Premise With digitization and data sharing initiatives underway over the last 15 years, an important need has been prioritizing specimens to digitize. Because duplicate specimens are shared among herbaria in exchange and gift programs, we investigated the extent to which unique biogeographic data are held in small herbaria vs. these data being redundant with those held by larger institutions. We evaluated the unique specimen contributions that small herbaria make to biogeographic understanding at county, locality, and temporal scales. Methods We sampled herbarium specimens of 40 plant taxa from each of eight states of the United States of America in four broad status categories: extremely rare, very rare, common native, and introduced. We gathered geographic information from specimens held by large (≥100,000 specimens) and small (<100,000 specimens) herbaria. We built generalized linear mixed models to assess which features of the collections may best predict unique contributions of herbaria and used an Akaike information criterion‐based information‐theoretic approach for our model selection to choose the best model for each scale. Results Small herbaria contributed unique specimens at all scales in proportion with their contribution of specimens to our data set. The best models for all scales were the full models that included the factors of species status and herbarium size when accounting for state as a random variable. Conclusions We demonstrated that small herbaria contribute unique information for research. It is clear that unique contributions cannot be predicted based on herbarium size alone. We must prioritize digitization and data sharing from herbaria of all sizes.

中文翻译：

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小型植物标本​​馆为县、地区和时间尺度提供独特的生物地理记录

前提 随着数字化和数据共享计划在过去 15 年中进行，一个重要的需求是优先考虑标本的数字化。因为在交换和礼物计划中，标本馆之间共享重复的标本，我们调查了小型标本馆中保存的独特生物地理数据的程度与这些数据与大型机构保存的数据冗余的程度。我们评估了小型植物标本​​馆对县、地区和时间尺度上的生物地理理解的独特标本贡献。方法 我们从美利坚合众国八个州中的每一个州抽取了 40 种植物分类群的标本馆标本，分为四大类：极其稀有、非常稀有、普通本地和引进。我们从大型（≥100,000 个标本）和小型（<100, 000 个标本）标本馆。我们建立了广义线性混合模型来评估集合的哪些特征可以最好地预测植物标本的独特贡献，并使用基于 Akaike 信息标准的信息理论方法进行模型选择，为每个尺度选择最佳模型。结果小型植物标本​​馆在所有尺度上贡献了独特的标本，与它们对我们的数据集的标本贡献成比例。所有尺度的最佳模型是包含物种状态和植物标本馆大小因素的完整模型，当将状态考虑为随机变量时。结论 我们证明了小型植物标本​​馆为研究提供了独特的信息。很明显，仅根据植物标本馆的大小无法预测独特的贡献。我们必须优先考虑各种规模的植物标本馆的数字化和数据共享。