Plant environmental memory: implications, mechanisms and opportunities for plant scientists and beyond

Abstract

Plants are extremely plastic organisms. They continuously receive and integrate environmental information and adjust their growth and development to favour fitness and survival. When this integration of information affects subsequent life stages or the development of subsequent generations, it can be considered an environmental memory. Thus, plant memory is a relevant mechanism by which plants respond adaptively to different environments. If the cost of maintaining the response is offset by its benefits, it may influence evolutionary trajectories. As such, plant memory has a sophisticated underlying molecular mechanism with multiple components and layers. Nonetheless, when mathematical modelling is combined with knowledge of ecological, physiological, and developmental effects as well as molecular mechanisms as a tool for understanding plant memory, the combined potential becomes unfathomable for the management of plant communities in natural and agricultural ecosystems. In this review, we summarize recent advances in the understanding of plant memory, discuss the ecological requirements for its evolution, outline the multilayered molecular network and mechanisms required for accurate and fail-proof plant responses to variable environments, point out the direct involvement of the plant metabolism and discuss the tremendous potential of various types of models to further our understanding of the plant's environmental memory. Throughout, we emphasize the use of plant memory as a tool to unlock the secrets of the natural world.

Keywords: Ecology; epigenetics; intergenerational effects; memory; metabolism; modelling; plasticity.

Figure 1.

The strength of the temporal correlation between the environmental value at the time of the cue (x-axis of subplots) and the time of selection (y-axis of subplots) is pivotal for the evolution of an environmental plant memory. Therefore, an adaptive plant memory can evolve only when the temporal correlation is sufficiently strong (B, D vs. A, C). The time span between the environmental cue and the time of selection relative to the life span of the plant determines whether the memory is conserved across a plant’s life or across generations (A, B vs. C, D). In general terms, when the time span of prediction is short, but the environmental correlation is strong, within-generation memory can evolve (D vs. C); while when that span is long, transgenerational memory is favoured (B vs. A). The subplots show potential values for example of environments. (A) Annual rain in one year is usually not correlated with the mean annual temperature in a later year and accordingly is a poor predictor for offspring heat response. However, (B) in rain-limited habitats, rain is a good predictor of next year’s seedling density (i.e. temporal correlation between two different environmental variables) and accordingly modulates offspring germination via a trans-generational environmental memory. (C) The increasing spring temperatures due to climate change frequently cause early budbreak but represent a poor predictor for late spring frost, resulting in severe frost damage due to missing within-generation plasticity to prepare for the frost. However, (D) generally, increasing temperatures after winter represent a reliable cue for the start of the growing season (i.e. temporal autocorrelation within the time series of temperature values), so that plants can find the best time for budbreak using within-generation memory. The points represent hypothetical data points from different years or geographic coordinates with point colour as year/site identifier.

Figure 2.

Plant memory is regulated by the interaction of different genetic, epigenetic and metabolic mechanisms (‘shaded sphere’). The role of each of these components in the establishment, transmission, maintenance and dissipation of within- and transgenerational effects is dependent on the environmental stimuli and the kind of memory involved. Yet, it is not always fully understood how plant memories that correlate with enhanced adaptation to recurring environmental stimuli are retained (‘dark box’). To help bridging this knowledge gap, we can use the empirical data on the contributing molecular components of a known response (‘upper arrows’) to inform and help train mathematical models that make predictions about future physiological, ecological and evolutionary responses of plants (‘bottom arrows’) living in natural and agricultural ecosystems. Thus, the power of plant memory knowledge can be unleashed and can be used to guide agriculture, conservation and management efforts.