Declustering aims to divide earthquake catalogs into independent events (mainshocks), and dependent (clustered) events, and is an integral component of many seismicity studies, including seismic hazard assessment. We assess the effect of declustering on the frequency–magnitude distribution of mainshocks. In particular, we examine the dependence of the b‐value of declustered catalogs on the choice of declustering approach and algorithm‐specific parameters. Using the catalog of earthquakes in California since 1980, we show that the b‐value decreases by up to 30% due to declustering with respect to the undeclustered catalog. The extent of the reduction is highly dependent on the declustering method and parameters applied. We then reproduce a similar effect by declustering synthetic earthquake catalogs with known b‐value, which have been generated using an epidemic‐type aftershock sequence model. Our analysis suggests that the observed decrease in b‐value must, at least partially, arise from the application of the declustering algorithm on the catalog, rather than from differences in the nature of mainshocks versus fore‐ or aftershocks. We conclude that declustering should be considered as a potential source of bias in seismicity and hazard studies.

中文翻译：

---

分簇对主震大小分布的影响

去聚类旨在将地震目录划分为独立事件（主震）和相关（聚类）事件，并且是许多地震活动性研究（包括地震危险性评估）的组成部分。我们评估了去聚类对主震频率-震级分布的影响。特别是，我们检查了去聚类目录的 b 值对去聚类方法和算法特定参数选择的依赖性。使用自 1980 年以来加利福尼亚州的地震目录，我们表明由于相对于未分簇的目录进行分簇，b 值下降了 30%。减少的程度在很大程度上取决于应用的去聚类方法和参数。然后我们通过对已知 b 值的合成地震目录进行去聚类来重现类似的效果，这些是使用流行型余震序列模型生成的。我们的分析表明，观察到的 b 值的下降至少部分是由于在目录上应用了去聚类算法，而不是由于主震与前震或余震的性质不同。我们得出的结论是，在地震活动性和灾害研究中，应该将去聚类视为潜在的偏差来源。