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.
Li, X., B. Li, G. Wang, X. Zhan, and M. Holyoak. 2020. Deeply digging the interaction effect in multiple linear regressions using a fractional-power interaction term. MethodsX 7: 101067. https://doi.org/10.1016/j.mex.2020.101067
In multiple regression Y ~ β0 + β1X1 + β2X2 + β3X1 X2 + ɛ., the interaction term is quantified as the product of X1 and X2. We developed fractional-power interaction regression (FPIR), using βX1M X2N as the interaction term. The rationale of FPIR is that the slopes of Y-X1 regression along the X2 gr…