Quantitative estimation of phenotypic plasticity: bridging the gap between the evolutionary concept and its ecological applications

Summary Global change and emerging concepts in ecology and evolution are leading to a growing interest in phenotypic plasticity (PP), the environmentally contingent trait expression observed in a given genotype. The need to quantify PP in a simple manner in comparative ecological studies has resulted in the prevalence of various indices instead of the classic approaches, i.e. a comparison of slopes in the norms of reactions (trait vs. environment plots). The objectives of this study were: (i) to review the most common methods for quantitative estimation of PP; (ii) to apply them to a specific case study of growth and shoot–root allocation responses to irradiance in seedlings of four woody species grown at 1%, 6%, 20% and 100% full sunlight; and (iii) to propose new methods of estimating PP. The 17 different plasticity indices analysed rendered disparate results, with cross‐overs in species PP rankings. Statistical comparisons of PP among species were not possible with most of the indices due to the lack of confidence intervals. The non‐linear responses of the traits made the use of the slope of the reaction norm to quantify PP unrealistic, and raised awareness on values derived from studies that consider just two environments. We propose an alternative approach to quantify PP based on phenotypic distances among individuals of a given species exposed to different environments, which is summarized in a relative distance plasticity index (RDPI) that allows for statistical comparisons of PP between species (or populations within species). RDPI was significantly correlated with 12 out of the 17 PP indices analysed. An index including the environmental range leading to the different phenotypes (environmentally standardized plasticity index, ESPI), and thus expressing plasticity per unit of environmental change, is also proposed. The new indexes can statistically segregate and unambiguously rank species according to their PP, which can foster a better understanding of plant ecology and evolution, particularly when common protocols are used by different investigators.