Seed Dormancy and Delayed Flowering in Monocarpic Plants: Selective Interactions in a Stochastic Environment

Abstract

We explore the effects of temporal variation in multiple demographic rates on the joint evolution of delayed reproduction and seed dormancy using integral projection models (IPMs). To do this, we extend the standard IPM to include a discrete state variable representing the number of seeds in the seed bank, density-dependent recruitment, and temporal variation in demography. Parameter estimates for Carlina vulgaris and Carduus nutans are obtained from long-term studies. Carlina is relatively long lived and has a short-lived seed bank, whereas most Carduus plants flower in their first year and the seed bank is long lived. Using the evolutionarily stable strategy (ESS) approach, we predict the observed flowering and germination strategies. There is excellent agreement between the predictions and the field observations. The effects of temporal variation on the joint ESS are partitioned into components arising from nonlinear averaging (systematic changes in the mean resulting from the interaction between variability and nonlinearity) and nonequilibrium dynamics (fluctuations in fitness caused by temporal variation). This shows that temporal variation can have substantial effects on the observed flowering and germination strategies and that covariance between demographic processes is important. We extend the models to include spatial population structure and assess the robustness of the results from the nonspatial models.

Evolutionary bet-hedging in the real world: empirical evidence and challenges revealed by plants

“…Further, we can establish whether there is a particular flowering or germination strategy that, once established, cannot be invaded by any rare mutant strategies; this strategy is the evolutionarily stable strategy (ESS). ESSs identified using this approach very closely match observed flowering size and germination delays in three monocarpic plant systems Rees et al 2006;Ellner & Rees 2007).…”

“…Linking traits to their effect on bet-hedging then becomes particularly difficult, since all the different pathways and their effect on both the mean and the variance in fitness need to be accounted for. The partitioning approach discussed above (see also Rees et al 2006) for decomposing the effect of different sources of temporal variation on the ESS, although intuitively sensible, needs a firmer theoretical foundation. It is likely some of the approaches developed by Peter Chesson for analysing community dynamics in stochastic environments (e.g.…”

Modes of response to environmental change and the elusive empirical evidence for bet hedging

“…The consistent use of 'bet hedging' in titles, abstracts or keywords would facilitate the identification of research common to this area. Some of the most sophisticated treatments of bet hedging [17,85] recognize implicitly that fluctuating selection will result in evolutionarily stable strategies that may differ from those that maximize average expected fitness, and contain no specific searchable reference to the field of bet hedging. The coverage of the empirical literature is thus as comprehensive as possible in spanning taxa and range of tests.…”

Experimental evolution of bet hedging under manipulated environmental uncertainty in Neurospora crassa

“…However, empirical evidence for bet hedging remains scant [12]. Evidence is restricted to demonstrations of interspecific divergence [13] or population differentiation [14,15] in putative bet-hedging traits across environments that differ in predictability, or the documentation of the evolution of candidate bet-hedging traits under conditions in which they may be advantageous [16,17], with very few strong studies confirming fitness benefits of putative bethedging traits under fluctuating conditions [18][19][20][21]. Tests of bet hedging under field conditions are difficult because they require evaluating both environmental variance and its fitness effects over multiple generations.…”