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Mislabeling of an Invasive Vine (Celastrus orbiculatus) as a Native Congener (C. scandens) in Horticulture

Published online by Cambridge University Press:  14 December 2017

David N. Zaya*
Affiliation:
Graduate Student, Undergraduate Student, and Professor, Department of Biological Sciences, University of Illinois at Chicago, 845 West Taylor Street, Chicago IL 60607
Stacey A. Leicht-Young
Affiliation:
Postdoctoral Fellow and Plant Ecologist, U.S. Geological Survey, Great Lakes Science Center, 1574 North 300 East, Chesterton, IN 46304
Noel B. Pavlovic
Affiliation:
Postdoctoral Fellow and Plant Ecologist, U.S. Geological Survey, Great Lakes Science Center, 1574 North 300 East, Chesterton, IN 46304
Christopher S. Hetrea
Affiliation:
Graduate Student, Undergraduate Student, and Professor, Department of Biological Sciences, University of Illinois at Chicago, 845 West Taylor Street, Chicago IL 60607
Mary V. Ashley
Affiliation:
Graduate Student, Undergraduate Student, and Professor, Department of Biological Sciences, University of Illinois at Chicago, 845 West Taylor Street, Chicago IL 60607
*
*Corresponding author’s E-mail: dzaya1@illinois.edu
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Abstract

The horticultural industry is an important source of invasive ornamental plant species, which is part of the motivation for an increased emphasis on using native alternatives. We were interested in the possibility that plants marketed in the midwestern United States as the native Celastrus scandens, or American bittersweet, were actually the difficult-to-distinguish invasive Celastrus orbiculatus (oriental bittersweet) or hybrids of the two species. We used nuclear microsatellite DNA loci to compare the genetic identities of 34 plants from 11 vendors with reference plants from wild populations of known species identity. We found that 18 samples (53%) were mislabeled, and 7 of the 11 vendors sold mislabeled plants. Mislabeled plants were more likely to be purchased through Internet or phone order shipments and were significantly less expensive than accurately labeled plants. Vendors marketed mislabeled plants under five different cultivar names, as well as unnamed strains. Additionally, the most common native cultivar, ‘Autumn Revolution,’ displays reproductive characteristics that diverge from the typical C. scandens, which could be of some concern. The lower price and abundance of mislabeled invasive plants introduces incentives for consumers to unknowingly contribute to the spread of C. orbiculatus. Revealing the potential sources of C. orbiculatus is critical for controlling further spread of the invasive vine and limiting its impact on C. scandens populations.

Information

Type
Research and Education
Copyright
© Weed Science Society of America, 2017 
Figure 0

Figure 1 Distribution of Celastrus vendors in the midwestern United States. Circles represent vendors that were visited in person; squares represent vendors that shipped the product. Red points represent vendors that exclusively sold C. scandens; yellow points represent vendors that exclusively sold C. orbiculatus; and the single orange point represents a vendor that delivered both species. The dashed line represents the approximate western edge of the C. orbiculatus invasion front (from EDDMapS 2017).

Figure 1

Table 1 Sources and genetic identities for Celastrus samples.a

Figure 2

Table 2 Microsatellite genotypes for horticultural Celastrus samples.a

Figure 3

Figure 2 Bayesian clustering results from Structure with two inferred clusters (K=2) for Celastrus individuals. Results for each individual are represented in a single column. The colors in each column show the proportion of the individual’s genome assigned to the two clusters. “Test samples” (N=34) are plants purchased for this study. The other three categories were control plants of known genetic identity (N=378). For clarity, only 16 randomly selected control samples in each category are shown.

Figure 4

Figure 3 Prices of correctly labeled C. scandens (n=5) and mislabeled C. orbiculatus (n=7). Heavy solid lines represent the median, while dashed lines represent the mean.