Science Enabled by Specimen Data

Wint, G. R. W., T. Balenghien, E. Berriatua, M. Braks, C. Marsboom, J. Medlock, F. Schaffner, et al. 2023. VectorNet: collaborative mapping of arthropod disease vectors in Europe and surrounding areas since 2010. Eurosurveillance 28. https://doi.org/10.2807/1560-7917.es.2023.28.26.2200666

Background Arthropod vectors such as ticks, mosquitoes, sandflies and biting midges are of public and veterinary health significance because of the pathogens they can transmit. Understanding their distributions is a key means of assessing risk. VectorNet maps their distribution in the EU and surrounding areas. Aim We aim to describe the methodology underlying VectorNet maps, encourage standardisation and evaluate output. Method s: Vector distribution and surveillance activity data have been collected since 2010 from a combination of literature searches, field-survey data by entomologist volunteers via a network facilitated for each participating country and expert validation. Data were collated by VectorNet members and extensively validated during data entry and mapping processes. Results As of 2021, the VectorNet archive consisted of ca 475,000 records relating to > 330 species. Maps for 42 species are routinely produced online at subnational administrative unit resolution. On VectorNet maps, there are relatively few areas where surveillance has been recorded but there are no distribution data. Comparison with other continental databases, namely the Global Biodiversity Information Facility and VectorBase show that VectorNet has 5–10 times as many records overall, although three species are better represented in the other databases. In addition, VectorNet maps show where species are absent. VectorNet’s impact as assessed by citations (ca 60 per year) and web statistics (58,000 views) is substantial and its maps are widely used as reference material by professionals and the public. Conclusion VectorNet maps are the pre-eminent source of rigorously validated arthropod vector maps for Europe and its surrounding areas.

Outammassine, A., S. Zouhair, and S. Loqman. 2021. Global potential distribution of three underappreciated arboviruses vectors ( Aedes japonicus , Aedes vexans and Aedes vittatus ) under current and future climate conditions. Transboundary and Emerging Diseases 69. https://doi.org/10.1111/tbed.14404

Arboviruses (arthropod-borne viruses) are expanding their geographic range, posing significant health threats to millions of people worldwide. This expansion is associated with efficient and suitable vector availability. Apart from the well-known Aedes aegypti and Ae. albopictus, other Aedes species…

Orr, M. C., A. C. Hughes, D. Chesters, J. Pickering, C.-D. Zhu, and J. S. Ascher. 2021. Global Patterns and Drivers of Bee Distribution. Current Biology 31: 451-458.e4. https://doi.org/10.1016/j.cub.2020.10.053

Insects are the focus of many recent studies suggesting population declines, but even invaluable pollination service providers such as bees lack a modern distributional synthesis. Here, we combine a uniquely comprehensive checklist of bee species distributions and >5,800,000 public bee occurrence re…

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…

Daniel, J., J. Horrocks, and G. J. Umphrey. 2019. Efficient Modelling of Presence-Only Species Data via Local Background Sampling. Journal of Agricultural, Biological and Environmental Statistics 25: 90–111. 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., D. C. Wham, C. E. Hill, and H. M. Hines. 2019. Unsupervised machine learning reveals mimicry complexes in bumblebees occur along a perceptual continuum. Proceedings of the Royal Society B: Biological Sciences 286: 20191501. 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…

Rankin, A. M., R. S. Schwartz, C. H. Floyd, and K. E. Galbreath. 2019. Contrasting consequences of historical climate change for marmots at northern and temperate latitudes. Journal of Mammalogy 100: 328–344. https://doi.org/10.1093/jmammal/gyz025

Many species that occupy high latitudes of North America were historically restricted to relatively small refugia during the Last Glacial Maximum (LGM). The geographic ranges of many of these species then expanded widely across the continent after glacial ice receded. In contrast, species whose LGM …