Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.

中文翻译：

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occTest：物种发生数据质量控制的综合方法


物种出现数据是有价值的信息，使人们能够估计地理分布、描述生态位及其演化特征并指导空间保护规划。物种发生数据的快速增加源于不断增加的数字化和聚合工作以及公民科学举措。然而，事件数据中持续存在的质量问题可能会影响科学发现的准确性，这凸显了在生物多样性分析中过滤错误事件记录的重要性。