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      Integrating Biodiversity Infrastructure into Pathogen Discovery and Mitigation of Emerging Infectious Diseases

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          Abstract

          The global human suffering, economic damage, and social disruption we are currently experiencing from the COVID-19 pandemic stem from inadequate preparedness and ineffective response to emerging pathogens. At its core, the COVID-19 pandemic is a consequence of our fundamental ignorance of our planet's natural ecosystems and the effects of our encroachment on them. Our reactive approaches to the emergence of zoonotic pathogens, which are responsible for approximately 75% of all new emerging infectious disease outbreaks, are too often based on limited knowledge of the origin, pathogenicity, and basic biology of the wild host and pathogen coupled with poor communication among relevant stakeholders. Others have pointed to this ignorance of viral diversity and offered solutions (Andersen et al. 2020), but a broad, fully integrative discussion of how to leverage existing infrastructure and to build new resources has been missing. In the present article, we call for the development of alternative tactics that are aimed at proactively meeting the daunting challenges to humanity posed by emerging zoonotic pathogens. The potential role of natural history specimens in pathogen discovery and mitigation is recognized in the museum world (DiEuliis et al. 2016, Dunnum et al. 2017) and by at least some disease ecologists (e.g., Mills and Childs 1998). However, relatively few in the One Health community (e.g., Kelly et al. 2020) embrace the value of leveraging existing biodiversity infrastructure (i.e., natural history collections, biorepositories, and their associated expertise and informatics resources) to more fully understand zoonotic pathogen emergence and reemergence. This concept is not new; in the early 1900 s, the American Museum of Natural History created the Department of Public Health (Brown 2014). Although a lack of funding put an early end to the initiative, the Department of Public Health made extensive progress, from clever exhibitions for the public to assembling a living collection of bacterial cultures (Brown 2014). Renewed efforts to align pathobiology with biodiversity discovery initiatives are critical. Moreover, linking both biodiversity infrastructure and building capacity closer to zoonotic pathogen surveys in biodiverse countries would substantially improve proactive responses to pandemics before they once again wreak havoc across the globe. Biodiversity science as a tool in biomedical research and response Earth's biodiversity is connected through a single evolutionary tree of life, and pathogens (whether viruses, bacteria, or eukaryotes) and their hosts represent millions of years of evolutionary interactions. Medical researchers have long used this knowledge to advance our understanding of how certain microbes cause disease in humans. For example, because fundamental aspects of malaria parasitism are extremely difficult to study in humans, New World monkeys—­particularly, owl monkeys in the genus Aotus—have been important models for studying strains of malaria to develop vaccines, some of which are now in clinical trials. Taxonomic research based on museum specimens (Hershkovitz 1983) demonstrated that geographically separated species of owl monkeys have varying tolerance to the parasite and that the failure to recognize these taxonomic differences can hamper research. We have only begun to understand how widespread and diverse coronaviruses are in nature, and important gaps in regional and phylogenetic coverage persist (Anthony et al. 2017). Understanding their functional interactions with host cells and developing the most effective strategies to combat pathogenic coronaviruses will require documenting genetic relationships of the virus and among the wild hosts (Andersen et al. 2020). Archiving these associations in accessible and curated specimen databases is crucial now and into the future (e.g., www.globalbioticinteractions.org). Building on a solid foundation of knowledge of evolutionary and ecological relationships of hosts and pathogens enables scientists to possibly predict the emergence of future zoonotic diseases and to respond to novel outbreaks more rapidly and efficiently (Brooks et al. 2019). The need to strengthen biodiversity infrastructure and increase discovery The detection and description of novel pathogens usually requires large numbers of host samples because of low prevalence (Plowright et al. 2019). The world's natural history collections contain more than 3 billion specimens. Although the vast majority of these specimens may not be suitable for pathogen discovery, specimens provide a powerful roadmap to the spatial and temporal distribution of global biodiversity. A growing trend in many museums (e.g., www.idigbio.org/content/dna-banks-and-genetic-resources-repositories-united-states, www.ggbn.org) is the establishment of cryopreserved biorepositories, including vertebrate samples that often preserve associated parasites. These collections represent multiple, diverse host samples archived broadly across space and time that could readily be probed for pathogens. More commonly, however, novel pathogen discovery involves field surveys of wild hosts. Unless a particular pathogen is targeted, survey strategies that focus on taxonomically diverse species across spatially broad distributions provide the best opportunities for detection. Typically, field surveys of terrestrial vertebrates are noninvasive (using swabs or fecal samples) and do not produce archived specimens, so they rarely contribute to the shared biodiversity infrastructure of the world's scientific community. By instead linking these field surveys to permanent natural history collections, future pathogen discovery would be connected more broadly to other avenues of biodiversity research and naturally promote integration and synergy across scientific disciplines. An additional benefit from closer ties between pathobiology and natural history collections involves the voucher concept. Biodiversity studies, when possible, should be backed by a permanent sample or voucher, which would facilitate replication and validation, extension, and integration across disciplines (Cook et al. 2016, Lendemer et al. 2020). To date, few of the published nonhuman betacoronavirus sequences are tied to a permanent sample that would allow implementation of these central tenets of the scientific method (but see Joffrin et al. 2020). A change in practice, through improved communication between biodiversity and biomedical scientists, would both enhance the quality of any data collected from the pathogen and add value by enabling future analyses of the genotype, phenotype, and interactions of the same pathogen source. In addition to serving as permanent archives and providing samples for research, natural history collections and their associated biorepositories provide expertise in taxonomy, identification, phylogenetics, niche modeling, evolutionary dynamics, and other knowledge critical to pathogen monitoring, mitigation, and control. In the past few decades, museums have become hubs of biodiversity informatics, serving as the critical nexus between biological samples and sample-derived data (e.g., genomics, geographic information, isotope chemistry, CT scans). The current pandemic reminds us that natural history specimens are important but underappreciated reservoirs for studying the hosts and distributions of animal and human pathogens (see Harmon et al. 2019) and that the data connected to these specimens increase our understanding not only of the host organism but of the pathogens as well. Enhanced support of both physical and cyberinfrastructure for biodiversity collections would yield an information system to enable prediction and mitigation of future outbreaks and pandemics. The most biodiverse places on the planet occur in developing countries, so there is a huge need to develop local and regional capacity and scientific expertise in biodiversity research and collections. International scientific partnerships aiming to increase research transfer and building local capacity will help to match resources and technology available in developed countries. Therefore, it will facilitate early detection and mitigation in front of an outbreak. Given the tremendous need to understand how human-mediated loss of biodiversity and transformation of natural ecosystems will affect human health, building human capacity and strengthening ties between research and clinical infrastructure in developing countries is imperative. Informatics as a tool for disseminating knowledge Natural history institutions have produced extensive digital data and continue to digitize information from their physical collections. Online scientific databases (e.g., iDigBio, GBIF, VertNet, Arctos, Atlas of Living Australia, SpeciesLink) serve as portals to natural history archives, offering researchers around the world access to data and metadata (including linked genetic, environmental, and other information) associated with vouchered specimens. Furthermore, the development of this cyber-enabled information system is crucial for understanding our natural world and the relationships between biodiversity and human health. Connecting natural history archives and pathobiology is not only necessary but easier to achieve today than ever before. For example, free, online access to global specimen data provides efficient opportunities for loans of physical specimens from museums to biomedical laboratories for analysis of pathogens. Surprisingly, the robust cyberinfrastructure supporting living stock collections—which make viral, bacterial, and other pathogen lines and samples available to the biomedical research community—is not connected to that of natural history collections. These communities are only vaguely aware of each other's resources, despite obvious benefits for both basic and clinical research. However, a clear, long-term pathway must be implemented so that pathobiologists are fully aware of the varied resources available in natural history collections and can use and contribute to these resources. A new vision for predicting and responding to pandemics The twenty-first century has already seen multiple major new disease ­outbreaks—from SARS and MERS to Ebola and Zika—culminating in the current COVID-19 pandemic. What have we learned from these events, and how do we harness that knowledge for prediction and response? Ongoing encroachment by humans into natural ecosystems will continue to promote contact with potential pathogens. Absent global cooperation to restrict further habitat degradation and eliminate illegal wildlife trade, we need new approaches to gather, share, and interpret data and knowledge for deployment in preventing, predicting, and responding to future pandemics. We suggest five key elements as a framework for research and future resilience. Best practices must be developed for sample preparation. Biodiversity scientists, collections managers, disease ecologists, and microbiologists must converge on common guidelines for sampling, preserving, and archiving samples of both pathogens and hosts to ensure reproducible science and future access to samples studied in a particular context. Vouchering of host materials and pathogen preparations will require expanded capabilities in natural history collections and biorepositories, and cooperation among communities will be needed to ensure space and adequate curation of materials. Metadata requirements must be developed to accompany the physical specimens and samples collected, analyzed, and archived. The essential elements will be the application of universally unique identifiers for all specimens and their derivative products—including tissues, pathogen preparations, genetic sequences, and beyond. Again, communication among communities, including museum personnel, biomedical researchers, and personnel at global genetic databases, will be crucial for identifying and adopting metadata that will enhance the value of biological materials. Infrastructure, both physical and cyber, is required to support both current and future biological materials, whether in natural history collections, living stock collections, or other biorepositories. Because our knowledge of potential emerging pathogens is so limited and because the pathogens themselves evolve and diversify, we recommend expanded collection of field samples of organisms that are likely reservoirs of zoonotic diseases and other associated possible hosts. The preparation of these materials following the first element above will require expanded capacity and implementation of new curation methods in many institutions. Likewise, further investment in cyberinfrastructure to link together all known data and knowledge related to specimens, genetics, environment, literature, and more would enhance responses to future disease outbreaks. Perhaps the most important but most difficult element is the adoption and implementation of practices that change how a community conducts its science. We endorse open science concepts and practice and advocate increased communication and the development of new channels of dialogue and collaboration. This is particularly relevant within the integrative approaches to health that have increasingly become adopted, because they draw from multiple contributing sciences and sectors (Lerner and Berg 2017). The implementation of these elements requires strong leadership and financial support from a range of federal agencies, international partners, and private foundations worldwide to provide infrastructure and enable development of proactive approaches to future pandemics. Because the assets and returns are substantial for science, policy, and human well-being alike, we recommend that both research funders and the providers of official development aid engage in this effort. Such investment, even on the scale needed to accomplish the goals outlined in the present article, would be inconsequential compared to the loss of life and the economic catastrophe brought by COVID-19. Many of the pieces of our emerging vision are already in place, but a more resilient and integrated initiative that leverages and builds existing biodiversity infrastructure is critically needed.

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          The proximal origin of SARS-CoV-2

          To the Editor — Since the first reports of novel pneumonia (COVID-19) in Wuhan, Hubei province, China 1,2 , there has been considerable discussion on the origin of the causative virus, SARS-CoV-2 3 (also referred to as HCoV-19) 4 . Infections with SARS-CoV-2 are now widespread, and as of 11 March 2020, 121,564 cases have been confirmed in more than 110 countries, with 4,373 deaths 5 . SARS-CoV-2 is the seventh coronavirus known to infect humans; SARS-CoV, MERS-CoV and SARS-CoV-2 can cause severe disease, whereas HKU1, NL63, OC43 and 229E are associated with mild symptoms 6 . Here we review what can be deduced about the origin of SARS-CoV-2 from comparative analysis of genomic data. We offer a perspective on the notable features of the SARS-CoV-2 genome and discuss scenarios by which they could have arisen. Our analyses clearly show that SARS-CoV-2 is not a laboratory construct or a purposefully manipulated virus. Notable features of the SARS-CoV-2 genome Our comparison of alpha- and betacoronaviruses identifies two notable genomic features of SARS-CoV-2: (i) on the basis of structural studies 7–9 and biochemical experiments 1,9,10 , SARS-CoV-2 appears to be optimized for binding to the human receptor ACE2; and (ii) the spike protein of SARS-CoV-2 has a functional polybasic (furin) cleavage site at the S1–S2 boundary through the insertion of 12 nucleotides 8 , which additionally led to the predicted acquisition of three O-linked glycans around the site. 1. Mutations in the receptor-binding domain of SARS-CoV-2 The receptor-binding domain (RBD) in the spike protein is the most variable part of the coronavirus genome 1,2 . Six RBD amino acids have been shown to be critical for binding to ACE2 receptors and for determining the host range of SARS-CoV-like viruses 7 . With coordinates based on SARS-CoV, they are Y442, L472, N479, D480, T487 and Y4911, which correspond to L455, F486, Q493, S494, N501 and Y505 in SARS-CoV-2 7 . Five of these six residues differ between SARS-CoV-2 and SARS-CoV (Fig. 1a). On the basis of structural studies 7–9 and biochemical experiments 1,9,10 , SARS-CoV-2 seems to have an RBD that binds with high affinity to ACE2 from humans, ferrets, cats and other species with high receptor homology 7 . Fig. 1 Features of the spike protein in human SARS-CoV-2 and related coronaviruses. a, Mutations in contact residues of the SARS-CoV-2 spike protein. The spike protein of SARS-CoV-2 (red bar at top) was aligned against the most closely related SARS-CoV-like coronaviruses and SARS-CoV itself. Key residues in the spike protein that make contact to the ACE2 receptor are marked with blue boxes in both SARS-CoV-2 and related viruses, including SARS-CoV (Urbani strain). b, Acquisition of polybasic cleavage site and O-linked glycans. Both the polybasic cleavage site and the three adjacent predicted O-linked glycans are unique to SARS-CoV-2 and were not previously seen in lineage B betacoronaviruses. Sequences shown are from NCBI GenBank, accession codes MN908947, MN996532, AY278741, KY417146 and MK211376. The pangolin coronavirus sequences are a consensus generated from SRR10168377 and SRR10168378 (NCBI BioProject PRJNA573298) 29,30 . While the analyses above suggest that SARS-CoV-2 may bind human ACE2 with high affinity, computational analyses predict that the interaction is not ideal 7 and that the RBD sequence is different from those shown in SARS-CoV to be optimal for receptor binding 7,11 . Thus, the high-affinity binding of the SARS-CoV-2 spike protein to human ACE2 is most likely the result of natural selection on a human or human-like ACE2 that permits another optimal binding solution to arise. This is strong evidence that SARS-CoV-2 is not the product of purposeful manipulation. 2. Polybasic furin cleavage site and O-linked glycans The second notable feature of SARS-CoV-2 is a polybasic cleavage site (RRAR) at the junction of S1 and S2, the two subunits of the spike 8 (Fig. 1b). This allows effective cleavage by furin and other proteases and has a role in determining viral infectivity and host range 12 . In addition, a leading proline is also inserted at this site in SARS-CoV-2; thus, the inserted sequence is PRRA (Fig. 1b). The turn created by the proline is predicted to result in the addition of O-linked glycans to S673, T678 and S686, which flank the cleavage site and are unique to SARS-CoV-2 (Fig. 1b). Polybasic cleavage sites have not been observed in related ‘lineage B’ betacoronaviruses, although other human betacoronaviruses, including HKU1 (lineage A), have those sites and predicted O-linked glycans 13 . Given the level of genetic variation in the spike, it is likely that SARS-CoV-2-like viruses with partial or full polybasic cleavage sites will be discovered in other species. The functional consequence of the polybasic cleavage site in SARS-CoV-2 is unknown, and it will be important to determine its impact on transmissibility and pathogenesis in animal models. Experiments with SARS-CoV have shown that insertion of a furin cleavage site at the S1–S2 junction enhances cell–cell fusion without affecting viral entry 14 . In addition, efficient cleavage of the MERS-CoV spike enables MERS-like coronaviruses from bats to infect human cells 15 . In avian influenza viruses, rapid replication and transmission in highly dense chicken populations selects for the acquisition of polybasic cleavage sites in the hemagglutinin (HA) protein 16 , which serves a function similar to that of the coronavirus spike protein. Acquisition of polybasic cleavage sites in HA, by insertion or recombination, converts low-pathogenicity avian influenza viruses into highly pathogenic forms 16 . The acquisition of polybasic cleavage sites by HA has also been observed after repeated passage in cell culture or through animals 17 . The function of the predicted O-linked glycans is unclear, but they could create a ‘mucin-like domain’ that shields epitopes or key residues on the SARS-CoV-2 spike protein 18 . Several viruses utilize mucin-like domains as glycan shields involved immunoevasion 18 . Although prediction of O-linked glycosylation is robust, experimental studies are needed to determine if these sites are used in SARS-CoV-2. Theories of SARS-CoV-2 origins It is improbable that SARS-CoV-2 emerged through laboratory manipulation of a related SARS-CoV-like coronavirus. As noted above, the RBD of SARS-CoV-2 is optimized for binding to human ACE2 with an efficient solution different from those previously predicted 7,11 . Furthermore, if genetic manipulation had been performed, one of the several reverse-genetic systems available for betacoronaviruses would probably have been used 19 . However, the genetic data irrefutably show that SARS-CoV-2 is not derived from any previously used virus backbone 20 . Instead, we propose two scenarios that can plausibly explain the origin of SARS-CoV-2: (i) natural selection in an animal host before zoonotic transfer; and (ii) natural selection in humans following zoonotic transfer. We also discuss whether selection during passage could have given rise to SARS-CoV-2. 1. Natural selection in an animal host before zoonotic transfer As many early cases of COVID-19 were linked to the Huanan market in Wuhan 1,2 , it is possible that an animal source was present at this location. Given the similarity of SARS-CoV-2 to bat SARS-CoV-like coronaviruses 2 , it is likely that bats serve as reservoir hosts for its progenitor. Although RaTG13, sampled from a Rhinolophus affinis bat 1 , is ~96% identical overall to SARS-CoV-2, its spike diverges in the RBD, which suggests that it may not bind efficiently to human ACE2 7 (Fig. 1a). Malayan pangolins (Manis javanica) illegally imported into Guangdong province contain coronaviruses similar to SARS-CoV-2 21 . Although the RaTG13 bat virus remains the closest to SARS-CoV-2 across the genome 1 , some pangolin coronaviruses exhibit strong similarity to SARS-CoV-2 in the RBD, including all six key RBD residues 21 (Fig. 1). This clearly shows that the SARS-CoV-2 spike protein optimized for binding to human-like ACE2 is the result of natural selection. Neither the bat betacoronaviruses nor the pangolin betacoronaviruses sampled thus far have polybasic cleavage sites. Although no animal coronavirus has been identified that is sufficiently similar to have served as the direct progenitor of SARS-CoV-2, the diversity of coronaviruses in bats and other species is massively undersampled. Mutations, insertions and deletions can occur near the S1–S2 junction of coronaviruses 22 , which shows that the polybasic cleavage site can arise by a natural evolutionary process. For a precursor virus to acquire both the polybasic cleavage site and mutations in the spike protein suitable for binding to human ACE2, an animal host would probably have to have a high population density (to allow natural selection to proceed efficiently) and an ACE2-encoding gene that is similar to the human ortholog. 2. Natural selection in humans following zoonotic transfer It is possible that a progenitor of SARS-CoV-2 jumped into humans, acquiring the genomic features described above through adaptation during undetected human-to-human transmission. Once acquired, these adaptations would enable the pandemic to take off and produce a sufficiently large cluster of cases to trigger the surveillance system that detected it 1,2 . All SARS-CoV-2 genomes sequenced so far have the genomic features described above and are thus derived from a common ancestor that had them too. The presence in pangolins of an RBD very similar to that of SARS-CoV-2 means that we can infer this was also probably in the virus that jumped to humans. This leaves the insertion of polybasic cleavage site to occur during human-to-human transmission. Estimates of the timing of the most recent common ancestor of SARS-CoV-2 made with current sequence data point to emergence of the virus in late November 2019 to early December 2019 23 , compatible with the earliest retrospectively confirmed cases 24 . Hence, this scenario presumes a period of unrecognized transmission in humans between the initial zoonotic event and the acquisition of the polybasic cleavage site. Sufficient opportunity could have arisen if there had been many prior zoonotic events that produced short chains of human-to-human transmission over an extended period. This is essentially the situation for MERS-CoV, for which all human cases are the result of repeated jumps of the virus from dromedary camels, producing single infections or short transmission chains that eventually resolve, with no adaptation to sustained transmission 25 . Studies of banked human samples could provide information on whether such cryptic spread has occurred. Retrospective serological studies could also be informative, and a few such studies have been conducted showing low-level exposures to SARS-CoV-like coronaviruses in certain areas of China 26 . Critically, however, these studies could not have distinguished whether exposures were due to prior infections with SARS-CoV, SARS-CoV-2 or other SARS-CoV-like coronaviruses. Further serological studies should be conducted to determine the extent of prior human exposure to SARS-CoV-2. 3. Selection during passage Basic research involving passage of bat SARS-CoV-like coronaviruses in cell culture and/or animal models has been ongoing for many years in biosafety level 2 laboratories across the world 27 , and there are documented instances of laboratory escapes of SARS-CoV 28 . We must therefore examine the possibility of an inadvertent laboratory release of SARS-CoV-2. In theory, it is possible that SARS-CoV-2 acquired RBD mutations (Fig. 1a) during adaptation to passage in cell culture, as has been observed in studies of SARS-CoV 11 . The finding of SARS-CoV-like coronaviruses from pangolins with nearly identical RBDs, however, provides a much stronger and more parsimonious explanation of how SARS-CoV-2 acquired these via recombination or mutation 19 . The acquisition of both the polybasic cleavage site and predicted O-linked glycans also argues against culture-based scenarios. New polybasic cleavage sites have been observed only after prolonged passage of low-pathogenicity avian influenza virus in vitro or in vivo 17 . Furthermore, a hypothetical generation of SARS-CoV-2 by cell culture or animal passage would have required prior isolation of a progenitor virus with very high genetic similarity, which has not been described. Subsequent generation of a polybasic cleavage site would have then required repeated passage in cell culture or animals with ACE2 receptors similar to those of humans, but such work has also not previously been described. Finally, the generation of the predicted O-linked glycans is also unlikely to have occurred due to cell-culture passage, as such features suggest the involvement of an immune system 18 . Conclusions In the midst of the global COVID-19 public-health emergency, it is reasonable to wonder why the origins of the pandemic matter. Detailed understanding of how an animal virus jumped species boundaries to infect humans so productively will help in the prevention of future zoonotic events. For example, if SARS-CoV-2 pre-adapted in another animal species, then there is the risk of future re-emergence events. In contrast, if the adaptive process occurred in humans, then even if repeated zoonotic transfers occur, they are unlikely to take off without the same series of mutations. In addition, identifying the closest viral relatives of SARS-CoV-2 circulating in animals will greatly assist studies of viral function. Indeed, the availability of the RaTG13 bat sequence helped reveal key RBD mutations and the polybasic cleavage site. The genomic features described here may explain in part the infectiousness and transmissibility of SARS-CoV-2 in humans. Although the evidence shows that SARS-CoV-2 is not a purposefully manipulated virus, it is currently impossible to prove or disprove the other theories of its origin described here. However, since we observed all notable SARS-CoV-2 features, including the optimized RBD and polybasic cleavage site, in related coronaviruses in nature, we do not believe that any type of laboratory-based scenario is plausible. More scientific data could swing the balance of evidence to favor one hypothesis over another. Obtaining related viral sequences from animal sources would be the most definitive way of revealing viral origins. For example, a future observation of an intermediate or fully formed polybasic cleavage site in a SARS-CoV-2-like virus from animals would lend even further support to the natural-selection hypotheses. It would also be helpful to obtain more genetic and functional data about SARS-CoV-2, including animal studies. The identification of a potential intermediate host of SARS-CoV-2, as well as sequencing of the virus from very early cases, would similarly be highly informative. Irrespective of the exact mechanisms by which SARS-CoV-2 originated via natural selection, the ongoing surveillance of pneumonia in humans and other animals is clearly of utmost importance.
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            A Comparison of Three Holistic Approaches to Health: One Health, EcoHealth, and Planetary Health

            Several holistic and interdisciplinary approaches exist to safeguard health. Three of the most influential concepts at the moment, One Health, EcoHealth, and Planetary Health, are analyzed in this paper, revealing similarities and differences at the theoretical conceptual level. These approaches may appear synonymous, as they all promote the underlying assumption of humans and other animals sharing the same planet and the same environmental challenges, infections and infectious agents as well as other aspects of physical—and possibly mental—health. However, we would like to illuminate the differences between these three concepts or approaches, and how the choice of terms may, deliberately or involuntary, signal the focus, and underlying values of the approaches. In this paper, we have chosen some proposed and well-known suggestions of definitions. In our theoretical analysis, we will focus on at least two areas. These are (1) the value of the potential scientific areas which could be included and (2) core values present within the approach. In the first area, our main concern is whether the approaches are interdisciplinary and whether the core scientific areas are assigned equal importance. For the second area, which is rather wide, we analyze core values such as biodiversity, health, and how one values humans, animals, and ecosystems. One Health has been described as either a narrow approach combining public health and veterinary medicine or as a wide approach as in the wide-spread “umbrella” depiction including both scientific fields, core concepts, and interdisciplinary research areas. In both cases, however, safeguarding the health of vertebrates is usually in focus although ecosystems are also included in the model. The EcoHealth approach seems to have more of a biodiversity focus, with an emphasis on all living creatures, implying that parasites, unicellular organisms, and possibly also viruses have a value and should be protected. Planetary Health, on the other hand, has been put forward as a fruitful approach to deal with growing threats in the health area, not least globally. We conclude that there are actually important differences between these three approaches, which should be kept in mind when using any of these terms.
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              The Extended Specimen Network: A Strategy to Enhance US Biodiversity Collections, Promote Research and Education

              For more than two centuries, biodiversity collections have served as the foundation for scientific investigation of and education about life on Earth (Melber and Abraham 2002, Cook et al. 2014, Funk 2018). The collections that have been assembled in the past and continue to grow today are a cornerstone of our national heritage that have been treated as such since the founding of the United States (e.g., Jefferson 1799, Goode 1901a, 1901b, Meisel 1926). A diverse array of institutions throughout the United States, from museums and botanical gardens to universities and government agencies, maintain our biodiversity collections as part of their research and education missions. Collectively, these institutions and their staff are stewards for at least 1 billion biodiversity specimens that include such diverse objects as dinosaur bones, pressed plants, dried mushrooms, fish preserved in alcohol, pinned insects, articulated skeletons, eggshells, and microscopic pollen grains. In turn, these collections are a premier resource for exploring life, its forms, interactions, and functions, across evolutionary, temporal, and spatial scales (Bebber et al. 2010, Monfils et al. 2017, Schindel and Cook 2018). Biodiversity collections have historically consisted of physical objects and the infrastructure to support those objects (Bradley et al. 2014). However, the last two decades have witnessed a remarkable wave of digitization that has reshaped the collections paradigm to include digital data and infrastructure (Nelson and Ellis 2018), opening vast new areas for integrative biological research (e.g., a single plant specimen mounted on an herbarium sheet may be analyzed in multitude ways to yield data on flower morphology, DNA for applications from systematic studies to genome sequences, and isotopes for analyses of nitrogen to understand the mechanisms of phenology in relation to nitrogen uptake). In the United States, investment by the federal government through the National Science Foundation's (NSF) Advancing Digitization of Biodiversity Collections (ADBC) program has facilitated the digitization of approximately 62 million US biodiversity specimens since 2011 through 24 thematic collection networks connecting over 700 collections. These networks have helped to develop a collaborative infrastructure connecting specimen data, human resources, research, and education among institutions. The ADBC program has also provided support to iDigBio (the Integrated Digitized Biocollections), which is the central coordinating unit for the digitization effort. The final ADBC grants will be awarded in 2021. During the last several years, the Biodiversity Collections Network has led an effort to gather input from primary stakeholder communities regarding future directions for collections and their use in research and education. The effort culminated in a workshop held from 30 October through 1 November 2018 at Oak Spring Garden in Upperville, Virginia, during which a strategy was developed to maximize the value of collections for future research and education that builds on and leverages the accomplishments of the ADBC program. The strategy that was informed by stakeholders, refined by workshop participants, and vetted through public comment from scientific community is presented in the present article. The concept: Extended specimens Science, industry, and society rely on physical specimens housed in US biodiversity collections (e.g., Bradley et al. 2014, Tewksbury et al. 2014, Trejo-Salazar et al. 2016, DuBay and Fuldner 2017). Ongoing advances in data generation and analysis have transformed biodiversity collections from physical specimens to dynamic suites of interconnected resources enriched through study over time (Page et al. 2015, Soltis 2017, Nelson and Ellis 2018). The concept of an extended specimen (Webster 2017) conveys the current perspective of the biodiversity specimen as extending beyond the singular physical object to potentially limitless additional physical preparations and digital resources (figure 1; Schindel and Cook 2018). Figure 1. Example of an extended specimen generated by the Dimensions of Biodiversity award to study lichen biodiversity gradients in the Southern Appalachian Mountain Biodiversity Hotspot of the eastern United States. The specimen (E. Tripp 6292) was collected in Little River Canyon National Preserve, Alabama, and formally described as Lecanora markjohnstonii by the project team in a paper lead authored by a graduate student from University of Colorado, Boulder. The primary specimen extensions were created and disseminated by The New York Botanical Garden. The initiative: An extended specimen network The monumental effort to digitize millions of specimens has resulted in a more accessible and integrated body of information on species occurrence in space and time. Imaging of specimens has provided access to verification and validation of species identification. New and emerging techniques (e.g., CT scanning, isotopes, and AI) are actively unveiling new sources of data and information related to collected specimens. Researchers in biological informatics have provided new methods to analyze and integrate data to address emerging questions. The next step in advancing and enhancing biodiversity collections infrastructure must take into account the rapid development of novel applications for biodiversity data and the growing body of data and resources derived from specimens. Addressing the new hypotheses that researchers may generate, and serving new user communities, will require richer, more complex, and more interconnected networks of information about biodiversity specimens. The Extended Specimen Network (ESN) is an initiative that would enhance the research potential of specimens, through digitization and links with associated extended data. These extensions will scale from molecules to the ecosphere, and would include genetic, phenotypic, behavioral, and environmental data, as well as biotic interaction networks and new multimedia components (e.g., 2D and 3D specimen images, in situ field images, videos of field conditions). These data reside in disparate databases, have not yet been digitized or made accessible to the scientific community, and are not linked directly to the specimens with which they are associated. Physical specimens are the critical objects that represent the depth and breadth of biodiversity held in US collections, and specimens are the hubs through which these complex data are linked and can be verified and enhanced. The creation of the ESN will leverage and even drive data integration technologies. Once they are integrated and accessible, the extended specimens have the potential to transform the sciences. The ESN will therefore include the primary physical specimen, all associated physical preparations (e.g., tissue subsamples), and all associated digital data (e.g., micrographs, habit photographs, trait data, genomic data and other molecular markers). The network will involve digitization and extension of existing specimens, and drive the collection of new specimens purposefully collected and accessioned with these extended attributes in mind. The ESN will rely on the development of new data integration mechanisms necessary to link all of the dynamic components together across collections, data types, and existing and evolving databases. These links will help researchers study and better understand the rules that govern how organisms grow, diversify, and interact with one another and how environmental change and human activities may affect those rules. The ESN is also ideally suited to educating the next generation of data and biodiversity scientists. The combination of object-based learning and digital data will provide a unique gateway to data literacy for the twenty-first century scientist (Petrelli et al. 2013, Hannan et al. 2016). As we look to develop our current and future workforce and foster an informed citizenry, the openly accessible ESN will provide scalable learning opportunities for K–12, undergraduate, graduate, and lifelong learning in data literacy for life sciences. The ESN will promote discovery The ESN will stimulate new avenues of investigation, expedite existing ones, and provide an enhanced resource for making science-based policy decisions. By linking physical specimens to the data derived from them (e.g., gene sequences, images, behavior, geographic ranges, and species interactions) and making all of the derived data searchable and easily discoverable, we will have a rich and accessible integrated data source that can be used to advance diverse areas of research. For instance, it will be possible to more fully define and understand the traits that make up organisms, their relationships with each other, and the ecosystems they inhabit. Such information has direct benefits and can inform science relative to fundamental questions that challenge society and the quality of human life. These questions include how crops can be more effectively and efficiently grown in changing climates, how we can sustain and renewably use biological resources in our oceans (Palkovacs et al. 2012), and how zoonotic diseases are transmitted and spread (Samy et al. 2016). In addition to addressing complex questions with broad societal benefits, the ESN will facilitate the as yet incomplete work of documenting and naming the organisms that make up global biodiversity. Machine learning and other novel data science and engineering techniques can help speed identification of museum specimens in the ESN and may aid in recognizing hidden novelties. Most current portals for digitized specimen data have user interfaces designed for access primarily by biodiversity scientists and collections professionals. To take full advantage of the rich data content and broad relevance of the ESN, the interfaces need to be redesigned to both attract and facilitate use by a broader user base. Certain analyses, data cleaning procedures, and static query parameters, among other features can be added to allow users to interact with the data in more substantive ways. The existing interfaces are set up to retrieve relevant occurrence records from a search on the basis of a taxonomic name, geographic unit, or time period. The ESN will provide an interface that can allow the user to query data in dynamic and discipline specific ways. Future portals, designed for broader uses and broader user bases, could allow for automated queries that include an ability to assess data quality, fitness for use, and information gaps. This would allow users to answer questions such as Do the available data comprise a representative set, or are critical data lacking because key specimens have not been collected or digitized? How many different species, as opposed to different species names, occur in a given region? How many specimens or species in a given query possess a specific trait or suite of traits? Do the organisms of the region occur in populations that are genetically distinct from other populations of the same species? Have unique interactions among organisms been documented in the region of interest? The ESN will enable seamless data integration, attribution, and use tracking Central to the success of the ESN is the development and implementation of a system of identifiers and specimen tracking protocols. These will enable dynamic linking of extended specimen components that would otherwise be separated in physical or digital spaces, elucidate relationships between items in disparate collections (tissue:voucher, plant:pollinator, host:parasite, etc.), and facilitate interoperability with data sources outside of our immediate realm (Guralnick et al. 2015). It will also allow collections institutions to follow the use of their specimens and develop metrics for measuring their impact, particularly when used in concert with unique identifiers (e.g., DOIs) assigned to individual data sets. Such metrics permit collections to demonstrate their value, as well as better acquire and manage resources. Currently, collections lack access to the data that demonstrate their full contributions to specimen-based research through citation in publications, vouchering of molecular data (through the National Center for Biotechnology Informatics, NCBI), or products created from direct specimen use (images, CT scans, DNA extracts, etc.). In addition to providing a discrete and reliable framework for quantifying the impact of biodiversity collections, the new system of tracking will create the potential for cost recovery when specimens are used in commercial enterprise. Use in applied research (e.g., pharmacology, human health, food security) and commercial communities (e.g., pharmaceuticals, agriculture) will further demonstrate the value of collections to additional communities and contribute to the increased sustainability of biodiversity collections. A further benefit of the new tracking system is that it will also allow biodiversity collections to meet new international standards for documenting the use of specimens and their derived data. An example is the Nagoya Protocol, which is a supplemental agreement to the Convention on Biological Diversity that establishes an international legal framework for access to and methods of sharing benefits of genetic resources. It requires that countries providing specimens define their access procedure and requires users (countries and institutions) to report on and share benefits on their use. Implementing and sustaining the extended specimen network Establishing a comprehensive network of extended specimen data that integrates the wealth of biodiversity and expertise held in US collections and associated data repositories will require a monumental effort, comparable to building a new telescope for planetary exploration. However, the focus on digital and human infrastructure, rather than physical infrastructure, makes the magnitude of the effort required to build and sustain such a resource harder to comprehend. Therefore, a major challenge to develop and maintain the ESN will be to establish the unity of the resource, workforce, and scope of effort required to build and maintain it across a network of collections-based institutions. Creating, growing, and sustaining the ESN requires building and maintaining a network of data providers, a centralized database infrastructure, and an educated workforce. For consistency and sustainability, this requires a central coordinating unit with long term secure funding, which is outside the scope of existing grant programs. Building on the models of the National Center for Ecological Analysis Synthesis, and the National Evolutionary Synthesis Center and the NCBI, a securely funded coordinating center would anchor the ESN and support the data resources. If driven by the stakeholder community, it can serve as a common portal to share established techniques, emerging resources, and common tools for contributing to and sustain the ESN. We suggest that a distributed ESN platform will be indispensable and that stable funding is required for the ESN to reach its full potential. The envisioned data integration mechanisms would facilitate data integration across major data resources. For example, GenBank (a nondistributed database managed by the NCBI through the National Institutes of Health) data would be integrated within the larger framework of the proposed ESN, thus enhancing the utility of this existing platform by effectively linking genotype, phenotype, and environment. Similarly, data from other new and ambitious efforts such as the Earth BioGenome Project, which aims to sequence, catalog, and characterize the genomes of all of Earth's eukaryotic biodiversity over a period of 10 years (Lewin et al. 2018), and isotopic data from IsoBank would also be integrated with and accessible through the ESN, as would data from new, comprehensive collecting initiatives, such as the NEON Biorepository (e.g., Kao et al. 2012). By integrating the nation's existing critical databases and bioinitiatives, the ESN will greatly enhance the nation's collective biological knowledge, resources, and potential. Index US biodiversity collections and their holdings Biological collections comprise the most comprehensive record of life on Earth; their potential will only be fully realized when the data contained within them are revealed and made more accessible for computational analyses. Many of the approximately 1469 US biodiversity collections are not digitized and do not have accurate estimates of the size or taxonomic breadth of their holdings. We need to address this information gap and take stock of the holdings in US biodiversity collections and characterize them in terms of taxonomic, temporal, and geographic emphases, and compile these data into a national collections index. The existing Index Herbariorum (Theirs 2019), an index of plant collections, is a logical model for this resource. An index of all US collections will allow the community to prioritize collections for digitization and facilitate completion tracking for the overall ESN. Complete and improve existing digitized data Significant proportions of the existing digitized specimen records are incomplete, with many entered as skeletal records lacking critical data fields (e.g., locality, date, collector). Geocoordinates need entry and verification for the vast majority of digitized specimens. A foundational step in building the ESN will involve completing and standardizing records to maximize their value and interoperability. Development of computational tools that can infer missing values or aid users in completing missing data must be a high priority. Efforts are in place taking advantage of a combination of image analysis (including optical character recognition) and data pattern matching. Identifying and filling gaps in biodiversity data Biodiversity specimens have become critical for researchers documenting and investigating environmental change. We must continue to collect specimens and build our collections to inform research into the future. New collections may be especially important in areas that are undergoing rapid change or reduction, such as high-elevation mountain ecosystems, tropical forests, the Atlantic and Gulf coastlines, and the Arctic. Continued collection and integration of new specimens is central to the success of the ESN and as we learn more about how specimens can be used to inform science, we must adjust our sampling protocols to implement a holistic, next-generation approach to the collection of biodiversity specimens. As was discussed by Schindel and Cook (2018), a next-generation approach must be focused on nested sampling that extends beyond the single organism (e.g., a single plant), to include nested sampling of the biotic associates (e.g., soil microbes, epiphytes, endophytes, and parasites spanning from viruses to arthropods and fungi) and data on its environment (e.g., community composition, microclimate, macroclimate, habitat quality). In addition to nested sampling and detailed observations, we need to augment our collecting patterns to conduct targeted sampling to fill existing gaps. Links among nested samples can facilitate new and dynamic research opportunities and transform our capacity to understand life on Earth. Build and strengthen strategic partnerships The ESN will enable the expansion of existing partnerships and creation of new strategic engagements. There is a strong need for interdisciplinary development among biology, biological collections, and the computer and data sciences community in order to build, improve, and maintain next-generation collections infrastructure, workforce, and accessibility. We will continue to embrace an openness to collaboration with nontraditional partners in academia and industry that fosters bidirectional benefits. Build dynamic links with data aggregators Some of the extended components that need to be linked to existing biodiversity specimens via the ESN are hosted in a growing variety of databases such as the Catalogue of Life checklist, the Biodiversity Heritage Library, the Barcode of Life Data System, the NCBI, and the Encyclopedia of Life Traitbank. Establishing a multidirectional means of data exchange with aggregators is a necessity. Collaboration with programs such as the NSF-funded National Ecological Observatory Network (NEON), the Long Term Ecological Research Network, and Critical Zone Observatories, will ensure that standards and protocols are developed that enable interoperability between collections data and occurrence records both past and present. Furthermore, standardization of extended specimen data driven by the ESN (and the taxonomic expertise across the ESN) will make the data collected by future researchers using these centers computable and therefore accessible to a broad audience of users. Facilitate data integration across international biodiversity organizations Participation to the fullest extent possible in the Global Biodiversity Information Facility proposed alliance for biodiversity knowledge (Hobern et al. 2019) will facilitate local work and help align efforts to document, describe, and quantify US biodiversity in relation to other global efforts, including the Atlas of Living Australia and the Distributed System of Scientific Collections, a new European Union program. The ESN also provides the ideal framework within which to identify and address persistent issues in specimen-based data sharing, including the development of standardized taxonomies and ontologies. This could be a strategic goal in conjunction with pursuit of collaboration with data aggregators from Mexico (CONABIO) and Canada (Canadensys) to Brazil (SpeciesLink) to permit the seamless transfer of data needed for large-scale understanding of the breadth of global biodiversity, its distribution and change over time. The extended specimen network and twenty-first century learners The ESN has significant transformative potential for scientific research and policy. The ESN can serve as an effective tool to educate and inform broad and diverse audiences about biodiversity and data science. Below we outline the roles that the ESN could have in the realms of formal and informal education. Formal education The ESN and collections community has significant potential to engage, educate, and empower the next generation of biodiversity data stewards, researchers, and ESN data users. Biodiversity data and ESN usage, require skills and competencies that align naturally with next-generation science standards outlined for K–12 science curricula (NRC 2013) and the undergraduate biology concepts and competencies included in Vision and Change in Undergraduate Biology Education: A Call to Action (Brewer and Smith 2011). The digital data and specimens central to biodiversity science can be valuable resources and incorporated seamlessly into existing courses, including subject matter in evolution, biodiversity, systematics, taxonomy, and ecology. Specimen-based data make science accessible through the specimen itself, which is tangible, place based, and engaging, as well as through aggregated specimen data that are verifiable, relevant, and a logical gateway to data literacy (Petrelli et al. 2013, Hannan et al. 2016, Monfils et al. 2017). The place-based capacity of collections data combined with the social and societal relevance of biodiversity science can serve a role in creating inclusive, culturally relevant, and socially conscious educational materials that engage a broad and diverse audience in biodiversity science. By defining biodiversity data literacy skills, creating a learning progression that incorporates the ESN and data literacy into formal education, and providing accessible materials with teacher training and educator interfaces that facilitate use in the classroom, we can support an increasingly biodiversity literate society and train the next generation of data literate scientists. Informal education As digital resources centered around the ESN expand, so too will informal education opportunities. Indeed, we likely cannot reach the full potential of the ESN without strong involvement of the citizen science community. Many citizen science projects are already structured on monitoring biodiversity: eBird, eButterfly, iNaturalist, and the US National Phenology Network, for example, provide platforms for contributing sightings or recordings of organisms or a particular attribute of an organism. Internet-based projects can involve the public directly in the development and maintenance of the ESN through contributing to collections-based science and databases. Projects such as Notes from Nature (Hill et al. 2012), the Smithsonian Transcription Center, and CitSciScribe are platforms that invite the public to add digital data to images of specimens. Tasks include transcription, morphological measurements, and phenological annotations. Furthermore, the majority of these projects contribute directly to active research projects. Such programs are broadly inclusive and engage participants from a wide range of ages, abilities, and interests, and with minimal start-up costs. The ESN will advance the NSF’s 10 big ideas If implemented, the new strategy for biodiversity collections proposed in the present article will provide a powerful scientific tool for the biological sciences. As we outline below, it will also establish a resource that will enable progress toward cross-cutting challenges at the frontiers of science reflected in the 10 big ideas recently identified by the NSF. Understanding the rules of life Under­standing the rules by which biological and environmental factors influence the wide range of organisms on which humans depend will require diverse data accessed from specimens spanning the tree of life. Biodiversity specimens are a source of genomic, phenomic, and environmental data, the three basic data types required for identifying causal and predictive relationships across these scales. Collections provide these fundamental data, although, as was outlined above, they have not yet been exposed through comprehensive digitization and data linkages. When the vision of the ESN is fully realized, it will be possible to examine key evolutionary traits across spatial and temporal scales, using diverse combinations of data types from the genome to the phenome and beyond. Previously unrecognized patterns may also be discovered using new AI methods, and these could address specific research questions such as how genetic regulators of similar phenotypes evolve in relation to environment. Harnessing data for twenty-first century science and engineering The digitization of natural history collections has already contributed to a deluge of data from the nation's scientific facilities. As we broaden the knowledge bank of specimens with additional genotypic, phenotypic, and environmental data, the amount of data will further increase exponentially. The ESN will be a prime example of a cohesive, national scale approach to research data infrastructure through the development and implementation of new tools to integrate data. In addition, specimen-based data provides a unique opportunity to educate students in data science, train a data-enabled workforce, and train future biodiversity data professionals. Collections data, alongside the archived specimens, are an engaging and accessible data source that can provide students an opportunity to experience the entirety of the data pathway while practicing verifiable and testable science. Midscale infrastructure Much of the support required for the ESN falls in the gap between what the NSF currently funds as either small or large infrastructure. Specifically, the computer and human infrastructure required for data acquisition, deployment, and training to support the ESN represent midscale infrastructure needs, both in terms of funding level and the scientific research it will support. Although many aspects of the ESN would be characterized as midscale infrastructure, it is important to highlight that support for the ESN coordinating center itself would likely fall within the scope of large infrastructure. Navigating the new Arctic The Arctic biota has been minimally sampled over the past two centuries. Arctic biodiversity specimens are stored in relatively few US collections and provide our best baselines for understanding the implications of rapid environmental changes on life (e.g., Bond et al. 2015) in a geopolitical region that is increasingly critical to the global economy and security. Because of the rapid rate of annual warming in the Arctic, we should immediately build international coalitions that will invest in spatially extensive, site intensive natural history collections that will provide the biodiversity infrastructure necessary to critically assess change. Over time, specimens and their associated digitized data, accessed via the ESN, would provide the samples required by diverse technologies (e.g., genomics, isotope ecology), a robust historical context for the proposed network of observational platforms, and a reference for the identification, distribution, behavior, and response of species and their pathogens in the Arctic (Cook et al. 2013, Hoberg et al. 2013). Growing convergent research at NSF Enhancement of the roles that collections-derived data can play in understanding and protecting human health, and in education, are key objectives of the new agenda. This could be achieved through the centralized efforts to integrate and share data more effectively and widely. The ESN combines diverse data sources linked to physical biodiversity specimens and, as such, is a physical manifestation of convergent research that will clearly demonstrate the power of this approach. The future of work at the human technology frontier The use of biodiversity collections in projects to both refine current techniques in machine learning and to document variation among organisms as exhibited by specimens holds great promise (e.g., Carranza-Rojas et al. 2017, McAllister et al. 2018). The use of these tools will lead to new avenues of data analysis, requiring new skills for researchers and data managers. Collections professionals will find themselves at this frontier. Supporting the adoption of new technology and documenting the experience through training and best practices is a key aim of the strategy presented in the present article. The work carried out by this community may prove transferable to other communities using the tools and workflows developed as part of the ESN. Enhancing science and engineering through diversity The ESN requires new generations of taxonomic expertise. The place-based capacity of biodiversity specimens and associated data combined with the social and societal relevance of biodiversity science can serve a role in creating inclusive, culturally relevant, and socially conscious educational materials that engage a broad and diverse audience in biodiversity science. Biodiversity collections institutions have significant potential to engage a broad range of people to create a scientifically literate work force and build the ranks of both the scientific and engineering communities. Immediate action items to support the ESN Although a long-term funding structure for the ESN will take time to develop, steps can be taken immediately to initiate the process, including the following: A robust, comprehensive specimen identifier system should be developed in collaboration with other international data aggregators and providers to enable transparent and uncomplicated integration of biodiversity data with other data sources. The system must also facilitate the attribution of collections’ role in discovery, policy, and promoting transparency for broader issues involving multiple stakeholders (e.g., access and benefit sharing). An authoritative, comprehensive, and self-updateable index of US collections institutions should be created, similar to the Index Herbariorum for global herbaria, with structured metadata to describe their holdings. This is the first step toward expediting the discovery of undigitized collections and revealing these to the research community. The digitization of existing material should continue, with a focus on underrepresented taxa (e.g., those in entomology, paleontology, and archeology collections), including data gaps in time, space, and scale, and incorporating of specimens held in small regional and individual researcher collections. These efforts must also include improvement of previously digitized specimen data by imaging specimens, completing skeletal records, and augmenting data with georeferencing. New protocols must be developed for the collection and dissemination of data-rich samples and nested samples that provide greater context for understanding the biotic and abiotic interactions of organisms, and comprehensive data sets must be created for research and education. An accessible educator and student interface, baseline analysis tools, and vetted educational materials should be developed to enable integration of biodiversity data in K–12 and undergraduate course work. New tools and resources, combined with training opportunities, will facilitate educator adoption of data-centric educational materials that foster student engagement with digital biodiversity data. Creating an accessible entry into digital biodiversity data will enable training of an informed, digitally fluent workforce. Broad-scale adoption of core biodiversity data literacy skills and competencies in K–12 and undergraduate curricula should be championed in order to foster a biodiversity savvy future workforce, engage new end users in novel uses of biodiversity data, and sustain and promote careers in advancing collections science, biodiversity research, and data literacy. Enhanced training of emerging and established professionals for interdisciplinary work in biodiversity, data science, and informatics should be supported. Team Science skills to work collaboratively across disciplines should be emphasized, together with soft skills related to communication, creativity, and critical thinking, because these are paramount to conducting transformative science, communicating research, and cultivating and leveraging relationships with new research and user communities.
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                Contributors
                Journal
                Bioscience
                Bioscience
                bioscience
                Bioscience
                Oxford University Press
                0006-3568
                1525-3244
                01 July 2020
                24 June 2020
                24 June 2020
                : 70
                : 6
                : 531-534
                Affiliations
                Museum of Southwestern Biology and with the Biology Department, University of New Mexico , Albuquerque
                Infectious Disease Surveillance Center, National Institute of Infectious Diseases , Tokyo, Japan
                Departamento de Invetigación de Enfermedades Emergentes y Zoonóticas, Instituto Conmemorativo Gorgas de Estudios de la Salud , Panama City, Republic of Panama
                Negaunee Integrative Research Center, The Field Museum of Natural History , Chicago, Illinois
                Museum of Southwestern Biology and with the Biology Department, University of New Mexico, Albuquerque, and with the Museo de Mastozoologia QCAZ, Universidad Catolica del Ecuador , Quito, Ecuador
                Florida Museum of Natural History, the UF Biodiversity Institute, and the Department of Biology, University of Florida , Gainesville
                Museum of Southwestern Biology, University of New Mexico , Albuquerque
                Gantz Family Collections Center, The Field Museum of Natural History , Chicago, Ilinois
                Biology Department, University of New Mexico , Albuquerque
                Faculty of Resource Science and Technology, Universiti Malaysia Sarawak, Jalan Datuk Mohammad Musa , Kota Samarahan, Sarawak, Malaysia
                iDigBio and iDigInfo, Florida State University , Tallahassee
                Department of Biology, Bucknell University , Lewisburg, Pennsylvania
                Research Associate, Museum of Texas Tech University , Lubbock
                Division of Vertebrate Zoology's Department of Mammalogy, American Museum of Natural History , New York, New York
                William and Lynda Steere Herbarium, New York Botanical Garden , the Bronx, New York
                Department of Ecology and Evolutionary Biology and with the Museum of Zoology, University of Michigan , Ann Arbor
                School of Life Sciences, Arizona State University , Tempe
                Centre for Environmental Sciences, Research Group Zoology: Biodiversity and Toxicology, Hasselt University , Diepenbeek, Belgium
                Department of Forestry and Wildlife Management, Maasai Mara University , Narok, Kenya
                Departamento de Vertebrados, Museu Nacional, Universidade Federal do Rio de Janeiro , Rio de Janeiro, Brazil
                Pacific Center for Emerging Infectious Diseases Research, the John A. Burns School of Medicine, University of Hawaii , Manoa, Honolulu, Hawaii
                Florida Museum of Natural History and with the UF Biodiversity Institute, University of Florida , Gainesville
                Author notes
                Article
                biaa064
                10.1093/biosci/biaa064
                7340541
                32665736
                781bc860-3a17-4095-9426-23fb136d0aa5
                © The Author(s) 2020. Published by Oxford University Press on behalf of the American Institute of Biological Sciences.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Pages: 4
                Funding
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: DBI-1115210 for 2011–2018
                Award ID: DBI-1547229 for 2016–2021
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                AcademicSubjects/SOC02100

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