Background Morphological leaf traits are frequently used to quantify, understand and predict plant and vegetation functional diversity and ecology, including environmental and climate change responses. Although morphological leaf traits are easy to measure, their coverage for characterising variation within species and across temporal scales is limited. At the same time, there are about 3100 herbaria worldwide, containing approximately 390 million plant specimens dating from the 16th to 21st century, which can potentially be used to extract morphological leaf traits. Globally, plant specimens are rapidly being digitised and images are made openly available via various biodiversity data platforms, such as iDigBio and GBIF. Based on a pilot study to identify the availability and appropriateness of herbarium specimen images for comprehensive trait data extraction, we developed a spatio-temporal dataset on intraspecific trait variability containing 128,036 morphological leaf trait measurements for seven selected species. New information After scrutinising the metadata of digitised herbarium specimen images available from iDigBio and GBIF (21.9 million and 31.6 million images for Tracheophyta; accessed date December 2020), we identified approximately 10 million images potentially appropriate for our study. From the 10 million images, we selected seven species (Salix bebbiana Sarg., Alnus incana (L.) Moench, Viola canina L., Salix glauca L., Chenopodium album L., Impatiens capensis Meerb. and Solanum dulcamara L.) , which have a simple leaf shape, are well represented in space and time and have high availability of specimens per species. We downloaded 17,383 images. Out of these, we discarded 5779 images due to quality issues. We used the remaining 11,604 images to measure the area, length, width and perimeter on 32,009 individual leaf blades using the semi-automated tool TraitEx. The resulting dataset contains 128,036 trait records. We demonstrate its comparability to trait data measured in natural environments following standard protocols by comparing trait values from the TRY database. We conclude that the herbarium specimens provide valuable information on leaf sizes. The dataset created in our study, by extracting leaf traits from the digitised herbarium specimen images of seven selected species, is a promising opportunity to improve ecological knowledge about the adaptation of size-related leaf traits to environmental changes in space and time.

中文翻译：

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来自超过两个世纪的数字化植物标本图像的七种植物的综合叶片大小特征数据集

背景 形态叶特征经常用于量化、理解和预测植物和植被功能多样性和生态学，包括环境和气候变化响应。尽管形态叶特征很容易测量，但它们在表征物种内和跨时间尺度上的变异的覆盖范围是有限的。同时，全球约有 3100 个植物标本馆，包含约 3.9 亿个 16 至 21 世纪的植物标本，可用于提取叶片形态特征。在全球范围内，植物标本正在迅速数字化，图像通过各种生物多样性数据平台（如 iDigBio 和 GBIF）公开提供。基于一项初步研究，以确定植物标本图像用于综合性状数据提取的可用性和适用性，我们开发了一个关于种内性状变异性的时空数据集，其中包含 7 个选定物种的 128,036 个形态叶性状测量值。新信息 在仔细检查了 iDigBio 和 GBIF 提供的数字化植物标本图像的元数据（2190 万和 3160 万张气管植物图像；访问日期为 2020 年 12 月）后，我们确定了大约 1000 万张可能适合我们研究的图像。从 1000 万张图像中，我们选择了 7 个物种（Salix bebbiana Sarg.、Alnus incana (L.) Moench、Viola canina L.、Salix glauca L.、Chenopodium album L.、Impatiens capensis Meerb.和 Solanum dulcamara L.），它有一个简单的叶子形状，在空间和时间上都有很好的代表性，并且每个物种的标本可用性很高。我们下载了 17,383 张图片。其中，由于质量问题，我们丢弃了 5779 张图像。我们使用半自动工具 TraitEx 使用剩余的 11,604 张图像来测量 32,009 个单独叶片的面积、长度、宽度和周长。结果数据集包含 128,036 条特征记录。我们通过比较 TRY 数据库中的特征值来证明其与遵循标准协议在自然环境中测量的特征数据的可比性。我们得出结论，植物标本室提供了有关叶子大小的有价值的信息。我们研究中创建的数据集，通过从七个选定物种的数字化植物标本图像中提取叶子特征，