Pollen data are widely used to reconstruct past climate changes, using relationships between modern pollen abundance in surface samples and climate at the surface-sample sites as a calibration. Visualisation of modern pollen data in multi-dimensional climate space provides a way to establish that taxon abundances are well behaved before using them in climate reconstructions. Visualisation is also helpful for ecological interpretation of variations in pollen abundance in space and time. Here we present Generalized Additive Models for the distribution of 195 European pollen and pteridophyte spore taxa in a bioclimate space defined by seasonal temperatures (as mean temperature of the coldest month and annual growing degree days) and an annual moisture index. These models can be used to explore the realised climate niche of pollen taxa and to build statistical models for palaeoclimate reconstruction. The data set is released under a Creative Commons BY licence. When using the data set, we kindly request that you cite this article.

中文翻译：

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欧洲花粉类群的气候空间

花粉数据被广泛用于重建过去的气候变化，使用地表样本中现代花粉丰度与地表样本点气候之间的关系作为校准。多维气候空间中现代花粉数据的可视化提供了一种方法，可以在将分类群用于气候重建之前确定它们的丰度表现良好。可视化也有助于对花粉丰度在空间和时间上的变化进行生态解释。在这里，我们展示了 195 种欧洲花粉和蕨类植物孢子分类群在由季节性温度（最冷月份的平均温度和年度生长期日数）和年度水分指数定义的生物气候空间中分布的广义加性模型。这些模型可用于探索已实现的花粉类群气候生态位，并为古气候重建建立统计模型。该数据集是在知识共享许可下发布的。在使用数据集时，我们恳请您引用这篇文章。