Publication in: Spring 2023 Issue

Population Demographic Modeling of American Ginseng (Panax quinquefolius L.), Populations in Western North Carolina
Kathryn Brown
Faculty Mentor(s):
Jonathan Horton
Abstract / Summary:
American ginseng (Panax quinquefolius L.), is an herbaceous perennial understory plant distributed throughout deciduous forests in eastern North America. Ginseng is widely sought-after for the medicinal compounds (ginsenosides), in its roots. A majority of harvested ginseng is sold for use in traditional Asian medicine. Overharvest and scarcity of Asian ginseng (Panax ginseng L.), led to mass exports of American ginseng to Asia starting in the early 1700s. American ginseng has since been overexploited and has experienced major population declines. Wild ginseng harvest is regulated in many states to conserve and protect populations of the species, yet illegal poaching still occurs. Ginseng is slow growing and typically reemerges each year from its roots as leafy stems in different size classes, which are often categorized by the number of leaves present. Their above-ground vegetative growth year-to-year can increase, stay the same size class, or revert back to smaller size classes (typically in response to stress),. Using several years of demographic data collected between 2011 and 2022 from six western North Carolina populations, demographic models were created to understand patterns, demographic change, and the long-term viability of these populations. The demographic monitoring of these populations did not include extensive fertility data (seed production and seed fate),. Instead, published fertility data from a study in West Virginia were used. Models can be used to gain a better understanding of the population dynamics of wild ginseng in western North Carolina as well as simulate the effects of different harvesting intensities, which can aid in developing sustainable harvesting protocols. The developed models predicted all six populations to have a positive growth rate (?>1),. Modeled predictions did not match observed demographics. This suggests that the developed model does not accurately capture demographic data. This work also highlights demographic monitoring work, such as collecting regionally specific fertility data, that is needed to more accurately model wild ginseng populations in western North Carolina.
Publication Date: