). Developmental

psychobiology: Prenatal, perinatal, and early postnatal

aspects of behavioral development. Annual Review of

Psychology, 38, 91–128.

Hernandez-Lloreda, M. V., & Colmenares, F. (2003). Assessing

continuity and stability of maternal styles in a colony of

baboons (Papio hamadryas). Folia Primatologica, 74,

198.

Hernandez-Lloreda, M. V., & Colmenares, F. (2005). Mother–

infant relationships in hamadryas baboons: Predictors of

individual differences and discontinuities in developmental

pathways. Journal of Comparative Psychology, 119.

Hernandez-Lloreda, M. V., & Colmenares, F. (2004). Partner

contribution to an ongoing dyadic relationship in hamadryas

baboons: Multivariate multilevel modelling of mother–

offspring relationships in hamadryas baboons. Folia Prima-

tologica, 75, 382.

Hernandez-Lloreda, M. V., Colmenares, F., & Martınez-Arias,

R. (2003). Application of hierarchical linear modelling to the

study of trajectories of behavioural development. Animal

Behaviour, 65, 607–613.

Hernandez-Lloreda, M. V., Colmenares, F., & Martınez-Arias,

R. (2004). Application of piecewise hierarchical linear

growth modeling to the study of discontinuities in behavioral

development. Journal of Comparative Psychology, 118, 316–

324.

Hinde, R. A. (1974). Biological bases of human social behavior.

New York: McGraw-Hill.

Hinde, R. A. (Ed.). (1983). Primate social relationships: An

integrated approach. Oxford: Blackwell.

Hofer, M. A. (1987). Early social relationships: A psychobiol-

ogist’s view. Child Development, 58, 633–647.

Hoo, M.-W. (1998). Evolution. In G. Greenberg, & M. M.

Haraway (Eds.), Comparative psychology, a handbook

(pp. 107–119). New York: Garland.

Hood, K. E. (1998). Dynamical systems and dialectical

processes in development and evolution. In G. Greenberg,

& M. M. Haraway (Eds.), Comparative psychology, a

handbook (pp. 98–104). New York: Garland.

Hox, J. J., & Kreft, I. G. (1994). Multilevel analysis methods.

Sociological Methods & Research, 22, 283–299.

Hrdy, B. S. (1999). Mother nature. A history of mothers,

infants, and natural selection. New York: Pantheon.

Immelmann, K., Barlow, G. W., Petrinovich, L., & Main, M.

(Eds.). (1981). Behavioral development. Cambridge: Cambridge

University Press.

Johnston, J. D., & Gottlieb, G. (2000). Neophenogenesis: A

developmental theory of phenotypic evolution. Journal of

Theoretical Biology, 147, 471–495.

Kappeler, P. M., Pereira, M. E., & van Schaik, C. P. (2003).

Primate life histories and socioecology. In P. M. Kappeler, &

M. E. Pereira (Eds.), Primate life histories and socioecology

(pp. 1–23). Cambridge: Cambridge University Press.

Kraemer, G. W. (1992). A psychobiological theory of

attachment. Behavioral and Brain Sciences, 15, 493–541.

Kummer, H. (1984). From laboratory to desert and back: a

social system of hamadryas baboons. Animal Behaviour, 32,

965–971.

Lewkowicz, D. J., & Lickliter, R. (Eds.). (2002). Concepts of

development. New York: Psychology Press.

Lewontin, R. (1983). Gene, organism, and environment. In D.

S. Bendall (Ed.), Evolution from molecules to man (pp. 273–

285). Cambridge: Cambridge University Press.

Lycett, J. E., Henzi, S. P., & Barrett, L. (1998). Maternal invest-

ment in mountain baboons and the hypothesis of reduced

care. Behavioural Ecology and Sociobiology, 42: 49–56.

MacCallum, R. C., & Kim, C. (2000). Modeling multivariate

change. In T. D. Little, K. U. Schanabel, & J. Baumrt (Eds.),

Modeling longitudinal and multilevel data (pp. 51–68). New

Jersey: LEA.

Maestripieri, D. (1994). Mother–infant relationships in three

species of macaques (Macaca mulatta, M. nemestrina, M.

arctoides). I. Development of the mother–infant relationship

in the first three months. Behaviour, 131, 75–96.

Maestripieri, D. (2001). Intraspecific variability in parenting

styles of rhesus macaques (Macaca mulatta): The role of the

social environment. Ethology, 107, 237–248.

Maestripieri, D. (2002). Parent-offspring conflict in primates.

International Journal of Primatology, 23, 923–951.

Maestripieri, D. (2003). Attachment. In D. Maestripieri (Ed.),

Primate psychology (pp. 108–143). Cambridge: Harvard

University Press.

Maestripieri, D. (2004). Genetic aspects of mother–offspring

conflict in rhesus macaques. Behavioral Ecology and Socio-

biology, 55, 381–387.

Martin, P., & Bateson, P. P. G. (1993). Measuring behaviour:

An introductory guide. Cambridge: Cambridge University Press.

Michel, G. F. (2001). Growth curve analyses are best suited to

examine the relation between developmental pathways and

selective breeding: Comment on Hofer, Shair, Masmela, &

Brunelli, ‘‘Developmental effects of selective breeding for

an infantile trait: The rat pup ultrasonic isolation call’’.

Developmental Psychobiology, 39, 247–250.

Michel, G. F., & Moore, C. L. (1995). Developmental

psychobiology, an interdisciplinary science. Cambridge, Mass:

The MIT Press.

Montgomery, D. C., Peck, E. A., & Vining, G. G. (2001).

Introduction to linear regression analysis (3rd ed.) New York:

Wiley.

Nash, L. T. (1978). The development of mother–infant

relationship in wild baboons (Papio anubis). Animal

Behaviour, 26, 746–759.

Nash, L. T., & Wheeler, R. L. (1982). Mother–infant relation-

ships in non-human primates. In H. E. Fitzgerald, J. A.

Mullins, & P. Gage (Eds.), Child nurturance: Primate behavior

and child nurturance (Vol. 3) (pp. 27–59). New York: Plenum.

Nicolson, N. A. (1982). Weaning and the development of

independence in olive baboons. Ph.D. thesis, University of

Harvard.

Nicolson, N. A. (1987). Infants, mothers, and other females. In

B. B. Smuts, D. L. Cheney, R. M. Seyfarth, R. W. Wrangham,

& T. T. Struhsaker (Eds.), Primate societies (pp. 330–342).

Chicago: Chicago University Press.

Oyama, S. (1982). A reformulation of the idea of maturation. In

P. P. G. Bateson, & P. H. Klopfer (Eds.), Perspectives in

ethology (pp. 101–131). New York: Plenum.

316 Hernandez-Lloreda and Colmenares

Oyama, S. (2000). Evolution’s eye. A systems view of the

biology-culture divide. London: Duke University Press.

Oyama, S., Griffiths, P. E., & Gray, R. D. (2001). Introduction:

what is developmental systems theory? In S. Oyama, P. E.

Griffiths, & R. D. Gray (Eds.), Cycles of contingency.

Developmental systems and evolution (pp. 1–11). London:

The MIT Press.

Pereira, M. E., & Altmann, J. (1985). Development of social

behavior in free-living nonhuman primates. In E. S. Watts

(Ed.), Nonhuman primate models for human growth and

development (pp. 217–309). New York: Alan Liss.

Pryce, C. R., Martin, R. D., & Skuse, D. (Eds.). (1995).

Motherhood in human and nonhuman primates. Biosocial

determinants. Basel: Karger.

Ransom, T. W., & Rowell, T. E. (1972). Early social

development of feral baboons. In F. E. Poirier (Ed.),

Primate socialization (pp. 105–144). New York: Random

House.

Raudenbush, S. W. (2001). Comparing personal trajectories and

drawing causal inferences from longitudinal data. Annual

Review of Psychology, 52, 501–525.

Raudenbush, S. W., Bryk, A. S., Cheong, F., & Congdon, R.

(2004). HLM 6: Hierarchical linear and nonlinear modeling.

Chicago: Scientific Software international.

Rhine, R. J., Norton, G. W., & Westlund, B. J. (1984). The

waning of dependence in infant free-ranging yellow baboons

(Papio cynocephalus) of Mikumi National Park. American

Journal of Primatology, 7, 213–228.

Rhine, R. J., Norton, G. W., Wynn, G. M., & Wynn, R. D. 1985.

Weaning of free-ranging infant baboons (Papio cynocephalus)

as indicated by one-zero and instantaneous sampling of

feeding. International Journal of Primatology, 6, 491–499.

Rowell, T. E., Din, N. A., & Omar, A. (1968). The social

development of baboons in their first three months. Journal of

Zoology, 155, 461–483.

Sackett, G. P., Sameroff, A. J., Cairns, R. B., & Suomi, S. J.

(1981). Continuity in behavioral development: Theoretical

and empirical issues. In K. Immelmann, G. W. Barlow, L.

Petrinovich, & M. Main (Eds.), Behavioral development

(pp. 23–57). Cambridge: Cambridge University Press.

Snijders, T. A. B., & Bosker, R. J. (1999). Multilevel analysis:

An introduction to basic and advanced multilevel modeling.

London: Sage Publications.

Suomi, S. J. (1995). Influence of attachment theory on etholo-

gical studies of biobehavioral development in nonhuman

primates. In S. Goldberg, R. Muir, & J. Kerr (Eds.), Attach-

ment theory: Social, developmental, and clinical perspectives

(pp. 185–201). Hillsdale, NJ: The Analytic Press.

Suomi, S. J. (1997). Early determinants of behaviour: Evidence

from primate studies. British Medical Bulletin, 53, 170–184.

Suomi, S. J., Novak, M. A., & Well, A. (1996). Aging in rhesus

monkeys: Different windows on behavioral continuity and

change. Developmental Psychology, 32, 1116–1128.

Turkewitcz, G. (1992). Developmental psychobiology. New

York: The New York Academy of Sciences.

Van der Leeden, R. (1998). Multilevel analysis of longitudinal

data. In C. C. J. Bijleveld ,& X. Van der Kamp (Eds.),

Longitudinal data analysis (pp. 268–315). London. Sage.

Wasser, L. M., & Wasser, S. K. (1995). Environmental variation

and developmental rate among free ranging yellow baboons

(Papio cynocephalus). American Journal of Primatology, 35,

15–30.

Willett, J. B. (1988). Questions and answers in the measurement

of change. In E. Rothkopf (Ed.), Review of Research in

Education (1988–1989) (pp. 345–422). Washington, DC:

American Educational Research Association.

Wohlwill, J. (1973). The study of behavioral development. San

Diego, CA: Academic Press.

Zucchini, W. (2000). An introduction to model selection.

Journal of Mathematical Psychology, 44, 41–61.

Developmental Pathways and Mother–Infant Relationships 317