Functional rarity (FR) - a feature combining a species’ rarity with the distinctiveness of its traits - represents a promising tool to better understand the ecological importance of rare species and consequently to protect functional diversity more efficiently. Yet, we lack a systematic understanding of FR on both the species level (which species are functionally rare and why) and the community level (how is FR associated with biodiversity and environmental conditions). Here, we quantify FR for 218 plant species from German hay meadows on a local, regional, and national scale by combining data from 6500 vegetation relevés and 15 ecologically relevant traits. We investigate the association between rarity and trait distinctiveness on different spatial scales via correlation measures and show which traits lead to low or high trait distinctiveness via distance-based redundancy analysis. We test how species richness and FR are correlated and use boosted regression trees to determine environmental conditions driving species richness and FR. On the local scale, only rare species showed high trait distinctiveness while on larger spatial scales rare and common species showed high trait distinctiveness. As infrequent trait attributes (e.g., legumes, low clonality) led to higher trait distinctiveness, we argue that functionally rare species are either specialists or transients. While specialists occupy a particular niche in hay meadows leading to lower rarity on larger spatial scales, transients display distinct but maladaptive traits resulting in high rarity across all spatial scales. More functionally rare species than expected by chance occurred in species-poor communities indicating that they prefer environmental conditions differing from characteristic conditions of species-rich hay meadows. Finally, we argue that functionally rare species are not necessarily relevant for nature conservation, since many were transients from surrounding habitats. Yet, FR can facilitate our understanding of why species are rare in a habitat and under which conditions these species occur.

Data in this dataset were requested from external resources and are either:
a) publicly available, or
b) not publicly available due to privacy or ethical restrictions.

Data sources and instructions to request/download the data are given in the README file.

Required software:
R (4.1.2) to load ".RData" files
RStudio to open ".R" files containing the code used to carry out the analysis