Investment in reproduction for 14 iteroparous perennials is large and associated with other life-history and functional traits

While theoretical models predict reproductive allocation (RA) should approach 100% of available energy as a plant ages, available empirical data suggest much lower RA values in perennial plants. In this study, we have two aims. First, we assess whether the discrepancy between theory and data arises from methodological differences in how growth and RA are calculated. Specifically, we hypothesize RA in older plants is large when compared to growth in leaf area, that is, after excluding turnover of stem and leaf tissues. Second, we hypothesize that species with cheap tissues or those that are shorter reach RA = 0.5 at a younger age. We measured investment in leaf, stem and reproduction on individuals from 14 co-occurring woody perennial iteroparous species. A fire chronosequence allowed us to use a space-for-time substitution to estimate RA schedules for each species, simultaneously measuring reproductive and vegetative production on individuals differing in age. For most (11 of 14) species, we found RA eventually reached 100% of available energy, with another two species reaching at least 80%. Increases in RA were associated with a decline in growth of leaf area. Comparing species, we found that species with cheap leaves reached RA = 0.5 sooner (they could be called fast-living), whereas delayed maturation and slower increases in RA were associated with greater maximum height. Synthesis. Explicitly accounting for the cost of leaf replacement leads to the high estimates of reproductive allocation in perennial plants predicted by theoretical models, limiting or even halting leaf area expansion. For some species, so much energy is allocated to reproduction that leaf area declines year-upon-year for multiple growing seasons preceding death. Connecting lifetime reproductive allocation schedules with leaf area expansion, leaf life span, and plant maximum height demonstrates how reproductive allocation schedules synthesize a plant’s life-history strategy, making them a valuable tool for connecting plant traits and demography.