Predicting the invasion of a southern African savannah by the black wattle ( Acacia mearnsii )
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ORIGINAL PAPER
Predicting the invasion of a southern African savannah by the black wattle (Acacia mearnsii) Muhoyi Hardlife1 • Ndaimani Henry1 • Tagwireyi Paradzayi1 • Kudzai Shaun Mpakairi1 Gopito Eliah2
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Received: 12 December 2018 / Accepted: 24 February 2019 Ó Northeast Forestry University 2019
Abstract Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology. The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism. In this study, by examining the key variables that influence Acacia mearnsii, we sought to understand its potential invasion in eastern Zimbabwe. We used the maximum entropy (MaxEnt) method against a set of environmental variables to predict the potential invasion front of A. mearnsii. Our study showed that the predictor variables, i.e., aspect, elevation, distance from streams, soil type and distance from the nearest A. mearnsii plantation adequately explained (training AUC = 0.96 and test AUC = 0.93) variability in the spatial distribution of invading A. mearnsii. The front of invasion by A. mearnsii seemed also to occur next to existing A. mearnsii plantations. Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A. mearnsii in Zimbabwe and other areas under threat from A. mearnsii invasion. We recommend that the plantation
Project funding: This research received no external funding. The online version is available at http://www.springerlink.com. Corresponding editor: Tao Xu. & Kudzai Shaun Mpakairi [email protected] 1
Department of Geography and Environmental Science, University of Zimbabwe, P. O. Box MP 167, Mount Pleasant, Harare, Zimbabwe
2
Mushandike College of Wildlife Management, Private Bag 9036, Masvingo, Zimbabwe
owners pay for the control of A. mearnsii invasion about their plantations. Keywords Area under curve (AUC) MaxEnt Receiver operating characteristic (ROC) curve Spatial distribution
Introduction Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology. Such an understanding can assist in generating spatially explicit models which help explain the spread dynamics of invasive species (Peterson and Vieglais 2001; Peterson 2003). Subsequently, such models inform efforts that seek to manage and control biological invasions, including the efficient allocation of limited resources to the control of invasive species (Leung et al. 2002; Giljohann et al. 2011) as well as providing the empirical justification for invasion control (Myers et al. 2000; Olckers 2004). The control of biological invasions has become critical in the past few decades because biological invasions are thought to be a major threat to endemism (Pimm et al. 1995; Mack et al. 2000; Gurevitch and Padilla 2004). For instance, invasive species have been reported to reduce the richness of native species by 50–86% (Holmes and Cowling 1997; Albins 2
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