量化入侵扩散的时空变化
Quantifying Spatio-Temporal Variation of Invasion Spread
摘要：
入侵物种的扩散可能会对环境和生态产生深远的影响。了解入侵传播模式和驱动入侵的潜在过程是预测和管理入侵的关键。我们结合了一套统计方法，以一种新的方式来表征当地的传播特性，并展示了它们的应用程序，使用模拟和历史数据入侵昆虫。我们的方法使用了一个高斯过程来拟合入侵等待时间的曲面，以表征传播的向量场。使用这种方法，我们估计与统计不确定性的速度和方向的蔓延在每个位置。分层扩散模型的仿真验证了该方法的准确性。我们展示了我们如何将当地的传播率与环境协变量联系起来，这两个案例研究是：舞毒蛾（舞毒蛾）的传播，以及北美的铁杉绵球蚜（松盖球蚜）。我们提供了一个R-包，自动计算任何空间参考的等待时间数据。
英文摘要：
The spread of invasive species can have far reaching environmental and ecological consequences. Understanding invasion spread patterns and the underlying process driving invasions are key to predicting and managing invasions. We combine a set of statistical methods in a novel way to characterize local spread properties and demonstrate their application using simulated and historical data on invasive insects. Our method uses a Gaussian process fit to the surface of waiting times to invasion in order to characterize the vector field of spread. Using this method we estimate with statistical uncertainties the speed and direction of spread at each location. Simulations from a stratified diffusion model verify the accuracy of our method. We show how we may link local rates of spread to environmental covariates for two case studies: the spread of the gypsy moth (Lymantria dispar), and hemlock wolly adelgid (Adelges tsugae) in North America. We provide an R-package that automates the calculations for any spatially referenced waiting time data.
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