Novel Computed Tomography-based tools reliably quantify plant reproductive investment

Abstract

The flower is a bisexual reproductive unit where both genders compete for resources. Counting pollen and ovules in flowers is essential to understand how much is invested in each gender. Classical methods to count very numerous pollen grains and ovules are inefficient when pollen grains are tightly aggregated, and when fertilization rates of ovules are unknown. We thus established novel, Computed-Tomography-based counting techniques. In order to display the potential of our methods in very difficult cases, we counted pollen and ovules across inflorescences of deceptive and rewarding species of European orchids, which possess both very large numbers of pollen grains (tightly aggregated) and ovules. Pollen counts did not significantly vary across inflorescences and pollination strategies, whereas deceptive flowers had significantly more ovules than rewarding flowers. The within inflorescence variance of pollen to ovule ratios in rewarding flowers was four times higher than in deceptive flowers, possibly demonstrating differences in the constraints acting on both pollination strategies. We demonstrate the inaccuracies and limitations of previously established methods, and the broad applicability of our new techniques: they allow measurement of reproductive investment without restriction on object number or aggregation, and without specimen destruction.