Science Enabled by Specimen Data

Moreno, I., J. M. W. Gippet, L. Fumagalli, and P. J. Stephenson. 2022. Factors affecting the availability of data on East African wildlife: the monitoring needs of conservationists are not being met. Biodiversity and Conservation. https://doi.org/10.1007/s10531-022-02497-4

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.

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…

Rotenberry, J. T., and P. Balasubramaniam. 2020. Connecting species’ geographical distributions to environmental variables: range maps versus observed points of occurrence. Ecography 43: 897–913. https://doi.org/10.1111/ecog.04871

Connecting the geographical occurrence of a species with underlying environmental variables is fundamental for many analyses of life history evolution and for modeling species distributions for both basic and practical ends. However, raw distributional information comes principally in two forms: poi…

Liu, X., T. M. Blackburn, T. Song, X. Li, C. Huang, and Y. Li. 2019. Risks of Biological Invasion on the Belt and Road. Current Biology 29: 499-505.e4. https://doi.org/10.1016/j.cub.2018.12.036

China’s Belt and Road Initiative (BRI) is an unprecedented global development program that involves nearly half of the world’s countries [1]. It not only will have economic and political influences, but also may generate multiple environmental challenges and is a focus of considerable academic and p…