With rapid and less predictable environmental change emerging as the ‘new norm’, understanding how individuals tolerate environmental stress via plastic, often reversible changes to the phenotype (i.e. reversible phenotypic plasticity, RPP) remains a key issue in ecology. Here, we examine the potential for better understanding how organisms overcome environmental challenges within their own lifetimes by scrutinizing a somewhat overlooked aspect of RPP, namely the rate at which it can occur. Whilst recent advances in the field provide indication of the aspects of environmental change where RPP rates may be of particular ecological relevance, we observe that current theoretical models do not consider the evolutionary potential of the rate of RPP. Although, recent theory underscores the importance of environmental predictability in determining the slope of the evolved reaction norm for a given trait (i.e. how much plasticity can occur), a hitherto neglected possibility is that the rate of plasticity might be a more dynamic component of this relationship than previously assumed.  If the rate of plasticity itself can evolve, as empirical evidence foreshadows rates of plasticity may have the potential to alter the level predictability in the environment as perceived by the organism and thus influence the slope of the evolved reaction norm. However, optimality in the rate of phenotypic plasticity, its evolutionary dynamics in different environments and influence of constraints imposed by associated costs remain unexplored and may represent fruitful avenues of exploration in future theoretical and empirical treatments of the topic. We conclude by reviewing published studies of RPP rates, providing suggestions for improving the measurement of RPP rates, both in terms of experimental design and in the statistical quantification of this component of plasticity.

The data contained in this dataset was obtained from a literature search performed in December 2021. To identify published empirical research focusing on the rate of phenotypic plasticity, we entered the search terms in Web of Science: (ALL= ("acclimation" or "phenotypic plasticity") AND ALL = ("time-course*" or "time-scale*" or "time-period*" or "response-time*")). We opted to exclude the word “rate” from this search due to the high number of false results that were returned in preliminary trials. This initial search yielded 885 papers. We then scanned the title and abstract (if available) of these papers, excluding cases where it could be determined unambiguously that the rate of plasticity was not a focus of the study. This reduced the initial list to 276 papers. Due to time constraints, we excluded studies where the full text version of the paper could not be located online (n = 16) and then scanned the text of each of the remaining papers, omitting those that (i) were review articles, (ii) implemented a gradual (rather than acute) change in the environmental variable under manipulation, (iii) were performed in field conditions, (iv) did not contain data showing a time-course of change in the phenotypic variable(s) of interest and (v) implemented only a transient treatment exposure to the environmental variable of interest (e.g. heat shock experiments).

From each of the 170 papers, we then extracted data for the variables listed below. The abbreviated name used in the data file contained in this dataset is stated in parentheses, along with a brief description of the values each variable could assume: year of publication (year: integer), taxonomic group (taxon.group: categorical - plant/animal/bacteria), species name (species: character), environmental variable subject to manipulation (env.var: character), phenotypic trait(s) measured (trait: character), the acclimation status of the control groups (acc.type.control: categorical - initial-environment/initial- and new-environment/none), number of phenotypic measurements made during time-course of acclimation to new environment (timepoints.treatment: integer), statistical quantification of the rate of plasticity (rate.quant: categorical - yes/no), reference (ref: character).

Exploration of the extracted data revealed a high diversity of phenotypic traits. To aid quantitative interpretation, each of the recorded traits was placed into one of 7 categories. Where a given grouping maybe ambiguous, we list several illustrative examples below. The categories were:  life history (e.g. body size, population growth rate), behaviour (e.g. prey search time, swimming speed), thermal tolerance (e.g. CTmin, heat knockdown time), morphological (e.g. body shape, leaf thickness), gene expression (e.g. mRNA level associated with a given gene), bioenergetic (e.g. traits involved in photosynthesis, respiration or energy conversion) and biochemical (e.g. enzyme activities, fluid osmolality, fluid ion concentration). Likewise, a high diversity of environmental variables was also evident in the extracted data. We thus categorized these variables into 13 groups. Again, where there may be potential for ambiguity in a given grouping, we list several examples. The 13 groups were:  pH, carbon dioxide concentration, oxygen concentration, population density, water availability, temperature, predation (e.g. predator kairomones), nutrition (e.g. food quantity, food quality or nitrogen availability), chemical exposure (e.g. exposure to copper or aluminum ions), light (e.g. light intensity, level of UV radiation) and salinity (i.e. salt concentration). Two final groups that require further explanation are physical environment (e.g. water flow, background color) which includes aspects of the physical environment not covered by any of the previous groupings, and a group we termed interaction to describe instances where two environmental variables were subject to simultaneous experimental manipulation (e.g. temperature × food availability). This variable is termed env.var.category (character variable).