Phenotypic Plasticity



Adrienne Nicotra


The phenotype, unlike the genotype, varies over the course of an organism’s life and depending on the environment in which the organism develops. Over the years it’s become clear that this -phenotypic plasticity’ is a characteristic that is under selection and of ecological and evolutionary significance (Nicotra, Atkinet al. 2010). Plasticity of key functional traits may determine an organism’s ability to establish(Schlichting 1986b), further, if the plasticity increases that organisms’ fitness it may enable the taxon to persist in highly variable environments or over broad niches.

All organisms possess some degree of phenotypic plasticity, but for sessile organisms like plants, plasticity may be of particular importance.


Phenotypic plasticity describes the range of phenotypes a single genotype can express as a function of its environment (Bradshaw 1965; Schlichting 1986a). In this context the term genotype refers to the complete genome of a single genetic individual, not a particular gene sequence.

Terminology and equations

Adaptive plasticity: Phenotypic plasticity that increases the global fitness of a genotype.

Fitness:the fitness of an individual is taken as the relative abundance and success of its genes (often measured as number of surviving offspring) over multiple generations. In many cases, especially with large or long-lived species direct estimates of fitness are not feasible and total biomass, seed number or biomass, survivorship or growth rates of a single generation are used as proxies.

Genotype:When we refer to a genotype here we do so in a population genetic sense, not in reference to molecular sequence of a single gene, but to the complete genome.

Phenotype: The appearance or characteristics of an organism resulting from both genetic and environmental influences. In our terms all organisms have a phenotype not just those expressing a mutation in a given gene of interest.

Phenotypic Plasticity: The range of phenotypes a single genotype can express as a function of its environment.

Measurement approaches

This section draws heavily from (Nicotra and Davidson 2010).

To assess plasticity an experimental design needs to allow quantification of the effects of environment, genotype and their interaction (G * E interaction) on the expression of a trait. The plasticity is reflected in a significant environment effect, and variation between genotypes in plasticity is exhibited by a significant G * E interaction. Note therefore that plasticity cannot be measured on only a single plant (Scheiner 2002). The treatment conditions (e.g. water supply, nutrient or light levels) used should generally be realistic in terms of amount and timing of application, and yet must differ adequately to elicit plastic responses. When aiming to predict plastic responses to novel conditions, it may be valuable to work outside the range of water availability currently experienced – to reveal the -hidden reaction norms’ of plasticity (Schlichting 2008).

Demonstrating that an observed plastic response to water is adaptive requires assessing fitness or fitness components (Caruso et al. 2006). Ideally fitness is assessed across multiple generations e.g. assessments of seed viability (Goergen and Daehler, 1992) and incorporates longevity and survival of adult plants (deFalco et al. 2003). Where measurements on offspring are not possible, assessment of reproductive output can provide useful surrogates e.g. seed weight or the number of flowers (e.g. Sans et al. 2004). For many species, especially long-lived ones, proxies of fitness such as growth rate and biomass are considered acceptable alternatives. In the case of fruit and grain crops, yield or harvest index are appropriate fitness proxies. Statistical techniques to specifically assess the adaptive value of plasticity include linear models and multiple regression analysis and selection analysis (Lande and Arnold 1983; Rausher 1992; Scheiner and Callahan 1999; Weinig, Johnstonet al. 2006).

Plasticity of any given trait can itself evolve in response to selection. Artificial selection experiments have proven informative in examining the underlying genetic mechanisms behind plasticity and in quantifying the selection potential for plasticity (see refs in Nicotra and Davidson 2010).

In addition our understanding of the molecular and genetic mechanisms underlying plasticity is increasing steadily (see Nicotra, Atkinet al. 2010; Nicotra and Davidson 2010).

Until recently the most limiting factor for the progress of plasticity studies was a lack of capacity for precise and efficient phenotyping. The emergence of high throughput phenotyping techniques hold promise for addressing this limitation (e.g. the Australian Plant Phenomics Facility

Ranges of values

There are several methods for assessing the plasticity of a trait and some effort has been made to establish normalized indices of plasticity that can be used to compare across experiments or species. These include the significance of the environment effect and G* E interaction terms in a linear model, the co-efficient of variation (CV, standard deviation/mean*100) across a set of growth environments, deriving a normalised index for the trait across the environmental range, for example (max-min)/(max+min), (for further discussion see Valladares, Gianoliet al. 2007), or the slope of the trait response to the growth environments – the reaction norm (see Schlichting and Pigliucci 1998 for a discussion of the history of the reaction norm). The theoretical reaction norm of response to water would encompass all possible water availabilities found in a species’ range, whereas in practice only a few are generally considered.

Literature References

Bradshaw AD (1965) Evolutionary significance of phenotypic plasticity in plants. Advances in Genetics 13, 115-155.

Lande R, Arnold S (1983) The measurement of selection on correlated characters. Evolution 37, 1210-1226.

Nicotra AB, Atkin OK, et al. (2010) Plant phenotypic plasticity in a changing climate. Trends in Plant Science 15(12), 684-692.

Nicotra AB, Davidson A (2010) Adaptive phenotypic plasticity and plant water use. Functional Plant Biology 37(2), 117-127.

Rausher MD (1992) The Measurement of Selection on Quantitative Traits – Biases Due to Environmental Covariances between Traits and Fitness. Evolution 46(3), 616-626.

Scheiner SM (2002) Selection experiments and the study of phenotypic plasticity. Journal of Evolutionary Biology 15(6), 889-898.

Scheiner SM, Callahan HS (1999) Measuring natural selection on phenotypic plasticity. Evolution 53(6), 1704-1713.

Schlichting CD (1986a) The evolution of phenotypic plasticity. Ann Rev Ecol Syst 17, 667-693.Schlichting CD (1986b) The Evolution of Phenotypic Plasticity in Plants. Annual Review of Ecology and Systematics 17, 667-693.

Schlichting CD (2008) Hidden reaction norms, cryptic genetic variation, and evolvability. Annals of the New York Academy of Science 1133, 187-203.

Schlichting CD, Pigliucci M (1998) ‘Phenotypic Evolution: A Reaction Norm Perspective.’ 1st edn. (Sinauer Associates: Sunderland, MA) 387

Valladares F, Gianoli E, Gomez JM (2007) Ecological limits to plant phenotypic plasticity. New Phytologist 176(4), 749-763.

Weinig C, Johnston J, German ZM, Demink LM (2006) Local and global costs of adaptive plasticity to density in Arabidopsis thaliana. American Naturalist 167(6), 826-836.

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