OOS 6-10
Increase the mean, reduce the variance, or bet on a bonanza: How should plants respond to environmental variability in pollen receipt?

Monday, August 10, 2015: 4:40 PM
327, Baltimore Convention Center
Joshua M. Rapp, Department of Evolution and Ecology, University of California, Davis, CA, USA
Sebastian J. Schreiber, Department of Evolution and Ecology, University of California, Davis, CA, USA
Jay A. Rosenheim, Department of Entomology, University of California, Davis, CA, USA
Neal M. Williams, Department of Entomology, University of California, Davis, CA, USA
Lawrence D. Harder, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
Background/Question/Methods

In deterministic environments, organisms should exactly match resource use with resource harvest, so that excessive allocation to resource harvest does not limit allocation to other functions. In stochastic environments, however, this strategy will lead to lower fitness because resource availability will sometimes be lower than the mean, and constraints on resource use will limit the ability of the organism to capitalize on resource bonanzas. Here we model optimal plant reproductive allocation strategies under conditions of environmentally stochastic pollen availability. We hypothesize that plants can respond to environmental variability in pollen by (1) increasing mean pollen receipt by allocating more resources to pollen attraction, (2) reduce the variance in pollen receipt by employing more flowers, and/or (3) capitalize on pollen “bonanzas” by producing more ovules. Because these strategies involve allocation trade-offs, we expect the optimal strategy to lower potential fitness under mean pollen availability, while increasing expected fitness under stochastic pollen availability. We explore scenarios of varying costs for flower initiation, ovule production, pollen attraction, and seed maturation, and include the possibility that increasing flower number leads to diminishing fitness returns as pollinators become less efficient at providing out-cross pollen to individual flowers. 

Results/Conclusions

The optimal allocation strategy under variable pollen had lower potential fitness at mean pollen receipt, but higher expected fitness under stochastic pollen receipt than the deterministic strategy. Increasing flower number was near-universal response to pollen variability, except when constraints on flower number were severe. Increased allocation to ovules was universal at the plant level, but because flower number also increased, the number of ovules per flower often declined with increasing pollen variability. Increasing allocation to pollen attraction was also employed, but only when the cost of attracting pollen was cheap relative to the cost of maturing a seed. When attracting pollen was expensive, allocation to pollen attraction declined with increasing pollen variability. The optimal strategy in all cases resulted in coefficients of variation of (1) pollen receipt at the plant level, (2) zygotes per plant, and (3) seeds per plant that were lower than the coefficient of variation in pollen receipt per flower. The optimal fitness strategy may often include multiple modes of organismal adaptation to environmental variation in resource availability. Understanding plant strategies for coping with stochastic pollen availability may enhance our understanding of pollen limitation in natural systems.