Science Enabled by Specimen Data

Lake, T. A., Briscoe Runquist, R. D., & Moeller, D. A. (2020). Predicting range expansion of invasive species: Pitfalls and best practices for obtaining biologically realistic projections. Diversity and Distributions, 26(12), 1767–1779. doi:10.1111/ddi.13161 https://doi.org/10.1111/ddi.13161

Aim: Species distribution models (SDMs) are widely used to forecast potential range expansion of invasive species. However, invasive species occurrence datasets often have spatial biases that may violate key SDM assumptions. In this study, we examined alternative methods of spatial bias correction a…

Brightly, W. H., Hartley, S. E., Osborne, C. P., Simpson, K. J., & Strömberg, C. A. E. (2020). High silicon concentrations in grasses are linked to environmental conditions and not associated with C 4 photosynthesis. Global Change Biology. doi:10.1111/gcb.15343 https://doi.org/10.1111/gcb.15343

The uptake and deposition of silicon (Si) as silica phytoliths is common among land plants and is associated with a variety of functions. Among these, herbivore defense has received significant attention, particularly with regards to grasses and grasslands. Grasses are well known for their high sili…

[1]P. Talhinhas, “An annotated checklist of rust fungi (Pucciniales) occurring in Portugal,” Sydowia An International Journal of Mycology, vol. 71, pp. 65–84, Jun. 2019. https://doi.org/10.12905/0380.sydowia71-2019-0065

In this work we have retrieved and analysed data for 2319 occurrences of rust fungi from 246 Pucciniales taxa in Portugal based on 115 publications and our own surveys, totalizing 683 rust taxon-host taxon unique combinations. This list was updated according to current taxonomic framework and georef…