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Xu, X.-T., J. Szwedo, D.-Y. Huang, W.-Y.-D. Deng, M. Obroślak, F.-X. Wu, and T. Su. 2022. A New Genus of Spittlebugs (Hemiptera, Cercopidae) from the Eocene of Central Tibetan Plateau. Insects 13: 770. https://doi.org/10.3390/insects13090770

The superfamily Cercopoidea is commonly named as “spittlebugs”, as its nymphs produce a spittle mass to protect themselves. Cosmoscartini (Cercopoidea: Cercopidae) is a large and brightly colored Old World tropical tribe, including 11 genera. A new genus Nangamostethos gen. nov. (type species: Nangamostethostibetense sp. nov.) of Cosmoscartini is described from Niubao Formation, the late Eocene of central Tibetan Plateau (TP), China. Its placement is ensured by comparison with all the extant genera of the tribe Cosmoscartini. The new fossil represents one of few fossil Cercopidae species described from Asia. It is likely that Nangamostethos was extinct from the TP due to the regional aridification and an overturn of plant taxa in the late Paleogene.

Vilardo, G., M. Faccoli, J. C. Corley, and M. V. Lantschner. 2022. Factors driving historic intercontinental invasions of European pine bark beetles. Biological Invasions 24: 2973–2991. https://doi.org/10.1007/s10530-022-02818-2

Largely assisted by global trade, alien insect species are being introduced into new territories at unprecedented rates. Among forest insects, pine bark beetles (Coleoptera: Curculionidae, Scolytinae) are a large and diverse group commonly recognized as successful invaders and important tree mortality agents in pine forests and commercial plantations. In this study, we collected information on the native and invaded distribution of 51 European bark beetles developing in Pinus species. We analyzed their invasion history in the Southern Hemisphere and the Americas and explored several factors that can help explain their invasion success: (1) propagule pressure: interception frequency in the non-native range(2) invasibility: potential establishment area based on climatic matching and host availability and (3) invasiveness: biological traits of the bark beetles ( i.e. , feeding habit, host range, body size, mating system, colonization behavior). We found that most (87%) of the introductions of the species to new regions occurred in the period 1960–2013, and that variables related with the three main factors were relevant in explaining invasion success. Propagule pressure was the factor that best explained bark beetle invasion probability, followed by invasibility of the novel area. In turn, biological attributes like mating system, body size and host range were also relevant, but showed a lower relative importance. Our study contributes to understand the main factors that explain forest insect invasion success. This information is critical for predicting future invasions to new regions and optimizing early-detection and biosecurity policies.

Li, D., Z. Li, Z. Liu, Y. Yang, A. G. Khoso, L. Wang, and D. Liu. 2022. Climate change simulations revealed potentially drastic shifts in insect community structure and crop yields in China’s farmland. Journal of Pest Science. https://doi.org/10.1007/s10340-022-01479-3

Climate change will cause drastic fluctuations in agricultural ecosystems, which in turn may affect global food security. We used ecological niche modeling to predict the potential distribution for four cereal aphids (i.e., Sitobion avenae, Rhopalosiphum padi, Schizaphis graminum, and Diurphis noxia…

Kolanowska, M. 2021. The future of a montane orchid species and the impact of climate change on the distribution of its pollinators and magnet species. Global Ecology and Conservation 32: e01939. https://doi.org/10.1016/j.gecco.2021.e01939

The aim of this study was to evaluate the impact of global warming on suitable niches of montane orchid, Traunsteinera globosa, using ecological niche modelling approach. Additionally, the effect of various climate change scenarios on future changes in the distribution and overlap of the orchid magn…

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…

Yoon, S., and W.-H. Lee. 2021. Methodological analysis of bioclimatic variable selection in species distribution modeling with application to agricultural pests (Metcalfa pruinosa and Spodoptera litura). Computers and Electronics in Agriculture 190: 106430. https://doi.org/10.1016/j.compag.2021.106430

MaxEnt is a machine-learning-based species distribution modeling tool that is widely used to evaluate the occurrence possibility of a species. The characteristics of the algorithm requires that bioclimatic variables are appropriately selected in order for the model to predict species occurrence as p…

Arfianti, T., and M. J. Costello. 2021. The distribution of benthic amphipod crustaceans in Indonesian seas. PeerJ 9: e12054. https://doi.org/10.7717/peerj.12054

Amphipod crustaceans are an essential component of tropical marine biodiversity. However, their distribution and biogeography have not been analysed in one of the world’s largest tropical countries nested in the Coral Triangle, Indonesia. We collected and identified amphipod crustaceans from eight s…

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…

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…