Francis David Morice
F. D. Morice; F. Morice; Rev. F. D. Morice
23 Junho, 1849 – 21 Setembro, 1926
entomologist, classical scholar, translator, zoological collector
English clergyman, classical scholar, and entomologist (1849-1926)
http://www.wikidata.org/entity/Q5480693
Morice, Francis. 2025. Natural history specimens collected and/or identified and deposited. [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8316542
Ciência habilitada por dados de espécimes
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…
[NO TITLE AVAILABLE] https://doi.org/10.7679/j.issn.2095-1353.2019.022
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…
Uludag, A., N. Aksoy, A. Yazlık, Z. F. Arslan, E. Yazmış, I. Uremis, T. A. Cossu, et al. 2017. Alien flora of Turkey: checklist, taxonomic composition and ecological attributes. NeoBiota 35: 61–85. https://doi.org/10.3897/neobiota.35.12460
The paper provides an updated checklist of the alien flora of Turkey with information on its structure. The alien flora of Turkey comprises 340 taxa, among which there are 321 angiosperms, 17 gymnosperms and two ferns. Of the total number of taxa, 228 (68%) are naturalized and 112 (32%) are casual. …