Phenotypic plasticity and evolution
Phenotypic plasticity has long been investigated by those interested in evolutionary studies. Certainly around the turn of the 20th century, Darwinian views were opposed by some botanists because of phenotypic plasticity. Henslow (1895) provides a number of examples, such as two kinds of Ampelopsis, one of which forms suckers on mechanical stimulation, the other which forms them regardless of stimulation. Henslow (1895) supported Lamarckian views to explain these data, but genetic assimilation is a much more likely hypothesis. That is, the original character is the result of temporary adaptation, and natural selection increases the numbers of individuals more able to optimize the character before finally simple mutations ensure the character becomes fixed.
Suggestions that genetic assimilation is a major mechanism in evolution have recurred from time to time. Baldwin (1896) called this organic selection, and may have been the first to suggest the possibility. Waddington (1957) supported genetic assimilation using several examples, with the most prominent being the well-known callosities in the ostrich which occur where the bird lies down. It might be thought that these would be an adaptive feature, but they are clearly visible on the embryo inside the egg, supporting genetic assimilation mechanisms. The important feature in genetic assimilation is the persistence of the environmental situation, so that the novel, initially adaptive behaviour persists. With time, genes and gene combinations originate that allow the strategy to develop with greater rapidity, higher probability or lower cost (Bateson, 1963). Eventually mutations appear that fix the trait regardless of environmental signalling. Thus, in these cases, natural selection merely ratifies an adaptation that has already been developed and tested.
The molecular origin of genetic assimilation must occur in signal transduction processes. However, genetic assimilation enables the evolutionary process to move forward more quickly and efficiently, avoiding the tedious trial-and-error process that would involve the alternative view; the random production of such characters complete in all respects. Further discussion of this important aspect of phenotypic plasticity can be found in Bradshaw (1965); Bradshaw and Hardwick (1989); Bazzaz (1996); Schlichting and Pigliucci (1998); Sultan (2000), and references therein.
The timing of many developmental processes is certainly subject to plastic modification (Bradford and Trewavas, 1994). Even environmental influences on the parent can be detected in the resulting seedlings, certainly to one or more generations (Mazer and Gorchov, 1996) and in certain cases much longer (Durrant, 1962). Phenotypic plasticity is generally not all-or-none but usually varies quantitatively, a phenomenon described as the norm of reaction (Schlichting and Pigliucci, 1998). Plasticity is adaptive; this has recently been made clear (Ackerley et al., 2000), and thus phenotypic plasticity fulfils the requirement for intelligent behaviour. Phenotypic plasticity is a visible witness to the complex computational capability plants can bring to bear to finely scrutinize the local environment and act upon it. However, plasticity can be limited to certain characteristics in plant development, with others remaining stable. When grown under low and high fertility, Polypogon plants exhibited a 100-fold variation in the numbers of spikelets per panicle, whilst glume and seed size varied by only 10 % (Bradshaw, 1965). In the well-known Clausen et al. (1940) experiments (see diagrams in Schlichting and Pigliucci, 1998), plasticity was observed in the size of vegetative parts, numbers of shoots, leaves and flowers, elongation of stems and hairiness. But pinnate leaf shape, leaf margin serration, shape of the inflorescence and floral characters remained stable within limits, at least under the conditions investigated.
The presence of morphological plasticity for specific traits is genotype dependent (e.g. Sultan and Bazzaz, 1993a, b, c) and thus individual in character as required by the definition of plant intelligence. But many life history characters, such as mortality, growth rate and fecundity—important components of fitness—are more dependent on the environment than the genotype (Antonovics and Primack, 1982). Thus, the perception of the genotype is changing from a blueprint that describes a single fixed outcome to a constrained repertoire of environmentally contingent and intelligent processes. The phenotype is ultimately constructed from synergistic developmental systems in which genes and gene products interact in a complex fashion with signal transduction networks, in turn directly responsive to numerous and constantly changing environmental factors (Trewavas and Mahlo, 1997).
Phenotypic plasticity enables individuals or genotypes to assume obviously different phenotypes during the life cycle (Schlichting, 1986; Sultan, 2000). Moreover, given the variety of environmental parameters and the different orders and combinations in which they occur in the wild, the potential number of distinguishable phenotypes must be enormous. Phenotypic variation can even cause substantial problems in taxonomic classification. Just as animal behaviour is constrained by genetic capabilities, so ultimate genetic constraints on phenotypic change will be present. But with plants refining their discrimination to local conditions, perhaps the enormous numbers of distinguishable phenotypes corresponds well with the number of behavioural variations available to any animal.
But plasticity indicates foresight. For plants that experience, for example, either periods of water stress or shading, morphological adaptations in the leaves improve fitness but at a cost that would not be experienced by other individuals that received adequate water or light. It is here that the capacity for intelligent behaviour must be paramount. Just as any animal will assess the totality of its sensory environment and respond, a plant will carry out the same assessment of all conditions and adjust its growth and development from that assessment. Furthermore, faced with new patterns of environmental variation, plasticity enables the individual to come up with some sort of solution first time. Those individuals that have the best behavioural solution will survive better and go on to reproduce. Further improvement by selection can be expected if the new environment remains. Repetitive and reproducible changes in the environment easily lead in turn to genetically proscribed behaviour by natural selection if the new environmental constraint is permanent.
Phenotypic plasticity is much more readily obvious in plants than in animals. Development continues throughout the plant life cycle and is thus subject to environmental influences to a greater extent. Theoretically, every plant body contains its environmental history, if that could be read.
A Darwinian mechanism for phenotypic plasticity
In mammalian brains, phenotypic plasticity underpins the process of learning and memory. Except in early development, neural cell numbers do not increase, and changes in function are provided, as already described, by changes in either number of dendrite connections or synaptic adhesion that form the adaptive neural networks essential for intelligent behaviour. It is the ability to create new computational networks that either direct the flow of information into different channels or reference previously held memories that are crucial. Once new dendrites form or decay the neural cell becomes effectively a cell with different functions. In early development, new cells with new dendrites and thus connections arising from mitosis obviously contribute, although memory may perhaps be more easily retained in non-dividing cells.
Because plants lack an obvious specific tissue for computation and because cell division/development continues throughout the life cycle, new mechanisms for computation may be required. What is suggested here is: (1) the basic elements of computation are individual cells in tissues; (2) that computational cellular networks are formed as the tissue develops, best fitted for the environmental state of the time; and (3) each individual plant (genet) accumulates tissues (ramets) with different computational capabilities, so reflecting the history of experience. Just as the process of learning in a brain could be represented as a time series, a set of snapshots of developing brain connections, in plants, each snapshot may possibly be represented by developing plasmodesmatal connections or equally, successive new tissues. So, instead of changing dendrite connections, plants form new networks by creating new tissues, a series of developing brains as it were, that can act like parallel processors each with slightly different computational capabilities. In this way, the successive plant tissues act as repositories of memory of environmental states which, if such information can be conveyed elsewhere, contribute to the whole plant assessment. Evidence for this view is very limited, but plants do abscind their leaves as conditions change and can form new and obviously different leaves in the new conditions (Addicott, 1982). It is also known that as leaves age, stomatal function weakens, thus there are leaves with varying potential on any one individual plant (Willmer and Fricker, 1996).
But how do different tissues arise from the same growing meristem, or are apical meristems identical throughout their life? Progressive changes in successive leaves are known to occur in certain plants under constant conditions of growth (Steeves and Sussex, 1972), and bud dormancy can vary according to the age and position of the bud (Gregory and Veale, 1957). Rooting of branches from some trees (e.g. Taxus) results in plants with maintenance of the same plagio-gravitropic angle of shoot growth. In others, such as Hevea, cuttings only form adventitious roots and the main tap root is not regenerated. But to explain how phenotypic plasticity arises from what is often assumed to be an identical meristem, we can borrow from an idea by Edelman (1993). He summarized evidence that indicated that connections in the brain were often very variable, although behaviour might be similar, suggesting that pre-specified point-to-point wiring did not occur. Neural territories and maps are often unique to each individual, for example. He suggested that experience selected out certain groups of neurones by chance whose original connections constructed a weak response. These networks were then reinforced by increased synaptic adhesion with additional signalling. Channels of information flow were thus deepened, improving the quality of the response. Therefore, the final neural network constructed depended initially on a kind of ‘Neural Darwinism’. The suggestion here is that the true meristem produces cells that are anatomically indistinguishable but that differ in molecular and physiological capabilities. During development, as cells leave the true meristem, environmental conditions will result in the preponderant replication of certain cells with particular physiological patterns (over others) which, in due course, give rise to phenotypic plasticity; a kind of cloning (Steeves and Sussex, 1972). Perhaps cells in the transition region between division and expansion are where selection occurs in roots (Barlow and Baluska, 2000). In the apical meristem, larger leaves might originate as the environmental conditions select cells capable of expanding longer or to a larger final size. Maybe these cells would differ in sensitivity to auxin or kinin. Self-evidently, only young, developing tissues in plants can express morphological plasticity. Examples of responses of very young tissues to ABA and cold treatment leading to different morphologies and tissues (Spirodela turions) are to be found in Smart and Trewavas (1983). Also, morphological data provided by Milthorpe (1956) indicate that young cucumber leaves of a certain age only respond to cold treatments.
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