Centre for Invasion Biology, Department of Botany & Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.
Conserv Biol. 2012 Apr;26(2):267-77. doi: 10.1111/j.1523-1739.2011.01804.x. Epub 2012 Jan 11.
We developed a method to predict the potential of non-native reptiles and amphibians (herpetofauna) to establish populations. This method may inform efforts to prevent the introduction of invasive non-native species. We used boosted regression trees to determine whether nine variables influence establishment success of introduced herpetofauna in California and Florida. We used an independent data set to assess model performance. Propagule pressure was the variable most strongly associated with establishment success. Species with short juvenile periods and species with phylogenetically more distant relatives in regional biotas were more likely to establish than species that start breeding later and those that have close relatives. Average climate match (the similarity of climate between native and non-native range) and life form were also important. Frogs and lizards were the taxonomic groups most likely to establish, whereas a much lower proportion of snakes and turtles established. We used results from our best model to compile a spreadsheet-based model for easy use and interpretation. Probability scores obtained from the spreadsheet model were strongly correlated with establishment success as were probabilities predicted for independent data by the boosted regression tree model. However, the error rate for predictions made with independent data was much higher than with cross validation using training data. This difference in predictive power does not preclude use of the model to assess the probability of establishment of herpetofauna because (1) the independent data had no information for two variables (meaning the full predictive capacity of the model could not be realized) and (2) the model structure is consistent with the recent literature on the primary determinants of establishment success for herpetofauna. It may still be difficult to predict the establishment probability of poorly studied taxa, but it is clear that non-native species (especially lizards and frogs) that mature early and come from environments similar to that of the introduction region have the highest probability of establishment.
我们开发了一种预测非本地爬行动物和两栖动物(爬行动物和两栖动物)建立种群潜力的方法。这种方法可以为防止引入入侵的非本地物种提供信息。我们使用增强回归树来确定九个变量是否影响加利福尼亚州和佛罗里达州引入的爬行动物和两栖动物的建立成功率。我们使用独立数据集来评估模型性能。传播压力是与建立成功率最相关的变量。幼体期短的物种和在区域生物群中与亲缘关系较远的物种比开始繁殖较晚的物种和与亲缘关系较近的物种更有可能建立。平均气候匹配(原生和非原生范围之间气候的相似性)和生活方式也很重要。青蛙和蜥蜴是最有可能建立的分类群,而蛇和海龟的建立比例要低得多。我们使用最佳模型的结果编制了一个基于电子表格的模型,以便于使用和解释。从电子表格模型中获得的概率评分与建立成功率密切相关,与增强回归树模型为独立数据预测的概率也密切相关。然而,使用独立数据进行预测的错误率远高于使用训练数据进行交叉验证的错误率。这种预测能力的差异并不排除使用该模型来评估爬行动物和两栖动物建立的可能性,因为 (1) 独立数据没有两个变量的信息(这意味着模型的全部预测能力无法实现),并且 (2) 模型结构与最近关于爬行动物和两栖动物建立成功率的主要决定因素的文献一致。对于研究较少的分类群,预测建立概率可能仍然很困难,但很明显,成熟早且来自与引入地区相似环境的非本地物种(尤其是蜥蜴和青蛙)建立的可能性最高。