Categorization of species as native or nonnative using DNA sequence signatures without a complete reference library

New genetic diagnostic approaches have greatly aided efforts to document global biodiversity and improve biosecurity. This is especially true for organismal groups in which species diversity has been underestimated historically due to difficulties associated with sampling, the lack of clear morphological characteristics, and/or limited availability of taxonomic expertise. Among these methods, DNA sequence barcoding (also known as "DNA barcoding") and by extension, meta-barcoding for biological communities, has emerged as one of the most frequently utilized methods for DNA-based species identifications. Unfortunately, the use of DNA barcoding is limited by the availability of complete reference libraries (i.e., a collection of DNA sequences from morphologically identified species), and by the fact that the vast majority of species do not have sequences present in reference databases. Such conditions are critical especially in tropical locations that are simultaneously biodiversity rich and suffer from a lack of exploration and DNA characterization by trained taxonomic specialists. To facilitate efforts to document biodiversity in regions lacking complete reference libraries, we developed a novel statistical approach that categorizes unidentified species as being either likely native or likely nonnative based solely on measures of nucleotide diversity. We demonstrate the utility of this approach by categorizing a large sample of specimens of terrestrial insects and spiders (collected as part of the Moorea BioCode project) using a generalized linear mixed model (GLMM). Using a training data set of known endemic (n = 45) and known introduced species (n = 102), we then estimated the likely native/nonnative status for 4,663 specimens representing an estimated 1,288 species (412 identified species), including both those specimens that were either unidentified or whose endemic/introduced status was uncertain. Using this approach, we were able to increase the number of categorized specimens by a factor of 4.4 (from 794 to 3,497), and the number of categorized species by a factor of 4.8 from (147 to 707) at a rate much greater than chance (77.6% accuracy). The study identifies phylogenetic signatures of both native and nonnative species and suggests several practical applications for this approach including monitoring biodiversity and facilitating biosecurity.

Worldwide Engagement for Digitizing Biocollections (WeDigBio): The Biocollections Community's Citizen-Science Space on the Calendar

The digitization of biocollections is a critical task with direct implications for the global community who use the data for research and education. Recent innovations to involve citizen scientists in digitization increase awareness of the value of biodiversity specimens; advance science, technology, engineering, and math literacy; and build sustainability for digitization. In support of these activities, we launched the first global citizen-science event focused on the digitization of biodiversity specimens: Worldwide Engagement for Digitizing Biocollections (WeDigBio). During the inaugural 2015 event, 21 sites hosted events where citizen scientists transcribed specimen labels via online platforms (DigiVol, Les Herbonautes, Notes from Nature, the Smithsonian Institution's Transcription Center, and Symbiota). Many citizen scientists also contributed off-site. In total, thousands of citizen scientists around the world completed over 50,000 transcription tasks. Here, we present the process of organizing an international citizen-science event, an analysis of the event's effectiveness, and future directions—content now foundational to the growing WeDigBio event.

The notes from nature tool for unlocking biodiversity records from museum records through citizen science

Legacy data from natural history collections contain invaluable and irreplaceable information about biodiversity in the recent past, providing a baseline for detecting change and forecasting the future of biodiversity on a human-dominated planet. However, these data are often not available in formats that facilitate use and synthesis. New approaches are needed to enhance the rates of digitization and data quality improvement. Notes from Nature provides one such novel approach by asking citizen scientists to help with transcription tasks. The initial web-based prototype of Notes from Nature is soon widely available and was developed collaboratively by biodiversity scientists, natural history collections staff, and experts in citizen science project development, programming and visualization. This project brings together digital images representing different types of biodiversity records including ledgers , herbarium sheets and pinned insects from multiple projects and natural history collections. Experts in developing web-based citizen science applications then designed and built a platform for transcribing textual data and metadata from these images. The end product is a fully open source web transcription tool built using the latest web technologies. The platform keeps volunteers engaged by initially explaining the scientific importance of the work via a short orientation, and then providing transcription “missions” of well defined scope, along with dynamic feedback, interactivity and rewards. Transcribed records, along with record-level and process metadata, are provided back to the institutions.  While the tool is being developed with new users in mind, it can serve a broad range of needs from novice to trained museum specialist. Notes from Nature has the potential to speed the rate of biodiversity data being made available to a broad community of users.