All organisms are faced with trade-offs when they allocate energy to reproduction, in particular with other vital rates such as growth and survival. Life history theory offers predictions for when an organism should begin reproducing, based on vital rates and the cost of reproduction. For semelparous species, the costs are obvious—reproduction is followed by death—and a number of studies have now calculated the optimal size or age at which monocarpic plants should flower. However, for iteroparous species, costs are more subtle, and much less well understood. We developed a quantitative framework to study optimal reproductive strategies in iteroparous plants, in particular to determine at what size or age plants should begin flowering and how much energy they should allocate to reproduction. Specifically, we incorporated quantifiable costs of reproduction into integral projection models (IPMs) and used these models to calculate a set of parameters for which fitness, as measured by the net reproductive rate (R0), is maximized. We created this framework using simulated demographic data for a generic perennial and then applied it to long-term data sets for five perennial plant species.
As expected, in the absence of costs, our model predicts that plants should flower as soon as they are born and produce infinite seeds. In the presence of costs, optimal parameter combinations are finite and peaks in fitness are present due to the trade-offs between reproduction and survival and/or growth. For the species in which we were able to estimate costs (3 out of 5), observed flowering strategies were similar to the predicted optima. Our study is one of the first to use a demographic approach to demonstrate costs of reproduction in perennial plants and to model how those costs influence optimal reproductive strategies. Our results will contribute to refining life history theory for plants where reproduction is costly but not necessarily lethal.