COS 192-3 - A stochastic dynamic programming approach to predict life history evolution in invasive plants

Friday, August 10, 2012: 8:40 AM
Portland Blrm 256, Oregon Convention Center
Cristina F. Aragón, Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, Ingrid M. Parker, Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA and Marc Mangel, Department of Applied Mathematics and Statistics and Center for Biomolecular Science and Engineering, University of California at Santa Cruz, Santa Cruz, CA
Background/Question/Methods

Invasive species offer excellent opportunities to test evolutionary hypothesis and to study basic processes in population biology. In particular, invasive species represent attractive study models to test the predictions of life history theory, since the selective pressures in the native and introduced habitats can be remarkably different. Some plant species display changes in life history traits where they are introduced, including changes in schedules of mortality and reproduction. Specifically, several monocarpic species have been observed to partially shift towards polycarpy and delay time to first reproduction in their introduced range. These patterns have often been explained by the release, in the new environment, from the coevolved natural enemies (e.g. herbivores, seed predators). However, the role of natural enemies as selective forces in the evolution of life histories is still poorly integrated into plant life history theory. We used state-dependent life history models to identify the optimal allocation strategy in Verbascum thapsus, a monocarpic species displaying life history variation, under different scenarios of enemy pressure. We developed a stochastic dynamic programming algorithm to identify developmental pathways (size at maturity, reproductive effort) that optimize lifetime reproductive success under alternative assumptions about growth and mortality, as would occur in native and new habitats.

Results/Conclusions

Our model illustrates trade-offs between allocation to reproduction, growth and mortality based on the common currency of expected lifetime seed production. The optimal allocation decisions represent a life-history strategy that would be favoured by natural selection, given the model assumptions. Using the stochastic dynamic programming model we predict strongly divergent optimal reproductive strategies when the effects of generalist and specialist enemies are included, compared with the baseline model where those effects are ignored. Including the effects of natural enemies in the model shifted the optimal strategy toward smaller sizes at first reproduction, with a gradual increase in reproductive effort with size. Our model suggests that plants may adopt strategies of polycarpy and delayed maturity to maximize reproductive success in their new range, where populations are released from specialist enemies (more than generalist enemies), which tend to affect the reproductive stages (i.e. seed predators). In this sense, our results provide circumstantial evidence that reproduction-related mortality caused by natural enemies can select for the monocarpic strategy in the native range. Our work pinpoints the important selective role that natural enemies may have in the evolution of plant life histories, and provides valuable insights to be considered in the study of invasive plants.