Science Enabled by Specimen Data

Afonin, A. N., Fedorova, Y. A., & Li, Y. S. (2019). Characterization of the Occurrence and Abundance of the Common Ragweed (Ambrosia artemisiifolia L.) with Regard to Assessment of Its Expansion Potential in European Russia. Russian Journal of Biological Invasions, 10(3), 220–226. doi:10.1134/s2075111719030032 https://doi.org/10.1134/S2075111719030032

A field study of common ragweed (Ambrosia artemisiifolia L.) in European Russia provided information on the occurrence and abundance of the species and enabled a prediction of the possible boundaries of species naturalization. As a result, the understanding of the ecological limits of common ragweed…

Schubert, M., Marcussen, T., Meseguer, A. S., & Fjellheim, S. (2019). The grass subfamily Pooideae: Cretaceous–Palaeocene origin and climate‐driven Cenozoic diversification. Global Ecology and Biogeography. doi:10.1111/geb.12923 https://doi.org/10.1111/geb.12923

Aim: Frost is among the most dramatic stresses a plant can experience, and complex physiological adaptations are needed to endure long periods of sub‐zero temperatures. Owing to the need to evolve these complex adaptations, transitioning from tropical to temperate climates is regarded as difficult. …

Schubert, M., Groenvold, L., Sandve, S. R., Hvidsten, T. R., & Fjellheim, S. (2019). Evolution of cold acclimation and its role in niche transition in the temperate grass subfamily Pooideae. Plant Physiology, pp.01448.2018. doi:10.1104/pp.18.01448 https://doi.org/10.1104/pp.18.01448

The grass subfamily Pooideae dominates the grass floras in cold temperate regions, and has evolved complex physiological adaptations to cope with extreme environmental conditions like frost, winter and seasonality. One such adaptation is cold acclimation, wherein plants increase their frost toleranc…

Sullivan, J., Smith, M. L., Espíndola, A., Ruffley, M., Rankin, A., Tank, D., & Carstens, B. (2019). Integrating life history traits into predictive phylogeography. Molecular Ecology. doi:10.1111/mec.15029 https://doi.org/10.1111/mec.15029

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive …