Immediately recognizing the Achilles heel of invasive plants, IPMs, and the curious case of Chinese tallow tree etiolation

Dylan J. White, Rabin Thapa and Thomas P. Wakefield, Dept. of Mathematics and Statistics, Youngstown State University, Youngstown, OH, Logan K. Gerig and Ian J. Renne, Dept. of Chemical and Biological Sciences, Youngstown State University, Youngstown, OH, Timothy P. Spira, Dept. of Biological Sciences, Clemson University, Clemson, SC

Background/Question/Methods
Ecological issues associated from non-native, invasive species range from disruption of ecosystem processes to local extinction of native species. Finding a science-based, strategic approach to minimize their adverse effects, while simultaneously maximizing control measure efficacy, is a primary goal of invasive species management. However, acquiring demographic data to achieve this is costly. Integrated population models (IPMs) have replaced population projection matrices as a means of demographic analysis, and for good reason – by applying a continuous function to a population’s vital rates (i.e., survival, growth and fecundity), they avoid the arbitrariness of size- or age-classification schemes, and the mathematical problems which result. In coastal South Carolina, demographic data on ~4,500 individuals were collected over three years from five populations of Chinese tallow tree (CTT, Triadica sebifera), one of the most problematic invasive plant species in southeastern and Gulf Coast regions of the U.S – these were analyzed using IPMs. We asked: 1) is there a single most effective management strategy to apply to all CTT populations (e.g., targeting small or large individuals only)?, and 2) is there a populational phenotypic metric which indicates how the population is growing, and thus, which size classes to target for most effective control?
Results/Conclusions
We found that CTT annual population growth rate, lambda, varied widely, across years and among populations, with all but one population having positive growth. Moreover, applying the same management strategy (e.g., simulated 90% mortality of small or large individuals) resulted in differential control because the relative contribution of various size classes to lambda, as determined by elasticity analysis, differed as a function of lambda. For example, larger individuals disproportionately drove population growth in slow-growing populations and vice versa. Importantly, we found that degree of CTT etiolation, as measured by height:diameter-at-breast-height ratios, correlated strongly negatively with lambda. This suggests that degree of etiolation, an easily measured phenotypic trait, can provide CTT managers with a tool that circumvents laborious, multi-year data collection efforts, and offers quick guidance to strategically manage populations with different demographics and population growth. For example, trees with large height:diameter-at-breast-height ratios indicate slow-growing populations, and thus large individuals should be targeted for most effective population growth control. In contrast, in rapidly-growing populations characterized by small height:diameter-at-breast-height ratios, small individuals should be targeted. If other relatively shade-intolerant, exotic species exhibit similar patterns, our approach may be extended to those in need of immediate management, but where no demographic data exists.