Download Natural selection and animal personality

Natural selection and animal personality
Niels J. Dingemanse1,2) & Denis Réale3)
(1 Animal Ecology Group, Centre for Evolutionary and Ecological Studies, University of
Groningen, PO Box 14, 9750 AA Haren, The Netherlands; 3 Canadian Research Chaire in
Behavioural Ecology and Groupe de Recherche en Ecologie Comportementale et Animale,
Département des Sciences Biologiques, Université du Québec à Montréal, CP-8888,
Succursale Centre-ville, Montréal, Québec, H3C 3P, Canada)
(Accepted: 1 February 2005)
Summary
Recent progress has been made on the study of personality in animals, both from a mechanistic and a functional perspective. While we start knowing more about the proximal mechanisms responsible for the consistent differences in behaviour between individuals in a population, little is known yet about the relationship between the phenotypic distribution of personality traits, or combinations of traits, and fitness. Here we provide an overview of the
available literature on the fitness consequences of personality traits in natural populations.
We start by a description of two case studies that have examined the role of natural selection on personality traits in the wild (i.e., the great tit, Parus major and bighorn sheep, Ovis
canadensis), and review other studies that have reported some links between personality traits
and fitness indices, in a large variety of animal species. We continue by outlining both direct
approaches (i.e., measuring correlational selection on personality trait combinations) and indirect approaches (i.e., comparing correlations between personality traits within and between
populations) to study suites of correlated traits from an adaptive perspective. This review,
we hope, will be able to stimulate the use of the phenotypic selection analysis applied to the
study of selection on personality traits in animals.
Keywords: personality, behavioural syndromes, reproductive success, sexual selection, correlational selection, genetic constraints.
Introduction
Behavioural flexibility is often regarded to be unlimited, immediate, and reversible (Sih et al., 2004a, b), allowing individuals to maximize their fitness
2)
Corresponding author’s e-mail address: [email protected]
© Koninklijke Brill NV, Leiden, 2005
Behaviour 142, 1165-1190
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in the many different environments they encounter during life. Contrary to
this notion of behavioural plasticity as the major adaptive cause of phenotypic variation in behaviour (Houston & McNamara, 1999; Dall et al., 2004;
Neff & Sherman, 2004), animals often show very limited behavioural plasticity (Sih et al., 2004a, b) and commonly differ consistently in their reaction
towards the same environmental stimuli (Clark & Ehlinger, 1987; Wilson et
al., 1994; Boissy, 1995; Wilson, 1998; Gosling, 2001; Greenberg & MettkeHofmann, 2001). These individual differences in behaviour are, moreover,
frequently expressed across a wide range of contexts and situations: individuals commonly differ consistently in whole suites of functionally-distinct
behavioural traits (Sih et al., 2004a, b). For instance, in birds (Verbeek et
al., 1996), rodents (Koolhaas et al., 2001), and fish (Huntingford, 1976), animals that are relatively aggressive towards conspecifics are also bolder in
exploring novel environments and predators. These individual differences in
suites of correlated traits have been named behavioural syndromes (Sih et al.,
2004a, b), coping strategies (Koolhaas et al., 2001), temperament (Boissy,
1995; Clarke & Boinski, 1995) or animal personality traits (Buss, 1991;
Gosling, 2001).
The evolutionary origin and maintenance of phenotypic variation in animal personality is poorly understood (Stamps, 1991; Wilson et al., 1994;
Wilson, 1998; Dingemanse et al., 2004; Dall et al., 2004; Sih et al., 2004a).
Both mechanistic and functional approaches need to be applied to gain full
understanding of why this behavioural variation persists (Stamps, 1991,
2003). The mechanistic approach seeks to evaluate how phenotypes result
from the combined influences of genetic and environmental factors; the functional approach how the interaction between phenotypes and their environment affects fitness. Variation in personality has received considerable attention from the mechanistic viewpoint; the emerging pattern is that individual
differences in single components of animal personality (e.g., aggressiveness)
are moderately heritable and relatively stable over the entire life of the individual (Boissy, 1995; Koolhaas et al., 1999; Bouchard & Loehlin, 2001)
and that phenotypic correlations between components of personality (e.g.,
between aggressiveness and boldness) often originate from strong underlying genetic correlations (Bakker, 1994; Bult & Lynch, 2000; van Oers et al.,
2004a; Bell, 2005). In contrast, functional approaches towards understanding variation in personality have received far less attention (Réale & FestaBianchet, 2003; Dingemanse et al., 2004; Dall et al., 2004), despite the fact
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that only the combination of both approaches (in the same study system) will
allow an informed evaluation of how behavioural traits might (co)evolve under different environmental conditions (Fisher, 1930; Endler, 1986).
This paper has a three-fold aim. First, we aim to provide an overview of
the available literature on the fitness consequences of personality traits in natural populations. In doing so, we largely concentrate our discussion on few
study systems where both mechanistic and functional approaches have been
applied to understand natural variation in personality, and where selection on
behavioural phenotypes has been measured in all major life-history stages
and over a number of years; thus providing first detailed descriptions of how
and when natural selection may operate on animal personality traits. We further discuss examples of a range of study systems where selection on animal
personality has been measured incompletely using short-term proxies for
fitness only. We emphasize the importance of applying a holistic approach
when studying animal personality from an adaptive perspective. Notably,
various studies have addressed some (supposed) functional aspect of human personality, e.g., susceptibility to illness (Grossarthmaticek & Eysenck,
1990; Schmitz, 1992) or levels of stress hormones (Bruce et al., 2002), but
direct links between personality and fitness have rarely been addressed (but
see Eaves et al., 1990; Mealey & Segal, 1993; Wilson, 1994; Nettle et al.,
2005). Our review thus focusses primarily on nonhuman animals.
To date, the few available naturalistic studies have addressed the functional consequences of animal personality by describing how selection operates on single components of animal personality (e.g., exploratory behaviour of novel environments as a measure of ‘avian personality’ in great tits;
Dingemanse et al., 2002). Our second aim is to point out that, ultimately,
such studies cannot provide functional explanations for the existence of animal personality per se, as this would require insight in why individuals show
consistency in their behaviour, either across time, generations, contexts or
situations (Dall et al., 2004; Sih et al., 2004a). We outline both direct and
indirect approaches to study suites of correlated traits from an adaptive perspective.
Our third and last aim is to stimulate the use of the phenotypic selection
approach (Lande & Arnold, 1983) when quantifying fitness consequences of
animal personality, as this approach produces standardized estimates of the
strength of selection that can directly be compared with those derived from
other studies on the same or other types of traits (Kingsolver et al., 2001).
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Natural selection and personality
Natural selection is measured by the covariance between traits and fitness
(Endler, 1986), allowing one to estimate both the shape (Brodie et al., 1995)
(i.e., directional, stabilizing, disruptive) and the strength of selection (Kingsolver et al., 2001), including patterns of selection on correlated characters
(Lande, 1979; Lande & Arnold, 1983; Kingsolver et al., 2001) as well as
correlational selection (selection for optimal trait combinations; Barton &
Turelli, 1991). These estimation models thus provide a suitable method for
studying selection on suites of correlated traits, like life-history syndromes or
personality traits (Réale & Festa-Bianchet, 2003). When quantitative genetic
parameters have also been quantified (i.e., heritability of and genetic correlations between components of personality traits), one can make an informed
evaluation of the evolutionary consequences of the imposed selective regime
(Falconer & Mackay, 1996; Roff, 1997; Lynch & Walsh, 1998), including
the evolution of genetic correlations between behavioural traits (Roff, 1996),
i.e., animal personality. Here we discuss the few yet available field studies
on the fitness consequences of animal personality, with special reference to
two study species in the wild, great tit (Parus major) and the bighorn sheep
(Ovis canadensis), where both quantitative genetics parameters and fitness
landscapes of animal personality have been quantified simultaneously and in
natural populations, providing a first insight in the evolutionary potential of
personality traits.
Fitness consequences of personality in great tits
Individual differences in suites of correlated traits
Laboratory studies on hand-reared great tits showed that individuals differed in their reaction toward novel or challenging stimuli, comparable to
how rodents differ in reactivity (Verbeek et al., 1994; Koolhaas et al., 2001;
Groothuis & Carere, 2005). In these birds, speed of exploration of novel (laboratory) environments is positively correlated with aggressiveness towards
conspecifics (Verbeek et al., 1996; Carere et al., in press), boldness towards
novel objects (Verbeek et al., 1994), risk-taking (van Oers et al., 2004b,
2005a) and scrounging (Marchetti & Drent, 2000) during foraging, and stress
responsiveness (Carere et al., 2001, 2003; Carere & van Oers, 2004). Two
bi-directional selection experiments, the first on a combined score for exploration and boldness (‘early exploratory behaviour’; Drent et al., 2003) and
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the second on risk-taking behaviour (van Oers et al., 2004b), gave realized
heritabilities of 0.54 and 0.19 respectively and evidence for a strong genetic
correlation (0.84) between early exploratory behaviour and risk-taking under
laboratory conditions (van Oers et al., 2004a). Repeatabilities (range: 0.270.66; Dingemanse et al., 2002) and narrow-sense heritabilities (0.34±0.13;
Dingemanse et al., 2004) were considerably lower for wild great tits, suggesting that environmental factors (i.e., those controlled for in the laboratory)
also influenced exploratory behaviour in the wild (Riska et al., 1989; see also
Carere et al., 2005 for a discussion on environmental sources of variation in
great tits). Alltogether, these quantitative genetics studies showed that great
tits differ in suites of (genetically) correlated traits, with the extremes of the
trait distribution (ranging from ‘slow’ to ‘fast’ exploratory behaviour) reflecting alternative behavioural strategies to cope with novel or challenging
stimuli (Verbeek et al., 1994; Drent et al., 2003; Carere et al., in press). Relatively high levels of both additive and nonadditive genetic variance in early
exploratory behaviour of laboratory-bred great tits (van Oers et al., 2004c)
suggested a history of fluctuating selection pressures in this population (see
van Oers et al., 2005b).
Measuring personality of wild animals
To quantify selection on avian personality in the wild, large numbers of
wild great tits (1342 individuals between 1998-2002; N.J. Dingemanse, pers.
comm.) were captured from a nest-box population in the Netherlands and
transported to the laboratory where they were housed individually (Dingemanse et al., 2002). The following morning, exploratory behaviour was measured for each bird individually in a sealed room containing five artificial
trees (following Verbeek et al., 1994), before the birds were released back
in the wild at their individual place of capture. The total number of flights
and hops within the first 2 mins were used as an index of their exploratory
behaviour (Dingemanse et al., 2002). Exploratory behaviour was both repeatable and heritable (see above), and unrelated to age, body condition, or sex
(Dingemanse et al., 2002). Subsequent field studies revealed that the fitness
consequences of avian personality were complex (Figures 1, 2).
Fitness consequences: adult annual survival
Selection as measured by adult annual survival acted on exploratory behaviour (based on one test per individual), but the effects were always opposite
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Figure 1. Overview of the consequences of exploratory behaviour of wild adult great tits
(Parus major) for two major fitness components (survival and production of recruits). Arrows
represent measured (solid lines) or presumed (broken lines) direct or indirect relationships as
based on the correlational studies discussed in the text. Symbols indicate the shape of linear
(+: positive; −: negative) and non-linear (s: stabilising selection; d: disruptive selection)
relationships. Notably, the relation between exploratory behaviour and offspring mass was
variable (denoted ‘v’), as offspring body mass was a function of the interaction between
the personality type of the individual and its mate. In cases where the consequences of
exploratory behaviour differed between years or classes of individuals, the relationships have
been given for each group separately (for more details see Figure 2). These descriptive studies
suggested that fast-exploring adults survived relatively well in environments with intensified
intra-sexual competition (ISC), but that they survived relatively poorly when ISC was relaxed,
and that the overall shape of natural selection was stabilizing. For more details see the text.
for males and females, and reversed between years (Figure 2; Dingemanse et
al., 2004). In a year with masting of beeches Fagus sylvaticus (2000), when
great tits experience relaxed competition for winter food (Perdeck et al.,
2000), and subsequent high recruitment rates in spring (i.e., intensified competition for territorial space), fast-exploring adult males and slow-exploring
adult females had highest survival. This pattern was reversed in two years
(1999, 2001) with little winter food and subsequent low recruitment rates,
when slow-exploring adult males and fast-exploring adult females had highest survival rates.
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Figure 2. Schematic overview of the fitness consequences of exploratory behaviour of
novel environments (ranging from ‘slow’ to ‘fast’) in wild great tits (Parus major) for two
types of years (poor [1999/2001] = no beech masting; rich [2000] = beech masting) (Dingemanse et al., 2004). The arrows indicate the shape of selection (→ directional selection
favouring fast; ← directional selection favouring slow; →← stabilising; ←→ disruptive)
for two main fitness components, adult annual survival and offspring recruitment, Hatched
bars indicate nonsignificant trends. For more details see text.
Temporal variability in environmental conditions
Dingemanse et al. (2004) hypothesized that beech masting affected the
strength of intra-sexual competition but that these effects were always opposite for territorial males and females (Figures 1, 2): because females were
subordinate to males (Dingemanse & de Goede, 2004), they were likely to be
most affected by competition for winter food. Beech masting therefore may
result in relaxed intra-sexual competition among females, while competition
is intensified in years without beech mast. As only males defend territories,
they are likely to be most affected by competition for territorial space. In
years with beech masting, recruitment rates are high (Perdeck et al., 2000),
resulting in intensified intra-sexual competition among males (Both et al.,
1999), while in non-beech mast years competition is relaxed. The complex
patterns in adult survival (Figures 1, 2) may thus reflect that fast-exploring
adults survived relatively well in years with intensified intra-sexual competition, and that they survived relatively poorly when competition was relaxed.
Notably, the potential cause for the poor survival of fast-exploring adults
in such years has not yet been identified. This notion of differential competitive ability was supported by the finding that fast-exploring adults dominated
slow-exploring adults when competing for winter food (Dingemanse & de
Goede, 2004) and that fast-exploring adults bred on the best breeding terri-
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tories (Both et al., 2005). Factors affecting adult survival are summarized in
Figure 1.
Between-year fluctuation in selection on personality traits in the great tits
is similar to results from other studies on other types of traits (Merilä et al.,
2001). This result indicates that selection studies should be performed on the
long-term if we want to understand both the immediate consequences (within
a year) and longer term effects (across several generations) of selection on
populations.
Fitness consequences: offspring production and recruitment
Slow-exploring females had higher nest success (were more likely to produce at least one fledged offspring), and produced larger offspring than fastexploring females (Both et al., 2005). Pairs of assortative phenotypes, consisting of two slow partners or two fast partners, produced offspring with
highest body mass in all years of the study (Both et al., 2005). Selection
as measured by the number of these offspring that survived and bred in the
study area (‘offspring recruitment’) acted on female, and to a lesser extent on
male exploratory behaviour and fluctuated between years (Figure 2; Dingemanse et al., 2004). Selection on exploratory behaviour was stabilising in the
two years without beech masting, but was disruptive in the year with beech
masting. The personality of both the male and the female parent contributed
to this pattern of disruptive selection, as pairs consisting of assorted partners (i.e., fast-fast or slow-slow pairs) produced most recruits in the beech
crop year (Dingemanse et al., 2004). These assorted pairs also produced offspring of highest body mass (see above), and as body mass affects competitive ability and juvenile winter survival in years with intense competition for
resources among juveniles (Both et al., 1999), this pattern of disruptive selection probably acted via offspring body mass in the year with beech crop.
Interestingly, pairs of medium-exploring adults nevertheless produced most
recruits in years without beech crop, suggesting that the higher than average offspring body mass of assortative pairs only increased fitness in certain
years and that other characteristics of the offspring phentoype (e.g., their
exploratory behaviour, see Figure 1) affected offspring recruitment.
Fitness consequences: explaining variable patterns in offspring recruitment
While these variable patterns in adult survival have now resulted in testable
hypotheses, (i.e., fluctuating and sex-specific survival (Figure 2) reflected
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variable selection for competitive ability with sexes; Figure 1), sources of
variation in offspring recruitment are not well understood (see question
marks in Figure 1). As outlined above, the variance in offspring recruitment partly resulted from variation in parental breeding performance, but
primarily in years with beech crop. Offspring recruitment patterns may
also have been partly mediated directly via exploratory behaviour inherited
from parents to offspring (e.g., by affecting offspring foraging success; Figure 1). Field studies showed that exploratory behaviour affects both competitive ability and settlement decisions of juveniles: fast-exploring juveniles
had lowest dominance ranks when nonterritorial (Dingemanse & de Goede,
2004) and came to breed further from home (Dingemanse et al., 2003).
Evolutionary consequences
Natural selection acted on avian personality, but the direction of selection
varied between sexes, age-classes and years with different selective regimes.
Because exploratory behaviour of wild great tits is heritable (see above) and
affects components of fitness, selection on avian personality can lead to evolutionary change (Fisher, 1930; Endler, 1986). While considering that the
response to selection depends both on the frequency with which individuals experience different selective environments as well as the strength of
selection in these environments (Figure 1), the overall pattern of selection
turned out to be stabilising (Dingemanse et al., 2004): Adults of intermediate phenotype had highest offspring recruitment rates in most years, as
masting of beeches occurs only about once every three years (Perdeck et al.,
2000). Furthermore, the variance in adult survival was lowest for intermediate phenotypes, resulting in highest overall life expectancy. Taking these
long-term fitness consequences into consideration, adult males may have
maximized their fitness by means of adaptive mate choice: adult males of
extreme phenotype were mated disassortatively with respect to personality
type (Dingemanse et al., 2004), allowing them to produce offspring of intermediate phenotype and increase their lifetime fitness. Notably, disassortative
mating seemed maladaptive when only considering that assortative pairs had
highest reproductive success (Both et al., 2005). Temporal variability in selection as observed for this study system can slow down the loss of genetic
variation in avian personality (Sasaki & Ellner, 1997; Burger & Gimelfarb,
2002), but it cannot, however, provide an ultimate explanation for the maintenance of genetic variation in avian personality. Either a balance between
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mutation, selection and migration in a spatially variable environment (Nevo,
1988; Frank & Slatkin, 1990) or frequency-dependent selection (Maynard
Smith, 1982) probably need to be invoked to explain this behavioural diversity from an adaptive perspective (Dingemanse et al., 2004; Both et al.,
2005). Similarly, we do yet need to reveal why individual great tits showed
such limited behavioural plasticity, as behavioural flexibility seems adaptive
in such a temporally variable environment (Dall, 2004).
Fitness consequences of boldness and docility in bighorn sheep
Individual differences in correlated behaviours
In a wild Canadian population of bighorn sheep, individuals differed consistently in their willingness to enter corral traps baited with salt (Réale et
al., 2000). This behavioural variability was assumed to reflect individual differences in boldness (i.e., willingness to take the risk involved in licking
salt), where boldness was measured as the yearly number of times a ewe
was captured in the trap. Repeatability (between years) and heritability estimates were 0.36 and 0.21 respectively. Ewes captured in the trap were also
compared for their docility during handling: a docility score (based on a 7point scale) was used to measure how much individuals struggled during
handling. Docility was highly repeatable both within (r = 0.65-0.66) and
between years (r = 0.86); while some ewes were relatively docile, others
struggled to escape. There was a negative — though weak — phenotypic correlation between boldness and docility: shy ewes were also relatively docile.
This negative pattern appeared to be caused by the absence of shy, nondocile ewes. Estimation of quantitative genetics parameters using the ‘animal model’ (Lynch & Walsh, 1998) revealed significant heritabilities of both
behaviours as well as a moderate negative genetic correlation between these
behaviours (D. Reale & D. Coltman, unpubl. data).
Fitness consequences: reproductive success
Using standard multiple regression techniques to evaluate selection on correlated characters (Lande & Arnold, 1983), selection on each behaviour was
measured independently of selection on the other (Réale et al., 2000; Réale
& Festa-Bianchet, 2003). Selection measured with age at first reproduction
as a fitness index acted both on boldness and docility (Réale et al., 2000).
Bold ewes reproduced at an earlier age than shy ewes. Similarly, docile ewes
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tended to reproduce at an earlier age than nondocile ewes. Selection measured with weaning success (the number of lambs weaned between first reproduction and the end of the study) as fitness index acted on boldness only,
with bold ewes having higher weaning success than shy ewes (Réale et al.,
2000).
Fitness consequence: adult annual survival
Selection measured with adult annual survival as a fitness index acted both
on boldness and docility, but the effects differed between years (Réale &
Festa-Bianchet, 2003). In the first year of the study, with low predation by
cougars Puma concolor, survival was high and unrelated to either age or
boldness (docility was not yet measured). In both of the following two years,
when predation by cougars was intense, survival rates dropped substantially
and selection acted both on age and boldness. These two years, young or
bold ewes survived better than old or shy ewes, respectively. In the second
year with high predation, when docility was also measured, survival related
also to docility and its interaction with age: survival was lowest for ewes
that were both young and nondocile. In the fourth year of the study, when
predation of cougars was again low, survival was again high and unrelated to
either age, boldness, or docility.
Evolutionary consequences
As both boldness and docility were moderately heritable and genetically correlated (see above), the documented selective pressures acting on these traits
could lead to evolutionary change (Fisher, 1930; Endler, 1986). While considering all major fitness components, boldness appeared to be under directional selection favouring bold ewes (Réale et al., 2000; Réale & FestaBianchet, 2003). Bold ewes started reproducing earlier in life, had highest
reproductive output, and in years with cougar predation also had higher survival than shy ewes. Docility also appeared to be under directional selection,
although the selection gradients were less steep (Réale et al., 2000; Réale
& Festa-Bianchet, 2003): docility did not directly affect reproductive output, but docile ewes tended to start reproducing earlier in life than nondocile
ewes, and survival selection in years with cougar predation favoured docile
individuals among young ewes. As boldness and docility were negatively
correlated, directional selection for bold ewes indirectly selects for nondocile
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ewes, and vice versa, directional selection for docile ewes indirectly selects
for shy ewes. The negative genetic correlation between boldness and docility
is thus likely to act as an evolutionary constraint by preventing both traits
from evolving to their independent optimum, at the same time, however,
providing a partial explanation for the persistence of genetic variation in
both behavioural traits (Mangel & Stamps, 2001). Alternatively, the negative phenotypic and genetic correlations may have resulted from selection
acting against ewes that show a combination of both high shyness and low
docility. Unfortunately, because of sample size limitation, this study could
not estimate correlational selection on boldness and docility in ewes.
Fitness studies in other species
Several field studies on other species have also shown a link between some
personality traits and (usually single components of) fitness, though integrative studies as the ones described above are still rare. Here we give examples
of documented naturalistic fitness studies on animal personality in a range of
animal taxa.
Fitness studies of personality in monkeys
Another example illustrating the ecological importance of personality traits
is the extensive studies on free-ranging and captive rhesus monkeys (Macaca
mulatta). These studies have shown that many behavioural traits are related with the rate of turn-over of a neurotransmitter (serotonin: 5-HT) in
the central nervous system, and affect individual fitness (Figure 3). First,
cerebrospinal fluid concentration of 5-HIAA and other monoamine concentrations and associated behaviour expressions (e.g., impulsivity, aggressiveness) have been shown to be both repeatable and heritable in this species
and other nonhuman primates (Clarke et al., 1995; Higley & Linnoila, 1997;
Fairbanks et al., 2004). Young males with low 5-HIAA concentration are
less often engaged in grooming and social activities (Mehlman et al., 1995),
and more often involved in violent aggressive interactions (Mehlman et al.,
1994) with their conspecifics than males with high 5-HIAA concentration.
These males were also more often wounded and dispersed at an earlier age
(Mehlman et al., 1994, 1995). The same phenomenon has been observed
for low 5-HIAA females, which stay in their natal group but can hardly
reach a high dominance rank (Higley et al., 1996a). Low 5-HIAA individuals
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Figure 3. Serotonin turn-over, behaviour, and fitness in rhesus monkeys (Macaca mulatta). Serotonin has been measured by the Cerebrospinal Fluid concentration of 5-hydroxyindolacetic acid (5-HIAA), a metabolite of serotonine (5-HT: 5-HydroxyTryptamin). Symbols indicate the shape of the relationship (+: positive; −: negative). For more details see
text.
also take more life threatening risks, such as leaping from treetop to treetop
(Mehlman et al., 1994; Westergaard et al., 2003b). As a result, low 5-HIAA
individuals are characterised by premature death (Higley et al., 1996b). CSF
5-HIAA concentration can also affect fitness, through its effects on reproductive behaviour. For example, low 5-HIAA males less often consort with
oestrus females and are less often involved in heterosexual mounts and insemination (Mehlman et al., 1997), whereas low 5-HIAA females are more
protective mothers and experience a higher rate of foetal and infant loss
(Cleveland et al., 2003; Westergaard et al., 2003a). Considering all the evidence for selection favouring high 5-HIAA levels individuals over low level
ones, Mehlman et al. (1997) questionned the mechanisms responsible for the
maintenance of variation of these traits over time. Here we can provide two
possible explanations: First, 5-HIAA concentration may be subject to correlational selection with other traits, which would allow the maintenance of
genetic variation for each traits (see also examples on bighorn sheep and humans for a similar line of argumentation). Second, environmental conditions
of the free-ranging and/or captive populations may differ strongly from natural environments, resulting in different selection pressures. For example, in
a natural environment low 5-HIAA individuals might perform better when
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confronted with predators or when searching for new favourable habitats.
This study on rhesus macaques is one of the most complete investigations of
the link between a neurotransmitter, behaviour, life history and fitness.
Fitness studies of boldness in freshwater fish
Personality variation has received considerable attention in freshwater fish,
started by a paper of Huntingford (1976) on the aggressiveness-boldness syndrome in three-spined stickleback (Gasterosteus aculeatus). In recent years,
various studies have attempted to evaluate functional consequences of personality variation in fish. In Trinidad killifish (Rivulus hartii), individuals
that were bold in exploration of novel environments dispersed furthest (for
similar findings in other taxa see Dingemanse et al., 2003; Armitage & Van
Vuren, 2003; Krakov, 2003) and had larger growth rates (Fraser et al., 2001).
Laboratory studies on other species of freshwater fish have found similar
results (Magnhagen & Staffan, 2003; Ward et al., 2004; Westerberg et al.,
2004) and showed that bold fish grew quicker because of their competitive
superiority in direct competition for food (Höjesjö et al., 2002; Ward et al.,
2004; Sundström et al., 2004). A recent study on brown trout (Salmo trutta),
however, underlined the importance of measuring fitness in various environments that individuals may encounter (Réale & Festa-Bianchet, 2003;
Dingemanse et al., 2004), by showing that aggressive individuals had highest growth rates in simple habitats where food could easily be monopolised,
but lowest growth rates in spatially complex habitats (Höjesjö et al., 2004).
A capture-recapture study on wild brown trout further showed that survivorship did not differ between aggression phenotypes, suggesting that laboratory studies may only provide limited insight in the fitness consequences of
animal personality in the wild (Höjesjö et al., 2002). Importantly, the evidence from field studies in other taxa (see above) suggests that different
qualitative patterns of selection on personality traits may be shown when
selection is measured using different fitness components (Réale & FestaBianchet, 2003; Dingemanse et al., 2004), implying that insight in the overall fitness landscapes of personality traits in fish can probably not be based
on a single component of fitness.
Fitness studies in captivity
Fitness consequences of variation in personality have also been recorded in
captivity and may have consequences for the conservation of captive stocks
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(McDougall et al., in press). For instance, a study done on black rhinoceros
(Diceros bicornis) in 24 zoos has shown that in captivity females with lower
chasing/stereotypy/mouthing behaviour have highest reproductive success
(Carlstead et al., 1999). On the other hand, fear, docility, and activity (i.e.,
patrolling) were not significantly related to reproductive success. The same
type of multizoo study has been conducted on 44 cheetahs (Acinonyx jubatus) (Wielebnowshi, 1999). In this study non-breeders were more fearful
than breeders, but non-breeders did not differ in their activity or agressiveness from breeders. Studies on farmed fish also strongly suggest that selection can act on personality traits. Farmed stocks, characterized by intense
competition for resources and relaxed predation pressure, are often bolder,
take greater risks during foraging, and are more aggressive than their wild
ancestors (Sundström et al., 2004; for a review see Huntingford & Adams,
2005).
Personality and sexual selection
Few studies have measured natural selection acting on personality traits, but
even fewer have investigated the scope for a link between personality and
sexual selection. As far as we know, there are only three studies (all laboratory studies) that examined this link. The first example comes from a
study by Godin and Dugatkin (1996) on Trinidadian guppy (Poecilia reticulata), where bright males inspect predators more often than drab males (i.e.,
they are bolder) and females prefer bold males over shy ones, irrespective
of their colour pattern. The second example comes from a study on mate
preference in great tits from selection lines for early exploratory behaviour
(Groothuis & Carere, 2005). In these birds, adult males of a selection line
for ‘fast exploration’ (for details see Drent et al., 2003) showed higher rates
of courtship display towards females of the fast-line compared to females of
the slow-line; males of the slow-line, however, showed no preference for female personality (Groothuis & Carere, 2005). A third example comes from a
recent study on a captive population of zebra finches (Taeniopygia guttata).
In these birds, individual females differed in their preference for aggressive
males due to nongenetic maternal effects (Forstmeier et al., 2004). Both bird
studies show individual differences in preference for personality of sexual
partners, highlighting that studies on personality and sexual selection should
provide exciting results and therefore deserve more attention.
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Adaptive perspectives to study correlated behaviours
Evidence for strong genetic correlations between behavioural traits in laboratory populations of birds (Drent et al., 2003; van Oers et al., 2004a), fish
(Bakker & Sevenster, 1989; Bakker, 1994), and rodents (Sluyter et al., 1995;
Koolhaas et al., 1999) suggests that behavioural traits are often structured in
personality traits because they are controlled by the same hormones (Koolhaas et al., 1999; Ketterson & Nolan, 1999) or genes (Sih et al., 2004a, b).
Personality traits have therefore often been proposed to act as evolutionary
constraints (Sih et al., 2004a, b), because components of personality might
be difficult to decouple (Loeschke, 1987; Ketterson & Nolan, 1999). The
reason why whole suites of behavioural traits are often correlated has however, received very limited attention from a functional perspective (Wilson
et al., 1994; Coleman & Wilson, 1998; Dall et al., 2004; Sih et al., 2004a;
Bell, 2005). From an adaptionist’s viewpoint, correlations between behavioural traits are not necessarily set and if present should reflect adaptation to
the environment (Roff, 1996; Wilson, 1998). Notably, all of the fitness studies reviewed in above section of this paper have measured selection acting
on single behavioural traits, whereas functional explanations for personality
variation (i.e., consistent individual differences in suites of correlated behavioural traits) would require insight in conditions favouring phenotypic
(or genetic) correlations among behavioural traits. Here we discuss both direct and indirect approaches to study the adaptive nature of personality per
se.
Direct approaches: measuring correlational selection
The adaptive nature of correlations between behavioural traits can be measured directly by using the phenotypic selection approach (Lande & Arnold,
1983), where fitness is measured as a function of both behaviour x, behaviour
y (both measured on each individual) and their interaction (Figure 4). Here
x and y could represent the same behaviour at different ontogenic stages,
which would allow one to evaluate the adaptive nature of consistent individual differences in a single behavioural trait. X and y could also represent
functionally-distinct behaviours, for instance aggressiveness and risk-taking
behaviour, which would allow one to evaluate the adaptive nature of phenotypic correlations between traits. Knowledge of the fitness landscape would
allow one to evaluate whether an observed association between x and y (i.e.,
Natural selection and animal personality
1181
Figure 4. Illustration of how multivariate fitness landscapes can help to evaluate whether
correlations between behavioural traits would be adaptive. Dots represent all possible behavioural types (large dots have high fitness, small dots have low fitness). We show two behaviours (x and y) that could either represent the same type of trait in different situations (e.g.,
levels of activity in the absence vs presence of predators) or two functionally distinct traits
(e.g., x = aggressiveness and y = risk-taking behaviour); (a) stabilising selection favours
a single optimum and correlations between x and y would not be adaptive; (b-d) selection
favours a range of behavioural types (i.e., there is more than one phenotype with high fitness), and the ‘ridge’ of high fitness (b-c) indicates that correlational selection favours a
positive correlation between x and y. When considering only one behaviour in different situations, dots on the x = y line represent ‘inflexible’ (or stable) phenotypes, i.e., animals that
show the same behaviour in both environments, and all other dots represent ‘flexible’ (or
plastic) phenotypes. In that case, the fitness landscapes provide information on both adaptive
individual differentiation (b-d but not a) and on adaptive behavioural flexibility (a, b, d but
not c). For more details see the text.
either positive, negative, or absent) is adaptive. For example, imagine a population where x and y are positively correlated. In the case of Figure 4a,
selection favours a single optimal phenotype (large dot, scoring low on x and
high on y). The observed positive correlation between x and y would thus
not be adaptive. In contrast, in the case of positive correlational selection on
x and y (as depicted by a ‘ridge’ of high fitness within the landscape; Figures
4b&c), a positive correlation between x and y would be adaptive.
When x and y represent the same behaviour in different situations (e.g.,
activity in the presence vs absence of predators; Sih et al., 2003; Quinn &
Creswell, 2005), the fitness landscape provides information not only on the
adaptive nature of individual consistency but also on the adaptive nature of
behavioural flexibility. For instance, in case 4a behavioural flexibility would
be adaptive, as a single flexible phenotype has highest fitness. Situation 4a
would thus correspond to what Sih et al. (2004b) have called a behavioural
carry-over. Situation 4c illustrates a case where the higher fitness is associated with ‘inflexible’ phenotypes (i.e., selection favors constant behavioural
phenotypes in both environments), whereas situation 4b illustrates a case
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Dingemanse & Réale
of adaptive phenotypic plasticity or flexibility (selection favors an overall decrease in the trait between situation 1 and 2). Notably, if the fitness landscape
would look like Figure 4d, selection would favour two distinct behavioural
types (as suggested for coping behaviour in rodents; Koolhaas et al., 1999):
one inflexible phenotype (upper-right large dot, scoring high on x and y)
that does not adjust its behaviour in the different situations, and one flexible
phenotype (lower-right large dot, scoring low on x and y) that changes its
behaviour in the different situations.
We know of only one study that has yet measured correlational selection (Barton & Turelli, 1991; Brodie et al., 1995) on personality traits. In
their study on Australian women, Eaves et al. (1990) combined a survey of
reproductive success of 1101 postmenopausal females with information on
their personality using the Eysenck Personality Questionaire. They showed
that the function relating fitness (measured as life time reproductive success) to neuroticism and extraversion was saddle-shaped, with the highest fitness for both the high-extravert/low-neurotic and low-extravert/highneurotic females, intermediate fitness for females that had intermediate
scores on both axes, and lowest fitness for low-extravert/low neurotic and
high-extravert/high-neurotic females. Their results thus showed that selection favoured a negative correlation between neuroticism and extraversion.
We cannot emphasize enough that studies of correlational selection are crucial were we ever to understand personality variation from an adaptive perspective.
Indirect approaches: studying correlations within and across populations
Comparative approaches provide an alternative way to study the adaptive
nature of behavioural correlations. The ‘genetic constraint models’ predict
that correlations between traits should always be similar, irrespective of the
environmental conditions, and that correlations between traits within populations should be similar to correlations on the population level (Lande,
1979). For instance, the constraint model would predict that if aggressiveness is positively correlated with boldness within populations, populations
that are on average more aggressive should also be relatively bold. In its
most extreme form (i.e., when the correlated behaviours are influenced by
the same genes), the genetic constraint would be absolute. The ‘adaptive divergence models’ on the other hand predict that both correlations within and
Natural selection and animal personality
1183
between populations should ultimately be a function of the selective environment (Lande, 1986). For instance, the adaptive divergence model would
predict within-population behavioural correlations to be function of the environmental conditions, and would not necessarily predict within and between
population correlations to be identical. Notably, even if a genetic correlation is adaptive in the current environment, it would still act as a short-term
evolutionary constraint when environmental conditions change. Whereas the
predictions of these models have often been tested for morphological traits,
few studies have attempted to do the same for behavioural traits (but see
Palmer & Dingle, 1986; Riechert & Hedrick, 1993; Bell, 2005). Support
for the adaptive divergence model comes from recent work on threespined
stickleback, where both phenotypic and genetic correlations between intraspecific aggressiveness and boldness towards predators differed between
two populations (Bell, 2005). However, there are circumstances in which
both models give the same predictions, particularly when selection favours
the same correlation in all environments (Lande, 1979). Positive phenotypic
correlations between intraspecific aggressiveness and anti-predator behaviour as documented for each of two populations of a spider (Agelenopsis
aperta) (Riechert & Hedrick, 1993), can therefore not readily be interpreted.
It should be argued here, that population differentiation in behavioural correlations does not necessarily imply adaptive divergence, and direct approaches
are advisable at all times.
What could be done next?
Two main approaches are available to the study of personality and fitness:
the first one is to consider a priori that some personality phenotypes are
more fit than others in particular conditions, according to our intuition of the
function of personality. This approach runs the risk of providing a ‘just so
story’ about the function of personality trait. The second approach (i.e. the
one that we strongly recommend) is to provide a scientific test of selection
on personality traits, directly by looking at the link between fitness and the
phenotypic variation of a personality trait, or of a set of traits, using the methods proposed by quantitative genetics (Lande & Arnold, 1983; Endler, 1986;
Brodie et al., 1995; Kingsolver et al., 2001), or indirectly, by comparing
correlations between several populations that experience different environments (Lande, 1979, 1986). Indeed, the studies that we reviewed here show
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that it is possible to provide evidence that in many circumstances personality can be subject to natural or sexual selection pressures, and thus illustrate
the ecological importance of personality traits. Using this approach we could
test adaptive hypotheses (Fairbairn & Reeve, 2001) provided by theoretical
models (Dall et al., 2004). In the future, with the increase in the number
of estimates on selection gradients (Lande & Arnold, 1983) on personality
traits it will be possible to compare the strength of selection on those traits
with other behaviour, and with life history or morphological traits (Kingsolver et al., 2001). This approach has another advantage: by questioning the
existence, the strength, and the shape, of selection on personality traits we
encourage the publication of results showing both evidence or the absence
of evidence for selection on these traits, therefore allowing comparisons of
selection patterns between personality traits and other types of traits. Until
now, we have only been able to review cases where at least a significant relationship between phenotypic variation in one personality trait and fitness has
been found. This may overemphasise the ecological importance of personality traits.
Several adaptive hypotheses to explain the maintenance of variance of
personality traits rely on particular assumptions regarding the selection
pressures acting on those traits (e.g., correlational selection, frequencydependent selection, of environmental and temporal heterogeneity; see above).
We would like to point out that these selection patterns could only be detected statistically with large sample sizes (Kingsolver et al., 2001), and
therefore encourage studies testing the occurrence of selection on personality traits to try to collect data on a minimum of 100 individuals. Multivariate
selection analyses, coupled with long term studies of selection in the wild
(e.g., populations experiencing different environments; Fairbairn & Reeve,
2001), experimental modification of environmental conditions, and of phenotypic (co)variations (i.e., phenotypic engineering: Sinervo & Denardo, 1996;
Ketterson & Nolan, 1999), will allow us to examine the generality of evolutionary mechanisms shaping the distribution of personality traits and their
covariation in animals and humans.
Acknowledgements
Denis Réale was supported by a grant from the Natural Sciences and Engineering Research
Council of Canada. We are grateful to Marco Festa-Bianchet, Jon Jorgenson and others who
Natural selection and animal personality
1185
have collected field data over the years at Ram Mountain, and to Christiaan Both, Claudio
Carere, Piet Drent, Piet de Goede, Ton Groothuis, Kees van Oers, Arie van Noordwijk, Joost
Tinbergen and others who helped collecting data on avian personalities in the wild, and Alison
Bell, Felicity Huntingford, Charlotte Hemelrijk, Ani Kazem, Andy Sih, and Jon Wright for
inspiring discussions.
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