Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

Abstract

Aim We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent‐based, simulation framework. Location East Texas and Louisiana, USA. Methods We drew upon extensive field data from the US Forest Service and the US Geological Survey to calculate spread rate from 2003 to 2008 and to parameterize logistic regression models estimating habitat quality for Chinese tallow within individual habitat cells. We applied the regression analyses to represent population spread rate as a function of habitat quality, integrated this function into a logistic model representing local spread, and coupled this model with a dispersal model based on a lognormal kernel within the simulation framework. We simulated invasions beginning in 2003 based on several different dispersal velocities and compared the resulting spatial patterns to those observed in 2008 using cross Mantel’s tests. We then used the best dispersal velocity to predict range expansion to the year 2023. Results Chinese tallow invasion is more likely in low and flat areas adjacent to water bodies and roads, and less likely in mature forest stands and in pine plantations where artificial regeneration by planting seedlings is used. Forecasted invasions resulted in a distribution that extended from the Gulf Coast of Texas and Louisiana northward and westward as much as 300 km, representing approximately 1.58 million ha. Main conclusions Our new approach of calculating time series projections of annual range expansion should assist land managers and restoration practitioners plan proactive management strategies and treatments. Also, as field sampling continues on the national array of FIA plots, these new data can be incorporated easily into the present model, as well as being used to develop and/or improve models of other invasive plant species.

Invasion of Eastern Texas Forestlands by Chinese Privet: Efficacy of Alternative Management Strategies

“…However, Chinese privet does have the potential to disperse long distances via seed dispersal by songbirds [6,39]. Although not documented for Chinese privet, seed dispersal by birds has been estimated at around 1000 m [40] and 1200 m [41] for Chinese tallow (Triadica sebifera (L.) Small) in North Carolina and Texas, respectively, and around 5 km to 10 km for swamp privet (Forestiera acuminate (Michx.) Poir.)…”

Species Distribution Model for Management of an Invasive Vine in Forestlands of Eastern Texas

“…We identified most of our potential independent variables following a recent study focused on the invasion of Japanese honeysuckle in forestlands of the southern United States [27]; however, we did not use exactly the same set of independent variables and we used a different modeling approach. The possibility remains that there might be a more powerful model [83] and/or a more useful set of explanatory variables [66]. Evaluation of the relative merits of the different methodological approaches to geographical distribution modeling currently is a topic of much debate [83,86,87], but is beyond the scope of the present study.…”

“…The control of biological invasions has become a topic discussed at the highest scientific, policy and management levels [65]. While long-term invasive plant management strategies are recognized as essential to reduce the ecological damage and economic costs associated with invasions, the development and implementation of such plans lags considerably behind [66]. Most of invasive plant management strategies, including that of Japanese honeysuckle, have emphasized controlling highly infested areas, despite this knowledge.…”

Plants on the move: Assisted migration of forest trees in the face of climate change

“…The other two caveats are generic problems related to structural uncertainty in the mathematical representation of natural systems (Walters, 1986). The possibility always remains that important independent variables will be excluded and that the relative importance of the included variables will depend on the current state of the system (Wang et al, 2011). However, the advantage of this approach is that, provided the data, additional variables could be easily included in the model.…”