SEARCH

SEARCH BY CITATION

Keywords:

  • heterogeneity;
  • hierarchical selection;
  • independence;
  • integration;
  • modularity;
  • phenotypic plasticity;
  • reaction norm

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Conclusions
  5. Acknowledgements
  6. References

Based on empirical evidence from the literature we propose that, in nature, phenotypic plasticity in plants is usually expressed at a subindividual level. While reaction norms (i.e. the type and the degree of plant responses to environmental variation) are a property of genotypes, they are expressed at the level of modular subunits in most plants. We thus contend that phenotypic plasticity is not a whole-plant response, but a property of individual meristems, leaves, branches and roots, triggered by local environmental conditions. Communication and behavioural integration of interconnected modules can change the local responses in different ways: it may enhance or diminish local plastic effects, thereby increasing or decreasing the differences between integrated modules exposed to different conditions. Modular integration can also induce qualitatively different responses, which are not expressed if all modules experience the same conditions. We propose that the response of a plant to its environment is the sum of all modular responses to their local conditions plus all interaction effects that are due to integration. The local response rules to environmental variation, and the modular interaction rules may be seen as evolving traits targeted by natural selection. Following this notion, whole-plant reaction norms are an integrative by-product of modular plasticity, which has far-reaching methodological, ecological and evolutionary implications.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Conclusions
  5. Acknowledgements
  6. References

Bradshaw (1965) defined plasticity as ‘… shown by a genotype when its expression is able to be altered by environmental influences’. Phenotypic plasticity is often depicted as a norm of reaction. Norm of reaction diagrams compare the mean phenotypic values expressed by a single genotype (or closely related genotypes) under two or more environmental conditions (e.g. Via & Lande, 1985; Schlichting, 1986; Schlichting & Pigliucci, 1998). The major part of the extensive literature on the ecological and evolutionary significance of plasticity (e.g. Schmitt & Wulff, 1993; Scheiner, 1993; de Jong, 1995; Via et al., 1995; Sultan & Spencer, 2002; Pigliucci et al., 2003; Schmitt et al., 2003) implicitly assumes that functional individuals find themselves in a single environment at the time in which they express a single phenotype (but see Winn, 1996a, 1996b). In this paper, we argue that, for the plasticity of many plant traits, this may be the exception rather than the rule. We review the prevalent form of plasticity in plants as a very different phenomenon, expressed as potentially adaptive response to fine grained heterogeneity at a structural level smaller than the functional individual.

All higher plants are composed of repetitive functional units, which are produced during ontogenetic development (White, 1979; Preston & Ackerly, 2004). We will use the term module throughout this paper to refer to repeated, often semiautonomous structural and functional subunits of plants. It is important to realize that this notion of modularity differs markedly from the concept of modularity used in (animal) developmental genetics (see West-Eberhard, 2003; Preston & Ackerly, 2004). A plant individual can be seen as a collection of modular units, which are often arranged in a nested hierarchical way. Modules have their own demographic properties; each of them is born, matures, senesces and dies. The life cycle and life history of modules can often be remarkably independent from whole-plant development (Preston & Ackerly, 2004), and they take usually place on smaller time scales than whole-plant ontogenetic progression. Here we will argue that in modular organisms, not only growth and development, but also environmentally induced changes in the expression of traits (i.e. phenotypic plasticity) takes place at the level of the module.

Plastic responses are induced by spatio-temporal variation in environmental factors, such as in the availability of light, water and nutrients. Empirical evidence suggests that in many natural environments, much of this heterogeneity is expressed at a scale smaller than the zone of influence (sensuCasper et al., 2003) of the functional individual (Stark, 1994; Wilson, 2000). This is true for features of the above-ground (Baldocchi & Collineau, 1994; Ryel et al., 1994; Tang & Washitani, 1995) as well as the below-ground environment (Hook et al., 1991), implying that any single plant is likely to experience multiple environmental conditions simultaneously (Jackson & Caldwell, 1993; Stark, 1994; Wilson, 2000; Guo et al., 2002; Schimel & Bennett, 2004). The size of the plant in relation to the spatial scale of heterogeneity determines the likelihood and the average degree of within-plant variation in biotic and abiotic conditions. We argue that the phenotypic plasticity of plants is tailored to this small-scale variation and primarily expressed at the organizational level of modules. Whole-plant plasticity is the sum of all environmentally induced modular responses, plus all interaction effects that are due to communication and behavioural integration of modules.

The objective of this paper is to propose a new modular concept of phenotypic plasticity. Throughout we will focus on morphological responses at the modular level, but the concept is fully applicable to virtually all types of inducible plant responses to fine-scaled variation in habitat conditions (e.g. plasticity in physiological and biochemical traits, environmental effects on reproductive traits, including the induction of flowering). First, we briefly discuss allometric growth trajectories (i.e. developmentally programmed changes in the shape and function of modules and whole plants) and its role as null-model for plant development under (theoretically) uniform conditions. We will then discuss inducible modifications of this template as a result of local (modular) responses, induced by local microhabitat conditions. Next, we show that local responses may be modified through integration and module interactions in various ways. Finally, we discuss the implications of this modular concept of plant plasticity for empirical approaches that aim at studying the evolution of environmentally inducible variation of plant phenotypes and link it to conceptual models of hierarchical selection and microevolution in plants.

An allometric null-model for plasticity and developmental reaction norms

The shape of plants at birth diverges considerably from the shape of plants at maturity (Evans, 1972). Intrinsic, i.e. pre-programmed alterations in the quantitative relations between plant parts during development are usually referred to as allometric changes, and occur in the absence of environmental variation. For example, the relationship between height and mass is typically curvilinear, with large plants increasing proportionally more in mass than in height (Weiner, 2004). Weiner (2004) has referred to these patterns as ‘apparent plasticity’ because they are the result of a developmentally programmed growth trajectory. While allometric variation may itself be an evolutionarily dynamic trait shaped by natural selection (Preston & Ackerly, 2004), it should not be considered a component of phenotypic plasticity. Allometric changes can easily be confounded with true plasticity in studies, which involve variation in environmental conditions that affect the rate of plant development (Coleman & McConnaughay, 1995; Huber & Stuefer, 1997; Huber et al., 1999; Preston & Ackerly, 2004). If the trait is scored at a common point in time, the difference in ontogenetic stage will inevitably cause trait differences, also in the absence of direct environmentally induced effects on the trait under study (Fransen et al., 1999; Weiner, 2004). This potential confusion between plasticity and allometry can be avoided by taking plant ontogeny explicitly into account when studying putative adaptive plasticity (Huber & Stuefer, 1997; Preston & Ackerly, 2004).

Ontogenetic trajectories do not only affect the size and shape of plants, but they also alter their responses to the environment. Depending on the developmental stage of plants, the same environmental cues may trigger quantitatively and qualitatively different responses. This phenomenon, termed ‘ontogenetic contingency’ by Diggle, 1994 (see Watson et al., 1995), has been ignored for a long time and has only recently been implemented explicitly in conceptual models of phenotypic plasticity. The concept of ‘developmental reaction norms’ (DRN) developed by Schlichting & Pigliucci (1998) attempts to include the ontogenetic stage of plant individuals as one of the main axes determining the outcome of plasticity studies. The ontogenetic response schedule of plants (i.e. DRN) is a likely target of selection and a potential constraint on the expression of environmentally induced phenotypic variation (Schlichting & Pigliucci, 1998).

We propose to extend the notion of allometric trajectories, developmental reaction norms and ontogenetic contingency to modular subunits of plants and to their response to environmental conditions. Like whole plants, modules also follow pre-programmed developmental routes, which can be altered by the environment. Depending on their ontogenetic stage they are likely to express different degrees and different types of plasticity. Module size (e.g. internode or petiole elongation) and module shape (e.g. leaf shape), for instance, can only be modified during developmental phases that include growth, while plastic responses such as sun-fleck photosynthesis and inducible defences are likely to be expressed in mature modules, and they may be (partially) absent in young, developing modules. Developmental switches such as decisions about the fate of meristems (vegetative or generative) are plastic responses, which can only be expressed during the earliest stages of module differentiation. Even though little is known about allometries and developmental reaction norms at the modular level, each type of inducible response is likely to have a specific ontogenetic window, outside which it can not, or can not optimally, be expressed.

Phenotypic plasticity as a local modular response

Above- and below-ground modules of plants may deviate from the intrinsic null-model of allometric development by responding plastically to the local conditions that they experience. The expression of local plastic responses implies that modules perceiving environmental cues also process them locally and produce an appropriate inducible response. The local stimulation of root branching by soil patches of high nutrition is an example of local modular plasticity. Drew and co-workers were the first to experimentally demonstrate that lateral roots branch more profusely and grow faster in soil compartments with high nutrient concentrations compared to roots exposed to low soil nitrate or phosphate content (Drew et al., 1973; Drew, 1975). A great number of studies have demonstrated that many plant species exhibit selective placement of roots into nutrient-rich spots within their zone of influence (reviewed by Robinson, 1994; Hodge, 2004). Due to such localized plastic responses in the root system, plants grow equally well or even better when similar amounts of nutrients are supplied heterogeneously rather than homogeneously (e.g. Birch & Hutchings, 1994; Fransen et al., 1998).

Localised modular responses have also been described for trees. More and larger buds develop on branches in sunny patches than on branches in shaded patches (Jones & Harper, 1987; Sprugel et al., 1991; Stoll & Schmid, 1998), resulting in the well-known crown-asymmetry of trees at forest edges or near gaps (Harper, 1985; Young & Hubbell, 1991). Moreover, shaded branches of trees are likely to develop leaves with morphological and physiological properties that enhance light capture and photosynthetic efficiency under low light conditions. Shade leaves typically develop independently from sun leaves, which may be formed on branches of the same tree that experience better light conditions. Sprugel et al. (1991) argued that branch independence contributes to the efficiency of light foraging because little resource is invested in building leaves and branches in shaded areas.

The shade–avoidance syndrome of plants in which stems or stem analogues increase in length in response to low red to far-red ratio and other shade signals is perhaps the best studied example of phenotypic plasticity in plants (e.g. Schmitt & Wulff, 1993; Smith & Whitelam, 1997; Schmitt et al., 2003; Pierik et al., 2004). However, few studies appreciate that the light regime is in fact detected, and the responses expressed, at an organizational level smaller than the individual. Studies by Thompson (1993) have shown that information about the spectral composition of light can be perceived at a modular level and that local light cues trigger local plastic responses. Single nodes of shaded Trifolium repens plants were illuminated by small red light emitting diodes, which significantly increased the local red : far-red ratio at the node and the base of its petiole (Fig. 1a). The shaded plants produced long petioles and supplementary red light significantly reduced the petiole length. This effect was strongest at the illuminated node and declined along the main stolon with increasing distance to the light treated node (Fig. 1b). These results indicate that the light regime may be detected, and the morphological response expressed, at a scale of a single node and its leaf. By covering either the node or the petiole tip with opaque paint, Thompson (1995) subsequently showed that radiation received at the petiole tip altered petiole elongation but did not affect stolon internode length or stolon branching. Other studies with clonal plants confirm the findings that petiole elongation is mostly responsive to the local light regime (Dong, 1993; Robin et al., 1994a,b). We conclude that the shade-avoidance response is induced by local cues and it is realized by local responses of plant parts.

image

Figure 1. Effects of localised shading on petiole elongation in Trifolium repens. (a) The position of illumination by red light emitting diodes (LED). A very narrow angle of radiation (30°) ensured that only a single node on a plant was irradiated. (b) The effects of shading (•), shading with a red supplement (▪), and shading with a bright red supplement (▴) on elongation of the petiole at the illuminated node (#1) and three petioles at nodes acropetally to the illuminated node. ‘Bright’ red LEDs had a greater concentration of total output in the red waveband than red light emitting diodes. LSD bars are shown for P = 0.05. Adapted from Thompson (1993); reproduced by permission of Blackwell Publishing.

Download figure to PowerPoint

Integration: modulation of local plastic responses

An implication of small-scale heterogeneity expressed within the zone-of-influence of an individual is that modules of a single plant are very likely to be simultaneously exposed to a variety of conditions. Notwithstanding its localised nature, the response of modules may significantly be altered, both quantitatively and qualitatively, by interactive effects with other connected modules that experience different conditions. Integration may essentially result in three types of possible modifications. First, local responses to environmental quality may be enhanced by module interactions. Second, the response may be averaged-out or quantitatively weakened. Third, module integration may qualitatively alter local plastic responses by inducing a novel response, which is not expressed in the absence of among-module variation in the inducing cue. The examples in the following paragraphs are mainly drawn from the literature on clonal plants. There is a long tradition of studies with clonal plants on integration effects, probably because modular plasticity is often very conspicuous and relatively easy to study in spatially extensive clonal networks. However, current evidence suggests that localized plastic responses and modular interactions in the expression of plasticity are equally prevalent in nonclonal plants.

The responses of internode length to variation in light availability in clonal species serve as examples of how module integration can alter local plastic effects. In the experimental study by Evans & Cain (1995) internode length in Hydrocotyle bonariensis was not significantly different for plants of the same genotype growing in control trays without grass (high light conditions) and in trays covered uniformly with grass (shaded conditions; Fig. 2). The results of this set of treatments, as is common practice in plasticity studies, would lead to the conclusion that internode distance is a nonplastic trait in H. bonariensis. However, in an additional treatment simulating environmental heterogeneity in light conditions, internodes of the target species were significantly longer if they were formed in the grass patches rather than in the open areas (Fig. 2). This implies that module integration has triggered the expression of a plastic response that was absent in treatments providing homogeneous resource conditions. Similarly, nonresponsive internode lengths in the stoloniferous herb Ranunculus repens measured in experimental shading studies (Lovett Doust, 1987; Huber et al., 1998) contrast with significant plastic responses in the field where plants of the same species were exposed to heterogeneous light conditions (Waite, 1994). These results not only support the notion of plasticity as a local response that is modifiable by module integration, but they also challenge the validity of conclusions based on experimental studies that assume plasticity to be a whole-plant response to coarse-grained habitat heterogeneity.

image

Figure 2. Plasticity in internode distance (i.e. internode length) in Hydrocotyle bonariensis. Small clonal fragments were grown in trays in one out of three treatments: without grass (‘no grass’), with grass (Cynodon dactylon) grown across the entire tray (‘full grass’), or with grass grown in eight regularly spaced patches (‘patchy grass’). Bars indicate means for internode distance (± se) in the three treatments. IN and OUT refer to internode distances within and outside the grass patches, respectively, for the patchy grass treatment. Adapted from Evans & Cain (1995); reproduced by permission of the Ecological Society of America.

Download figure to PowerPoint

Dong (1995) subjected individuals of the two clonal herbs Hydrocotyle vulgaris and Lamiastrum galeobdolon to a split light treatment in which the primary stolons were growing along the border of two different light conditions (high and low light; Fig. 3), and compared the morphology of the secondary stolons produced in this heterogeneity treatment with stolons formed under uniformly high and low light conditions. As expected, stolon internodes and petioles were longer, and leaf areas were larger in plants raised at low as compared to high light conditions (Fig. 3). However, in H. vulgaris, all phenotypic values except internode length tended to increase in the heterogeneous compared to the homogeneous treatments (Fig. 3). By contrast, integration in L. galeobdolon resulted in an averaging of the responses. Differences in specific leaf area between the two light treatments even disappeared completely in this species when plants were grown in the split treatment (Fig. 3). Dong (1995) suggested that an enhancement of the local response may improve the ability to forage for light in the open habitats in which H. vulgaris occurs, while a more equal performance of all ramets might be more profitable in the shaded habitats of L. galeobdolon.

image

Figure 3. Plasticity in: (a) petiole length, (b) lamina (i.e. leaf) area, and (c) specific leaf area (SLA) in Hydrocotyle vulgaris and Lamium galeobdolon. Primary stolons were grown at the border between two patches, separating shade cages with 23% (L23) or 70% (L70) of daylight. Note that Hydrocotyle forms one and Lamiastrum two secondary branches per node. Values shown are means (± se) for ramets at the secondary stolons only. After Dong (1995).

Download figure to PowerPoint

Effects of module integration on plasticity are also apparent in roots (Hutchings & de Kroon, 1994; Robinson, 1994) and in the responses of trees and annual species to environmental variation. Stoll & Schmid (1998) studied the growth and architecture of branches on mature Pinus sylvestris trees at the edge and in the centre of a forest. Sun-lit branches at the forest edge showed larger growth increments, more lateral branches, higher survival and reproduction than shaded branches. Surprisingly however, shaded branches of edge trees had fewer lateral branches and shorter growth increments than shaded branches of central trees, resulting in a lower needle dry mass per branch, in spite of more favourable light conditions at the forest edge (Fig. 4). Sprugel (2002) lists a number of studies on trees in which shaded or otherwise stressed tree branches are suppressed when connected to unshaded (or unstressed) branches. Similar effects of integration have been described for responses of shoot branches in annuals. Sachs & Novoplansky (1997) review a number of studies with pea plants in which different branches were exposed to contrasting environmental conditions. For example, if one of the branches of a two-branched pea plant was placed in the dark it started to elongate its internodes, but only if the other branch was cut. If the other branch was intact and in the light, the darkened branch was suppressed and likely to die.

image

Figure 4. Correlative inhibition in Pinus sylvestris. Total needle dry mass (mean ± se; n = 4) for sun branches (open symbols) and shade branches (closed symbols) of trees at the edge of a forest patch. The two middle lines are the mean values for four control branches of trees in the centre of the forest patch. Needle mass includes all orders of needles from the completely sampled branch tips. Trees around the patch were cut in 1989. Adapted from Stoll & Schmid (1998); reproduced by permission of Blackwell Publishing.

Download figure to PowerPoint

A marked example for modular integration specific for clonal plants is given by the phenomenon referred to as ‘spatial division of labour’ (Stuefer et al., 1996; Alpert & Stuefer, 1997; Hutchings & Wijesinghe, 1997; Stuefer, 1998). If some ramets of a clonal plant grow in a microsite with a high light and low water availability, and other interconnected ramets experience complementary resource conditions (i.e. low light and high water supply), the two ramet groups can specialise morphologically for the uptake of the locally most abundant resource, and exchange local surplus resources in a bi-directional way. Specialising ramets produce relatively more roots where the availability of water is high, and relatively more leaf tissue where there is more light (i.e. specialisation for abundance; Stuefer et al., 1994, 1996; de Kroon et al., 1996, see Fig. 5). By contrast, if all ramets are subjected to the same resource conditions, they exhibit the classical root-shoot allocation response by maximizing allocation to the organs that acquire the most limiting resource (i.e. specialisation for scarcity; Stuefer et al., 1996; Alpert & Stuefer, 1997; Hutchings & Wijesinghe, 1997; Stuefer, 1998, see Fig. 5). Due to local specialisation and bidirectional resource exchange, plants growing under heterogeneous conditions produced about 70% more biomass and clonal offspring than plants growing under uniform resource conditions (Stuefer et al., 1994, 1996). Division of labour can be seen as an extreme example for subindividual plasticity, which is qualitatively changed by the interaction of modules exposed to complementary resource supply.

image

Figure 5. Spatial division of labour in the stoloniferous herb Trifolium repens. Two interconnected clone parts (I and II, respectively) were grown in different combinations of light and water availability. L+ and L− refer to high and low light availability, and W+ and W− to high and low water availability, respectively. The graphs show mean root-mass-ratios (i.e. percentage biomass allocation to roots, ± se) in two spatially heterogeneous treatments (black bars) and two homogeneous treatments (grey bars). Bars with the same letter represent clone parts that were interconnected. Thus, in the heterogeneous treatments, one clone part under L+W− was connected to the other part under L−W+. After Stuefer et al. (1996).

Download figure to PowerPoint

Ecological consequences and evolutionary implications

We postulate that, in nature, phenotypic plasticity in plants is expressed at a modular level within the individual, i.e. that individual meristems, leaves, branches and roots respond to changes and differences in local environmental conditions. Whole-plant plasticity is the sum of all modular responses triggered by local environmental conditions plus all interaction effects that are due to communication and behavioural integration of modules. Recognizing the modular nature of plasticity has important ecological and evolutionary consequences, as well as implications for the nature of constraints operating on the expression of plasticity.

The interplay between habitat heterogeneity and plant plasticity is determined by the spatio-temporal scale of environmental variation relative to the spatial and temporal scale of modular responses (Stuefer, 1996; Ackerly, 1997). Plants can track and exploit resource-rich patches above and below ground through morphological plasticity of resource capturing organs. Such responses are beneficial if, and only if, the resource-rich patch lasts longer than the minimum response time of the resource capturing modules (Ackerly, 1997), and if these resource-capturing modules are in a developmental state that allows for morphological change. Environmental variation at a very small temporal scale such as understory sun flecks or ephemeral nutrient pulses can not usually be tracked by morphological plasticity. Localized physiological responses (such as light fleck photosynthesis and enhanced nutrient uptake kinetics) are then used to exploit environmental heterogeneity (Chazdon & Pearcy, 1991; Hutchings & de Kroon, 1994).

It has been hypothesized that under conditions of relatively long-lasting patches, integration effects that enhance the morphological response will increase foraging efficiency by reducing the placement of modules in areas of low resource availability (de Kroon & Schieving, 1990; Birch & Hutchings, 1994; Sprugel, 2002). Our examples suggest indeed that local responses and module integration may act in concert to increase total resource uptake and whole plant performance. The benefits of environmental tracking through modular plasticity above and below ground depend largely on the spatio-temporal match between resource distribution and plastic module responses, and on the pattern and frequency with which relevant environmental variation occurs in the natural habitat of a species (Huber et al., 2004). Depending on the conditions, strictly local or highly integrated responses of modules will be favoured. However, critical assessments of the costs and benefits of modular plasticity in different species and different environments are largely lacking.

The modular concept of plasticity has implications for the measurement and visualisation of plasticity. The commonly used reaction norm approach to study plasticity originates from classical research on unitary organisms such as Drosophila (Schlichting & Pigliucci, 1998), and does therefore not take into account the modular organization of plants. Plotting the response of genetic individuals (whole plants) to different environmental conditions is an illustrative and useful method if: (i) the relevant environmental variation occurs at the scale of the individual; and (ii) if all the modular subunits of a functional individual perceive and respond uniformly to environmental variation. Both of these conditions are not commonly met by plants, as argued in previous sections. Even though reaction norms (i.e. the sum of all rules on how to respond to environmental variation) are a property of genotypes, they are expressed at the level of semiautonomous modular units, and their expression is likely to vary among modules (Preston & Ackerly, 2004).

While many studies document modular responses in norm of reaction diagrams, these are implicitly extrapolated to responses of the whole plant. If we accept that plasticity is expressed at a modular level, and modular response and communication rules are the primary targets of natural selection on plasticity, we should aim at measuring intraplant variation in relation to local habitat conditions, rather than viewing this variation as undesirable noise blurring our estimates of elusive whole-plant plasticities. Studying trait variation and co-variation at a subindividual level may provide crucial insight into the expression of variable phenotypes within individuals, which may itself be an adaptive, evolving strategy (Preston & Ackerly, 2004). In addition, such an approach can elucidate the type and degree of selection pressures operating on module interactions, which have been studied in some detail for floral development but not for whole plant responses to environmental variation (Preston & Ackerly, 2004). Since many (if not all) plant traits of primary importance for fitness are expressed at the modular level, selection is likely to favour genotypes with module response and interaction rules that fit best the prevailing conditions in the natural environment of the plant. In this way these rules can evolve as traits of individual genotypes.

In addition to studying trait variation and co-variation at the modular level, future research efforts should be directed specifically to investigating the within-plant topology of environmentally inducible gene expression involved in the production of plastic responses. In spite of remarkable technical capabilities to explore gene expression patterns in time and in space, little effort has been made so far to acquire specific information on within-plant compartmentalization of signal perception, between-module signal transduction (communication) and subsequent gene expression within plants exposed to fine-grained heterogeneity in environmental conditions. The shade–avoidance syndrome (Smith, 2000; Casal et al., 2004) and inducible systemic resistance to herbivores and pathogens (Kessler & Baldwin, 2002; Katagiri, 2004; Pieterse & Van Loon, 2004) may provide useful model systems to unravel the modular molecular nature of plant phenotypic plasticity.

It follows from the discussion above that selection on whole-plant plastic responses seems unlikely if not impossible due to the lack of central control and given the functional (semi)independence of plant structures. Hence we suggest that modular plasticity, the ontogenetic window of plasticity, and the spatio-temporal extent of module communication, are evolving traits under selection. Future studies should specifically address genetic variation, environmental effects, and genotype–environment interactions for these traits and relate them to fitness consequences in different environments. The study of intraplant variation in phenotypically plastic traits for different genotypes, species and environments will help elucidate the evolutionary dynamics of what appears to be the functional basis of all plant plasticity.

The modular concept of plasticity proposed here, with modular subunits rather than genetic individuals as the main players in the interaction between genotype and environment, calls for the explicit inclusion of hierarchical selection arguments into conceptual models and empirical studies on the evolution of plant plasticity (Tuomi & Vuorisalo, 1989; Pedersen & Tuomi, 1995). The net benefits (or costs) of plastic responses manifest themselves in the fitness of genetic individuals. Genets are replicators (sensuTuomi & Vuorisalo, 1989), which translate fitness effects into allele frequencies in populations. However, in contrast to unitary organisms, genetic individuals of modular organisms are not themselves ecological interactors (sensuTuomi & Vuorisalo, 1989), but they consist of numerous subunits, which react in an autonomous or integrative way to environmental variation, thereby codetermining the fitness of the genet. Current models on phenotypic plasticity in plants may have to be adjusted to explicitly include localized, hierarchical responses to environmental variation, which translate into fitness gains (or losses).

Conclusions

  1. Top of page
  2. Summary
  3. Introduction
  4. Conclusions
  5. Acknowledgements
  6. References

The modular concept of plant plasticity proposed here emphasizes the central ecological and evolutionary role of module response rules and module interaction rules, and their dependence on the ontogenetic and environmental context within which they operate. The fitness of a modular organism is determined by the sum of fitness-enhancing and fitness-reducing effects at the organizational level of individual modules and groups of interacting modules (Haukioja, 1991). The notion of plants as populations of semiautonomous, interactive modules was proposed 25 years ago (White, 1979), and the call for including hierarchical selection arguments into the conceptual models of plant evolutionary ecology has been launched in the past (Tuomi & Vuorisalo, 1989). Nevertheless, the majority of past and current research on plant plasticity ignores the fact that modules, and not individuals, perceive environmental signals and respond to them, either in an autonomous or an integrative way. Paraphrasing Haukioja's (1991) statement that ‘a tree is not a tightly integrated organism but a by-product of its parts’, we propose that plasticity of whole plants is a by-product of modular responses, shaped by hierarchical selection.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Conclusions
  5. Acknowledgements
  6. References

We are grateful to Maxine A. Watson for sharing her scientific interests and friendship over many years. Her ideas on modularity have been a source of inspiration for this paper. We thank Jacob Weiner and Ronald Pierik for discussion and valuable comments to earlier drafts.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Conclusions
  5. Acknowledgements
  6. References
  • Ackerly D. 1997. Allocation, leaf display, and growth in fluctuating light environments. In: BazzazFA, GraceJ, eds. Plant Resource Allocation. New York: Academic Press, 231264.
  • Alpert P, Stuefer JF. 1997. Division of labour in clonal plants. In: De KroonH, Van GroenendaelJ, eds. The Ecology and Evolution of Clonal Plants. Leiden, the Netherlands: Backhuys Publishers, 137154.
  • Baldocchi D, Collineau S. 1994. The physical nature of solar radiation in heterogeneous canopies: spatial and temporal attributes. In: CaldwellMM, PearcyRW, eds. Exploitation of Environmental Heterogeneity by Plants. Ecophysiological Processes Above- and Belowground. San Diego, USA: Academic Press, 2171.
  • Birch CPD, Hutchings MJ. 1994. Exploitation of patchily distributed soil resources by the clonal herb Glechoma hederaceae. Journal of Ecology 82: 653664.
  • Bradshaw AD. 1965. Evolutionary significance of phenotypic plasticity in plants. Advances in Genetics 13: 115155.
  • Casal JJ, Fankhauser C, Coupland G, Blazquez MA. 2004. Signalling for developmental plasticity. Trends in Plant Science 9: 309314.
  • Casper BB, Schenk HJ, Jackson RB. 2003. Defining a plant's belowground zone of influence. Ecology 84: 23132321.
  • Chazdon RL, Pearcy RW. 1991. The importance of sunflecks for forest understorey plants. Bioscience 41: 760766.
  • Coleman JS, McConnaughay KDM. 1995. A non-functional interpretation of a classical optimal-partitioning example. Functional Ecology 9: 951954.
  • Diggle PK. 1994. The expression of andromonoecy in Solanum hirtum (Solanaceae) – phenotypic plasticity and ontogenetic contingency. American Journal of Botany 81: 13541365.
  • Dong M. 1993. Morphological plasticity of the clonal herb Lamiastrum galeobdolon (L.) Ehrend. & Polatschek in response to partial shading. New Phytologist 124: 291300.
  • Dong M. 1995. Morphological responses to local light conditions in clonal herbs from contrasting habitats, and their modification due to physiological integration. Oecologia 101: 282288.
  • Drew MC. 1975. Comparison of the effects of a localized supply of phosphate, nitrate, ammonium and potassium on the growth of the seminal root system, and the shoot, in barley. New Phytologist 75: 479490.
  • Drew MC, Saker LR, Ashley TW. 1973. Nutrient supply and the growth of the seminal root system in barley. I. The effect of nitrate concentration on the growth of axies and laterals. Journal of Experimental Botany 24: 11891202.
  • Evans CG. 1972. The Qualitative Analysis of Plant Growth. Oxford, UK: Blackwell Scientific Publications.
  • Evans JP, Cain ML. 1995. A spatially explicit test of foraging behavior in a clonal plant. Ecology 76: 11471155.
  • Fransen B, De Kroon H, Berendse F. 1998. Root morphological plasticity and nutrient acquisition of perennial grass species from habitats of different nutrient availability. Oecologia 115: 351358.
  • Fransen B, De Kroon H, De Kovel C, Van Den Bosch F. 1999. Disentangling the effects of selective root placement and inherent growth rate on plant biomass accumulation in heterogeneous environments: a modelling study. Annals of Botany 84: 305311.
  • Guo D, Mou P, Jones RH, Mitchell RJ. 2002. Temporal changes in spatial patterns of soil moisture following disturbance: an experimental approach. Journal of Ecology 90: 338347.
  • Harper JL. 1985. Modules, branches and the capture of resources. In: JacksonJBC, BussLW, CookRE, eds. Population Biology and Evolution of Clonal Organisms. New Haven, USA: Yale University Press, 133.
  • Haukioja E. 1991. The influence of grazing on the evolution, morphology and physiology of plants as modular organisms. Philosophical Transactions of the Royal Society of London Series B -Biology Sciences 333: 241247.
  • Hodge A. 2004. The plastic plant: root responses to heterogeneous supplies of nutrients. New Phytologist 162: 924.
  • Hook PB, Burke IC, Lauenroth WK. 1991. Heterogeneity of soil and plant N and C associated with individual plants and openings in North American shortgrass priarie. Plant and Soil 138: 247256.
  • Huber H, Fijan A, During HJ. 1998. A comparative study of spacer plasticity in erect and stoloniferous herbs. Oikos 81: 576586.
  • Huber H, Kane NC, Heschel MS, Von Wettberg EJ, Banta J, Leuck AM, Schmitt J. 2004. Frequency and microenvironmental pattern of selection on plastic shade-avoidance traits in a natural population of Impatiens capensis. American Naturalist 163: 548563.
  • Huber H, Lukacs S, Watson MA. 1999. Spatial structure of stoloniferous herbs: an interplay between structural blue-print, ontogeny and phenotypic plasticity. Plant Ecology 141: 107115.
  • Huber H, Stuefer JF. 1997. Shade induced changes in the branching pattern of a stoloniferous herb: functional response or allometric effect? Oecologia 110: 478486.
  • Hutchings MJ, De Kroon H. 1994. Foraging in plants: the role of morphological plasticity in resource acquisition. Advances in Ecological Research 25: 159238.
  • Hutchings MJ, Wijesinghe DK. 1997. Patchy habitats, division of labour and growth dividends in clonal plants. Trends in Ecology and Evolution 12: 390394.
  • Jackson RB, Caldwell MM. 1993. The scale of nutrient heterogeneity around individual plants and its quantification with geostatistics. Ecology 74: 612614.
  • Jones M. Harper JL. 1987. The influence of neighbours on the growth of trees. I. The demography of buds in Betula pendula. Proceedings of the Royal Society of London, Series B 232: 118.
  • De Jong G. 1995. Phenotypic plasticity as a product of selection in a variable environment. American Naturalist 145: 493512.
  • Katagiri F. 2004. A global view of defense gene expression regulation – a highly interconnected signaling network. Current Opinion in Plant Biology 7: 506511.
  • Kessler A, Baldwin IT. 2002. Plant responses to insect herbivory: The emerging molecular analysis. Annual Review of Plant Biology 53: 299328.
  • De Kroon H, Fransen B, Van Rheenen JWA, Van Dijk A, Kreulen R. 1996. High levels of inter-ramet water translocation in two rhizomatous Carex species, as quantified by deuterium labelling. Oecologia 106: 7384.
  • De Kroon H, Schieving F. 1990. Resource partitioning in relation to clonal growth strategy. In: Van GroenendaelJ, De KroonH, eds. Clonal Growth in Plants – Regulation and Function. The. Hague, the Netherlands: SPB Academic Publishing, 113130.
  • Lovett Doust L. 1987. Population-dynamics and local specialization in a clonal perennial (Ranunculus repens). 3. Responses to light and nutrient supply. Journal of Ecology 75: 555568.
  • Pedersen B, Tuomi J. 1995. Hierarchical selection and fitness in modular and clonal organisms. Oikos 73: 167180.
  • Pierik R, Whitelam GC, Voesenek LACJ, De Kroon H, Visser EJW. 2004. Canopy studies on ethylene-insensitive tobacco identify ethylene as a novel element in blue light and plant-plant signalling. Plant Journal 38: 310319.
  • Pieterse CM, Van Loon L. 2004. NPR1: the spider in the web of induced resistance signaling pathways. Current Opinion in Plant Biology 7: 456464.
  • Pigliucci M, Pollard H, Cruzan MB. 2003. Comparative studies of evolutionary responses to light environments in Arabidopsis. American Naturalist 161: 6882.
  • Preston KA, Ackerly DD. 2004. Allometry and evolution in modular organisms. In: PigliucciM, PrestonKA, eds. Modularity and Phenotypic Complexity. Oxford, UK: Oxford University Press, 80106.
  • Robin C, Hay MJM, Newton PCD. 1994a. Effect of light quality (red: far-red ratio) and defoliation treatments applied at a single phytomer on axillary bud outgrowth in Trifolium repens L. Oecologia 100: 236242.
  • Robin C, Hay MJM, Newton PCD, Greer DH. 1994b. Effect of light quality (red: far-red ratio) at the apical bud of the main stolon on morphogenesis of Trifolium repens L. Annals of Botany 74: 119123.
  • Robinson D. 1994. The responses of plants to non-uniform supplies of nutrients. New Phytologist 127: 635674.
  • Ryel RJ, Beyschlag W, Caldwell MM. 1994. Light field heterogeneity among tussock grasses: Theoretical considerations of light harvesting and seedling establishment in tussocks and uniform tiller distributions. Oecologia 98: 241246.
  • Sachs T, Novoplansky A. 1997. What does aclonal organization suggest concerning clonal plants? In: De KroonH, Van GroenendaelJ, eds. The Ecology and Evolution of Clonal Plants. Leiden, the Netherlands: Backhuys Publishers, 5577.
  • Scheiner SM. 1993. Genetics and evolution of phenotypic plasticity. Annual Review of Ecology and Systematics 24: 3568.
  • Schimel JP, Bennett J. 2004. Nitrogen mineralization: Challenges of a changing paradigm. Ecology 85: 591602.
  • Schlichting CD. 1986. The evolution of phenotypic plasticity in plants. Annual Review of Ecology and Systematics 17: 667693.
  • Schlichting CD, Pigliucci M. 1998. Phenotypic Evolution: a Reaction Norm Perspective. Sunderland, USA: Sinauer.
  • Schmitt J, Stinchcombe JR, Heschel MS, Huber H. 2003. The adaptive evolution of plasticity: Phytochrome-mediated shade avoidance responses. Integrative and Comparative Biology 43: 459469.
  • Schmitt J, Wulff RD. 1993. Light spectral quality, phytochrome and plant competition. Trends in Ecology and Evolution 8: 4751.
  • Smith H. 2000. Phytochromes and light signal perception by plants – an emerging synthesis. Nature 407: 585591.
  • Smith H, Whitelam GC. 1997. The shade avoidance syndrome: multiple responses mediated by multiple phytochromes. Plant, Cell & Environment 20: 840844.
  • Sprugel DG. 2002. When branch autonomy fails: Milton's Law of resource availability and allocation. Tree Physiology 22: 11191124.
  • Sprugel DG, Hinckley TM, Schaap W. 1991. The theory and practice of branch autonomy. Annual Review of Ecology and Systematics 22: 309334.
  • Stark JM. 1994. Causes of soil heterogeneity at different scales. In: CaldwellMM, PearcyRW, eds. Exploitation of Environmental Heterogeneity by Plants. Ecophysiological Processes Above- and Belowground. San Diego, USA: Academic Press, 255284.
  • Stoll P, Schmid B. 1998. Architecture, biomass allocation, and bud demography of Pinus sylvestris branches in heterogeneous light environments. Journal of Ecology 86: 934945.
  • Stuefer JF. 1996. Potential and limitations of current concepts regarding the response of clonal plants to environmental heterogeneity. Vegetatio 127: 5570.
  • Stuefer JF. 1998. Two types of division of labour in clonal plants: benefits, costs and constraints. Perspectives in Plant Ecology Evolution and Systematics 1: 4760.
  • Stuefer JF, De Kroon H, During HJ. 1996. Exploitation of environmental heterogeneity by spatial division of labour in a clonal plant. Functional Ecology 10: 328334.
  • Stuefer JF, During HJ, De Kroon H. 1994. High benefits of clonal integration in two stoloniferous species, in response to heterogeneous light conditions. Journal of Ecology 82: 511518.
  • Sultan SE, Spencer HG. 2002. Metapopulation structure favors plasticity over local adaptation. American Naturalist 160: 271283.
  • Tang YH, Washitani I. 1995. Characteristics of small-scale heterogeneity in light availability within a Miscanthus sinensis canopy. Ecological Research 10: 189197.
  • Thompson L. 1993. The influence of the radiation environment around the node on morphogenesis and growth of white clover (Trifolium repens). Grass and Forage Science 48: 271278.
  • Thompson L. 1995. Sites of photoperception in white clover. Grass and Forage Science 50: 259262.
  • Tuomi J, Vuorisalo T. 1989. Hierarchical selection in modular organisms. Trends in Ecology and Evolution 4: 209213.
  • Via S, Gomulkiewicz R, De Jong G, Scheiner SM, Schlichting CD, Van Tienderen PH. 1995. Adaptive phenotypic plasticity: Consensus and controversy. Trends in Ecology and Evolution 10: 212217.
  • Via S, Lande R. 1985. Genotype–environment interaction and the evolution of phenotypic plasticity. Evolution 39: 505522.
  • Waite S. 1994. Field evidence of plastic growth responses to habitat heterogeneity in the clonal herb Ranunculus repens. Ecological Research 9: 311316.
  • Watson MA, Geber MA, Jones CS. 1995. Ontogenetic contingency and the expression of plant plasticity. Trends in Ecology and Evolution 10: 474475.
  • Weiner J. 2004. Allocation, plasticity, and allometry in plants. Perspectives in Plant Ecology Evolution and Systematics 6: 207215.
  • West-Eberhard MJ. 2003. Developmental Plasticity and Evolution. New York, USA: Oxford University Press.
  • White J. 1979. The plant as a metapopulation. Annual Review of Ecology and Systematics 10: 109145.
  • Wilson SD. 2000. Heterogeneity, diversity and scale in plant communities. In: HutchingsMJ, JohnEA, StewartAJA, eds. The Ecological Consequences of Environmental Heterogeneity. Oxford, UK: Blackwell, 5369.
  • Winn AA. 1996a. Adaptation to fine-grained environmental variation: An analysis of within-individual leaf variation in an annual plant. Evolution 50: 11111118.
  • Winn AA. 1996b. The contributions of programmed developmental change and phenotypic plasticity to within-individual variation in leaf traits in Dicerandra linearifolia. Journal of Evolutionary Biology 9: 737752.
  • Young TP, Hubbell SP. 1991. Crown asymmetry, treefalls, and repeat disturbance of tropical forest gaps. Ecology 72: 14641471.