From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories

High rate of species misidentification reduces the taxonomic certainty of European biodiversity databases of ivies (Hedera L.)

The digitization of natural history specimens and the popularization of citizen science are creating an unprecedented availability of large amounts of biodiversity data. These biodiversity inventories can be severely affected by species misidentification, a source of taxonomic uncertainty that is rarely acknowledged in biodiversity data management. For these reasons, taxonomists debate the use of online repositories to address biological questions at the species level. Hedera L. (ivies) provides an excellent case study as it is well represented in both herbaria and online repositories with thousands of records likely to be affected by high taxonomic uncertainty. We analyze the sources and extent of taxonomic errors in the identification of the European ivy species by reviewing herbarium specimens and find a high misidentification rate (18% on average), which varies between species (maximized in H. hibernica: 55%; H. azorica: 48%; H. iberica: 36%) and regions (maximized in the UK: 38% and Spain: 27%). We find a systematic misidentification of all European ivies with H. helix behind the high misidentification rates in herbaria and warn of even higher rates in online records. We compile a spatial database to overcome the large discrepancies we observed in species distributions between online and morphologically reviewed records.

Bioinspire-Explore: Taxonomy-Driven Exploration of Biodiversity Data for Bioinspired Innovation

Successful bioinspired design depends on practitioners' access to biological data in a relevant form. Although multiple open-access biodiversity databases exist, their presentation is often adapted to life scientists, rather than bioinspired designers. In this paper, we present a new tool, "Bioinspire-Explore", for navigating biodiversity data in order to uncover biological systems of interest for a range of sectors. Bioinspire-Explore allows users to search for inspiring biological models via taxa (species, genera, etc.) as an entry point. It provides information on a taxon's position in the "tree of life", its distribution and climatic niche, as well as its appearance. Bioinspire-Explore also shows users connections in the bioinspiration literature between their taxon of interest and associated biological processes, habitats, and physical measurements by way of their semantic proximity. We believe Bioinspire-Explore has the potential to become an indispensable resource for both biologists and bioinspired designers in different fields.

Chemical Constituents Isolated from the Lichen Biome of Selected Species Native to North America

A lichen is a symbiotic association composed of a primary mycobionts and one or more photobionts living mutualistically together, forming a distinct morphological entity beneficial to their partnership and to other associated fungi, photobionts, and bacteria that collectively make up the lichen biome. The taxonomic identification of a lichen species often requires determination of the primary mycobiont's secondary metabolites, the key morphological characteristics of the thallus, and how it relates to other lichen species as seen in DNA phylogeny. This chapter covers lichens and their bionts, taxonomic identification, and their chemical constituents as exemplified by what is found in lichen biomes, especially those endemic to North America. Extraction and isolation, as well as updates on dereplication methods using mass spectrometric GNPS and NMR spectroscopic spin network fingerprint procedures, and marker-based techniques to identify lichens are discussed. The isolation and structure elucidation of secondary metabolites of an endolichenic Penicillium species that produces bioactive compounds will be described in detail.

A detailed workflow to develop QIIME2-formatted reference databases for taxonomic analysis of DNA metabarcoding data

Background

The DNA metabarcoding approach has become one of the most used techniques to study the taxa composition of various sample types. To deal with the high amount of data generated by the high-throughput sequencing process, a bioinformatics workflow is required and the QIIME2 platform has emerged as one of the most reliable and commonly used. However, only some pre-formatted reference databases dedicated to a few barcode sequences are available to assign taxonomy. If users want to develop a new custom reference database, several bottlenecks still need to be addressed and a detailed procedure explaining how to develop and format such a database is currently missing. In consequence, this work is aimed at presenting a detailed workflow explaining from start to finish how to develop such a curated reference database for any barcode sequence.

Results

We developed DB4Q2, a detailed workflow that allowed development of plant reference databases dedicated to ITS2 and rbcL, two commonly used barcode sequences in plant metabarcoding studies. This workflow addresses several of the main bottlenecks connected with the development of a curated reference database. The detailed and commented structure of DB4Q2 offers the possibility of developing reference databases even without extensive bioinformatics skills, and avoids ‘black box’ systems that are sometimes encountered. Some filtering steps have been included to discard presumably fungal and misidentified sequences. The flexible character of DB4Q2 allows several key sequence processing steps to be included or not, and downloading issues can be avoided. Benchmarking the databases developed using DB4Q2 revealed that they performed well compared to previously published reference datasets.

Conclusion

This study presents DB4Q2, a detailed procedure to develop custom reference databases in order to carry out taxonomic analyses with QIIME2, but also with other bioinformatics platforms if desired. This work also provides ready-to-use plant ITS2 and rbcL databases for which the prediction accuracy has been assessed and compared to that of other published databases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01067-5.

Mining rare Earth elements: Identifying the plant species most threatened by ore extraction in an insular hotspot

Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.

Species in lichen-forming fungi: balancing between conceptual and practical considerations, and between phenotype and phylogenomics

Lichens are symbiotic associations resulting from interactions among fungi (primary and secondary mycobionts), algae and/or cyanobacteria (primary and secondary photobionts), and specific elements of the bacterial microbiome associated with the lichen thallus. The question of what is a species, both concerning the lichen as a whole and its main fungal component, the primary mycobiont, has faced many challenges throughout history and has reached new dimensions with the advent of molecular phylogenetics and phylogenomics. In this paper, we briefly revise the definition of lichens and the scientific and vernacular naming conventions, concluding that the scientific, Latinized name usually associated with lichens invariably refers to the primary mycobiont, whereas the vernacular name encompasses the entire lichen. Although the same lichen mycobiont may produce different phenotypes when associating with different photobionts or growing in axenic culture, this discrete variation does not warrant the application of different scientific names, but must follow the principle "one fungus = one name". Instead, broadly agreed informal designations should be used for such discrete morphologies, such as chloromorph and cyanomorph for lichens formed by the same mycobiont but with either green algae or cyanobacteria. The taxonomic recognition of species in lichen-forming fungi is not different from other fungi and conceptual and nomenclatural approaches follow the same principles. We identify a number of current challenges and provide recommendations to address these. Species delimitation in lichen-forming fungi should not be tailored to particular species concepts but instead be derived from empirical evidence, applying one or several of the following principles in what we call the LPR approach: lineage (L) coherence vs. divergence (phylogenetic component), phenotype (P) coherence vs. divergence (morphological component), and/or reproductive (R) compatibility vs. isolation (biological component). Species hypotheses can be established based on either L or P, then using either P or L (plus R) to corroborate them. The reliability of species hypotheses depends not only on the nature and number of characters but also on the context: the closer the relationship and/or similarity between species, the higher the number of characters and/or specimens that should be analyzed to provide reliable delimitations. Alpha taxonomy should follow scientific evidence and an evolutionary framework but should also offer alternative practical solutions, as long as these are scientifically defendable. Taxa that are delimited phylogenetically but not readily identifiable in the field, or are genuinely cryptic, should not be rejected due to the inaccessibility of proper tools. Instead, they can be provisionally treated as undifferentiated complexes for purposes that do not require precise determinations. The application of infraspecific (gamma) taxonomy should be restricted to cases where there is a biological rationale, i.e., lineages of a species complex that show limited phylogenetic divergence but no evidence of reproductive isolation. Gamma taxonomy should not be used to denote discrete phenotypical variation or ecotypes not warranting the distinction at species level. We revise the species pair concept in lichen-forming fungi, which recognizes sexually and asexually reproducing morphs with the same underlying phenotype as different species. We conclude that in most cases this concept does not hold, but the actual situation is complex and not necessarily correlated with reproductive strategy. In cases where no molecular data are available or where single or multi-marker approaches do not provide resolution, we recommend maintaining species pairs until molecular or phylogenomic data are available. This recommendation is based on the example of the species pair Usnea aurantiacoatra vs. U. antarctica, which can only be resolved with phylogenomic approaches, such as microsatellites or RADseq. Overall, we consider that species delimitation in lichen-forming fungi has advanced dramatically over the past three decades, resulting in a solid framework, but that empirical evidence is still missing for many taxa. Therefore, while phylogenomic approaches focusing on particular examples will be increasingly employed to resolve difficult species complexes, broad screening using single barcoding markers will aid in placing as many taxa as possible into a molecular matrix. We provide a practical protocol how to assess and formally treat taxonomic novelties. While this paper focuses on lichen fungi, many of the aspects discussed herein apply generally to fungal taxonomy. The new combination Arthonia minor (Lücking) Lücking comb. et stat. nov. (Bas.: Arthonia cyanea f. minor Lücking) is proposed.

Biodiversity at the global scale: the synthesis continues

Traditionally, the generation and use of biodiversity data and their associated specimen objects have been primarily the purview of individuals and small research groups. While deposition of data and specimens in herbaria and other repositories has long been the norm, throughout most of their history, these resources have been accessible only to a small community of specialists. Through recent concerted efforts, primarily at the level of national and international governmental agencies over the last two decades, the pace of biodiversity data accumulation has accelerated, and a wider array of biodiversity scientists has gained access to this massive accumulation of resources, applying them to an ever-widening compass of research pursuits. We review how these new resources and increasing access to them are affecting the landscape of biodiversity research in plants today, focusing on new applications across evolution, ecology, and other fields that have been enabled specifically by the availability of these data and the global scope that was previously beyond the reach of individual investigators. We give an overview of recent advances organized along three lines: broad-scale analyses of distributional data and spatial information, phylogenetic research circumscribing large clades with comprehensive taxon sampling, and data sets derived from improved accessibility of biodiversity literature. We also review synergies between large data resources and more traditional data collection paradigms, describe shortfalls and how to overcome them, and reflect on the future of plant biodiversity analyses in light of increasing linkages between data types and scientists in our field.

Data integration enables global biodiversity synthesis

The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world's largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

The Global Museum: natural history collections and the future of evolutionary science and public education

Natural history museums are unique spaces for interdisciplinary research and educational innovation. Through extensive exhibits and public programming and by hosting rich communities of amateurs, students, and researchers at all stages of their careers, they can provide a place-based window to focus on integration of science and discovery, as well as a locus for community engagement. At the same time, like a synthesis radio telescope, when joined together through emerging digital resources, the global community of museums (the ‘Global Museum’) is more than the sum of its parts, allowing insights and answers to diverse biological, environmental, and societal questions at the global scale, across eons of time, and spanning vast diversity across the Tree of Life. We argue that, whereas natural history collections and museums began with a focus on describing the diversity and peculiarities of species on Earth, they are now increasingly leveraged in new ways that significantly expand their impact and relevance. These new directions include the possibility to ask new, often interdisciplinary questions in basic and applied science, such as in biomimetic design, and by contributing to solutions to climate change, global health and food security challenges. As institutions, they have long been incubators for cutting-edge research in biology while simultaneously providing core infrastructure for research on present and future societal needs. Here we explore how the intersection between pressing issues in environmental and human health and rapid technological innovation have reinforced the relevance of museum collections. We do this by providing examples as food for thought for both the broader academic community and museum scientists on the evolving role of museums. We also identify challenges to the realization of the full potential of natural history collections and the Global Museum to science and society and discuss the critical need to grow these collections. We then focus on mapping and modelling of museum data (including place-based approaches and discovery), and explore the main projects, platforms and databases enabling this growth. Finally, we aim to improve relevant protocols for the long-term storage of specimens and tissues, ensuring proper connection with tomorrow’s technologies and hence further increasing the relevance of natural history museums.

Climate Change, Bioclimatic Models and the Risk to Lichen Diversity

This paper provides an overview of bioclimatic models applied to lichen species, supporting their potential use in this context as indicators of climate change risk. First, it provides a brief summary of climate change risk, pointing to the relevance of lichens as a topic area. Second, it reviews the past use of lichen bioclimatic models, applied for a range of purposes with respect to baseline climate, and the application of data sources, statistical methods, model extents and resolution and choice of predictor variables. Third, it explores additional challenges to the use of lichen bioclimatic models, including: 1. The assumption of climatically controlled lichen distributions, 2. The projection to climate change scenarios, and 3. The issue of nonanalogue climates and model transferability. Fourth, the paper provides a reminder that bioclimatic models estimate change in the extent or range of a species suitable climate space, and that an outcome will be determined by vulnerability responses, including potential for migration, adaptation, and acclimation, within the context of landscape habitat quality. The degree of exposure to climate change, estimated using bioclimatic models, can help to inform an understanding of whether vulnerability responses are sufficient for species resilience. Fifth, the paper draws conclusions based on its overview, highlighting the relevance of bioclimatic models to conservation, support received from observational data, and pointing the way towards mechanistic approaches that align with field-scale climate change experiments.

The history and impact of digitization and digital data mobilization on biodiversity research

The first two decades of the twenty-first century have seen a rapid rise in the mobilization of digital biodiversity data. This has thrust natural history museums into the forefront of biodiversity research, underscoring their central role in the modern scientific enterprise. The advent of mobilization initiatives such as the United States National Science Foundation's Advancing Digitization of Biodiversity Collections (ADBC), Australia's Atlas of Living Australia (ALA), Mexico's National Commission for the Knowledge and Use of Biodiversity (CONABIO), Brazil's Centro de Referência em Informação (CRIA) and China's National Specimen Information Infrastructure (NSII) has led to a rapid rise in data aggregators and an exponential increase in digital data for scientific research and arguably provide the best evidence of where species live. The international Global Biodiversity Information Facility (GBIF) now serves about 131 million museum specimen records, and Integrated Digitized Biocollections (iDigBio) in the USA has amassed more than 115 million. These resources expose collections to a wider audience of researchers, provide the best biodiversity data in the modern era outside of nature itself and ensure the primacy of specimen-based research. Here, we provide a brief history of worldwide data mobilization, their impact on biodiversity research, challenges for ensuring data quality, their contribution to scientific publications and evidence of the rising profiles of natural history collections.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.

Contrasting spatial, temporal and environmental patterns in observation and specimen based species occurrence data

Species occurrence data records the location and time of an encounter with a species, and is valuable for many aspects of ecological and evolutionary analyses. A key distinction within species occurrence data is between (1) collected and preserved specimens that can be taxonomically validated (i.e., natural history collections), and (2) observations, which are more error prone but richer in terms of number and spread of observations. In this study we analyse the distribution in temporal, spatial, taxonomic and environmental coverage of specimen- and observation based species occurrence data for land plants in Norway, a region with strong climatic and human population density gradients. Of 4.8 million species occurrence records, the majority (78%) were observations. However, there was a greater species richness in the specimen record (N = 4691) than in the observation record (N = 3193) and most species were recorded more as specimens than observations. Specimen data was on average older, and collected later during the year. Both record types were highly influenced by a small number of prolific contributors. The species most highly represented in the observation data set were widespread or invasive, while in the specimen records, taxonomically challenging species were overrepresented. Species occurrence records were unevenly spatially distributed. Both specimen and observation records were concentrated in regions of Norway with high human population density and with high temperatures and precipitation, but in different regions within Norway. Observation and specimen records thus differ in taxonomic, temporal, spatial and environmental coverage for a well-sampled group and study region, potentially influencing the ecological inferences made from studies utilizing species occurrence data. The distribution of observation data dominates the dataset, so inferences of species diversity and distributions do not correspond to the evolutionary or physiological knowledge of species, which is based on specimen data. We make recommendations for users of biodiversity data, and collectors to better exploit the complementary strengths of these distinct biodiversity data types.

To increase trust, change the social design behind aggregated biodiversity data

Growing concerns about the quality of aggregated biodiversity data are lowering trust in large-scale data networks. Aggregators frequently respond to quality concerns by recommending that biologists work with original data providers to correct errors 'at the source.' We show that this strategy falls systematically short of a full diagnosis of the underlying causes of distrust. In particular, trust in an aggregator is not just a feature of the data signal quality provided by the sources to the aggregator, but also a consequence of the social design of the aggregation process and the resulting power balance between individual data contributors and aggregators. The latter have created an accountability gap by downplaying the authorship and significance of the taxonomic hierarchies-frequently called 'backbones'-they generate, and which are in effect novel classification theories that operate at the core of data-structuring process. The Darwin Core standard for sharing occurrence records plays an under-appreciated role in maintaining the accountability gap, because this standard lacks the syntactic structure needed to preserve the taxonomic coherence of data packages submitted for aggregation, potentially leading to inferences that no individual source would support. Since high-quality data packages can mirror competing and conflicting classifications, i.e. unsettled systematic research, this plurality must be accommodated in the design of biodiversity data integration. Looking forward, a key directive is to develop new technical pathways and social incentives for experts to contribute directly to the validation of taxonomically coherent data packages as part of a greater, trustworthy aggregation process.