Random sampling is an important statistical assumption, but virtually impossible when sampling a wild species as we cannot know where all the individuals exist. While interpopulation or intrataxa sampling methods have been developed, there are currently few intrataxon sampling methods to objectively decide where to sample wild taxa. We suggest a new sampling method which computes appropriate sampling locations from coordinates, assuming geographical autocorrelation of phylogeny within a taxon (isolation‐by‐distance). The computed locations encompass the highest genetic diversity, providing a genetically representative sample. In addition, it can utilize presence/absence information during sampling to reoptimize sampling scheme. Comparing to the single existing method of the similar purpose, the merits of ours is unnecessity of environmental data resulting in easy application, and is theoretically deduced. We tested this method using published phylogeographical data. The test result was generally encouraging, but the method failed where species showed uniform genetic structure or recent distribution expansion which violate the assumption of geographical autocorrelation of phylogeny. Though simple, our method constructs a methodological and statistical foundation for sampling wild species, and is applicable to revising taxonomic study and conservation biology.

中文翻译：

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应该在哪里采样野生物种？基于距离隔离的新方法客观给出了答案。

随机抽样是一个重要的统计假设，但在对野生物种进行抽样时几乎不可能，因为我们无法知道所有个体都在哪里。虽然已经开发了种群间或分类群内采样方法，但目前很少有分类群内采样方法来客观地决定在何处对野生分类群进行采样。我们建议了一种新的采样方法，该方法从坐标计算适当的采样位置，假设分类群内系统发育的地理自相关（距离隔离）。计算出的位置包含最高的遗传多样性，提供了具有遗传代表性的样本。此外，它还可以在采样期间利用存在/不存在信息来重新优化采样方案。与同类目的的单一现有方法相比，我们的优点是不需要环境数据，易于应用，是理论上推导出来的。我们使用已发表的系统地理学数据测试了这种方法。测试结果总体上令人鼓舞，但该方法在物种表现出一致的遗传结构或最近分布扩展的情况下失败，这违反了系统发育的地理自相关假设。我们的方法虽然简单，但为野生物种采样构建了方法论和统计基础，适用于修订分类学研究和保护生物学。但该方法在物种表现出统一的遗传结构或最近分布扩展的情况下失败，这违反了系统发育的地理自相关假设。我们的方法虽然简单，但为野生物种采样构建了方法论和统计基础，适用于修订分类学研究和保护生物学。但该方法在物种表现出统一的遗传结构或最近分布扩展的情况下失败，这违反了系统发育的地理自相关假设。我们的方法虽然简单，但为野生物种采样构建了方法论和统计基础，适用于修订分类学研究和保护生物学。