School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.
Mathematical Institute, University of Oxford, Oxford, United Kingdom.
PLoS One. 2024 Apr 2;19(4):e0300968. doi: 10.1371/journal.pone.0300968. eCollection 2024.
Models of invasive species spread often assume that landscapes are spatially homogeneous; thus simplifying analysis but potentially reducing accuracy. We extend a recently developed partial differential equation model for invasive conifer spread to account for spatial heterogeneity in parameter values and introduce a method to obtain key outputs (e.g. spread rates) from computational simulations. Simulations produce patterns of spatial spread which appear qualitatively similar to observed patterns in grassland ecosystems invaded by exotic conifers, validating our spatially explicit strategy. We find that incorporating spatial variation in different parameters does not significantly affect the evolution of invasions (which are characterised by a long quiescent period followed by rapid evolution towards to a constant rate of invasion) but that distributional assumptions can have a significant impact on the spread rate of invasions. Our work demonstrates that spatial variation in site-suitability or other parameters can have a significant impact on invasions and must be considered when designing models of invasive species spread.
入侵物种传播模型通常假设景观在空间上是均匀的；因此简化了分析但可能降低了准确性。我们将最近开发的用于入侵针叶树传播的偏微分方程模型扩展到考虑参数值的空间异质性，并引入了一种从计算模拟中获得关键输出（例如传播率）的方法。模拟产生的空间传播模式在质量上与外来针叶树入侵的草原生态系统中观察到的模式相似，验证了我们的空间显式策略。我们发现，不同参数的空间变化不会显著影响入侵的演变（其特征是长时间的静止期，然后迅速演变为入侵的恒定速率），但分布假设会对入侵的传播率产生重大影响。我们的工作表明，适宜性或其他参数的空间变化可能对入侵有重大影响，在设计入侵物种传播模型时必须考虑到这一点。
