scholarly journals Integrated Biodiversity Infrastructure for Decision Making 

Author(s):  
Hamish Holewa

The Atlas of Living Australia (ALA) is an Australian Government supported collaborative partnership of organisations that have stewardship of Australian biodiversity data. The ALA (www.ala.org.au) provides research infrastructure that enables delivery of biodiversity information to over 45,000 unique users in research, industry and government per annum. It delivers impact and enables research excellence in fields such as biodiversity, environmental management, ecology and genetic sciences. Integrated and consistent infrastructure and processes are fundamental to increasing value of collections and associated data. The Atlas of Living Australia has a mature industry engagement program that provides data standardisation, quality and analytical services to decision makers in all tiers of Australian government (local, state and federal). This program is built on formal partnerships between data providers (collection institutions) and analytical services (such as Virtual Laboratories and Research and Science Clouds www.ecocloud.org.au). The provision of high quality, authoritative data is critical to utilisation and uptake of these services and sector sustainability. This presentation will showcase data service and analytical methods for decision makers within the Australian context. It will also explore how international efforts such as DiSSCo assist in data stewardship, cultural change and system enhancement.

Author(s):  
Natalya Ivanova ◽  
Maxim Shashkov

Currently Russia doesn't have a national biodiversity information system, and is still not a GBIF (Global Biodiversity Information Facility) member. Nevertheless, GBIF is the largest source of biodiversity data for Russia. As of August 2020, >5M species occurrences were available through the GBIF portal, of which 54% were published by Russian organisations. There are 107 institutions from Russia that have become GBIF publishers and 357 datasets have been published. The important trend of data mobilization in Russia is driven by the considerable contribution of citizen science. The most popular platform is iNaturalist. This year, the related GBIF dataset (Ueda 2020) became the largest one for Russia (793,049 species occurrences as of 2020-08-11). The first observation for Russia was posted in 2011, but iNaturalist started becoming popular in 2017. That year, 88 observers added >4500 observations that represented 1390 new species for Russia, 7- and 2-fold more respectively, than for the previous 6 years. Now we have nearly 12,000 observers, about 15,000 observed species and >1M research-grade observations. The ratio of observations for Tracheophyta, Chordata, and Arthropoda in Russia is different compared to the global scale. There are almost an equal amount of observations in the global iNaturalist GBIF dataset for these groups. At the same time in Russia, vascular plants make up 2/3rds of the observations. That is due to the "Flora of Russia" project, which attracted many professional botanists both as observers and experts. Thanks to their activity, Russia has a high proportion of research-grade observations in iNaturalist, 78% versus 60% globally. Another consequence of wide participation by professional researchers is the high rate of species accumulation. For some taxonomic groups conspicuous species were already revealed. There are about 850 bird species in Russia of which 398 species were observed in 2018, and only 83 new species in 2019. Currently, the number of new species recorded over time is decreasing despite the increase in observers and overall user activity. Russian iNaturalist observers have shared a lot of archive photos (taken during past years). In 2018, it was nearly 1/4 of the total number of observations and about 3/4 of new species for the year, with similar trends observed during 2019. Usually archive photos are posted from December until April, but the 2020 pandemic lockdown spurred a new wave of archive photo mobilisation in April and May. There are many iNaturalist projects for protected areas in Russia: 27 for strict nature reserves and national parks, and about 300 for others. About 100,000 observations (7.5% of all Russian observations) from the umbrella project "Protected areas of Russia" represent >34% of the species diversity observed in Russia. For some regions, e.g., Novosibirsk, Nizhniy Novgorod and Vladimir Oblasts, almost all protected areas are covered by iNaturalist projects, and are often their only source of available biodiversity data. There are also other popular citizen science platforms developed by Russian researchers. The first one is the Russian birdwatching network RU-BIRDS.RU. The related GBIF dataset (Ukolov et al. 2019) is the third largest dataset for Russia (>370,000 species occurrences). Another Russian citizen science system is wildlifemonitoring.ru, which includes thematic resources for different taxonomic groups of vertebrates. This is the crowd-sourced web-GIS maintained by the Siberian Environmental Center NGO in Novosibirsk. It is noteworthy that iNaturalist activities in Russia are developed more as a social network than as a way to attract volunteers to participate in scientific research. Of 746 citations in the iNaturalist dataset, only 18 articles include co-authors from Russia. iNaturalist data are used for the management of regional red lists (in the Republic of Bashkortostan, Novosibirsk Oblast and others), and as an additional information source for regional inventories. RU-BIRDS data were used in the European Russia Breeding Bird Atlas and the new edition of the European Breeding Bird Atlas. In Russia, citizen science activities significantly contribute to filling gaps in the global biodiversity map. However, Russian iNaturalist observations available through GBIF originate from the USA. It is not ideal, because the iNaturalist GBIF dataset is growing rapidly, and in the future it will represent more than all other datasets for Russia combined. In our opinion, iNaturalist data should be repatriated during the process of publishing through GBIF, as it is implemented for the eBird dataset (Levatich and Ligocki 2020).


Author(s):  
Yvan Le Bras ◽  
Aurélie Delavaud ◽  
Dominique Pelletier ◽  
Jean-Baptiste Mihoub

Most biodiversity research aims at understanding the states and dynamics of biodiversity and ecosystems. To do so, biodiversity research increasingly relies on the use of digital products and services such as raw data archiving systems (e.g. structured databases or data repositories), ready-to-use datasets (e.g. cleaned and harmonized files with normalized measurements or computed trends) as well as associated analytical tools (e.g. model scripts in Github). Several world-wide initiatives facilitate the open access to biodiversity data, such as the Global Biodiversity Information Facility (GBIF) or GenBank, Predicts etc. Although these pave the way towards major advances in biodiversity research, they also typically deliver data products that are sometimes poorly informative as they fail to capture the genuine ecological information they intend to grasp. In other words, access to ready-to-use aggregated data products may sacrifice ecological relevance for data harmonization, resulting in over-simplified, ill-advised standard formats. This is singularly true when the main challenge is to match complementary data (large diversity of measured variables, integration of different levels of life organizations etc.) collected with different requirements and scattered in multiple databases. Improving access to raw data, and meaningful detailed metadata and analytical tools associated with standardized workflows is critical to maintain and maximize the generic relevance of ecological data. Consequently, advancing the design of digital products and services is essential for interoperability while also enhancing reproducibility and transparency in biodiversity research. To go further, a minimal common framework organizing biodiversity observation and data organization is needed. In this regard, the Essential Biodiversity Variable (EBV) concept might be a powerful way to boost progress toward this goal as well as to connect research communities worldwide. As a national Biodiversity Observation Network (BON) node, the French BON is currently embodied by a national research e-infrastructure called "Pôle national de données de biodiversité" (PNDB, formerly ECOSCOPE), aimed at simultaneously empowering the quality of scientific activities and promoting networking within the scientific community at a national level. Through the PNDB, the French BON is working on developing biodiversity data workflows oriented toward end services and products, both from and for a research perspective. More precisely, the two pillars of the PNDB are a metadata portal and a workflow-oriented web platform dedicated to the access of biodiversity data and associated analytical tools (Galaxy-E). After four years of experience, we are now going deeper into metadata specification, dataset descriptions and data structuring through the extensive use of Ecological Metadata Language (EML) as a pivot format. Moreover, we evaluate the relevance of existing tools such as Metacat/Morpho and DEIMS-SDR (Dynamic Ecological Information Management System - Site and dataset registry) in order to ensure a link with other initiatives like Environmental Data Initiative, DataOne and Long-Term Ecological Research related observation networks. Regarding data analysis, an open-source Galaxy-E platform was launched in 2017 as part of a project targeting the design of a citizen science observation system in France (“65 Millions d'observateurs”). Here, we propose to showcase ongoing French activities towards global challenges related to biodiversity information and knowledge dissemination. We particularly emphasize our focus on embracing the FAIR (findable, accessible, interoperable and reusable) data principles Wilkinson et al. 2016 across the development of the French BON e-infrastructure and the promising links we anticipate for operationalizing EBVs. Using accessible and transparent analytical tools, we present the first online platform allowing the performance of advanced yet user-friendly analyses of biodiversity data in a reproducible and shareable way using data from various data sources, such as GBIF, Atlas of Living Australia (ALA), eBIRD, iNaturalist and environmental data such as climate data.


Author(s):  
Gil Nelson ◽  
Deborah L Paul

Integrated Digitized Biocollections (iDigBio) is the United States’ (US) national resource and coordinating center for biodiversity specimen digitization and mobilization. It was established in 2011 through the US National Science Foundation’s (NSF) Advancing Digitization of Biodiversity Collections (ADBC) program, an initiative that grew from a working group of museum-based and other biocollections professionals working in concert with NSF to make collections' specimen data accessible for science, education, and public consumption. The working group, Network Integrated Biocollections Alliance (NIBA), released two reports (Beach et al. 2010, American Institute of Biological Sciences 2013) that provided the foundation for iDigBio and ADBC. iDigBio is restricted in focus to the ingestion of data generated by public, non-federal museum and academic collections. Its focus is on specimen-based (as opposed to observational) occurrence records. iDigBio currently serves about 118 million transcribed specimen-based records and 29 million specimen-based media records from approximately 1600 datasets. These digital objects have been contributed by about 700 collections representing nearly 400 institutions and is the most comprehensive biodiversity data aggregator in the US. Currently, iDigBio, DiSSCo (Distributed System of Scientific Collections), GBIF (Global Biodiversity Information Facility), and the Atlas of Living Australia (ALA) are collaborating on a global framework to harmonize technologies towards standardizing and synchronizing ingestion strategies, data models and standards, cyberinfrastructure, APIs (application programming interface), specimen record identifiers, etc. in service to a developing consolidated global data product that can provide a common source for the world’s digital biodiversity data. The collaboration strives to harness and combine the unique strengths of its partners in ways that ensure the individual needs of each partner’s constituencies are met, design pathways for accommodating existing and emerging aggregators, simultaneously strengthen and enhance access to the world’s biodiversity data, and underscore the scope and importance of worldwide biodiversity informatics activities. Collaborators will share technology strategies and outputs, align conceptual understandings, and establish and draw from an international knowledge base. These collaborators, along with Biodiversity Information Standards (TDWG), will join iDigBio and the Smithsonian National Museum of Natural History as they host Biodiversity 2020 in Washington, DC. Biodiversity 2020 will combine an international celebration of the worldwide progress made in biodiversity data accessibility in the 21st century with a biodiversity data conference that extends the life of Biodiversity Next. It will provide a venue for the GBIF governing board meeting, TDWG annual meeting, and the annual iDigBio Summit as well as three days of plenary and concurrent sessions focused on the present and future of biodiversity data generation, mobilization, and use.


2021 ◽  
pp. 60-76
Author(s):  
Jeffrey D. Myers

Physician assistant (PA) training is rooted in treating the whole patient and developing a trusting and collaborative partnership with patients and their families. This foundation is critical in the advance care planning (ACP) process for patients who are seriously or terminally ill. Understanding the ACP process, the components and reasons behind them, and the tools for successful discussions and decision-making is a key skill set for all healthcare providers, including PAs. This chapter examines the components of ACP, including advance directives, the POLST paradigm, decision-makers, prognostication, documentation, and legacy planning. ACP is key in capturing what is most important to our patients in terms of their health, their life, and their goals related to both.


2017 ◽  
Vol 28 (1) ◽  
pp. 12 ◽  
Author(s):  
Ted Lefroy ◽  
Luciana L. Porfirio

The proportion of funds received by the Commonwealth Scientific and Industrial Organisation (CSIRO) from sources other than Treasury, referred to as external earnings, has been used by the Australian government as an indicator of CSIRO's engagement with industry and contribution to the economy. Two periods of decline in external earnings in the 1940s and the 1980s were followed by enquiries into the organisation's purpose and operation, amendments to CSIRO's enabling legislation and introduction of measures to improve industry engagement. After 1988 these measures included a 30% external earnings target. External earnings subsequently rose from 24% of total revenue in 1988/89 to average 36% over the period to 2014/15, peaking at 51% in 2011. Following a review in 2002 the target was removed due to its unintended consequences that included encouraging competition with private industry, placing emphasis on earning capacity over public good, and acting as a disincentive to innovation and collaboration.


2018 ◽  
Vol 2 ◽  
pp. e26367
Author(s):  
Yvette Umurungi ◽  
Samuel Kanyamibwa ◽  
Faustin Gashakamba ◽  
Beth Kaplin

Freshwater biodiversity is critically understudied in Rwanda, and to date there has not been an efficient mechanism to integrate freshwater biodiversity information or make it accessible to decision-makers, researchers, private sector or communities, where it is needed for planning, management and the implementation of the National Biodiversity Strategy and Action Plan (NBSAP). A framework to capture and distribute freshwater biodiversity data is crucial to understanding how economic transformation and environmental change is affecting freshwater biodiversity and resulting ecosystem services. To optimize conservation efforts for freshwater ecosystems, detailed information is needed regarding current and historical species distributions and abundances across the landscape. From these data, specific conservation concerns can be identified, analyzed and prioritized. The purpose of this project is to establish and implement a long-term strategy for freshwater biodiversity data mobilization, sharing, processing and reporting in Rwanda. The expected outcome of the project is to support the mandates of the Rwanda Environment Management Authority (REMA), the national agency in charge of environmental monitoring and the implementation of Rwanda’s NBSAP, and the Center of Excellence in Biodiversity and Natural Resources Management (CoEB). The project also aligns with the mission of the Albertine Rift Conservation Society (ARCOS) to enhance sustainable management of natural resources in the Albertine rift region. Specifically, organizational structure, technology platforms, and workflows for the biodiversity data capture and mobilization are enhanced to promote data availability and accessibility to improve Rwanda’s NBSAP and support other decision-making processes. The project is enhancing the capacity of technical staff from relevant government and non-government institutions in biodiversity informatics, strengthening the capacity of CoEB to achieve its mission as the Rwandan national biodiversity knowledge management center. Twelve institutions have been identified as data holders and the digitization of these data using Darwin Core standards is in progress, as well as data cleaning for the data publication through the ARCOS Biodiversity Information System (http://arbmis.arcosnetwork.org/). The release of the first national State of Freshwater Biodiversity Report is the next step. CoEB is a registered publisher to the Global Biodiversity Information Facility (GBIF) and holds an Integrated Publishing Toolkit (IPT) account on the ARCOS portal. This project was developed for the African Biodiversity Challenge, a competition coordinated by the South African National Biodiversity Institute (SANBI) and funded by the JRS Biodiversity Foundation which supports on-going efforts to enhance the biodiversity information management activities of the GBIF Africa network. This project also aligns with SANBI’s Regional Engagement Strategy, and endeavors to strengthen both emerging biodiversity informatics networks and data management capacity on the continent in support of sustainable development.


Author(s):  
Carrie Seltzer

Since 2008, iNaturalist has been crowdsourcing identifications for biodiversity observations collected by citizen scientists. Today iNaturalist has over 25 million records of wild biodiversity with photo or audio evidence, from every country, representing more than 230,000 species, collected by over 700,000 people, and with 90,000 people helping others with identifications. Hundreds of publications have used iNaturalist data to advance research, conservation, and policy. There are three key themes that iNaturalist has embraced: social interaction; shareability of data, tools, and code; and scalability of the platform and community. The keynote will share reflections on what has (and has not) worked for iNaturalist while drawing on other examples from biodiversity informatics and citizen science. Insights about user motivations, synergistic collaborations, and strategic decisions about scaling offer some transferable approaches to address the broadly applicable questions: Which species is represented? How do we make the best use of the available biodiversity information? And how do we build something viable and enduring in the process?


2015 ◽  
Author(s):  
Kristy Deiner ◽  
Emanuel A. Fronhofer ◽  
Elvira Meächler ◽  
Jean-Claude Walser ◽  
Florian Altermatt

AbstractDNA sampled from the environment (eDNA) is becoming a game changer for uncovering biodiversity patterns. By combining a conceptual model and empirical data, we test whether eDNA transported in river networks can be used as an integrative way to assess eukaryotic biodiversity for broad spatial scales and across the land-water interface. Using an eDNA metabarcode approach we detected 296 families of eukaryotes, spanning 19 phyla across the catchment of a river. We show for a subset of these families that eDNA samples overcome spatial autocorrelation biases associated with classical community assessments by integrating biodiversity information over space. Additionally, we demonstrate that many terrestrial species can be detected; thus revealing that eDNA in river-water also incorporates biodiversity information across terrestrial and aquatic biomes. Environmental DNA transported in river networks offers a novel and spatially integrated way to assess total biodiversity for whole landscapes and will transform biodiversity data acquisition in ecology.“Eventually, all things merge into one, 32 and a river runs through it.” — Norman Maclean


2016 ◽  
Vol 11 ◽  
Author(s):  
Alex Asase ◽  
A. Townsend Peterson

Providing comprehensive, informative, primary, research-grade biodiversity information represents an important focus of biodiversity informatics initiatives. Recent efforts within Ghana have digitized >90% of primary biodiversity data records associated with specimen sheets in Ghanaian herbaria; additional herbarium data are available from other institutions via biodiversity informatics initiatives such as the Global Biodiversity Information Facility. However, data on the plants of Ghana have not as yet been integrated and assessed to establish how complete site inventories are, so that appropriate levels of confidence can be applied. In this study, we assessed inventory completeness and identified gaps in current Digital Accessible Knowledge (DAK) of the plants of Ghana, to prioritize areas for future surveys and inventories. We evaluated the completeness of inventories at ½° spatial resolution using statistics that summarize inventory completeness, and characterized gaps in coverage in terms of geographic distance and climatic difference from well-documented sites across the country. The southwestern and southeastern parts of the country held many well-known grid cells; the largest spatial gaps were found in central and northern parts of the country. Climatic difference showed contrasting patterns, with a dramatic gap in coverage in central-northern Ghana. This study provides a detailed case study of how to prioritize for new botanical surveys and inventories based on existing DAK.


Author(s):  
Beckett Sterner ◽  
Nathan Upham ◽  
Prashant Gupta ◽  
Caleb Powell ◽  
Nico Franz

Making the most of biodiversity data requires linking observations of biological species from multiple sources both efficiently and accurately (Bisby 2000, Franz et al. 2016). Aggregating occurrence records using taxonomic names and synonyms is computationally efficient but known to experience significant limitations on accuracy when the assumption of one-to-one relationships between names and biological entities breaks down (Remsen 2016, Franz and Sterner 2018). Taxonomic treatments and checklists provide authoritative information about the correct usage of names for species, including operational representations of the meanings of those names in the form of range maps, reference genetic sequences, or diagnostic traits. They increasingly provide taxonomic intelligence in the form of precise description of the semantic relationships between different published names in the literature. Making this authoritative information Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al. 2016) would be a transformative advance for biodiversity data sharing and help drive adoption and novel extensions of existing standards such as the Taxonomic Concept Schema and the OpenBiodiv Ontology (Kennedy et al. 2006, Senderov et al. 2018). We call for the greater, global Biodiversity Information Standards (TDWG) and taxonomy community to commit to extending and expanding on how FAIR applies to biodiversity data and include practical targets and criteria for the publication and digitization of taxonomic concept representations and alignments in taxonomic treatments, checklists, and backbones. As a motivating case, consider the abundantly sampled North American deer mouse—Peromyscus maniculatus (Wagner 1845)—which was recently split from one continental species into five more narrowly defined forms, so that the name P. maniculatus is now only applied east of the Mississippi River (Bradley et al. 2019, Greenbaum et al. 2019). That single change instantly rendered ambiguous ~7% of North American mammal records in the Global Biodiversity Information Facility (n=242,663, downloaded 2021-06-04; GBIF.org 2021) and ⅓ of all National Ecological Observatory Network (NEON) small mammal samples (n=10,256, downloaded 2021-06-27). While this type of ambiguity is common in name-based databases when species are split, the example of P. maniculatus is particularly striking for its impact upon biological questions ranging from hantavirus surveillance in North America to studies of climate change impacts upon rodent life-history traits. Of special relevance to NEON sampling is recent evidence suggesting deer mice potentially transmit SARS-CoV-2 (Griffin et al. 2021). Automating the updating of occurrence records in such cases and others will require operational representations of taxonomic concepts—e.g., range maps, reference sequences, and diagnostic traits—that are FAIR in addition to taxonomic concept alignment information (Franz and Peet 2009). Despite steady progress, it remains difficult to find, access, and reuse authoritative information about how to apply taxonomic names even when it is already digitized. It can also be difficult to tell without manual inspection whether similar types of concept representations derived from multiple sources, such as range maps or reference sequences selected from different research articles or checklists, are in fact interoperable for a particular application. The issue is therefore different from important ongoing efforts to digitize trait information in species circumscriptions, for example, and focuses on how already digitized knowledge can best be packaged to inform human experts and artifical intelligence applications (Sterner and Franz 2017). We therefore propose developing community guidelines and criteria for FAIR taxonomic concept representations as "semantic artefacts" of general relevance to linked open data and life sciences research (Le Franc et al. 2020).


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