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Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome‐scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data‐sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever. [ABSTRACT FROM AUTHOR]

Aim: Species occurrence records are essential to understanding Earth's biodiversity and addressing global environmental issues, but do not always reflect actual locations of occurrence. Certain geographical coordinates are assigned repeatedly to thousands of observation/collection records. This may result from imperfect data management and georeferencing practices, and can greatly bias the inferred distribution of biodiversity and associated environmental conditions. Nonetheless, these 'biodiverse' coordinates are often overlooked in taxon‐centric studies, as they are identifiable only in aggregate across taxa and datasets, and it is difficult to determine their true circumstance without in‐depth, focused investigation. Here we assess highly recurring coordinates in biodiversity data to determine artificial hotspots of occurrences. Location: Global. Taxon: Land plants, birds, mammals, insects. Methods: We identified highly recurring coordinates across plant, bird, insect and mammal records in the Global Biodiversity Information Facility, the largest aggregator of biodiversity data. We determined which are likely artificial hotspots by examining metadata from over 40 million records, assessing spatial distributions of associated datasets, contacting data managers and reviewing literature. These results were compiled into the Artificial Hotspot Occurrence Inventory (AHOI). Results: Artificial biodiversity hotspots generally comprised geopolitical and grid centroids. The associated uncertainty ranged from several square kilometres to millions. Such artificial biodiversity hotspots were most prevalent in plant records. For instance, over 100,000 plant occurrence records were assigned the centroid coordinates of Brazil, and points that have at least 1000 associated occurrences comprised over 9 million records. In contrast, highly recurring coordinates in animal data more often reflected actual sites of observation. Main conclusions AHOI can be used to (i) improve accuracy of biodiversity assessments; (ii) estimate uncertainty associated with records from artificial hotspots and make informed decisions on whether to include them in scientific studies; and (iii) identify problems in biodiversity informatics workflows and priorities for improvement. [ABSTRACT FROM AUTHOR]

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well‐being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within‐species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (Ne). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large‐scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long‐term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally. [ABSTRACT FROM AUTHOR]

The complete tree of life is now available, but methods to visualise it are still needed to meet needs in research, teaching and science communication. Dynamic visualisation of million‐tip trees requires many challenges in data synthesis, data handling and computer graphics to be overcome.Our approach is to automate data processing, synthesise data from a wide range of available sources, then to feed these data to a client‐side visualisation engine in parts. We develop a way to store the whole tree topology locally in a highly compressed form, then dynamically populate metadata such as text and images as the user explores.The result is a seamless and smooth way to explore the complete tree of life, including images and metadata, even on relatively old mobile devices.The underlying methods developed have applications that transcend tree of life visualisation. For the whole complete tree, we describe automated ID mappings between well known resources without resorting to taxonomic name resolution, automated methods to collate sets of public domain representative images for higher taxa, and an index to measure public interest of individual species.The visualisation layout and the client user interface are both abstracted components of the codebase enabling other zoomable tree layouts to be swapped in, and supporting multiple applications including exhibition kiosks and digital art.After 10 years of work, our tree of life explorer is now broadly complete, it has attracted nearly 1.5 million online users, and is backed by a novel long‐term sustainability plan. We conclude our description of the OneZoom project by suggesting the next challenges that need to be solved in this field: extinct species and guided tours around the tree. [ABSTRACT FROM AUTHOR]