Science Enabled by Specimen Data

Kopperud, B. T., S. Lidgard, and L. H. Liow. 2022. Enhancing georeferenced biodiversity inventories: automated information extraction from literature records reveal the gaps. PeerJ 10: e13921. https://doi.org/10.7717/peerj.13921

We use natural language processing (NLP) to retrieve location data for cheilostome bryozoan species (text-mined occurrences (TMO)) in an automated procedure. We compare these results with data combined from two major public databases (DB): the Ocean Biodiversity Information System (OBIS), and the Global Biodiversity Information Facility (GBIF). Using DB and TMO data separately and in combination, we present latitudinal species richness curves using standard estimators (Chao2 and the Jackknife) and range-through approaches. Our combined DB and TMO species richness curves quantitatively document a bimodal global latitudinal diversity gradient for extant cheilostomes for the first time, with peaks in the temperate zones. A total of 79% of the georeferenced species we retrieved from TMO (N = 1,408) and DB (N = 4,549) are non-overlapping. Despite clear indications that global location data compiled for cheilostomes should be improved with concerted effort, our study supports the view that many marine latitudinal species richness patterns deviate from the canonical latitudinal diversity gradient (LDG). Moreover, combining online biodiversity databases with automated information retrieval from the published literature is a promising avenue for expanding taxon-location datasets.

Ramírez, F., V. Sbragaglia, K. Soacha, M. Coll, and J. Piera. 2022. Challenges for Marine Ecological Assessments: Completeness of Findable, Accessible, Interoperable, and Reusable Biodiversity Data in European Seas. Frontiers in Marine Science 8. https://doi.org/10.3389/fmars.2021.802235

The ongoing contemporary biodiversity crisis may result in much of ocean’s biodiversity to be lost or deeply modified without even being known. As the climate and anthropogenic-related impacts on marine systems accelerate, biodiversity knowledge integration is urgently required to evaluate and monit…

Deka, M. A. 2022. Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping. Tropical Medicine and Infectious Disease 7: 15. https://doi.org/10.3390/tropicalmed7020015

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to b…

Qu, J., Y. Xu, Y. Cui, S. Wu, L. Wang, X. Liu, Z. Xing, et al. 2021. MODB: a comprehensive mitochondrial genome database for Mollusca. Database 2021. https://doi.org/10.1093/database/baab056

Mollusca is the largest marine phylum, comprising about 23% of all named marine organisms, Mollusca systematics are still in flux, and an increase in human activities has affected Molluscan reproduction and development, strongly impacting diversity and classification. Therefore, it is necessary to e…

Boag, T. H., W. Gearty, and R. G. Stockey. 2021. Metabolic tradeoffs control biodiversity gradients through geological time. Current Biology 31: 2906-2913.e3. https://doi.org/10.1016/j.cub.2021.04.021

The latitudinal gradient of increasing marine biodiversity from the poles to the tropics is one of the most conspicuous biological patterns in modern oceans.1, 2, 3 Low-latitude regions of the global ocean are often hotspots of animal biodiversity, yet they are set to be most critically affected b…

Yusri, S., V. P. Siregar, and Suharsono. 2019. Distribution Modelling of Porites (Poritidae) in Indonesia. IOP Conference Series: Earth and Environmental Science 363: 012025. https://doi.org/10.1088/1755-1315/363/1/012025

Porites (Poritidae) is one of the most temperature induced bleaching-resistant coral genera. Therefore, their presence is essential for coral reefs to survive when facing the threat of climate change. Species distribution modelling for Porites corals could provide predictive maps of species distribu…

Saeedi, H., and M. Costello. 2019. A world dataset on the geographic distributions of Solenidae razor clams (Mollusca: Bivalvia). Biodiversity Data Journal 7. https://doi.org/10.3897/bdj.7.e31375

Background: Using this dataset, we examined the global geographical distributions of Solenidae species in relation to their endemicity, species richness and latitudinal ranges and then predicted their distributions under future climate change using species distribution modelling techniques (Saeedi e…