Quantifying phenotypic plasticity: A call for consistency

In our 2025 Functional Ecology perspective, we argue that the explosive growth of phenotypic plasticity studies has not been matched by a comparable standardization of how plasticity is quantified. Although we all agree that plasticity is the ability of a genotype to express different phenotypes across environments, we show that researchers still diverge widely in practice, often treating plasticity as a vague property of organisms or species rather than a measurable attribute of specific traits.

Our central proposal is to recover a strictly trait‑ and genotype‑based view of plasticity, operationalized through reaction norms fitted with mixed‑effects models. We distinguish clearly between genotype‑implicit and genotype‑explicit approaches, emphasizing that only designs that track identifiable genotypes (clones, inbred lines, sibships, etc.) can meaningfully address G×E interactions and the evolutionary potential of plasticity. Our survey of recent literature reveals that barely half of the studies published between 2022 and 2024 explicitly control for genotype, which severely limits what we can infer about how plasticity evolves.

(a)Traditionally, plasticity is assessed using different individual sof the same genotype facing different environments.Thistype of plasticity is common for developmentally plastic traits. The finest level of analysis of plasticity here is the genotype. (b) Plasticity can be expressed when the same individuals face different environments and change the expression of a labile trait (within-individual plasticity). (c) In modular organisms, within-individual plasticity can emerge when different modules confront different environments. In this case, within- individual plasticity can occur not only for labile traits but also for developmentally plastic traits. (d) Plasticity can also occur in modular organisms when the same module faces different environments. Within-module plasticity will affect labile traits. Icons modified from vecta.io.

We also differentiate between environment‑implicit indices, based on qualitative contrasts among treatments, and environment‑explicit estimates, which quantify plasticity as the slope of a reaction norm across measured environmental gradients. Using simple simulations, we show that environment‑explicit metrics are less biased and more sensitive to the magnitude of environmental change than widely used indices such as RDPI. Building on this, we outline a hierarchy of mixed‑model tools to analyse increasingly complex situations: from basic reaction norms to within‑individual and within‑module plasticity, polyphenic traits with sigmoidal responses, and multidimensional plasticity involving multiple environmental drivers.

Rather than presenting this as the only possible route, we advocate this mixed‑model, reaction‑norm framework as a coherent, statistically robust baseline that can help the community compare results across systems. By treating plasticity explicitly as a trait property embedded in G×E structure, we aim to clarify conceptual debates and make empirical estimates of plasticity more interpretable and evolutionarily meaningful.

More information:
Gómez JM, Perfectti F, González Megías A, Armas C. 2025. Quantifying phenotypic plasticity: A call for consistency Functional Ecology 39: 2974–2984. LINK