In the last decades, the number of publications dedicated to the application of species distribution models (SDMs) to invasive alien plants (IAPs) has constantly increased. Although recent reviews have addressed very relevant issues in the application of SDMs, the modelling approaches (i.e., algorithms) applied to IAPs have not been systematized. Therefore, we undertook a bibliographic review of articles devoted to SDMs and IAPs, from 1996 to 2019. Our results indicate that maximum entropy, generalized linear models, boosted regression trees and random forest were the four most frequent types of modelling approaches. It was clear that there was a variety of different approaches, regarding the type of algorithm to be used. We discuss the characteristics of the most cited algorithms, providing examples of their application in SDMs dedicated to IAPs. We advocate the use of a combination of different algorithms, an intensive evaluation of predictors, a thorough validation process, and a critical analysis of model predictions.

在过去的几十年中，致力于将物种分布模型 (SDM) 应用于外来入侵植物 (IAP) 的出版物数量不断增加。尽管最近的评论已经解决了 SDM 应用中非常相关的问题，但应用于 IAP 的建模方法（即算法）尚未系统化。因此，我们对 1996 年至 2019 年专门讨论 SDM 和 IAP 的文章进行了书目审查。我们的结果表明，最大熵、广义线性模型、增强回归树和随机森林是四种最常见的建模方法类型。很明显，关于要使用的算法类型，有多种不同的方法。我们讨论了被引用最多的算法的特征，提供了它们在专用于 IAP 的 SDM 中的应用示例。