Science Enabled by Specimen Data

Grünig, M., Calanca, P., Mazzi, D., & Pellissier, L. (2020). Inflection point in climatic suitability of insect pest species in Europe suggests non‐linear responses to climate change. Global Change Biology. doi:10.1111/gcb.15313 https://doi.org/10.1111/gcb.15313

Climate change and globalization affect the suitable conditions for agricultural crops and insect pests, threatening future food security. It remains unknown whether shifts in species’ climatic suitability will be linear or rather non‐linear, with crop exposure to pests suddenly increasing when a cr…

Liu, X., Blackburn, T. M., Song, T., Wang, X., Huang, C., & Li, Y. (2020). Animal invaders threaten protected areas worldwide. Nature Communications, 11(1). doi:10.1038/s41467-020-16719-2 https://doi.org/10.1038/s41467-020-16719-2

Protected areas are the cornerstone of biodiversity conservation. However, alien species invasion is an increasing threat to biodiversity, and the extent to which protected areas worldwide are resistant to incursions of alien species remains poorly understood. Here, we investigate establishment by 8…

Zigler, K., Niemiller, M., Stephen, C., Ayala, B., Milne, M., Gladstone, N., … Cressler, A. (2020). Biodiversity from caves and other sub-terranean habitats of Georgia, USA. Journal of Cave and Karst Studies, 82(2), 125–167. doi:10.4311/2019lsc0125 https://doi.org/10.4311/2019LSC0125

We provide an annotated checklist of species recorded from caves and other subterranean habitats in the state of Georgia, USA. We report 281 species (228 invertebrates and 53 vertebrates), including 51 troglobionts (cave-obligate species), from more than 150 sites (caves, springs, and wells). Endemi…

McCoshum, S. M., & Geber, M. A. (2020). Land Conversion for Solar Facilities and Urban Sprawl in Southwest Deserts Causes Different Amounts of Habitat Loss for Ashmeadiella Bees. Journal of the Kansas Entomological Society, 92(2), 468. doi:10.2317/0022-8567-92.2.468 https://doi.org/10.2317/0022-8567-92.2.468

Land conversion for human use poses one of the greatest threats to terrestrial ecosystems and causes habitat loss for a myriad of species. The development of large solar energy facilities and urban sprawl are converting wild lands in the Southwest deserts of the USA for human use and resulting in ha…

Daniel, J., Horrocks, J., & Umphrey, G. J. (2019). Efficient Modelling of Presence-Only Species Data via Local Background Sampling. Journal of Agricultural, Biological and Environmental Statistics. doi:10.1007/s13253-019-00380-4 https://doi.org/10.1007/s13253-019-00380-4

In species distribution modelling, records of species presence are often modelled as a realization of a spatial point process whose intensity is a function of environmental covariates. One way to fit a spatial point process model is to apply logistic regression to an artificial case–control sample c…

Ezray, B. D., Wham, D. C., Hill, C. E., & Hines, H. M. (2019). Unsupervised machine learning reveals mimicry complexes in bumblebees occur along a perceptual continuum. Proceedings of the Royal Society B: Biological Sciences, 286(1910), 20191501. doi:10.1098/rspb.2019.1501 https://doi.org/10.1098/rspb.2019.1501

Müllerian mimicry theory states that frequency-dependent selection should favour geographical convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes, each containing a predominant phenotype. Outside a few exam…

Looney, C., Strange, J. P., Freeman, M., & Jennings, D. (2019). The expanding Pacific Northwest range of Bombus impatiens Cresson and its establishment in Washington State. Biological Invasions. doi:10.1007/s10530-019-01970-6 https://doi.org/10.1007/s10530-019-01970-6

Bombus impatiens, the common eastern bumble bee, is the first bumble bee established outside of its native range in North America. Native to the eastern portion of the continent, the species was imported to British Columbia in the early 2000s for greenhouse pollination and subsequently became establ…

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 …