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The Role of Soil and Landscape Factors in Chinese Privet (Ligustrum sinense) Invasion in the Appalachian Piedmont

Published online by Cambridge University Press:  20 January 2017

Donald L. Hagan*
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Elena A. Mikhailova
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Timothy M. Shearman
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Patrick T. Ma
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Jedidah S. Nankaya
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Samantha K. Hart
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
Hillary E. Valdetero
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
William C. Bridges
Affiliation:
Mathematical Sciences, Clemson University, Clemson, SC 29634
He Yun
Affiliation:
School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC 29634
*
Corresponding author's E-mail: [email protected]

Abstract

There is a limited understanding about the ecological mechanisms that enable certain plant species to become successful invaders of natural areas. This study was conducted to determine the soil and landscape characteristics that correlate with invasion of Chinese privet (CHP), and to develop a model to predict the probability of CHP invasion in Piedmont forests. A landscape ecosystem classification (LEC) system—based on the percentage of clay in the B horizon, depth to maximum clay (cm), exposure, terrain shape, and aspect (degrees)—was used to determine the soil moisture characteristics of invaded and uninvaded plots. Additional measurements included the cover classes of CHP and other species, litter depth (cm), slope (degrees), overstory basal area (m2 ha−1), and soil chemical properties. CHP invasion was negatively correlated with overstory basal area and slope and positively with litter depth and pH. A stepwise logistic regression model containing these four variables was highly sensitive, with an overall accuracy of 78%. Given the accuracy of this model, we propose that it can be used to calculate the probability of invasion in a given area, provided that some basic, readily obtainable site characteristics are known.

Type
Research Article
Copyright
Copyright © Weed Science Society of America 

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