Download What is plant behaviour?

Plant, Cell and Environment (2009) 32, 606–616
doi: 10.1111/j.1365-3040.2009.01929.x
What is plant behaviour?*
ANTHONY TREWAVAS
Institute of Molecular Plant Science, University of Edinburgh, Edinburgh EH9 3 JH, UK
ABSTRACT
The nature of plant behaviour is discussed, and it is concluded that it is best described as what plants do. The
possibility that plant behaviour is simply signal-induced
phenotypic plasticity is outlined, and some limitations of
this assumption are considered. Natural environments
present many challenges to growing plants, and the consequent signalling that plants perceive is becoming extremely
complex. Plant behaviour is active, purposeful and intentional, and examples are discussed. Much plant behaviour,
concerned with stress and herbivory, is also based on an
assessment of the future likelihood of further damaging
episodes and is therefore predictive. Plant behaviour
involves the acquisition and processing of information.
Informational terminology provides a suitable way of
incorporating the concepts of learning, memory and intelligence into plant behaviour, capabilities that plants are
rarely credited with. Finally, trade-offs, cost–benefit assessments and decision making are common plant behavioural
attributes. It is suggested that intelligent assessments that
involve the whole plant are essential to optimize these
adaptive capabilities.
Key-words: communication network; intelligence; intention;
purpose.
BEHAVIOUR IS WHAT PLANTS DO
Defining plant behaviour
The life cycle goal of any individual plant is optimal fitness,
usually equated to maximum numbers of viable seedlings or
more conveniently, for experimental purposes, the numbers
of seeds. Seed yield is known to be dependent on lifetime
acquired resources (carbohydrates, minerals and water, i.e.
food), extent of predation and success in reproduction.
Similar fitness requirements exist for animals – acquisition of
adequate food, avoidance of predators (or catching prey)
and successful reproduction. In animals, all these behavioural processes involve movement, and movement is
recognized as the basis of animal behaviour. Higher plants
spend their life cycle rooted in one position and, to the casual
observer, exhibit no movement, with only rare exceptions
like Mimosa. How then can plant behaviour be described?
Correspondence: A. Trewavas. Fax: +0131 650 5392; e-mail:
[email protected]
*This manuscript is part of the special issue on plant behaviour.
606
‘Among plants, form may be held to include something
corresponding to behaviour in the zoological field. The
animal can do things without inducing any essential change
in its bodily structure. When a bird uses its beak to pick up
food, the beak remains unchanged. But for most, but not all,
plants, the only available forms of action are either growth
or discarding of parts, both of which involve a change in
the size and form of the organism’ (Arber 1950, p. 3). This
statement identifies phenotypic plasticity as a form of
action in plants, that is, plant behaviour. The Latin word
habere, from which the word behaviour is derived, means
‘having’ or ‘being characterized by’. Arber’s statement indicates that plant behaviour is action, that is, doing something.
Behaviour is then what a plant does, rather than something
it is characterized by or has.
Behaviour and plasticity
In a seminal chapter, Silvertown & Gordon (1989) defined
plant behaviour as the response to signals, and this, along
with Arber’s description, equates plant behaviour with the
phenomenon of phenotypic plasticity (Trewavas 2003;
Sultan 2005; Karban 2008). Ecologists describe plasticity in
terms of ‘norms of reaction’ that specify the boundaries of
plastic variation to individual signals (Schlichting & Pigliucci 1998; Sultan 2000). Not all tissues exhibit plastic
responses (Bradshaw 1965).
Phenotypic plasticity is not unique to plants however.
Plant behaviour can, and indeed should, express a phenotypically local response to local signalling, but so can that
of other organisms. For example, human weightlifting specifically increases the development of the muscles most
involved. The real difference between plant and animal
behaviour was again indicated by Arber (1950, p. 136).
‘The individuality of the mammalian body is of a much
more fixed character; that body consists of a limited
number of organs which were once and for all marked out
in the embryo. With its parts arranged in an ordered hierarchy there is no such thing as indefinite succession of
limbs, of branches of limbs, numerically unfixed and liable
to impede one another but this is what we find among
plants’. Movement is essential for the higher animal lifestyle. Only with accurate replication of limb numbers and
complex coordination among them could this be reproducibly achieved. Thus, crucial embryological tissue specification is limited to the protected environments of the
egg or uterus, and subsequent plasticity is constrained to
more marginal changes in already specified organs. The
© 2009 The Author
Journal compilation © 2009 Blackwell Publishing Ltd
Plant behaviour 607
potential for plasticity is considered to have a genetic
basis, but its realization must be epigenetic.
Most higher plants have a modular structure, and the
plant body is plastically constructed from variable numbers
of leaves plus buds and branch roots. Plasticity enables the
phenotype to accurately occupy local space, change its phenotype as it grows, forage accurately for resources, competitively exclude neighbours and construct, within genetic/
environmental limitations, its own niche. The niche concept
involves little understood competitive and cooperative twoway signalling between individual and environment that is
important in community structure (Muller-Landau 2003;
Uriarte and Reeve 2003; Silvertown 2004; Donohue 2005;
Kelly et al. 2008; Liebold 2008). Badri & Vivanco (2009) in
this issue reviewed recent information on root exudates
that contribute to niche construction.
Predation is inevitable for wild plants, but numerous
dormant meristems, regrowth and often extraordinary
regenerative capacities can diminish but not eliminate the
potential reduction in fitness. It is also the reason that plants
do not place critical functions in one or two tissues as
animals do with heart or kidneys. Such specialization would
make the individual extremely vulnerable to even slight
predation. However, the phenotype is holistically determined. Excision of either a whole shoot or root inhibits
further plasticity changes until regeneration of the lost
organs is completed. Moreover, fitness itself is a function of
the integrated phenotype, not just the behaviour of individual tissues.
Limitations to equating behaviour just to
signal-induced changes
There are several problems with equating plant behaviour
only with plasticity. The term ‘reproductive behaviour’ is
often used to distinguish whether reproduction is sexual
or vegetative without regard to plasticity changes. Some
species do have separate male and female flowers, and
environmental conditions can change the proportions of
each, implicating plasticity, too (Trewavas 2007b). Tsvi
Sachs objected to essential developmental processes like
germination being classed as behaviour (quoted in Silvertown 1998). On the other hand, there is certainly inherent
plasticity in the germination phenotypes of almost any
species.
A further complication is the potential lack of reversibility in phenotypic responses raised in this issue by Metlen,
Aschehoug & Callaway (2009). As they pointed out, behavioural plasticity in secondary metabolite production is
reversible. But in contrast, abscission can be used to substantially reverse phenotypic changes, and innate animal
behaviour certainly appears irreversible.
A further issue is whether there is an intrinsic control
phenotype, generated in the absence of signalling and often
assumed to be a growth-room phenotype. This perception
is compounded by the relatively uniform appearance of
many field crops, a situation that has arisen because crop
plant breeders have (1) eliminated much signal-induced
behaviour and (2) selected only a few individuals (genotypes) for subsequent breeding out of a much greater range
of behavioural and genotypic variation (Lewontin 2001).
But all phenotypes are constructed from a complex twoway conversation between genes and the total environment. Growth-room environments are perceived and used
to specify only one out of a range of phenotypes. All that
genes can ever do is specify a norm of reaction; they are
not invariant determinants of phenotype or behaviour
(Lewontin 2001).
ENVIRONMENTAL SIGNALLING COMPLEXITY
AND BEHAVIOUR
Many signals are perceived
What growth rooms cannot mimic is the enormous complexity of the external environment experienced by the wild
plant. Behaviour is inextricably linked to environmental
signalling. Because plants are sessile organisms, they may
perceive more environmental signals and with greater sensitivity and discrimination than the roaming animal. ‘If
etiolated seedlings are placed between two sources of light
differing so slightly that the differences cannot be detected
by ordinary photometric methods, the seedling always
bends promptly towards the source of the more intense
light’ (Palladin 1918, p. 246) is certainly indicative.
In this special issue on plant behaviour, many articles
deal with particular kinds of environmental signalling.
Foraging is described as the behavioural alterations that
enhance the uptake of essential resources and De Kroon
et al. (2009) highlighted both the local and integrated signalling that underpins these vital processes. Mott (unpublished data) described the systems behaviour of complexes
of stomatal cells that are crucial for foraging for carbon
dioxide. Forde and Walch-Liu (2009) also reviewed the
important role of amino acids and nitrate in constructing
the root phenotype. The shoot phenotype is dependent on
the presence, absence and crucially the identity of neighbours (see pictures in Bazzaz 2000, p. 114), and these may
reflect the ubiquity of competition. Ballaré (2009) emphasized the critical role of phytochrome in both light foraging, overall resource allocation, herbivore defence and thus
shoot phenotype construction.
Volatile (gaseous) chemicals are increasingly seen as
important in plasticity. Well-established information has
already reported the phenotypic alterations induced by
humidity (water vapour), carbon dioxide, oxygen (in flooding responses and 10% oxygen environments), ethylene,
ozone and, more recently, nitric oxide. But as Galis et al.
(2009) and Dicke (2009) reviewed here, signalling via
volatile chemicals is of crucial importance in herbivory
resistance. Particular combinations of volatiles overcome
vascular constraints on systemic signalling (Frost et al.
2007), while other combinations signal adjacent plants
(Karban 2008). Different groups of volatiles again can be
herbivore specific, attracting predatory, parasitoid wasps
(De Moraes et al. 1998). Dodder, a parasitic plant, also
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608 A. Trewavas
homes in on its host by detecting stem-released volatiles
(Runyon, Mescher & De Moraes 2006), observations critical to understanding how Dodder maximizes the energy
gained from the host while minimizing its energy investment in coiling and haustoria formation (Kelly 1992). Apart
from ethylene, specific receptors for these volatiles await
characterization.
Other kinds of signalling have been detected, but their
current molecular basis remains unknown. As both Hodge
(2009) and Novoplansky (2009), again in this issue, indicated, root systems are not only able to sense the soil
volume in which they grow but can recognize and discriminate against the roots of adjacent conspecifics and thus
possess self-recognition. [Astonishingly bacteria have selfrecognition (Gibbs, Urbanowski & Greenberg 2008), indicating perhaps the ubiquity of self-recognition processes.]
Potentially, the roots of any individual plant avoid each
other as far as possible to improve the extent of soil space
occupied and exhibit a kind of territoriality (Schenk, Callaway & Mahall 1999). Furthermore, the root system exhibits
holistic responses to the patchy environment experienced.
These observations do imply complex signalling below
ground; could these root signals be presently unknown
volatiles, too (Erb et al. 2008)?
Other biotic signalling results from competition for soil
resources, from mycorrhizal and cooperative bacterial interactions and from allelopathic chemicals, disease, mutualism,
trampling and, finally, plant cooperation (Kelly et al. 2008).
Some of these signals, like disease and bacterial cooperation, are relatively well understood; the others are less well
characterized.
What makes for much greater complexity is that many
of these signals arrive coincidentally. Decisions among
often conflicting signals have to be made and priorities
determined on phenotypic change. Leyser (2009), in this
issue, described the role of auxin in leaf and branch initiation in which a coherent model is beginning to emerge.
The abiotic signals of light, gravity, mechanical signals, soil
structure and composition, minerals and water availability
add to the difficulties for the growing plant because each,
like the biotic signals, varies in direction, length of signalling and intensity. This enormous complexity of signalling
ensures that no plant behavioural response is autonomic, a
kind of behaviour that requires complete replication
under all environmental circumstances. Selection will
favour individuals that can best assess the probabilities of
particular kinds of behavioural action and optimize their
fitness.
This enormous signalling/environmental complexity is
best conceived by the reader as a complex but changing
topological surface composed of hills and valleys, and the
successful plant (from seed to flower) must navigate its
way through this topological and hazardous environmental
terrain, which keeps changing in structure, with minimal
expenditure of energy. Bazzaz (2000, pp. 91, 168) illustrated
striking, complex topological surfaces involving the influences of only two environmental parameters. How much
more complex with 20 or more?
BEHAVIOUR, MOVEMENT, PURPOSE
AND INTENTION
McDougall (1924) described behaviour in the following
way. Animals are behaving if they actively resist the push
and pull of the environment, exhibit persistence of activity
independently of the impression (signal) that may have
initiated it and exhibit variation in the direction of persistent movements. This definition would characterize plant
behaviour, too.
Movement and behaviour
Movement would seem to be the simplest criterion of behaviour, and movement has always been an essential
part of the animal lifestyle to find food, avoid predators (or
catch prey) and find mates. Predator–prey relations among
animals accelerated the evolutionary specialization of
sensory organs and muscles to respond to signals. The
nervous tissue, a rapid information transmission system,
then evolved, to link these two together. The faster the
prey responded and moved, the faster any effective predator
had to evolve in turn.Animal behaviour tends to be equated
with movement because we ourselves are animals, because
our perception/response system works at the rate of transmission of the nervous system (like most other animals) and
because we regard our own movement as behaviour.
Multicellular organisms that lack a nervous system can be
expected to operate on a very different timescale, and higher
plants are no exception. This change of timescale creates
problems for recognition of behaviour. Pfeffer (1906,
p. 2) early on recognized the problem. ‘The fact that in
large plants the power of growth and movement are
not strikingly evident has caused plants to be popularly
regarded as still life. Hence, the rapid movements of Mimosa
pudica were regarded as extraordinary for a plant, and the
same applies to the spontaneous movements performed by
Hedysarum gyrans (telegraph plant). If mankind from youth
upwards were accustomed to view nature under a magnification of 100 to 1000 times (seeing streaming or lower plant
sperm swimming) or to perceive the activities of weeks or
months in a minute as is possible by the aid of a kinematograph, this erroneous idea would be entirely dispelled’.
Pfeffer (1906) thus predicted time-lapse facilities that brings
plant behaviour, in some sense, to a more familiar human
timescale. The web site (http://plantsinmotion.bio.indiana.
edu/plantmotion/starthere.html) constructed by Roger
Hangartner contains many excellent time-lapse examples
that show behaviour that complies with the aforementioned
McDougall (1924) definition. One fundamental difference
between plant and animal behaviours is therefore in their
respective time frames.
The real value of time-lapse records is to uncover behaviour either difficult to record or missed by previous recording procedures. For example, the Attenborough (1995)
time-lapse films record a kind of rapid vertical/horizontal
shaking behaviour by a growing bramble stem that so far
has no explanation. Other revealing time-lapse movies are
© 2009 The Author
Journal compilation © 2009 Blackwell Publishing Ltd, Plant, Cell and Environment, 32, 606–616
Plant behaviour 609
to be found in Massa & Gilroy (2003) on root behaviour
encountering soil obstructions and Runyon et al. (2006) on
Dodder locating its prey by detecting host volatiles. Timelapse recording needs to be focused on the behaviour of
wild plants as well, because the timescale difference with
human observers implies that much novel behaviour may
simply have never been seen.
Purposeful behaviour
In a seminal paper, Aphalo & Ballare (1995) indicated how
plants were commonly perceived as ‘passive organisms’
undergoing a predetermined programme whose culmination was occasionally slowed by poor environments. They
argued instead that plant behaviour is both active and predictive. The ‘passive plant’ attitude almost certainly results
from experimental experience of plants in which signals are
imposed by the investigator to make plants perform in controlled conditions, perhaps, similar to the way circus animals
are made to perform. But in the wild, it is plants that must
compile environmental information and make active decisions to change development, in order to optimize life cycle
behaviour and eventual fitness.
Active behaviour may be more simply defined as a
dependence on metabolic energy (Rosenblueth, Weiner &
Bigelow 1943). True passive behaviour is then simply
limited to processes, like the explosive distribution of seeds,
that depend only on unequal drying of dead tissue or the
floating of seeds in the wind.
Active behaviour is most easily defined as purposeful
when it is goal oriented (Rosenblueth et al. 1943; Russell
1946). The goal is often achieved by some complex form of
negative feedback, and obvious examples (out of many) are
the adaptive responses of tropic bending to gravity or light.
In negative feedback, an information loop is constructed
from the signal to the responding cells to indicate the
margin of error from the goal and adjust behaviour accordingly (Trewavas 2007a). The clearest indications of a kind of
negative feedback control are the damped oscillations
around the goal that can sometimes be observed in tropic
bending (Trewavas 2003).
Other examples of more complex and less understood,
purposeful (goal-directed) behaviour are (1) the stem thickening that accompanies wind sway; (2) leaf abscission that
rebalances the water relations of a whole plant when water
supplies are diminished; (3) the (indeterminate?) elongation of the leaf petiole in water plants like Nymphaea,
which only stops when the leaf breaks surface; and (4)
the seasonal, average tree-leaf temperature that remains
remarkably uniform at about 21 °C from trees ranging
from the subtropical to the arboreal (Helliker & Richter
2008). This unusual form of long-term homeostasis, which
undoubtedly benefits photosynthetic processes, is suggested
to result from an interaction among internal leaf cooling,
leaf structure, branch structure and leaf distribution among
others, all important behavioural traits that have clearly
been optimized. Russell (1946) included several other good
plant examples. The molecular mechanism underpinning
goal-directed behaviour is clearly dependent on growth
substance involvement (auxin, ethylene, etc.) that is only
partly understood.
Certain forms of purposeful behaviour seem overwhelmingly controlled by one signal; the extreme sensitivity of
etiolated seedlings to unidirectional blue light that can
override opposing gravity signals is an obvious example.
The most obvious purposeful behaviour, however, arises
from an integration of different signals. Charles Darwin
(1880) showed experimentally how seedling roots sensed
the signals of touch, light, moisture and gravity simultaneously resulting in sensory integration (Trewavas 2007c).
Furthermore, he showed that growing roots could distinguish between these signals and decide which was the most
crucial to respond to. Both touch and humidity can override
the gravitational signal if applied in a different direction
(Eapen et al. 2003; Massa & Gilroy 2003), in a recent excellent expansion of Darwin’s observations on soil obstructions, indicating how the root response is integrated
between touch and gravity. Natural soil is very heterogenous both in texture and in the distribution of resources
(Bell & Lechowicz 1994). Signal integration is therefore
necessary. The successful plant must more correctly assess
the probabilities of appropriate action in constructing the
root phenotype.
Intentional behaviour
Piaget (1979, p. 1) described behaviour as follows:‘By behaviour, I refer to all the actions directed toward the outside
world in order to change conditions therein or to change
their own situation in relation to these surroundings’. This
definition is equally applicable to plant behaviour but
implies intention, usually defined as goal-directed behaviour. Do plants intend to resist herbivores; do they intend to
respond to gravity; do they intend to resist the common
stresses they experience? The description of the behaviour
of individual root systems as growing to actively deny
resources to competitors certainly implies intention (Maina,
Brown & Gersani 2002; Gruntmann & Novoplansky 2004).
The issue of intentional behaviour was raised and discussed at length by Scott-Turner (2007) in the context of
social insect colony behaviour. Relatively simple interactions between the individual insect organisms construct a
communication network with complex and some, recognizably, intentional properties. In analogous fashion, the communication network of cells and tissues that construct the
individual plant may be the mechanistic basis of intention in
plant behaviour.
Does intention imply cognitive involvement? Both Maturana and Varela (1980) and Bateson (1985) indicated that
cognition, defined as the act of knowing, is implicit in all life,
constructed as it is from complex hierarchical network
structures (Trewavas 2007a). These authors stated that even
organisms such as plants without nervous systems perceive,
respond and thus know about their environment; they are
therefore capable of cognition. ‘It is not too much to say
that a plant is capable of cognition in much the same way
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610 A. Trewavas
that a human being is. The plant gathers information about
its surroundings, combines this with internal information
about its internal state and makes decisions that reconcile
its well-being with its environment’ [Trewavas 2005a; modified from an original social insect quote by Seeley & Levien
(1987)].
The notion of intentional behaviour might also conflict
with the Neo-Darwinist view of natural selection that suggests organisms as passive in the face of random selection.
The alternative to simple selection from a systems framework and permitting intention is powerfully argued by
Gould (2002, p. 614 onwards).
MEMORY, LEARNING AND
INTELLIGENT BEHAVIOUR
The quality of biological information is
determined by constraint
Information theory was first posed by Shannon & Weaver
(1949). However, their concept of information based on
entropy has been difficult to apply to biology (Trewavas
2007a). Biological information can be equated to meaningful communication. This definition of information implies
that the quality of information gained is proportional to the
constraint with which it is sensed and transduced.
Meaningful plant signals (properly called semeotics) are
first distinguished by specific receptors; the greater the
selectivity exerted by the receptor, the higher the quality of
information conveyed to the cell. However, single receptors
can do little more than provide an all-or-nothing signal to
the cell. To provide further essential information on the
time length of the signal and its direction for example, other
related receptors are needed. Thus, families of receptors are
common, for example, the phytochromes, cryptochromes,
nitrate reductases, auxin receptors, calmodulins (calcium
receptors) and so on. Holistic integration of the information
provided by the receptor families and integrated with other
families helps provide a kind of ‘three-dimensional’ signal
perception in both space and time.
Constraint is equally important during signal transduction chains that depend on protein–protein interactions.
Cell cytoplasms contain anywhere from 20 to 40% protein,
and some membranes, such as the mitochondrial membrane, are 80% protein. Protein–protein interactions of all
kinds will therefore be common and without some discrimination, cellular responses will simply be destroyed by informational noise. Transduction sequences are constructed
from proteins whose adjacent members exhibit complementary surface topologies often induced by a prior signal.
For example, signal-induced changes in the surface topology of protein kinases may now enable specific interaction
with a protein substrate. Specific surface interactions
between these proteins, when they occur, will exhibit relatively strong binding and will last a relatively long period,
and information exchange will be high, as a result of constraint. In contrast, noisy interactions although frequent,
will be only weakly binding, short-lived and convey little or
no information. GTP-binding proteins are commonly used
by cells to ‘time’ the lengths of protein–protein interactions.
Only if the protein–protein interaction lasts longer than the
hydrolysis rate of GTP, do cells regard the interaction as
providing a high quality of information. It is in part for these
reasons that Nurse (2008) called for much greater research
emphasis on how information is gathered, processed, stored
and used, and how this generates higher-level phenomena.
Information terms for learning, memory and
intelligent behaviour
In informational language, memory is simply information
stored for later use, learning is simply acquisition of information and intelligent behaviour is the assessment of information that leads to adaptive, problem-solving responses.
Figure 1 indicates the various kinds of information categories that underpin plant behaviour with their different but
equivalent terminologies. The value of using information
terminology is that there is no implication concerning the
mechanisms involved in transmitting information (Box 1).
Nervous systems process information by mainly different
mechanisms to those used by cells of all kinds, but the
analogous learning, memory and intelligence behaviours
can be recognized in cells, tissues, whole plants and other
organisms.
Memory
Memory has been described by authors as contributing to a
variety of plant behavioural situations. Memory is probably
Box 1. Common misconceptions of the use of
words involved in information processing
Bruce et al. (2007) suggested that the use of the term
‘memory’ in plants implies a cognitive function.
However, neither learning, memory nor indeed intelligence are words limited to biological, let alone, cognitive
processes. For example, computers possess memory, and
the more advanced ones can learn. Some molecules
and steels are described as possessing a shape memory
induced by a particular annealing regime (e.g. Sehitoglu
et al. 2001). Intelligence has been used to refer to many
biological processes and organisms (Trewavas 2005b)
and machines. Plant biology has borrowed many words
that were originally designed to describe purely human
characteristics because the botanical process examined
was analogous. The plant ‘vascular system’ containing
‘veins’ and ‘vessels’ is analogous in function to the
human vascular system, but the mechanisms whereby
each works are entirely different. Hairs, stress, arms race,
battles, pathways, cross talk and foraging are a few other
borrowed words, and there are many more. However,
when defined in information terms, memory, learning
and intelligence are suitable terms for any organism
regardless of the precise mechanisms involved.
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Plant behaviour 611
Network
Molecules, cells, tissue, whole plant
Orchestration of information flow
[downward causation]
Information
storage
[memory]
Information
[signal (meaningful
information), cue]
Information
acquisition
[learning]
Information
assessment
[intelligence]
Meaningful
information out
[adaptive behaviour,
response,
problem solving]
Loop
Figure 1. Information flow through biological networks that initiates eventual behavioural changes. Biological networks are hierarchical;
they are constructed starting with cellular molecules, cells, tissues, individual plant (genet), population, niche or community. Each of these
levels in the hierarchy forms a network in its right. However, these networks differ markedly in the strength of connections that hold
them together, reflecting probably the fidelity with which information is perceived and interpreted between the constituents of the
network and the increasing noisiness of the information communication channels. The connections are strongest inside plant cells and
then weaken progressively: molecules > cells > tissues > plant > population > niche > communities. As the connection strengths weaken,
greater plasticity is experienced, but even in communities, there is some fidelity in communicated information. The psychologist Schull
(1990) argued strongly for a species population to express intelligent behaviour. The figure is presented in informational terms, and
alternative commoner words that describe analogous processes are indicated in brackets. However, one less than usual feature in
individual plants is the loop (earlier indicated as niche construction) that connects the adaptive response back to subsequent signalling.
As plants grow, they continually modify their own environment and the characteristics of future perceived signals.
essential in all plant behaviours. Only a few examples are
indicated here.
Several weeks of cold temperature can create a mitotically stable memory (vernalization) that can last for 300 d.
Chromatin remodelling may be the molecular underpin of
memory here (Goodrich & Tweedie 2002; Amasino 2004;
Sung & Amasino 2004), and phosphorylation pathways in
animals lead to chromatin remodelling (Stipanovich et al.
2008). Herbivory establishes a long-term memory of previous attacks that primes defence mechanisms, increasing
resistance against further attacks (Karban and Niiho 1995;
Baldwin & Schmelz 1996; Ruuhola et al. 2007; Karban
2008). Priming can last for years. Targeted illumination
generates a spatial memory of phototropic signals lasting
several hours that can override a shorter-term gravitropic
memory interpolated before or after illumination (Nick,
Sailer & Schafer 1990). The memory of mechanical stimulation and mineral imbalance can last for many days after
the signal has ceased (Desbiez et al. 1984; Verdus, Thellier &
Ripoli 1997). Tendril coiling requires both coincident blue
light and mechanical signals, but either signal, given separately, can be remembered for several hours (Trewavas
2005b). Stress effects from numerous treatments [cold, heat,
salinity, drought, ultraviolet (UV) light, mineral imbalance,
disease, etc., including, surprisingly, ABA] can be remembered and influence not only a later response (Goh, Nam &
Park 2003) but memory of some can also be passed to
subsequent generations (Durrant 1962; Molinier et al.
2006). The effect of previous plant neighbours on phenotypic development can be remembered for up to a year
after transplantation elsewhere (Turkington, Hamilton &
Gliddon 1991). In contrast, hypo-osmotic shock memory
can last about 20 min (Takahashi et al. 1997). Finally, the
Venus flytrap requires stimulation of two hairs to effect
closure; these have to be stimulated within 40 s of each
other (Shepherd 2005). One stimulation of a single hair is
thus remembered for 40 s.
No wild plant could survive without some memory of its
current perceived signals or without a cumulative memory
that collates its past information experience and integrates
it with present conditions so that the probabilities of potential futures could be assessed. The mentioned examples
indicate memory lasting from seconds to minutes, to hours,
to days, years or even longer. These surely reflect, in part
and rather crudely, the various known stages of many signal
transduction pathways. Generally, the earliest intracellular
events are ion flux changes and protein phosphorylation
modification (seconds, minutes, hours); slower events are
modification of gene expression and transacting factors
(hours, days). Even longer-term events are intercellular signalling modifications (hours, days or even months and
years) and, finally, chromatin remodelling (days to years).
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612 A. Trewavas
Each signal leaves an imprint specific both to the characteristics of the signal and the current state of the intracellular molecular network, thus modifying the topology of the
network. Additional signals within the appropriate time
frame are thus interpreted differently as information flows
through the modified structure.
Learning
Information storage, (memory) cannot be constructed
without information acquisition first (learning). Learning
can be simple; for example, heliotropic plants learn the
optimal direction of the sun and maintain that position of
leaf orientation. More complex learning involves reinforcement, and good examples are the plant responses to what
are commonly called the stress conditions of cold, drought,
heat, heavy metals, soil minerals, salinity, wind sway, flooding, excess/UV light, oxidative stress, herbicides, herbivory,
disease and even ABA (McKersie & Leshem 1994; Knight,
Brandt & Knight 1998; Goh et al. 2003; Trewavas 2005b;
Bohnert 2007; Dinenny et al. 2008; Frost et al. 2008; Voesink
& Pierik 2008). In all these cases, eventual resistance to a
severely damaging stress can be gained by a progressive
application of a milder but increasing strength of stress. This
learning response enables a quicker, more aggressive, adaptive resistance to subsequent stress episodes. This is clearly
a kind of trial-and-error learning (often called Thorndikean
learning) and has been called priming in the case of herbivory and disease. Priming is, however, straightforward
learning leading to a long-term memory that can last for
months (Frost et al. 2008). Another term applied only to the
abiotic stress stimuli is acclimation, a term that reflects the
passive (laboratory) control of plant behaviour and ignores
the clearly active role played by the wild plant in assessment
and response.
The behavioural responses to an increasing imposition of
stress, indicate that in the wild, this is really predictive
behaviour – a preparation for likely, more severe episodes
in the future. The progressive nature of the learning indicates that there is a trade-off between a commitment to a
full-blown resistance mechanism, which can be costly, balanced against an assessed probability that further episodes
might recur in the near future and ensuring a quicker
response if it does. The emphasis here is on probability;
certainty only occurs in the laboratory. The skill with which
these cost–benefit assessments can be made contributes
directly to ultimate fitness and requires an intelligent
assessment. Prediction of future loss of photosynthetic light
leading to shade-avoidance phenotypes is well established
(Aphalo & Ballare 1995).
The basis of this kind of learning (priming) in plants is not
understood, but in molecular terms multiple, interlinked,
positive feedback loops might offer the least cost of a longterm memory (Ingolis & Murray 2002; Bisjman & Groisman 2003; Xiong & Ferrell 2003; Acar, Becskei & Van
Oudenaarden 2005; Brandman et al. 2005). Learning would
involve the construction of these feedback processes. Such
regulatory, molecular-design circuits can produce graded
responses as well as complete conversion (Becskei,
Seraphin & Serreano 2001).
An alternative mechanism is the possibility that the progressive nature of the response may simply reflect the
numbers of cells that have passed a threshold in an allor-nothing response to the stress. On this basis, as the
stimulus is increased, more cells would undergo this allor-nothing change. This mechanism implies a substantial
variation in sensitivity of individual cells to the mentioned
stress signals. A possible indicant of such cell sensitivity
variation is to be found in guard cell closure. Whereas
some guard cells close with very low concentrations of
ABA, a closure of over 90% required four to five orders
of magnitude increase in ABA concentration (Trewavas
2003). Variation to the mentioned stress signals between
individual plants might also generate the progressive
nature when results are expressed as averages if again
there is a plant all-or-nothing response.
COST–BENEFIT ASSESSMENT, DECISION
MAKING AND INTELLIGENCE
Intelligence is the capacity for problem solving
What is meant by intelligence? For historical reasons only,
some mistakenly identify intelligent behaviour as being a
uniquely human characteristic. This perception has arisen
because of the importance of intelligence in education and
the dominance of educational psychologists in discussion of
intelligent behaviour from 1900 onwards. Psychology is, by
its nature, concerned predominantly with human behaviour, but it is quite clear that many, if not most psychologists,
do not think that intelligence is something limited to human
beings or indeed organisms with brains. Fitness and natural
selection are the arbiters of all kinds of organism behaviour
with the sole exception possibly of recent mankind. It is
the failure to recognize this crucial point that leads to all
kinds of controversies as to the nature of human intelligent behaviour among psychologists. Intelligent behaviour
evolved to increase fitness.
Sternberg, a psychologist who has written more extensively than others on intelligence (e.g. Sternberg 2006, Ciancolo & Sternberg 2004 and references in these), solicited the
opinions of some 20 psychologists as to the meaning of
intelligence (Sternberg & Detterman 1986). This was a
repeat of an investigation first carried out in 1921. In his
analysis of these articles, Sternberg (1986) indicated that
descriptions involving cognition or adaptation were equally
acceptable and identified problem solving as the commonest descriptor. The well-known IQ test is simply an adaptation to the presented situation of the test. Warwick (2001),
an Artificial Intelligence expert, generalized intelligent
behaviour to be the capacity for problem solving and
emphasized that intelligent behaviour in organisms other
than humans must be judged in terms of the capabilities of
the organism in question.To do otherwise is to be subjective
and anthropocentric. Sternberg (1986) himself identified
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Plant behaviour 613
intelligence as existing between species, within species,
within organisms, etc., and therefore broadly present in life
itself. Gardener (1983) and Steinhardt (2001) indicated that
even in humans, intelligence is a whole organism property.
Psychologists therefore do not limit intelligent behaviour to
humans or other advanced animals or even to cognitive
processes (Stenhouse 1974; Griffin 1976; Sternberg 1986;
Schull 1990; Warwick 2001).
Intelligent behaviour cannot be divorced from the situation that elicits it. All wild organisms face highly variable
situations in which they must attempt to optimize their
survival and produce the maximal numbers of siblings.
The capacity to solve the environmental problems that
vary enormously and threaten the optimization of fitness
requires intelligent solutions. The key term that underpins
intelligent behaviour is assessment. Optimal assessment
using stored information, interacting with the stage of
development and current acquired information, leads to
problem solving, successful adaptive responses and thus
increased fitness. Plant intelligence, like plant behaviour
itself, has suffered from an inability of easy human observation, leading to a common assumption that both must be
absent.
Problem solving and trade-offs
In the attempts by plants to optimize fitness, numerous
problems interfere. The individual plant has to accommodate the uneven distribution of light, minerals, soil structure
and water, competition, along with variation in rainfall,
wind and damage by disease pests and herbivores. Flowers
need to be positioned where pollination is optimal. The
costs and benefits of any behavioural change in growth and
development and the resources to back it up require assessment (Bazzaz 2000; De Jong and Klinkhamer 2005). Decisions need to be made about how best to redistribute the
limited internal resources among competing tissues to try
and provide ultimate success. As resource limitation
increases, it becomes increasingly crucial to make the right
decisions to increase the probability of success. The mechanisms used in decision making and trade-offs are currently
only weakly understood, and most research still uses wellnourished laboratory plants. Selection, however, will not
allow such decisions to be made at random!
Trade-offs of resources are known to occur between root
and shoot, between different shoots, roots, branches or
leaves, between vegetative and reproductive growth and
between vegetative growth and herbivore/disease resistance (Hutchings 1997; Lerdau & Gershenzon 1997; Bazzaz
2000; Weaver & Amasino 2001; De Jong and Klinkhamer
2005; Trewavas 2005a, 2007a; Frost et al. 2008). Natural pesticide levels in wild plants occupy 1–5% of their dry weight,
sufficient to reduce both growth and seed yield; any
increased synthesis as a result of attack will diminish growth
further. There will also be trade-offs in resources devoted to
different abiotic stress conditions that will need careful
assessment because an excess resistance response to one
will almost certainly diminish the capability to respond to
another. The multitude of problems requires intelligent,
adaptive responses.
A potential mechanism for plant intelligence; a
communication network
‘Plants have evolved an integrated complex of hormonal
systems – a coordinated but non-centralized intelligence
system . . . that manages bioenergetic resources’ (La Cerra
& Bingham 2002, p. 11). An adaptive representational
network has also been proposed to underpin intelligent
responses (Trewavas 2005a) and is also suggested for bacterial learning (Tagkopoulos, Liu & Tavazoie 2008).
Although the interactions among the seven or eight known
hormones are beginning to be understood, these on their
own may not provide a sufficiently complex network to deal
with the variety of presented problems experienced by wild
plants. The communication network may be made more
complex by including other molecules such as proteins, peptides, nucleic acids, small RNA’s oligosaccharides, sugars,
minerals, etc., that are known to move between cells (Trewavas 2003). As such networks must self-assemble, they will
also self-orchestrate, seeking their most stable configuration (Trewavas 2007a). Orchestration is commonly called
downward causation (Trewavas 2007a); an alternative term
is circular causality (Scott Kelso 1995). The importance of
downward causation in biological networks is also discussed
at length by Noble (2006) and Kauffman (2008).
Changes in orchestration will be continuous as the individual plant progresses from seed to flower and accommodates a changing panoply of signals that elicits adaptive
behaviour. Any signal, as information, contributes to its
own orchestration.Assessment of any signal arises naturally
from the present whole network structure that is itself a
compilation of present and past environmental and developmental history. Intelligent behaviour (adaptive problemsolving behaviour) is thus a property of the whole plant and
not individual tissues.
Plants that can place a root or shoot in the best position
to gain resources, as against indifferent or resource-absent
places, act intelligently. Those plants that most quickly estimate which branches or leaves no longer provide adequate
resource-gathering potential and block them from further
root resource access, have a higher capacity for problem
solving.Those plants that more accurately predict the future
resource availability or herbivore damage and decide on
resource distribution appropriately are smarter than others,
and the reward is a likely gain in fitness.
CONCLUSIONS
Plant behaviour is best described as what a plant does –
doing rather than having. The commonest misapprehension
about higher plants is that they are simple organisms. The
‘still life’ description indicated by Pfeffer (1906) is undoubtedly the major cause of that perception. In complexity of
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614 A. Trewavas
signalling and problem solving within their own environmental context, plants lack nothing compared with animals
in skill and behavioural complexity. There is an undoubted
need for plant biologists to investigate the design characteristics of plant cell protein and phosphorylation networks
and how these generate purposeful and potentially intentional goal-directed behaviour. While plant gene identification has been very successful, systems design is presently
under-investigated. Ecologists and molecular biologists are
needed to construct fruitful interactions centred around
wild behaviour, trade-off assessments, communication
networks, assessment and thus intelligence.
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