We review a model we developed in 2007 to predict the invasion potential of an introduced population, based on the relationship between juvenile growth (mean total length at age 2) and mean age-at-maturity, and test the model with data from 75 non-native populations of pumpkinseed Lepomis gibbosus in nine countries of Europe and western Asia. The database used to construct the model was derived from a mix of primary and secondary data collected between 1981 and 2016. Based on number of specimens collected or catch-per-unit-effort data, and/or comments by the original authors, populations were classified a priori as “invasive” or “non-invasive.” The plot of the proposed model placed populations in three invasiveness categories (non-invasive, transitional, invasive). Of those predicted by the model to be invasive, only 57% were correct with regard to their a priori classification, a result that was not statistically significant. For populations predicted by the model to be non-invasive, 70% were correct with regard to their a priori classification when “transitional” were grouped with non-invasive (P = 0.0024), and 64% were correct when “transitional” were excluded from the test (P = 0.12). Applications of the model to two other non-native freshwater fishes (black bullhead Ameiurus melas and crucian carp Carassius carassius) are also discussed. The lack of stronger statistical support for the model may have been the result of using life-history traits from the populations after they were introduced, as the source populations were unknown, as well as to shortcomings in the dataset that could affect a priori and modeled classifications. We conclude that such life-history models can be useful for predicting invasiveness status in non-native freshwater fishes, though the basis of the predictions, statistical or heuristic, will depend on the size and quality of the underlying life-history database.

中文翻译：

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能否从生活史特征预测淡水鱼的入侵性？

我们回顾了我们在 2007 年开发的一个模型，用于预测引入种群的入侵潜力，基于幼鱼生长（2 岁时的平均总长度）和平均成熟年龄之间的关系，并使用来自 75 个非- 欧洲和西亚九个国家的南瓜籽 Lepomis gibbosus 本地种群。用于构建模型的数据库来自 1981 年至 2016 年期间收集的主要和次要数据的混合。根据收集的样本数量或单位努力数据和/或原始作者的评论，人口是先验分类为“侵入性”或“非侵入性”。拟议模型的图将人群分为三个侵入性类别（非侵入性、过渡性、侵入性）。在模型预测为侵入性的那些中，只有 57% 的人对其先验分类是正确的，这一结果没有统计学意义。对于模型预测为非侵入性的人群，当“过渡性”与非侵入性分组时，70% 的先验分类是正确的（P = 0.0024），而排除“过渡性”时，64% 是正确的来自测试（P = 0.12）。还讨论了该模型在其他两种非本地淡水鱼类（黑牛头鱼和鲫鱼 Carassius carassius）中的应用。该模型缺乏更强的统计支持可能是由于在引入种群后使用了种群的生活史特征，因为源种群未知，以及数据集的缺陷可能影响先验和建模分类。