Caixia Wei, Mao Li, Limi Mao, Luke Mander, Phillip E Jardine, William D Gosling, Carina Hoorn
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引用次数: 0
Abstract
Grass-dominated biomes in South America comprise c. 20 million years of history, yet their evolution and underlying drivers remain poorly understood. Here we apply a novel approach that combines scanning electron microscopy imaging with computational analysis to quantify the morphometrics of grass (Poaceae) pollen micro-ornamentation from the Neotropics since the Early Miocene (23 million years ago). Three spatial-temporal pollen sets were assembled to further elucidate the variation and evolutionary traits of grasses through space and time. Our results reveals that three spatial-temporal pollen groups occupy unique, partially overlapping regions of their exine morphospace. The direction of this shift is consistent over time, progressing towards less dense ornamentation. Interestingly, the extent of the occupied morphospace did not vary significantly. This is the first time that the true morphological variation in Poaceae pollen micro-ornamentation becomes apparent through time. We hypothesize that changes in grass pollen exine since the Early Miocene were driven by evolutionary processes (evolutionary drift and/or directional selection), and potentially migration at the continental scale. The high diversity in pollen micro-ornamentation is likely related to their evolutionary success in the Neogene.
期刊介绍:
New Phytologist is a leading publication that showcases exceptional and groundbreaking research in plant science and its practical applications. With a focus on five distinct sections - Physiology & Development, Environment, Interaction, Evolution, and Transformative Plant Biotechnology - the journal covers a wide array of topics ranging from cellular processes to the impact of global environmental changes. We encourage the use of interdisciplinary approaches, and our content is structured to reflect this. Our journal acknowledges the diverse techniques employed in plant science, including molecular and cell biology, functional genomics, modeling, and system-based approaches, across various subfields.