Systematics and Glacial Population History of the Alternifolium Group of the Flowering Plant Genus Chrysosplenium (Saxifragaceae)
Issue Date
2008-01-01Author
Levsen, Nicholas David
Publisher
University of Kansas
Format
190 pages
Type
Dissertation
Degree Level
Ph.D.
Discipline
Ecology & Evolutionary Biology
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This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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Show full item recordAbstract
The flowering plant genus Chrysosplenium comprises approximately 57 species of herbaceous perennials. These species are mainly distributed in the Northern Hemisphere where they occur in moist habitats. Though the center of diversity, and presumed location of origin, for the genus is east temperate Asia, more recently radiating taxa have invaded the arctic of North America and Europe. There are six species of Chrysosplenium in North America and four of them (i.e., C. iowense, C. tetrandrum, C. wrightii, and C. rosendahlii) belong to the section Alternifolia. Termed the Alternifolium group, this collection of species presents an excellent opportunity to study the evolution of variation in arctic and alpine environments. Similar to many arctic taxa, these species display very little morphologic or genetic variation, but they exhibit diversity in chromosome number, breeding system, geographic distribution, and ecology. Though the Alternifolium group has been the subject of numerous taxonomic studies, no thorough investigation of its evolutionary history has been conducted. This study used a combination of genetic and phenotypic data (e.g., DNA sequence, Inter-Simple Sequence Repeat, morphology) to determine the patterns of variation present within the Alternifolium group and then used these patterns to infer historical processes that might have contributed to them. Through the course of the study, however, it also became necessary to investigate the applicability of genetic estimates derived from different molecular markers and statistical methods. Appropriate comparisons among genetic estimates are critical to accurately interpret results and generate new predictions.
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