Ciencia habilitada por datos de especímenes

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…

Klages, J. P., U. Salzmann, T. Bickert, C.-D. Hillenbrand, K. Gohl, G. Kuhn, et al. 2020. Temperate rainforests near the South Pole during peak Cretaceous warmth. Nature 580: 81–86. https://doi.org/10.1038/s41586-020-2148-5

The mid-Cretaceous period was one of the warmest intervals of the past 140 million years1,2,3,4,5, driven by atmospheric carbon dioxide levels of around 1,000 parts per million by volume6. In the near absence of proximal geological records from south of the Antarctic Circle, it is disputed whether p…

Inman, R., J. Franklin, T. Esque, and K. Nussear. 2018. Spatial sampling bias in the Neotoma paleoecological archives affects species paleo-distribution models. Quaternary Science Reviews 198: 115–125. https://doi.org/10.1016/j.quascirev.2018.08.015

The ability to infer paleo-distributions with limited knowledge of absence makes species distribution modeling (SDM) a useful tool for exploring paleobiogeographic questions. Spatial sampling bias is a known issue when modeling extant species. Here we quantify the spatial sampling bias in a North Am…