Download Rapid adaptation: a new dimension for evolutionary perspectives in

Popul Ecol (2010) 52:5–14
DOI 10.1007/s10144-009-0187-8
SPECIAL FEATURE: REVIEW
Rapid Adaptation
Rapid adaptation: a new dimension for evolutionary perspectives
in ecology
Masakazu Shimada • Yumiko Ishii
Harunobu Shibao
•
Received: 7 October 2009 / Accepted: 9 November 2009 / Published online: 5 December 2009
The Society of Population Ecology and Springer 2009
Abstract Although the study of adaptation is central to
biology, two types of adaptation are recognized in the
biological field: physiological adaptation (accommodation
or acclimation; an individual organism’s phenotype is
adjusted to its environment) and evolutionary–biological
adaptation (adaptation is shaped by natural selection acting
on genetic variation). The history of the former concept
dates to the late nineteenth and early twentieth centuries,
and has more recently been systemized in the twenty-first
century. Approaches to the understanding of phenotypic
plasticity and learning behavior have only recently been
developed, based on cellular–histological and behavioral–
neurobiological techniques as well as traditional molecular
biology. New developments of the former concepts in
phenotypic plasticity are discussed in bacterial persistence,
wing di-/polymorphism with transgenerational effects,
polyphenism in social insects, and defense traits for predator avoidance, including molecular biology analyses. We
also discuss new studies on the concept of genetic
accommodation resulting in evolution of phenotypic plasticity through a transgenerational change in the reaction
norm based on a threshold model. Learning behavior can
also be understood as physiological phenotypic plasticity,
associating with the brain–nervous system, and it drives the
accelerated evolutionary change in behavioral response
(the Baldwin effect) with memory stock. Furthermore,
choice behaviors are widely seen in decision-making of
animal foragers. Incorporating flexible phenotypic plasticity and learning behavior into modeling can drastically
change dynamical behavior of the system. Unification of
M. Shimada (&) Y. Ishii H. Shibao
Department of Systems Sciences, University of Tokyo,
Komaba, Tokyo 153-8902, Japan
e-mail: [email protected]
biological sciences will be facilitated and integrated, such
as behavioral ecology and behavioral neurobiology in the
area of learning, and evolutionary ecology and molecular
developmental biology in the theme of phenotypic
plasticity.
Keywords Behavioral neurobiology Choice behavior Genetic accommodation Memory and learning Phenotypic plasticity Predation switching
Introduction: rapid adaptation in nature
Two concepts of adaptation
Bock (1980) stated that biological adaptation is a property
of the phenotypic features of an organism relative to the
selection demands of the environment. Adaptation promotes properties of form and function that enable the
organism to survive in the environment. Although the study
of adaptation is central to biology, there have been two
interpretations of this concept. Futuyma (1986) noted that
‘‘In physiology, adaptation is often used to describe an
individual organism’s phenotypic adjustment to its environment, as in physiological acclimation. In evolutionary
biology, however, an adaptation is a feature that, because it
increases fitness, has been shaped by specific forces of
natural selection acting on genetic variation’’ (chap. 9,
p. 251).
In the latter concept, indeed, an emphasis on cost–benefit analysis of the individual fitness of traits has commonly
been emphasized in research fields first established in the
1970s, including evolutionary ecology (MacArthur 1972;
Pianka 1978; Ricklefs 1979), behavioral ecology (Krebs
and Davies 1978; 1981; Sibly and Smith 1985), and
123
6
sociobiology (Wilson 1975). Such traditional evolutionary
views originated from the mutation–selection concept in
the synthetic theory of population genetics (see Fisher
1930).
On the other hand, the former concept based on physiological and behavioral features of adaptation (including
acclimation, phenotypic plasticity, learning, and epigenetics) is related to short-term, condition-dependent changes
within a framework of genetic programming that is molded
in much longer evolutionary time scales of at least dozens
of generations. Although ‘acclimation’ and ‘accommodation’ have been widely recognized since the middle of the
twentieth century, the phenotypic plasticity includes these
classical concepts as a new terminology that has prevailed
in studies of plants, animals, and even bacteria (Pigliucci
2001; West-Eberhard 2003; Kirshner and Gerhart 2005).
We will show here the ubiquitous phenomena in nature.
Ubiquitous phenomena of rapid adaptation in nature
Polyphenism involving distinct morphologies has been
extensively reported in insects, for example, the di-/polymorphism of wing formation (in aphids, plant hoppers, and
locusts) and the cast differentiation of social insects (ants,
bees, wasps, and termites) (West-Eberhard 1989). In
addition, several prey–predator systems show inducible
defense traits for predator avoidance, such as the tadpole
and salamander system (Van Buskirk and Relyea 1998;
Wilson et al. 2005; Kishida and Nishimura 2006; Kishida
et al. 2006, 2009, 2010), and the Daphnia and predators
(small fish or larval phantom midge Chaoborus) system
(Levins 1968; Harvell 1990; Havel and Dodson 1984;
Tollrian 1993; Tollrian and Dodson 1999; Hammill et al.
2008; Engel and Tollrian 2009).
Molecular biology studies of the mechanisms of phenotypic plasticity have recently elucidated the conditional
partial on/off switching of the promoter and/or enhancer
region in gene expression (Gerhart and Kirshner 1997;
Kirshner and Gerhart 1998, 2005). Furthermore, epigenetic
traits (condition-dependent modification with methylation
and acetylation in DNA and histone proteins) can be prolonged over several generations (Kalisz and Purugganan
2004).
With respect to learning behavior, animals can lean from
environmental cues during foraging; for example, marks
and chemical kairomones enable predators to locate prey in
their habitat. However, as learning into long-term memory
has a cost (Mery and Kawecki 2005), the learning behavior
of animals involves a cost–performance balance from both
the evolutionary–ecological and behavioral–neurobiological points of view. Furthermore, a spreading effect of
learning behavior can include the generation of complicated population dynamics involving predator switching
123
Popul Ecol (2010) 52:5–14
(Oaten and Murdoch 1975; Murdoch and Oaten 1975; Ishii
and Shimada 2010). This is based on the trade-off of
attention (‘limited attention’; Dukas and Kamil 2001;
Dukas 2002, 2004), in which a predator’s attention to prey
is formed through ‘conditioning’ to the most common prey
in situations where multiple prey–predator systems occur
in the habitat. Integrated understanding of learning
behavior spreads from behavioral neurobiology to population dynamics and evolutionary ecology.
The potential for rapid adaptation will be naturally
selected through genetic variation on the basis of learning
and phenotypic plasticity (Kawecki 2010), which will
result in adaptive evolution at a longer time scale (the
Baldwin effect; Mery and Kawecki 2004b; Crispo 2007;
Paenke et al. 2007; Lande 2009). In recent decades,
learning behaviors have gradually been elucidated
through studies of behavioral neurobiology (Zupanc
2003), especially those involving prolonged memory
storage through stimulus repetition (Kandel 2001).
Incorporating such phenotypic plasticity and choice
behaviors into prey–predator systems can greatly change
a dynamical behavior of the system (Abrams 2010; Ishii
and Shimada 2010).
The aim of this review is to synthesize recent findings in
research on phenotypic plasticity and learning behavior
with reference to as many as possible molecular–cellular
biology, physiology and genome science developments,
and to propose a new dimension for evolutionary perspectives in ecology.
Phenotypic plasticity in physiological
and morphological adaptation
Bacterial phenotypic plasticity
Phenotypic plasticity occurs in prokaryotes as well as
eukaryotes. The most famous example is the conditiondependent gene expression based on the bacterial operon,
in which gene expression is clearly changed in response to
nutritional conditions (Jacob and Monod 1961). For
another example, the filament formation (elongation four or
five times longer in the cell length) has been widely
observed in Escherichia coli when they are cultivated
under environmental stress, e.g., poor nutrient medium or
high temperature (Maki et al. 2000).
It is also recognized that response of bacteria to antibiotics in bacterial growth media enables bacterial persistence. Wakamoto et al. (2005), Wakamoto and Yasuda
(2006a, b) and Ayano et al. (2006) reported that a proportion of successive Escherichia coli populations survived
when antibiotics were provided at intermittent intervals. If
resistance were a result of evolutionary change based on
Popul Ecol (2010) 52:5–14
mutation–selection processes, the survival ratio would be
higher in successive populations. However, the survival
ratio was constant under the antibiotic regime; such bacterial survivorship patterns have been termed ‘persistence’,
not resistance (Wakamoto et al. 2005; Wakamoto and
Yasuda 2006a, b). Stochastic gene expression has been
recognized here, whereby division and growth of daughter
cells is unbalanced and asymmetric with respect to cell size
and physiological properties (Blake et al. 2001; Furusawa
and Kaneko 2001; Baetz and Kaern 2006; Kaneko 2007;
Fraser and Kaern 2009).
Wing dimorphism and polymorphism in insects
Polyphenism involving distinct morphologies has been
extensively reported in insects in wing dimorphism (brachyptera and macroptera); in the plant hopper (Homoptera)
(Kishimoto 1956, 1976; Iwanaga et al. 1985, 1987;
Iwanaga and Tojo 1986; Morooka and Tojo 1992), the
aphid (Homoptera) (Dixon et al. 1993; Weisser et al. 1999;
Braendle et al. 2006), the water strider (Heteroptera)
(Vespäläinen 1978; Goodwyn and Fujisaki 2007), the bug
(Heteroptera) (Fujisaki 1992), and the cricket (Orthoptera)
(Roff 1986; Zera and Tiebel 1989; Zera et al. 1999; Zhao
and Zera 2002).
Wing dimorphism depends partly on the population
density. The brachiptera morph of the brown plant hopper
(Nilaparvata lugens) occurs at low population densities and
has high reproductive ability, whereas the macroptera
morph often emerges at high population density and has a
life history specialized for dispersal (Kishimoto 1956;
Morooka and Tojo 1992). The wing polymorphism in N.
lugens depends partly on the geographic strain, and the
emergence ratio of the macroptera morph of N. lugens
varies among localities from Japan to southeast Asia
(Iwanaga et al. 1985, 1987; Iwanaga and Tojo 1986;
S. Morooka, unpublished data).
Molecular genetic analysis in wing dimorphism/polymorphism has, however, not been conducted either in the
plant hopper or in the aphids, although Zera and Zhao
(2006) reported biochemical basis of trade-off between
dispersal and reproduction in a wing-polymorphic cricket,
G. firmus. Aphids are currently becoming an important
model organism, and a large community has begun to
develop genomic resources for A. pisum. Braendle et al.
(2005, 2006) reported that the male polymorphism is
controlled by a single locus on the X chromosome called
aphicarus (api) in the pea aphid, Acyrthosiphon pisum. In
aphids, males are haploid for the X chromosome, so one
allele of api causes winged males and the other causes
wingless males. Three api genotypes are seen in natural
populations: clones homozygous for the api-winged allele
that produce all winged males, clones homozygous for the
7
api-wingless allele that produce all wingless males, and
clones heterozygous for api that produce winged and
wingless males in equal proportions (Braendle et al. 2006).
The genome of the pea aphid A. pisum is currently being
sequenced at a certain consortium.
Polyphenism in social insects
Another widely reported example of polyphenism in social
insects is that of caste differentiation (polyethism) into
workers, soldiers, and queens (Wilson 1971, 1975;
Hölldobler and Wilson 1990). Colony mates have mother–
daughter relationships in hymenopterous insects (ants,
bees, and wasps), and different morphs (soldiers and normal) are genetic clones in the Homoptera (aphids).
Genetically closely related or clonal insects show various
properties in terms of morphology and behavior.
In social aphids, altruistic individuals termed soldiers
perform colony defense, housekeeping, and gall repair
(Shibao et al. 2010). As aphids reproduce parthenogenetically (thelytoky), all members of a genetic clone have
identical genomes. Nevertheless, social aphids display
adaptive caste polyphenism and short-term behavioral
flexibility, which permits rapid responses to changing
environmental and social stimuli. For example, in
Tuberaphis styraci, which has a sterile soldier caste in the
second instar, caste production in the colony is controlled
by positive and negative feedback mechanisms: a greater
density of other castes induces soldier production,
whereas increasing soldier density suppresses further
soldier production (Shibao et al. 2003, 2004a, b, c). In
this species, the soldiers not only defend the colony
against predators but also clean the gall by removing
waste products. When the soldiers are still young, they
undertake relatively safe tasks inside the colony such as
gall cleaning. As the soldiers age, their tasks involve
more dangerous activities outside the colony such as
colony defense. Thus, a colony can maintain a sufficient
work force and defense capability by constraining early
deaths to the sterile caste. The division of labor in the
aphid social system is adaptive and based on soldier-age
polyethism (Shibao et al. 2004d).
Molecular and cellular/histological mechanisms that
generate different morphs during caste polyphenism in
social insects have recently been elucidated by Miura and
colleagues. Soldier-specific gene expression (Miura et al.
1999; Koshikawa et al. 2005), modification of the mandibular motor neurons (Ishikawa et al. 2008), and juvenile
hormone (JH)-promoting caste differentiation (Cornette
et al. 2008) have been successively discovered in the termite Hodotermopsis sjostedti. Compound eye development
during caste differentiation in the termite, Reticulitermes
speratus, has been demonstrated (Maekawa et al. 2008).
123
8
The gene network analysis has rapidly been developed
in the 2000s. Abouheif and Wray (2002) characterized the
expression of several genes within the network of wing
polyphenism in reproductive (winged) and sterile (wingless) ant castes. They showed that the expression of genes
(e.g., en, Ubx, ap, exd, etc.) within the network was conserved in the winged castes of four ant species (genera
Neoformica, Myrmica, Crematogaster, and Pheidole),
whereas points of interruption within the network in the
wingless castes were evolutionarily unstable.
Furthermore, based on such gene network analysis, the
study of sociogenomics in social insects, especially the
honey bee, Apis melifera, has undergone a rapid increase
(Robinson et al. 2005; Whitfield et al. 2006; Grozinger et al.
2007). Robinson et al. (2005) and Weinstock et al. (2006)
claimed a new approach that is based on transcriptomics:
measuring changes in the expression of genes that correlate
with changes in behavior. Gene expression is measured in
the brains of individuals that have different behaviors of
interest. Transcript abundance, however, is not always predictive of protein abundance. Some differences in gene
expression may be a consequence, not a cause, of a behavioral change. Therefore, it is important to go beyond gene
expression–behavior correlations to manipulate transcript
abundance or protein activity through transgenesis, RNAi,
pharmacology with neurotransmitters, and so on (Robinson
et al. 2005; Weinstock et al. 2006). In addition, Elango et al.
(2009) reported epigenetics that DNA methylation was
widespread and associated with differential gene expression
in social castes in A. merifela. The transcriptomics-based
approach will be a powerful approach towards the gene
discovery, especially for model social species.
Inducible defense traits for predator avoidance
Woltereck (1909) presented firstly the term ‘‘reaction
norm’’ in the study of Daphnia inducible defense (see
Pigliucci 2001). Over the last 20 years, there have been
more than 100 reports of inducible defense traits for
predator avoidance in Daphnia species, including the
development of head and tail spines in D. rosea (Dodson
1972, 1984), D. pulex (Hammill et al. 2008), and D. lumholtzi (Engel and Tollrian 2009). Colony formation in a
phytoplankton genus Scenedesmus has also been reported
to be an inducible defense against grazers (Lurling and Van
Donk 2000; Van der Stap et al. 2008). Tadpoles of Rana
produce head bloating as an inducible defense in R. sylvatica (Van Buskirk and Relyea 1998), R. lessonae (Wilson
et al. 2005), and R. pirica (Kishida and Nishimura 2006;
Kishida et al. 2006, 2009, 2010). In addition, inducible
offense by predators has also been reported; large jaws that
enable tadpoles to be swallowed occur among morphs of
the salamander, Hynobius retardatus (Kishida et al. 2010).
123
Popul Ecol (2010) 52:5–14
Embryological formation of inducible defense trait,
neckteeth, was discovered by Laforsch and Tollrian (2004),
and molecular and cellular mechanisms of inducible
defense in Daphnia have recently been partially elucidated
by Imai et al. (2009). Colbourne et al. (2005) presented the
Daphnia genome database, and Eads et al. (2008) proposed
ecological genomics in Daphnia as the first results focusing
on adaptation in the stress response and environmental sex
determination, even though no paper has yet reported on
inducible defense traits.
For molecular genetics of tadpoles, Kurata et al. (2005)
and Mori et al. (2005) conducted cDNA subtraction and
microarray analysis to detect genes expressed in inducible
defense in Rana tadpoles. Mori et al. (2005) focused on the
bulgy body skin tissue (the major induced morphological
change and the most downstream end of the gene interaction system for phenotypic expression) and reported several
candidate genes. The bulgy-shaped body seems to be
highly related to the bullous pemphigoid antigen, which
causes the skin-blistering disorder, and tetranectin and
uromodulin may be related to the extracellular matrix
through myogenesis, protein secretion, and ion transport.
As the reverse transcriptase-like protein gene is known to
disrupt mammalian transcriptomes, retrotransposons may
be involved (Mori et al. 2005).
Transgenerational effects and genetic accommodation
in phenotypic plasticity
Inducible defense in infected plants
Agrawal et al. (1999) reported transgenerational effects in
inducible defense in the cruciferous plant, Raphanus sativus. They collected mature seeds from a parent plant that
had been affected by lepidopteran caterpillars during
development. The seeds were sown in the field, and equal
numbers of caterpillars were attached to each resulting
plant. It was found that the larval body mass was smaller
for plants that had been infected with larvae in the previous
generation than in plants that had not previously been
infected. The inducible defense was chemical in nature,
and production of the chemical substance in the seeds was
switched on during ripening.
Transgenerational density effects in locusts
The desert locust, Schistocerca gregaria, undergoes polyphenism in response to low (solitary) and crowded
(gregarious) population density phases. The former is
characterized by green body coloration, smaller hatchlings,
and solitary and sedentary habits, while the latter is characterized by dark-colored bodies, larger hatchlings, and
Popul Ecol (2010) 52:5–14
gregarious and migratory habits (Uvarov 1966). Variation
in these traits is continuous and not discrete, and transgenerational steps proceed toward the gregarious phase for
several generations (Tanaka and Maeno 2008). A strong
correlation is evident between coloration and body size;
green and small hatchlings come from eggs produced by
solitary females, whereas black and larger hatchlings come
from eggs produced by gregarious females (Faure 1932;
Tanaka and Maeno 2008; Maeno and Tanaka 2009).
Tawfik et al. (1999) investigated the molecular basis of
gregarious body pigmentation, and reported the isolation of
a neurohormone (comprising 11 amino acids) from the
corpora cardiaca. This neurohormone was identical to
[His(7)] corazonin, and its primary structure is similar to the
vertebrate melanophore-stimulating hormone. Treatment
with [His(7)] corazonin induced gregarious black patterns
even in isolated (solitary) nymphs (Tawfik et al. 1999).
Tanaka and Maeno (2006) manually tried to remove the
maternal effect by washing eggs with saline or by separating eggs individually within 1 h of egg deposition.
Neither washing nor separation of eggs at deposition
affected the percentage of green hatchlings. The variation
in hatchling body color was correlated closely to the body
weight at hatchling. Then Maeno and Tanaka (2009) conducted two methods of artificial miniaturization of eggs:
(1) removal of water from the eggs and (2) squeezing yolk
from the eggs. Using these methods, they successfully
reproduced a positive correlation between body size and
body color. These experiments have largely elucidated
polyphenism processes in the locust, and demonstrated
phenotypic plasticity without genetic differentiation, i.e.,
from solitary to gregarious phases for several generations
in transgenerational processes with maternal effects
(Maeno and Tanaka 2009).
Furthermore, Anstey et al. (2009) has recently reported
that a neurotransmitter, serotonin, was responsible for the
behavioral transformation from solitary to gregarious
phases in the locust, S. gregaria. Solitary locusts acquire
full gregarious behavioral characteristics within the first
2 h of forced crowding. This period coincides with a substantial but transient (\24 h) increase in the amount of
serotonin, specifically in the central nervous system, the
thoracic ganglia, but not the brain. They demonstrated a
neurochemical mechanism linking interactions between
individuals to large-scale changes in population structure
and the onset of mass migration.
Evolutionary changes through phenotypic plasticity:
Baldwin effect, genetic assimilation, and genetic
accommodation
For evolutionary change through phenotypic plasticity,
Price et al. (2003) pointed out that entry into a new
9
environment results in selection pressures favoring divergence from the ancestor, and that different environments
also directly induce changes in an individual’s behavior,
morphology, and physiology. Such changes are generically
named ‘‘phenotypic plasticity’’. This plasticity is adaptive,
in that individuals which show a plastic response have
higher fitness than those which do not (Price et al. 2003),
and it may have evolved as a consequence of variable
conditions (Levins 1968; Via and Lande 1985; Robinson
and Gukas 1999).
How does plasticity interact with environmental conditions to produce genetic change? First, we need to clarify
the terms ‘‘Baldwin effect’’ and ‘‘accommodation’’. Price
et al. (2003) summarized the process of genetic assimilation which was first outlined by Spalding (1873), who
argued that selection of those individuals which were the
best learners would eventually result in the appearance of
the behavior in the absence of learning. The idea that
plastic traits in phenotype could become genetically fixed
was raised by Baldwin (1896) and Morgan (1896) (the
‘‘Baldwin effect’’ termed by Simpson 1953; see Crispo
2007). Simpson (1953) defined the Baldwin effect as the
situation where ‘‘characters individually acquired by
members of the group may eventually, under the influence
of selection, be reinforced or replace similar hereditary
characters.’’
Baldwin (1896, 1902) often used the term ‘‘accommodation’’ in reference to non-heritable phenotypic changes
that increase the survival of the organism in the particular
environment in which the phenotypic change is induced.
West-Eberhard (2003, 2005) divided accommodation into
genetic and phenotypic components, and ‘‘phenotypic
accommodation’’ (West-Eberhard 2003, 2005) is the
modern-day equivalent of Baldwin’s accommodation (see
Crispo 2007). Baldwin (1902) noted that heritable variation
can occur in the same direction as the phenotypic response
(he termed ‘‘conincident variations’’) and phenotypes that
are originally environmentally induced can be selected
upon and inherited. Currently, this phenomenon is considered a type of ‘‘genetic accommodation’’ (Crispo 2007),
and an empirical experiment (Suzuki and Nijhort 2006)
will be demonstrated (see later).
On the other hand, Waddington (1953, 1959, 1961)
proposed that development would evolve to become
‘‘canalized’’ against environmental perturbations, via
selection acting on the developmental system, a process he
referred to as ‘‘genetic assimilation’’ (Waddington 1953,
1961). Specifically, he defined genetic assimilation as a
process ‘‘by which a phenotypic character, which initially
is produced only in response to some environmental
influence, becomes, through a process of selection, taken
over by the genotype, …’’ (Waddington 1961). Although
Waddington’s canalization and genetic assimilation may be
123
10
apparently similar to the Baldwin effect, the two concepts
have fundamental differences (Crispo 2007). Waddington’s
theory is based on the viewpoint that the environment
induces phenotypes that are adaptive, and then selection on
the developmental system acts to reduce responsiveness to
the environment (i.e., to reduce plasticity). Therefore, we
need to understand that Waddington’s genetic assimilation
and canalization is a special case of the general concept of
the Baldwin effect and genetic accommodation.
The experiment of genetic accommodation
Related species are likely to share genetic and developmental backgrounds. Therefore, Suzuki and Nijhort
(2006) reasoned that exposing hidden genetic variation by
stress (heat shock) could evolve a polyphenic regulatory
mechanism in a monophenic species that shared a recent
common ancestor with a polyphenic species. They
investigated this possibility using artificial selection to
evolve a larval color polyphenism in the tobacco hornworm, Manduca sexta, which is a monophenic species
with green larvae. A related species, M. quinquemaculata,
exhibits a larval color polyphenism, developing a black
phenotype at 20C and a green phenotype at 28C. Wildtype larval coloration was robust to thermal stress, with
fifth instar larvae remaining green following heat shock
treatment during the mid and late fourth larval instar
stage. Thus, their experiments examined the effect of
thermal stress in both the polyphenic line and the black
mutant line of M. sexta. The black mutation is a sexlinked recessive allele that reduces JH secretion, and the
black mutant phenotype can revert to a normal greencolored larva by treatment with JH.
Suzuki and Nijhort (2006) conducted an artificialselection experiment on the reaction norm (Schmalhausen
1949; Sarkar 2004), and the polyphenic line become more
and more green under the high-temperature condition. The
reaction norm in the temperature-dependent color score
(the greener the larva, the higher the score) dramatically
increased from 25 to 33C in the polyphenic line, although
larvae of the black mutant were constantly black at physiologically tolerable temperatures ranging from 25 to 33C.
Based on these experiments, a mechanistic view of the
evolution of polyphenism by genetic accommodation in the
threshold trait, JH titer, was developed (the term ‘genetic
assimilation’ is used for the monophenic form, based on
stabilization).
Furthermore, as the empirical test, Suzuki and Nijhort
(2008) conducted cross experiments between polyphenic
and monophenic strains, including F1 crosses, and showed
that the mechanism of genetic accommodation relies on
changes that are consistent with the current view of the
genetic basis of adaptive evolution.
123
Popul Ecol (2010) 52:5–14
Learning in behavioral adaptation as phenotypic
plasticity
Learning behaviors in vertebrates and insects
The new field of behavioral neurobiology, which has
emerged in recent decades (e.g., Carew 2000; Zupanc
2003), has focused on model organisms including the
mouse (Mus musculus; spatial orientation learning and
memory), the zebra finch (Taeniopygia guttat; song
learning), the zebra fish (Danio rerio; developmental
biology), the sea hare (Aplysia kurodai; sensitization and
memory storage), the fruit fly (Drosophila melanogaster;
associative learning) and the nematode (Caenorhabditis
elegance; perception of density gradient movement in
chemostasis).
Numerous behavioral neurobiology studies involving D.
melanogaster are reported annually, including a number
concerning associative learning in relation to olfactory cues
(e.g., Raine 2009; Yarali et al. 2009). Kawecki and colleagues (Mery and Kawecki 2003, 2004a; Kawecki 2010)
have been unique in investigating the fitness cost of
learning in D. melanogaster, especially the trade-off
between learning performance and certain fitness components including fecundity and longevity (Flatt and Kawecki
2007; Burger et al. 2008).
One of the most astonishing discoveries is that longterm memory is costly in D. melanogaster because it
requires protein synthesis inside the mushroom body, but
anesthesia-resistant memory (maintained for several hours)
has no cost (Mery and Kawecki 2005) because it does not
involve protein synthesis. The cost of long-term memory
increases when combined with stressful conditions, such as
desiccation.
Another notable finding has been the detection of the
Baldwin effect in D. melanogaster (Mery and Kawecki
2004b; Paenke et al. 2007; Kawecki 2010). Mery and
Kawecki (2004b) established experiments involving two
nutrient media (pineapple and orange) and two selection
regimes (‘innate’ and ‘learning’), and applied this 2 9 2
artificial selection regime design to D. melanogaster populations. The experimental chamber had two small dishes
containing either pineapple or orange medium. For the
‘learning pineapple’ treatment, the researchers added quinine to the alternative orange medium, so that the flies
would only lay eggs in the pineapple medium (i.e., reinforced learning for ‘pineapple’). Comparison of the
‘learning’ and ‘innate’ regimes showed that the ‘learning
pineapple’ regime was associated with a more rapid evolutionary pace (Mery and Kawecki 2004b), indicating that
learning drives evolutionary processes at a greater rate.
For genetic accommodation in wild animas in nature,
entry into very different environments must be
Popul Ecol (2010) 52:5–14
Fig. 1 Diagrammatic representation of the evolution of behavior and
the Baldwin effect
accompanied by behavioral and other plastic forms of
accommodation, and this will usually be followed by
selection in the context of these changes. Price et al. (2003)
presented an example: the development of tool using in the
woodpecker finch, Camarhynchus pallidus, on the Galapagos. Although tool using may have arisen and spread as a
result of cultural innovation, the habit now develops
independently of any tutoring (Tebbich et al. 2001), suggesting genetic accommodation.
Figure 1 shows a diagram of a modernized version of
the evolution of behaviors and the Baldwin effect. An
organism receives information from its environment (cognition), and its behavioral response has resultant consequences (Success or failure? How much reward?). As a
consequence of the response, neurotransmitters (e.g.,
dopamine, octopamine, or serotonin) are secreted in the
brain–nervous system of the individual, which promotes
memory storage, especially long-term memory. Memory
storage affects the next behavioral action, which is a phenotypic character that is genetically affected by the individual genotype with variation at the population level.
Therefore, behavioral characters are under natural selection. Furthermore, selection of genotypes in the adaptive
landscape that enhancing phenotypic plasticity is accelerated with convex fitness function (Paenke et al. 2007);
then, the behavioral consequence of learning provides
feedback to natural selection on genetic variance.
Choice behavior, learning-mediated population
dynamics, and adaptive dynamics
Ishii and Shimada (2010) showed antiphase oscillations of
two prey species of bruchid seed beetle, Callosobruchus
spp., parasitized by a pteromalid wasp, Anisopteromalus
11
calandrae, in a one predator–two prey experimental system. The oscillations can be generated by predation
switching by the wasp, which was based on the wasp
learning to attack the more abundant prey species. Continuous conditioning (about 24–48 h) during predation on
the same host resulted in A. calandrae establishing a
chemical search image of the common prey (Ishii and
Shimada 2010). Although theoretical predictions have been
investigated (Murdoch and Oaten 1975; Oaten and
Murdoch 1975), an empirical test has never been reported.
The empirical analysis of Ishii and Shimada (2010) is the
first report of antiphase oscillations and persistence of the
three-species system over a long period.
P.A. Abrams has developed models for various types of
adaptive changes including switching behavior for prey
types amongst generalist consumers (Abrams 1999, 2006,
2010), movement behavior from one patch to another
(Abrams 2007), and developmental plasticity (Abrams and
Rowe 1996). Abrams et al. (1993) compared adaptive
dynamics including learning (hereafter, small notation
‘‘adaptive dynamics’’) with traditional evolutionary
dynamics without adaptive change (hereafter, capital notation ‘‘Adaptive Dynamics’’ incorporating only mutation–
selection evolutionary process); the adaptive dynamic consequences, including behavioral adaptation, could change
drastically in the model. Therefore, Abrams (2005) emphasized the importance of including adaptive change and
comparing ‘adaptive dynamics’ with ‘Adaptive Dynamics’;
the latter refers to a specific set of methods for analyzing
mutation-limited evolutionary change.
Concluding remarks
This review has emphasized that rapid adaptation is ubiquitous in nature and has over-viewed recent research developments, including cellular–historical analyses and
molecular biology techniques, in the areas of phenotypic
plasticity and learning behavior. As Abrams (2005) has
pointed out, behavioral and evolutionary ecological research
on rapid adaptation (‘adaptive dynamics’; sensu Abrams
2005) will inform new understanding in the biological sciences. Unification of biological sciences will be enhanced;
for example, behavioral ecology and behavioral neurobiology in the area of learning, and evolutionary ecology and
molecular developmental biology in the area of phenotypic
plasticity.
Acknowledgments The authors are grateful to the Chief-in-Editor,
Dr. T. Saitoh of Hokkaido University, and the editorial office, Ms M.
Tanigawa, for supporting this symposium in the present issue, especially our long review. Special thanks should be given to Dr. T. Miura of
Hokkaido University and Dr. K. Fujisaki of Kyoto University for kindly
advising on the many important publications that we should cite. This
123
12
research was supported in part by the Ministry of Education, Science,
Sports and Culture, Grant-in-Aids for Scientific Research (B)
20370008.
References
Abouheif E, Wray GA (2002) Evolution of the gene network
underlying wing polyphenism in ants. Science 297:249–252
Abrams PA (1999) The adaptive dynamics of consumer choice. Am
Nat 153:83–97
Abrams PA (2005) Adaptive dynamics’ vs. ‘adaptive dynamics.
J Evol Biol 18:1162–1165
Abrams PA (2006) The effect of switching behavior on the
evolutionary diversification of generalist consumers. Am Nat
168:645–659
Abrams PA (2007) Habitat choice in predator-prey systems: spatial
instability due to interacting adaptive movement. Am Nat
169:581–594
Abrams PA (2010) Quantitative descriptions of resource choice in
ecological models. Popul Ecol 52:47–58
Abrams PA, Rowe L (1996) The effects of predation on the age and
size of maturity of prey. Evolution 50:1052–1061
Abrams PA, Matsuda H, Harada Y (1993) Evolutionarily unstable
fitness maxima and stable fitness minima in the evolution of
continuous traits. Evol Ecol 7:465–487
Agrawal AA, Laforsch C, Tollrian R (1999) Transgenerational
induction of defenses in animals and plants. Nature 401:60–63
Anstey ML, Rogers SM, Ott SR, Burrows M, Simpson SJ (2009)
Serotonin mediates behavioral gregarization underlying swarm
formation in desert locusts. Science 323:627–630
Ayano S, Wakamoto Y, Yamashita S, Yasuda K (2006) Quantitative
measurement of damage caused by 1064-nm wavelength optical
trapping of Escherichia coli cells using on-chip single cell
cultivation system. Biochem Biophys Res Commun 350:678–
684
Baetz K, Kaern M (2006) Predictable trends in protein noise. Nat
Genet 38:610–611
Baldwin JM (1896) A new factor in evolution. Am Nat 30:441–451
Baldwin JM (1902) Development and evolution. MacMillan, London
Blake WJ, Karen M, Cantor CR, Collins JJ (2001) Noise in eukaryotic
gene expression. Nature 422:633–637
Bock WJ (1980) The definition and recognition of biological
adaptation. Am Zool 20:217–227
Braendle C, Caillaud MC, Stern DL (2005) Genetic mapping of
aphicarus—a sex-linked locus controlling a wing polymorphism
in the pea aphid (Acyrthosiphon pisum). Heredity 94:435–442
Braendle C, Davis GK, Brisson JA, Stern DL (2006) Wing
dimorphism in aphids. Heredity 97:192–199
Burger JMS, Kolss M, Pont J, Kawecki TJ (2008) Learning ability
and longevity: a symmetrical evolutionary trade-off in Drosophila. Evolution 62:1294–1304
Carew TJ (2000) Behavioral neurobiology: the cellular organization
of natural behavior. Sinauer, New York
Colbourne JK, Singan VR, Gilbert DG (2005) wFleaBase: the
Daphnia genome database. BMC Bioinformatics 6:45
Cornette R, Koshikawa S, Miura T (2008) Histology of the hormoneproducing glands in the damp-wood termite Hodotermopsis
sjostedti (Isoptera, Termopsidae): a focus on soldier differentiation. Insects Sociaux 55:407–416
Crispo E (2007) The Baldwin effect and genetic assimilation:
revisiting two mechanism of evolutionary change mediated by
phenotypic plasticity. Evolution 61:2469–2479
Dixon AFG, Horth S, Kindlmann P (1993) Migration in insects—cost
and strategies. J Anim Ecol 62:182–190
123
Popul Ecol (2010) 52:5–14
Dodson SI (1972) Mortality in a population Daphnia rosea. Ecology
53:1011–1023
Dodson SI (1984) Predation of Heterocope septentroionalis on 2
species of Daphnia morphological defenses and their cost.
Ecology 65:1249–1257
Dukas R (2002) Behavioural and ecological consequences of limited
attention. Philos Trans R Soc Lond B 357:1539–1547
Dukas R (2004) Causes and consequences of limited attention. Brain
Behav Evol 63:197–210
Dukas R, Kamil AC (2001) Limited attention: the constraint
underlying search image. Behav Ecol 12:192–199
Eads BD, Andrews J, Colbourne JK (2008) Ecological genomics in
Daphnia: stress responses and environmental sex determination.
Heredity 100:184–190
Elango N, Hunt BG, Goodisman MAD, Yi SV (2009) DNA
methylation is widespread and associated with differential gene
expression in castes of the honeybee, Apis mellifera. Proc Natl
Acad Sci USA 106:11206–11211
Engel K, Tollrian R (2009) Inducible defenses as key adaptations for
the successful invasion of Daphnia lumholtzi in North America?
Proc R Soc Lond B 276:1865–1873
Faure JC (1932) The phase of locusts in South Africa. Bull Entomol
Res 23:293–405
Fisher (1930) Genetical theory of natural selection. Dover, New York
(reprinted in 1958)
Flatt T, Kawecki TJ (2007) Juvenile hormone as a regulator of the
trade-off between reproduction and life span in Drosophila
melanogaster. Evolution 61:1980–1991
Fraser D, Kaern M (2009) A chance at survival: gene expression noise
and phenotypic diversification strategies. Mol Microbiol
71:1333–1340
Fujisaki K (1992) A male fitness advantage to wing reduction in the
oriental chinch bug, Cavelerius saccharivorus Okajima (Hemiptera, Lygaediae). Res Popul Ecol 34:173–183
Furusawa C, Kaneko K (2001) Theory of robustness of irreversible
differentiation in a stem cell system: chaos hypothesis. J Theor
Biol 209:395–416
Futuyma D (1986) Evolutionary biology, 2nd edn. Sinauer, New York
Gerhart J, Kirshner MW (1997) Cells, embryos, and evolution: toward
a cellular and development understanding of phenotypic variation and evolutionary adaptability. Blackwell, New York
Goodwyn PP, Fujisaki K (2007) Sexual conflicts, loss of flight, and
fitness gains in locomotion of polymorphic water striders.
Entomol Exp Appl 124:249–259
Grozinger CM, Fan Y, Hoover SER, Winston ML (2007) Genomewide analysis reveals differences in brain gene expression
patterns associated with caste and reproductive status in honey
bees (Apis mellifera). Mol Ecol 16:4837–4848
Hammill E, Rogers A, Beckerman AP (2008) Costs, benefits and the
evolution of inducible defenses: a case study with Daphnia
pulex. J Evol Biol 21:705–715
Harvell CD (1990) The ecology and evolution of inducible defenses.
Q Rev Biol 65:323–340
Havel JE, Dodson SI (1984) Chaoborus predation on typical and
spined morphs of Daphnia pulex: behavioral observations.
Limnol Oceanogr 29:487–494
Hölldobler B, Wilson EO (1990) The ants. Harvard University Press,
Boston
Imai M, Naraki Y, Tochinai S, Miura T (2009) Elaborate regulations
of the predator-induced polyphenism in the water flea Daphnia
pulex: kairomone-sensitive periods and life-history tradeoffs.
J Exp Zool A 311:788–795
Ishii Y, Shimada M (2010) The effect of learning and search image on
prey-predator interactions. Popul Ecol 52:27–35
Ishikawa Y, Aonuma H, Miura T (2008) Soldier-specific modification
of the mandibular motor neurons in termites. PLoS ONE 3:e2617
Popul Ecol (2010) 52:5–14
Iwanaga K, Tojo S (1986) Effects of juvenile-hormone and rearing
density on wing dimorphism and oocyte development in the
brown planthopper, Nilaparvata lugens. J Insect Physiol 32:585–
590
Iwanaga K, Tojo S, Nagata T (1985) Immigration of the brown
planthopper, Nilaparvata lugens, exhibiting various response to
density in relation to wing mophism. Entomol Exp Appl 38:101–
108
Iwanaga K, Nakasuji F, Tojo S (1987) Wing polyphenism in Japanese
and foreign strains of the brown planthopper, Nilaparvata
lugens. Entomol Exp Appl 43:3–10
Jacob F, Monod J (1961) Genetic regulatory mechanisms in the
synthesis of proteins. J Mol Biol 3:318–356
Kalisz S, Purugganan MD (2004) Epialleles via DNA methylation:
consequences for plant evolution. Trend Evol Ecol 19:309–314
Kandel ER (2001) The molecular biology of memory storage: a
dialogue between genes and synapus. Science 294:1030–1038
Kaneko K (2007) Evolution of robustness to noise and mutation in
gene expression dynamics. PloS One 2(5):e434
Kawecki TJ (2010) Evolutionary ecology of learning: insights from
fruit flies. Popul Ecol 52:15–25
Kirshner M, Gerhart J (1998) Evolvability. Proc Natl Acad Sci USA
95:8420–8427
Kirshner MW, Gerhart JC (2005) The plausibility of life: resolving
Darwin’s dilemma. Yale University Press, New Haven
Kishida O, Nishimura K (2006) Flexible architecture of inducible
morphological plasticity. J Anim Ecol 75:705–712
Kishida O, Mizuta Y, Nishimura K (2006) Reciprocal phenotypic
plasticity in a predator-prey interaction between larval amphibians. Ecology 87:1599–1604
Kishida O, Trussell G, Nishimura K (2009) Top-down effects on
antagonistic inducible defense and offense. Ecology 90:1217–
1226
Kishida O, Trussell GC, Mougi A, Nishimura A (2010) Evolutionary
ecology of inducible morphological plasticity in predator-prey
interaction: toward the practical links with population ecology.
Popul Ecol 52:37–46
Kishimoto R (1956) Effect of crowding during the larval period on
the determination of the wing-form of the adults plant-hopper.
Nature 178:641–642
Kishimoto R (1976) Synoptic weather condition including longdistance immigration of planthoppers, Sogatella furcifera Horvath and Nilaparvata lugens Stal. Ecol Entomol 1:95–109
Koshikawa S, Cornette R, Hojo M, Maekawa K, Matsumoto T, Miura
T (2005) Screening of genes expressed in developing mandibles
during soldier differentiation in the termite Hodotermopsis
sjostedti. FEBS Lett 579:1365–1370
Krebs JR, Davies NB (1978) Behavioural ecology: an evolutionary
approach. Blackwell, London
Krebs JR, Davies NB (1981) An introduction to behavioural ecology.
Blackwell, London
Kurata Y, Mori T, Kawachi H, Kishida O, Hiraka I, Uchida N,
Nishimura K (2005) Genetic basis of phenotypic plasticity for
predator-induced morphological defenses in anuran tadpole
using cDNA subtraction and microarray analysis. Zool Sci
22:1435
Laforsch C, Tollrian R (2004) Embryological aspects of inducible
morphological defenses in Daphnia. J Morphol 262:701–707
Lande R (2009) Adaptation to an extraordinary environment by
evolution of phenotypic plasticity and genetic assimilation.
J Evol Biol 22:1435–1446
Levins R (1968) Evolution in changing environments. Princeton
University Press, Princeton
Lurling M, Van Donk E (2000) Grazer-induced colony formation in
Scenedesmus: are there costs to being colonial? Oikos 88:111–
118
13
MacArthur RH (1972) Geographical ecology: patterns in the distribution of species. Harper and Raw, New York
Maekawa K, Mizuno S, Koshikawa S, Miura T (2008) Compound eye
development during caste differentiation of the termite Reticulitermes speratus (Isoptera: Rhinotermitidae). Zool Sci 25:699–
705
Maeno K, Tanaka S (2009) Artificial miniaturization causes eggs laid
by crowd-reared (gregarious) desert locusts to produce green
(solitarious) offspring in the desert locust, Schistocerca gregaria.
J Insect Physiol 55:849–854
Maki N, Gestwicki JE, Lake EM, Kiessling LL, Adler J (2000)
Motility and chemotaxis of filamentous cells of Escherichia coli.
J Bacteriol 182:4337–4342
Mery F, Kawecki TJ (2003) A fitness cost of learning ability in
Drosophila melanogaster. Proc R Soc Lond B 270:2465–2469
Mery F, Kawecki TJ (2004a) An operating cost of learning in
Drosophila melanogaster. Anim Behav 68:589–598
Mery F, Kawecki TJ (2004b) The effect of learning on experimental
evolution of resource preference in Drosophila melanogaster.
Evolution 58:57–767
Mery F, Kawecki TJ (2005) A cost of long-term memory in
Drosophila. Science 308:1148
Miura T, Kamikouchi A, Sawata M, Takeuchi H, Natori S, Kubo T,
Matsumoto T (1999) Soldier caste-specific gene expression in
the mandibular glands of Hodotermopsis japonica (Isoptera:
Termopsidae). Proc Natl Acad Sci USA 96:13784–13879
Morgan CL (1896) On modification and variation. Science 4:733–
740
Mori T, Hiraka I, Kurata Y, Kawachi H, Kishida O, Nishimura K
(2005) Genetic basis of phenotypic plasticity for predatorinduced morphological defenses in anuran tadpole, Rana pirica,
using cDNA subtraction and microarray analysis. Biochem
Biophys Res Commun 330:1138–1145
Morooka S, Tojo S (1992) Maintenance and selection of strains
exhibiting specific wing forms and body color under highdensity conditions in the brown planthopper, Nilaparvata lugens
(Homoptera, Delphacidae). Appl Entomol Zool 27:445–454
Murdoch WW, Oaten A (1975) Predation and population stability.
Adv Ecol Res 9:1–131
Oaten A, Murdoch WW (1975) Switching, functional response, and
stability in predator-prey systems. Am Nat 109:299–318
Paenke I, Sendhoff B, Kawecki TJ (2007) Influence of plasticity and
learning on evolution under directional selection. Am Nat
170:E47–E58
Pianka ER (1978) Evolutionary ecology, 2nd edn. Harper and Row,
New York
Pigliucci M (2001) Phenotypic plasticity: beyond nature and nurture.
The Johns Hopkins University Press, Baltimore
Price TD, Qvarnström A, Irwin DE (2003) The role of phenotypic
plasticity in driving genetic evolution. Proc R Soc Lond B
270:1433–1440
Raine NE (2009) Cognitive ecology: environmental dependence of
the fitness costs of learning. Curr Biol 19:R486–R488
Ricklefs RE (1979) Ecology, 2nd edn. Chiron, London
Robinson BW, Gukas R (1999) The influence of phenotypic
modifications on evolution: the Baldwin effect and modern
perspectives. Oikos 85:582–589
Robinson GE, Grozinger CM, Whitfield CW (2005) Sociogenomics:
social life in molecular terms. Nat Rev Genet 6:257–270
Roff DA (1986) The genetic-basis of wing dimorphism in the sand
cricket, Gryllus firmus, and its relevance to the evolution of wing
dimorphisms in insects. Heredity 57:221–231
Sarkar S (2004) From the Reaktionsnorm to the evolution of adaptive
plasticity: a historical sketch, 1909–1999. In: DeWitt TD,
Scheiner SM (eds) Phenotypic plasticity. Oxford University
Press, Oxford, pp 10–30
123
14
Schmalhausen II (1949) Factors of evolution: the theory of stabilization selection. University of Chicago Press, Chicago
Shibao H, Lee J-M, Kutsukake M, Fukatsu F (2003) Aphid soldier
differentiation: density acts on both embryos and newborn
nymphs. Naturwissenschaften 90:501–504
Shibao H, Kutsukake M, Fukatsu F (2004a) Density triggers soldier
production in a social aphid. Proc R Soc Lond B 271:S71–
S74
Shibao H, Kutsukake M, Fukatsu F (2004b) Contact with non-soldiers
acts as a proximate cue of density-dependent soldier production
in a social aphid. J Insect Physiol 50:143–147
Shibao H, Kutsukake M, Fukatsu F (2004c) Density-dependent
induction and suppression of soldier differentiation in an aphid
social system. J Insect Physiol 50:995–1000
Shibao H, Kutsukake M, Lee J-M, Fukatsu F (2004d) Analysis of age
polyethism in a soldier-producing aphid, Tuberaphis styraci, on
an artificial diet. In: Simon J-C, Dedryver CA, Rispe C, Hullé M
(eds) Aphids in a new millennium. Proceedings of the XVI
international symposium on aphids. INRA, Versailles, pp 73–77
Shibao H, Kutsukake M, Matsuyama S, Fukatsu T, Shimada M (2010)
Mechanism regulating caste differentiation in an aphid social
system. Commun Integr Biol 3:1–5
Sibly RM, Smith RH (1985) Behavioural ecology: ecological
consequences of adaptive behaviour. Blackwell, London
Simpson GG (1953) The Baldwin effect. Evolution 7:110–117
Spalding D (1873) Instinct, with original observations on young
animals. MacMillan’s Mag 27:282–293
Suzuki Y, Nijhort HF (2006) Evolution of a polyphenism by genetic
accommodation. Science 311:650–652
Suzuki Y, Nijhort HF (2008) Genetic basis of adaptive evolution of a
polyphenism by genetic accommodation. J Evol Biol 21:57–66
Tanaka S, Maeno K (2006) Phase-related body-color polyophenism in
the hatching, re-examination of the material and crowding
effects. J Insect Physiol 52:1054–1061
Tanaka S, Maeno K (2008) Maternal effects on progeny body size and
color in the desert locust, Schistocera gregaria: examination of a
current view. J Insect Physiol 54:612–618
Tawfik AI, Tanaka S, De Loof A, Schoofs L, Baggerman G,
Waelkens E, Derua R, Milner Y, Yerushalmi Y, Pener MP
(1999) Identification of the gregarization-associated dark-pigmentotropin in locusts through an albino mutant. Proc Natl Acad
Sci USA 96:7083–7087
Tebbich S, Taborsky M, Fessl B, Blomqvist D (2001) Do woodpecker
finches acquire tool-use by social learning? Proc R Soc Lond B
268:2189–2193
Tollrian R (1993) Neckteeth formation in Daphnia pulex as an
example of continuous phenotypic plasticity—morphological
effects of Chaoborus kairomone concentration and their quantification. J Plankt Res 15:1309–1318
Tollrian R, Dodson SI (1999) Inducible defenses in cladoceran. In:
Tollrian R, Harvell CD (eds) The ecology and evolution of
inducible defenses. Princeton University Press, Princeton, pp
177–202
Uvarov B (1966) Grasshoppers and locusts, vol 1. Cambridge
University Press, Cambridge
Van Buskirk J, Relyea RA (1998) Selection for phenotypic plasticity
in Rana sylvatica tadpoles. Biol J Linn Soc 65:301–328
Van der Stap I, Vos M, Mooij WM (2008) Inducible defenses and
rotifer food chain dynamics. Hydrobiologia 593:103–110
Vespäläinen K (1978) Wing dimorphism and diapause in Gerris:
determination and adaptive significance. In: Dingle H (ed)
Evolution of insects migration and diapause. Springer, Heidelberg, pp 218–253
123
Popul Ecol (2010) 52:5–14
Via S, Lande R (1985) Genotype–environment interaction and the
evolution of phenotypic plasticity. Evolution 39:505–522
Waddington CH (1953) Genetic assimilation of an acquired character.
Evolution 7:118–126
Waddington CH (1959) Canalization of development and genetic
assimilation of acquired characters. Nature 183:1654–1655
Waddington CH (1961) Genetic assimilation. Adv Genet 10:257–290
Wakamoto Y, Yasuda K (2006a) Quantitative evaluation of cell-tocell communication effects in cell group class using on-chip
individual-cell-based cultivation system. Biochem Biophys Res
Commun 350:678–684
Wakamoto Y, Yasuda K (2006b) Epigenetic inheritance of elongated
phenotypes between generations revealed by individual-cellbased direct observation. Meas Sci Technol 17:3171–3177
Wakamoto Y, Ramsden J, Yasuda K (2005) Single-cell growth and
division dynamics showing epigenetic correlations. Analyst
130:311–317
Weinstock GM, Robinson GE, The Honeybee Genome Sequencing
Consortium (2006) Insights into social insects from the genome
of the honeybee Apis mellifera. Nature 443:931–949
Weisser WW, Braendle C, Minoretti N (1999) Predator-induced
morphological shift in the pea aphid. Proc R Soc Lond B
266:1175–1181
West-Eberhard MJ (1989) Phenotypic plasticity and the origins of
diversity. Ann Rev Ecol Syst 20:249–278
West-Eberhard MJ (2003) Developmental plasticity and evolution.
Oxford University Press, Oxford
West-Eberhard ML (2005) Phenotypic accommodation: adaptive
innovation due to developmental plasticity. J Exp Zool B Mol
Dev Evol 304B:610–618
Whitfield CW, Ben-Shahar Y, Brillet C, Leoncini I, Crauser D,
LeConte Y, Rodriguez-Zas S, Robinson GE (2006) Genomic
dissection of behavioral maturation in the honey bee. Proc Natl
Acad Sci USA 103:16068–16075
Wilson EO (1971) Insect societies. Belknap University Press, Boston
Wilson EO (1975) Sociobiology: the new synthesis. Harvard/Belknap
Press, Boston
Wilson RS, Kraft PG, Van Damme R (2005) Predator-specific
changes in the morphology and swimming performance of larval
Rana lessonae. Funct Ecol 19:238–244
Woltereck R (1909) Weitere experimenelle Untersuchungen über
Artveranderung, speziell über des Wesen quantitativer Artunterschiede bei Daphniden. Ver Deutsche Zool Gesell 19:110–172
(in German)
Yarali A, Ehser S, Hapil FZ, Huang J, Gerber B (2009) Odor intensity
learning in fruit flies. Proc R Soc Lond B 276:3413–3420
Zera AJ, Tiebel KC (1989) Differences in juvenile-hormone esteraseactivity between presumptive macropterous and brachypterous
Gryllus rubens—implications for the hormonal-control of wing
polymorphism. J Insect Physiol 35:7–17
Zera AJ, Zhao ZW (2006) Intermediary metabolism and life-history
trade-offs: differential metabolism of amino acids underlies the
dispersal-reproduction trade-off in a wing-polymorphic cricket.
Am Nat 167:889–900
Zera AJ, Sall J, Otto K (1999) Biochemical aspects of flight and
flightlessness in Gryllus: flight fuels, enzyme activities and
electrophoretic profiles of flight muscles from flight-capable and
flightless morphs. J Insect Physiol 45:275–285
Zhao ZW, Zera AJ (2002) Differential lipid biosynthesis underlies a
tradeoff between reproduction and flight capability in a wingpolymorphic cricket. Proc Natl Acad Sci USA 99:16829–16834
Zupanc GKH (2003) Behavioral neurobiology. Oxford University
Press, Heidelberg