ORCID Profile
0000-0001-5942-9053
Current Organisation
Global Biodiversity Information Facility
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Publisher: The University of Kansas
Date: 06-03-2022
Abstract: The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with participants globally through ,000 hours of viewing and ,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.
Publisher: Pensoft Publishers
Date: 07-09-2022
DOI: 10.3897/BISS.6.94209
Abstract: Assessing and addressing bio ersity needs are of critical and time-sensitive importance, with the post-2020 Global Bio ersity Framework’s Global Taxonomy Initiative underscoring the need to build capacity in how we conceptualize bio ersity (Abrahamse et al. 2021). Species—as biological units—and their names are the backbone for the data integration and synthesis needed for bio ersity research and conservation decision-making (Grace et al. 2021). In integrating name sources for a single taxonomic group, barriers frequently limit linking species names across regional and global authoritative sources. In response to such challenges, we present a case study testing a Globally Integrated Structure of Taxonomy (GIST) to ensure the integration of taxonomy in bio ersity and conservation sciences . This framework characterizes the components enabling transparent association of species names through synonymy (alternate names or spellings), authorship, specimens, versions and timest s, and taxonomic relationships in space and time. Taxonomy provides a critical link between bio ersity data types and databases. Efforts towards global taxonomic integration are confounded by insufficient connectivity between taxonomic assemblages, with implications for research, monitoring, and conservation practice (Christie et al. 2021, Jetz et al. 2019, McClure et al. 2020). In attempting to match multiple taxonomic groups across databases, we highlight current progress and remaining challenges to produce and use a GIST . We evaluate the standardized, comprehensive taxonomies of mammals, birds, reptiles, hibians, dragonflies and damselflies, butterflies, ants, plants, and crabs produced for the Map of Life project (Jetz et al. 2012), identifying which missing components impede their utility. We show that for terrestrial mammals, GIST standards are almost fulfilled, but for invertebrate taxa, such as butterflies, GIST standards are unmet, resulting in broken taxonomic links between aggregators of genetic, spatial, functional, and physical data. We find that even the comprehensive taxonomies we examine do not harmonize well with taxonomies of global genetics, phylogenetics, macroecology, and conservation databases. This is because current taxonomic data infrastructures on bio ersity respositories lack the necessary structural components, searchability, and name source transparency to fully integrate taxonomies, as different independently advancing data sources lack standard metadata practices and operable interfaces. The GIST components enable data linkage and provide clear sourcing and metadata, enabling taxonomic data accessibility, reuse, and interoperability. This structure can act as a step toward open and FAIR (Findable, Accessible, Interoperable, and Reusable) data practice as it relates to taxon names (Wilkinson et al. 2016). Without transparent, integrated, accessible, and updated taxonomic information, macroecological inferences and conservation decisions for even charismatic groups are impeded.
No related grants have been discovered for Kate Ingenloff.