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The National Science Foundation’s Arctic Data Center is the primary data repository for NSF-funded research conducted in the Arctic. There are major challenges in discovering and interpreting resources in a repository containing data as heterogeneous and interdisciplinary as those in the Arctic Data Center. This paper reports on advances in cyberinfrastructure at the Arctic Data Center that help address these issues by leveraging semantic technologies that enhance the repository’s adherence to the FAIR data principles and improve the Findability, Accessibility, Interoperability, and Reusability of digital resources in the repository. We describe the Arctic Data Center’s improvements. We use semantic annotation to bind metadata about Arctic data sets with concepts in web-accessible ontologies. The Arctic Data Center’s implementation of a semantic annotation mechanism is accompanied by the development of an extended search interface that increases the findability of data by allowing users to search for specific, broader, and narrower meanings of measurement descriptions, as well as through their potential synonyms. Based on research carried out by the DataONE project, we evaluated the potential impact of this approach, regarding the accessibility, interoperability, and reusability of measurement data. Arctic research often benefits from having additional data, typically from multiple, heterogeneous sources, that complement and extend the bases – spatially, temporally, or thematically – for understanding Arctic phenomena. These relevant data resources must be 'found', and 'harmonized' prior to integration and analysis. The findings of a case study indicated that the semantic annotation of measurement data enhances the capabilities of researchers to accomplish these tasks. 

A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change. 

ABSTRACT Fungi play many essential roles in ecosystems. They facilitate plant access to nutrients and water, serve as decay agents that cycle carbon and nutrients through the soil, water and atmosphere, and are major regulators of macro‐organismal populations. Although technological advances are improving the detection and identification of fungi, there still exist key gaps in our ecological knowledge of this kingdom, especially related to function.Trait‐based approaches have been instrumental in strengthening our understanding of plant functional ecology and, as such, provide excellent models for deepening our understanding of fungal functional ecology in ways that complement insights gained from traditional and ‐omics‐based techniques. In this review, we synthesize current knowledge of fungal functional ecology, taxonomy and systematics and introduce a novel database of fungal functional traits (Fun^Fun). Fun^Funis built to interface with other databases to explore and predict how fungal functional diversity varies by taxonomy, guild, and other evolutionary or ecological grouping variables. To highlight how a quantitative trait‐based approach can provide new insights, we describe multiple targeted examples and end by suggesting next steps in the rapidly growing field of fungal functional ecology.