A Test of Four Models to Predict the Risk of Naturalization of Non-native Woody Plants in the Chicago Region

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Kapler, Emily
Kordecki, Kristen
Gates, Galen
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Widrlechner, Mark
Associate Professor
Thompson, Janette
Morrill Professor
Dixon, Philip
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Natural Resource Ecology and Management
The Department of Natural Resource Ecology and Management is dedicated to the understanding, effective management, and sustainable use of our renewable natural resources through the land-grant missions of teaching, research, and extension.
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The Department of Agronomy seeks to teach the study of the farm-field, its crops, and its science and management. It originally consisted of three sub-departments to do this: Soils, Farm-Crops, and Agricultural Engineering (which became its own department in 1907). Today, the department teaches crop sciences and breeding, soil sciences, meteorology, agroecology, and biotechnology.

The Department of Agronomy was formed in 1902. From 1917 to 1935 it was known as the Department of Farm Crops and Soils.

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  • Department of Farm Crops and Soils (1917–1935)

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As leaders in statistical research, collaboration, and education, the Department of Statistics at Iowa State University offers students an education like no other. We are committed to our mission of developing and applying statistical methods, and proud of our award-winning students and faculty.
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North Central Regional Plant Introduction Station
The North Central Regional Plant Introduction Station manages and provides plant genetic resources and associated information. As a result of working at the station, student employees should improve their professional skills related to communications, ethics, leadership, problem solving, technical agronomy, international awareness, and an appreciation of diversity.
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The Department of Horticulture was originally concerned with landscaping, garden management and marketing, and fruit production and marketing. Today, it focuses on fruit and vegetable production; landscape design and installation; and golf-course design and management.
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Accurate methods to predict the naturalization of non-native woody plants are key components of risk-management programs being considered by nursery and landscape professionals. The objective of this study was to evaluate four decision-tree models to predict naturalization (fi rst tested in Iowa) on two new sets of data for non-native woody plants cultivated in the Chicago region. We identifi ed life-history traits and native ranges for 193 species (52 known to naturalize and 141 not known to naturalize) in two study areas within the Chicago region. We used these datasets to test four models (one continental-scale and three regional-scale) as a form of external validation. Application of the continental-scale model resulted in classifi cation rates of 72–76%, horticulturally limiting (false positive) error rates of 20–24%, and biologically signifi cant (false negative) error rates of 5–6%. Two regional modifi cations to the continental model gave increased classifi cation rates (85–93%) and generally lower horticulturally limiting error rates (16–22%), but similar biologically signifi cant error rates (5–8%). A simpler method, the CART model developed from the Iowa data, resulted in lower classifi cation rates (70–72%) and higher biologically signifi cant error rates (8–10%), but, to its credit, it also had much lower horticulturally limiting error rates (5–10%). A combination of models to capture both high classifi cation rates and low error rates will likely be the most effective until improved protocols based on multiple regional datasets can be developed and validated.


This article is from Journal of Environmental Horticulture 27, no. 4 (December 2009): 241–250.