Ciência habilitada por dados de espécimes

Li, D., X. Wang, K. Jiang, R. An, Y. Li, and D. Liu. 2024. The impact of climate change and the conservation of the keystone Asian honeybee using niche models and systematic prioritization C. Bahlai [ed.],. Journal of Economic Entomology. https://doi.org/10.1093/jee/toae018

Global warming has seriously disturbed the Earth’s ecosystems, and in this context, Asian honeybee (Apis cerana) has experienced a dramatic decline in recent decades. Here, we examined both direct and indirect effects of climate change on A. cerana through ecological niche modeling of A. cerana, and its disease pathogens (i.e., Chinese sacbrood virus and Melissococcus plutonius) and enemies (i.e., Galleria mellonella and Vespa mandarinia). Ecological niche modeling predicts that climate change will increase the potential suitability of A. cerana, but it will also cause some of the original habitat areas to become unsuitable. Outbreak risks of Chinese sacbrood disease and European Foulbrood will increase dramatically, while those of G. mellonella and V. mandarinia will decrease only slightly. Thus, climate change will produce an unfavorable situation for even maintaining some A. cerana populations in China in the future. Genetic structure analyses showed that the A. cerana population from Hainan Island had significant genetic differentiation from that of the mainland, and there was almost no gene flow between the 2, suggesting that urgent measures are needed to protect the unique genetic resources there. Through taking an integrated planning technique with the Marxan approach, we optimized conservation planning, and identified potential nature reserves (mainly in western Sichuan and southern Tibet) for conservation of A. cerana populations. Our results can provide insights into the potential impact of climate change on A. cerana, and will help to promote the conservation of the keystone honeybee in China and the long-term sustainability of its ecosystem services.

Vasconcelos, T., J. D. Boyko, and J. M. Beaulieu. 2021. Linking mode of seed dispersal and climatic niche evolution in flowering plants. Journal of Biogeography. https://doi.org/10.1111/jbi.14292

Aim: Due to the sessile nature of flowering plants, movements to new geographical areas occur mainly during seed dispersal. Frugivores tend to be efficient dispersers because animals move within the boundaries of their preferable niches, so seeds are more likely to be transported to environments tha…

Xue, T., S. R. Gadagkar, T. P. Albright, X. Yang, J. Li, C. Xia, J. Wu, and S. Yu. 2021. Prioritizing conservation of biodiversity in an alpine region: Distribution pattern and conservation status of seed plants in the Qinghai-Tibetan Plateau. Global Ecology and Conservation 32: e01885. https://doi.org/10.1016/j.gecco.2021.e01885

The Qinghai-Tibetan Plateau (QTP) harbors abundant and diverse plant life owing to its high habitat heterogeneity. However, the distribution pattern of biodiversity hotspots and their conservation status remain unclear. Based on 148,283 high-resolution occurrence coordinates of 13,450 seed plants, w…

Iqbal, I., A. Shabbir, K. Shabbir, M. Barkworth, F. Bareen, and S. Khan. 2020. Evolvulus nummularius (L.) L. (Convolvulaceae): a new alien plant record for Pakistan. BioInvasions Records 9: 702–711. https://doi.org/10.3391/bir.2020.9.4.04

Evolvulus nummularius (L.) L., a member of the Convolvulaceae, is native to Mexico and South America but nowadays grows around the world in many tropical and subtropical regions. Its presence in Pakistan, where it has become naturalized, is reported here for the first time. It was first discovered i…

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…