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Beyond species-specific assessments: an analysis and validation of environmental distance metrics for non-indigenous species risk assessment

机译:超越物种特定的评估:非土著物种风险评估的环境距离度量标准的分析和验证

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摘要

Environmental distance metrics quantify environmental similarity between locations using a number of environmental variables. They are commonly applied in aquatic non-indigenous species risk assessments to assess the relative risk of species transfer between different location pairs. Despite their application in governmental risk assessments globally, these metrics have not yet been empirically validated. We use empirical data for 419 species obtained from the Global Invasive Species Information Network database to perform a validation of environmental distance metrics. We explore the ability of environmental distance to discriminate presences from absences in both aquatic and terrestrial environments. We examine the effect of variable choice (both the number and types of variables included) and different metrics (Euclidean distance, Mahalanobis distance, and weighted versions of each) on metric performance. Environmental distance calculated using unweighted Euclidean distance performed best overall. When applied with appropriate variables, it was able to discriminate between presence and absence distances for up to 93 % of species. Variable choice significantly influenced metric performance, and including fewer, relevant variables outperformed applications where many variables were included. Our results support the use of environmental distance metrics in both aquatic and terrestrial environments.
机译:环境距离量度使用许多环境变量来量化位置之间的环境相似性。它们通常用于水生非本地物种风险评估中,以评估不同位置对之间物种转移的相对风险。尽管它们已在全球范围内应用于政府风险评估,但尚未通过经验验证。我们使用从全球入侵物种信息网络数据库中获得的419种物种的经验数据来验证环境距离指标。我们探索了环境距离在水生和陆地环境中区分存在与不存在的能力。我们研究了变量选择(包括变量的数量和类型)以及不同度量(欧几里得距离,马氏距离和每个变量的加权版本)对度量性能的影响。使用未加权欧几里得距离计算的环境距离总体上表现最佳。当应用适当的变量时,它可以区分多达93%的物种的存在和不存在距离。变量的选择会显着影响度量标准的性能,并且包含较少的相关变量的性能要优于包含许多变量的应用程序。我们的结果支持在水生和陆地环境中使用环境距离度量。

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