ChiroVox: a public library of bat calls

Recordings of bat echolocation and social calls are used for many research purposes from ecological studies to taxonomy. Effective use of these relies on identification of species from the recordings, but comparative recordings or detailed call descriptions to support identification are often lacking for areas with high biodiversity. The ChiroVox website (www.chirovox.org) was created to facilitate the sharing of bat sound recordings together with their metadata, including biodiversity data and recording circumstances. To date, more than 30 researchers have contributed over 3,900 recordings of nearly 200 species, making ChiroVox the largest open-access bat call library currently available. Each recording has a unique identifier that can be cited in publications; hence the acoustic analyses are repeatable. Most of the recordings available through the website are from bats whose species identities are confirmed, so they can be used to determine species in recordings where the bats were not captured or could not be identified. We hope that with the help of the bat researcher community, the website will grow rapidly and will serve as a solid source for bat acoustic research and monitoring.

Reviewing taxonomic bias in a megadiverse country: primary biodiversity data, cultural salience, and scientific interest of South African animals

Taxonomic bias, resulting in some taxa receiving more attention than others, has been shown to persist throughout history. Such bias in primary biodiversity data needs to be addressed because the data are vital to environmental management. This study reviews taxonomic bias in South African primary biodiversity data obtained from the Global Biodiversity Information Facility (GBIF). The focus was specifically on animal classes, and regression analysis was used to assess the influence of scientific interest and cultural salience on taxonomic bias. A higher resolution analysis of the two explanatory variables’ influence on taxonomic bias is conducted using a generalised linear model on a subset of herpetofaunal families from the focal classes. Furthermore, the potential effects of cultural salience and scientific interest on a taxon’s extinction risk are investigated. The findings show that taxonomic bias in South Africa’s primary biodiversity data has similarities with global scale taxonomic bias. Among animal classes, there is strong bias towards birds while classes such as Polychaeta and Maxillopoda are under-represented. Cultural salience has a stronger influence on taxonomic bias than scientific interest. It is, however, unclear how these explanatory variables may influence the extinction risk of taxa. We recommend that taxonomic bias can be reduced if primary biodiversity data collection has a range of targets that guide (but do not limit) accumulation of species occurrence records per habitat. Within this range, a lower target of species occurrence records accommodates species that are difficult to detect. The upper target means occurrence records for any species are less urgent but nonetheless useful and thus data collection efforts can focus on species with fewer occurrence records.

Phylogenomic and mitogenomic data can accelerate inventorying of tropical beetles during the current biodiversity crisis

Conservation efforts must be evidence-based, so rapid and economically feasible methods should be used to quantify diversity and distribution patterns. We have attempted to overcome current impediments to the gathering of biodiversity data by using integrative phylogenomic and three mtDNA fragment analyses. As a model, we sequenced the Metriorrhynchini beetle fauna, sampled from ~700 localities in three continents. The species-rich dataset included ~6,500 terminals, ~1,850 putative species delimited at 5% uncorrected pairwise threshold, possibly ~1,000 of them unknown to science. Neither type of data could alone answer our questions on biodiversity and phylogeny. The phylogenomic backbone enabled the integrative delimitation of robustly defined natural genus-group units that will inform future research. Using constrained mtDNA analysis, we identified the spatial structure of species diversity, very high species-level endemism, and a biodiversity hotspot in New Guinea. We suggest that focused field research and subsequent laboratory and bioinformatic workflow steps would substantially accelerate the inventorying of any hyperdiverse tropical group with several thousand species. The outcome would be a scaffold for the incorporation of further data from environmental sequencing and ecological studies. The database of sequences could set a benchmark for the spatiotemporal evaluation of biodiversity, would support evidence-based conservation planning, and would provide a robust framework for systematic, biogeographic, and evolutionary studies.

Translating TDWG Controlled Vocabularies

Users may be more likely to understand and utilize standards if they are able to read labels and definitions of terms in their own languages. Increasing standards usage in non-English speaking parts of the world will be important for making biodiversity data from across the globe more uniformly available. For these reasons, it is important for Biodiversity Information Standards (TDWG) to make its standards widely available in as many languages as possible. Currently, TDWG has six ratified controlled vocabularies*1, 2, 3, 4, 5, 6 that were originally available only in English. As an outcome of this workshop, we have made term labels and definitions in those vocabularies available in the languages of translators who participated in its sessions. In the introduction, we reviewed the concept of vocabularies, explained the distinction between term labels and controlled value strings, and described how multilingual labels and definitions fit into the standards development process. The introduction was followed by working sessions in which individual translators or small groups working in a single language filled out Google Sheets with their translations. The resulting translations were compiled along with attribution information for the translators and made freely available in JavaScript Object Notation (JSON) and comma separated values (CSV) formats.*7

The Obs-Services and their potentials for biodiversity data assessments with a test of the current reliability of photo-identification of Coleoptera in the field

The current reliability of species identifications by the Nature Identification API (NIA) of the app ObsIdentify is tested with a Coleoptera (Insecta) sample set from Germany. Seventy-five photographic beetle records taken with a smartphone camera under “average user” conditions are analysed in terms of correctness of the app’s identification result on various taxonomic levels, the displayed confidence level of the identification and the time until validation of the results. More than 60% of samples were identified correctly at the species level, but only 53% were validated within a month. The mechanisms by which users can upload pictures of their observations to be identified by the artificial intelligence and the validation process by experts are briefly explained. Regional specifics and further opportunities for data usage as well as currently existing problems are discussed and improvements are suggested. The expert validation of records is identified as a huge quality advantage of the Obs-Services. They are generally found to be a promising tool for lay people and professional institutions, despite still existing deficiencies such as identification failure in mutilated specimens, cryptic and rare species, doubtful species rarity ratings as well as the still insufficient capacity of validation. Experts and institutions are encouraged to volunteer as validators and collaborators.

Nocturnal Coleoptera and Hemiptera Diversity at Giam Siak Kecil Bukit Batu Biosphere Reserve Indonesia

Giam Siak Kecil Bukit Batu is a biosphere reserve which one of its functions is as a habitat for wildlife. However, biodiversity data in the Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB-BR) is still very minimal, including insects (Coleoptera and Hemiptera). This research was conducted to determine the diversity of Coleoptera and Hemiptera in the GSKBB Biosphere Reserve, Riau, Indonesia. The research was carried out using an exploratory method using "lights trap". The results of the study found 30 species, from 11 families of the order Coleoptera (23 species) and Hemiptera (7 species) in the GSKBB-BR. The diversity index of Coleoptera and Hemiptera at the observation site was moderate (H = 2.73), with a high evenness index (0.80). Scarabaeidae (order Coleoptera) is the family with the highest number of species found (8 species), while the most abundant species were Tibicen linnei and Pomponia fusca (Cicadidae/Hemiptera). Based on their functional roles, Coleoptera and Hemiptera with the highest number are herbivores (17 species), followed by predators (7 species) and decomposers (3 species). The range of values for temperature and humidity at the research site are in normal conditions. The GSKBB-BR area is an important remaining habitat for wildlife in Riau, including various types of insects (Coleoptera and Hemiptera); whose potential still needs to be revealed, and must be managed properly.

Identifying Black Corals and Octocorals From Deep-Sea Imagery for Ecological Assessments: Trade-Offs Between Morphology and Taxonomy

An increased reliance on imagery as the source of biodiversity data from the deep sea has stimulated many recent advances in image annotation and data management. The form of image-derived data is determined by the way faunal units are classified and should align with the needs of the ecological study to which it is applied. Some applications may require only low-resolution biodiversity data, which is easier and cheaper to generate, whereas others will require well-resolved biodiversity measures, which require a larger investment in annotation methods. We assessed these trade-offs using a dataset of 5 939 images and physical collections of black and octocorals taken during surveys from a seamount area in the southwest Pacific Ocean. Coral diversity was greatly underestimated in images: only 55 black and octocoral ‘phototaxa’ (best-possible identifications) were consistently distinguishable out of a known 210 species in the region (26%). Patterns of assemblage composition were compared between the phototaxa and a standardized Australian classification scheme (“CATAMI”) that uses morphotypes to classify taxa. Results were similar in many respects, but the identities of dominant, and detection of rare but locally abundant, coral entities were achieved only when annotation was at phototaxon resolution, and when faunal densities were recorded. A case study of data from 4 seamounts compared three additional classification schemes. Only the two with highest resolution – phototaxon and a combined phototaxon-morphological scheme – were able to distinguish black and octocoral communities on unimpacted vs. impacted seamounts. We conclude that image annotation schemes need to be fit-for-purpose. Morphological schemes such as CATAMI may perform well and are most easily standardized for cross-study data sharing, but high resolution (and more costly) annotation schemes are likely necessary for some ecological and management-based applications including biodiversity inventory, change detection (monitoring) – and to develop automated annotation using machine learning.

A cloud-based toolbox for the versatile environmental annotation of biodiversity data

A vast range of research applications in biodiversity sciences requires integrating primary species, genetic, or ecosystem data with other environmental data. This integration requires a consideration of the spatial and temporal scale appropriate for the data and processes in question. But a versatile and scale flexible environmental annotation of biodiversity data remains constrained by technical hurdles. Existing tools have streamlined the intersection of occurrence records with gridded environmental data but have remained limited in their ability to address a range of spatial and temporal grains, especially for large datasets. We present the Spatiotemporal Observation Annotation Tool (STOAT), a cloud-based toolbox for flexible biodiversity–environment annotations. STOAT is optimized for large biodiversity datasets and allows user-specified spatial and temporal resolution and buffering in support of environmental characterizations that account for the uncertainty and scale of data and of relevant processes. The tool offers these services for a growing set of near global, remotely sensed, or modeled environmental data, including Landsat, MODIS, EarthEnv, and CHELSA. STOAT includes a user-friendly, web-based dashboard that provides tools for annotation task management and result visualization, linked to Map of Life, and a dedicated R package (rstoat) for programmatic access. We demonstrate STOAT functionality with several examples that illustrate phenological variation and spatial and temporal scale dependence of environmental characteristics of birds at a continental scale. We expect STOAT to facilitate broader exploration and assessment of the scale dependence of observations and processes in ecology.