Assessing species-level gaps and biases in occurrence data

Do species attributes, range geometry or socio-economic factors impact variation in species occurrence information?

Data resources used via GBIF : 4,524,585 species occurrences
Geoffroy’s Tamarin (Saguinus geoffroyi)

Geoffroy’s Tamarin (Saguinus geoffroyi) by Henry De La Torre via iNaturalist. Photo licensed under CC BY-NC 4.0.

Gaps in data may hamper good species distribution modelling. When assessing quality of species occurrence data, an often suggested (but rarely tested) cause of species-level variation and bias is, that species attributes, e.g. body size and diurnal activity, affect detection and collection. In this study, researchers overlaid GBIF-mediated occurrences of 3,625 mammalian species with expert-drawn range maps, and assessed occurrences of species and higher taxonomic groups according to record count, range coverage and geographical bias. Relating these to species attributes, range geometry and socio-economic factors, the researchers found that primates stand out for below average record counts, and carnivores for below average range coverage. Marsupials, however, score high in both measures. On a global scale, coverage is, not surprisingly, positively correlated with record count. However, the role of species attributes is remarkably minor. The study concludes by recommending increased data mobilization in institutions near data gaps and added focus on understudied species.

Citations

Meyer C, Jetz W, Guralnick RP, Fritz SA and Kreft H (2016) Range geometry and socio-economics dominate species-level biases in occurrence information. Global Ecology and Biogeography. Wiley-Blackwell 25(10): 1181–1193. Available at doi:10.1111/geb.12483.

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