Science Enabled by Specimen Data

Boyd, R. J., M. A. Aizen, R. M. Barahona‐Segovia, L. Flores‐Prado, F. E. Fontúrbel, T. M. Francoy, M. Lopez‐Aliste, et al. 2022. Inferring trends in pollinator distributions across the Neotropics from publicly available data remains challenging despite mobilization efforts Y. Fourcade [ed.],. Diversity and Distributions 28: 1404–1415. https://doi.org/10.1111/ddi.13551

Aim Aggregated species occurrence data are increasingly accessible through public databases for the analysis of temporal trends in the geographic distributions of species. However, biases in these data present challenges for statistical inference. We assessed potential biases in data available through GBIF on the occurrences of four flower-visiting taxa: bees (Anthophila), hoverflies (Syrphidae), leaf-nosed bats (Phyllostomidae) and hummingbirds (Trochilidae). We also assessed whether and to what extent data mobilization efforts improved our ability to estimate trends in species' distributions. Location The Neotropics. Methods We used five data-driven heuristics to screen the data for potential geographic, temporal and taxonomic biases. We began with a continental-scale assessment of the data for all four taxa. We then identified two recent data mobilization efforts (2021) that drastically increased the quantity of records of bees collected in Chile available through GBIF. We compared the dataset before and after the addition of these new records in terms of their biases and estimated trends in species' distributions. Results We found evidence of potential sampling biases for all taxa. The addition of newly-mobilized records of bees in Chile decreased some biases but introduced others. Despite increasing the quantity of data for bees in Chile sixfold, estimates of trends in species' distributions derived using the postmobilization dataset were broadly similar to what would have been estimated before their introduction, albeit more precise. Main conclusions Our results highlight the challenges associated with drawing robust inferences about trends in species' distributions using publicly available data. Mobilizing historic records will not always enable trend estimation because more data do not necessarily equal less bias. Analysts should carefully assess their data before conducting analyses: this might enable the estimation of more robust trends and help to identify strategies for effective data mobilization. Our study also reinforces the need for targeted monitoring of pollinators worldwide.

Schneider, K., D. Makowski, and W. van der Werf. 2021. Predicting hotspots for invasive species introduction in Europe. Environmental Research Letters 16: 114026. https://doi.org/10.1088/1748-9326/ac2f19

Plant pest invasions cost billions of Euros each year in Europe. Prediction of likely places of pest introduction could greatly help focus efforts on prevention and control and thus reduce societal costs of pest invasions. Here, we test whether generic data-driven risk maps of pest introduction, val…

Busch, A. K., B. E. Wham, and J. F. Tooker. 2021. Life History, Biology, and Distribution of Pterostichus melanarius (Coleoptera: Carabidae) in North America J. Schmidt [ed.],. Environmental Entomology 50: 1257–1266. https://doi.org/10.1093/ee/nvab090

Pterostichus melanarius (Illiger, 1798) is a Palearctic generalist predator native to Europe. It was unintentionally introduced to North America at least twice in the mid 1920s and has since become widespread in Canada and the United States. Although P. melanarius is a valuable natural enemy in many…

Miller, E. F., R. E. Green, A. Balmford, P. Maisano Delser, R. Beyer, M. Somveille, M. Leonardi, et al. 2021. Bayesian Skyline Plots disagree with range size changes based on Species Distribution Models for Holarctic birds. Molecular Ecology 30: 3993–4004. https://doi.org/10.1111/mec.16032

During the Quaternary, large climate oscillations impacted the distribution and demography of species globally. Two approaches have played a major role in reconstructing changes through time: Bayesian Skyline Plots (BSPs), which reconstruct population fluctuations based on genetic data, and 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…

随机森林(Random forest)模型在2001年发表后得到广泛的关注。由于随机森林可以进行回归和判别等多种统计分析,而且不受正态性、方差齐性和自变量独立性等参数检验的前提条件的制约,其应用日益普遍,有被看作万能模型的趋势。实际上,随机森林是一种特点鲜明的模型,应用局部优化拟合观察值,在分析有偏效应关系的数据时,其结果往往不准确。本文以蝉科(Cicadidea)物种的分布数据为例,比较了随机森林在回归分析时与多元线性回归、广义可加模型和人工神经网络模型的差别,在判别分析时与线性判别分析的差别,强调了随机森林预测时的碎片化特点。结果显示随机森林在处理有多元共线性和交互作用的数据时,以及在判别…

Fletcher, T. L., A. Z. Csank, and A. P. Ballantyne. 2019. Identifying bias in cold season temperature reconstructions by beetle mutual climatic range methods in the Pliocene Canadian High Arctic. Palaeogeography, Palaeoclimatology, Palaeoecology 514: 672–676. https://doi.org/10.1016/j.palaeo.2018.11.025

Well-preserved beetle elytra from the fossil and subfossil record are used by palaeoclimatologists to estimate past temperatures. Beetle-derived estimates of temperature across the Pliocene Arctic are consistently lower than those derived from other palaeoclimate proxies. Here we test if that patter…

Hoekman, D., K. E. LeVan, C. Gibson, G. E. Ball, R. A. Browne, R. L. Davidson, T. L. Erwin, et al. 2017. Design for ground beetle abundance and diversity sampling within the National Ecological Observatory Network. Ecosphere 8. https://doi.org/10.1002/ecs2.1744

The National Ecological Observatory Network (NEON) will monitor ground beetle populations across a network of broadly distributed sites because beetles are prevalent in food webs, are sensitive to abiotic factors, and have an established role as indicator species of habitat and climatic shifts. We d…

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…

Zigler, K., M. Niemiller, C. Stephen, B. Ayala, M. Milne, N. Gladstone, A. Engel, et al. 2020. Biodiversity from caves and other sub-terranean habitats of Georgia, USA. Journal of Cave and Karst Studies 82: 125–167. 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…