School of Biological Sciences, Southern Illinois University, 1125 Lincoln Drive, Carbondale, IL 62901, USA.
Department of Biological Sciences, Rutgers University Newark, 195 University Ave, Newark, NJ 07102, USA.
Syst Biol. 2021 Aug 11;70(5):1033-1045. doi: 10.1093/sysbio/syab016.
Ancestral range estimation and projection of niche models into the past have both become common in evolutionary studies where the ancient distributions of organisms are in question. However, these methods are hampered by complementary hurdles: discrete characterization of areas in ancestral range estimation can be overly coarse, especially at shallow timescales, and niche model projection neglects evolution. Phylogenetic niche modeling accounts for both of these issues by incorporating knowledge of evolutionary relationships into a characterization of environmental tolerances. We present a new method for phylogenetic niche modeling, implemented in R. Given past and present climate data, taxon occurrence data, and a time-calibrated phylogeny, our method constructs niche models for each extant taxon, uses ancestral character estimation to reconstruct ancestral niche models, and projects these models into paleoclimate data to provide a historical estimate of the geographic range of a lineage. Models either at nodes or along branches of the phylogeny can be estimated. We demonstrate our method on a small group of dendrobatid frogs and show that it can make inferences given species with restricted ranges and little occurrence data. We also use simulations to show that our method can reliably reconstruct the niche of a known ancestor in both geographic and environmental space. Our method brings together fields as disparate as ecological niche modeling, phylogenetics, and ancestral range estimation in a user-friendly package. [Ancestral range estimation; ancestral state reconstruction; biogeography; Dendrobatidae; ecological niche modeling; paleoclimate; phylogeography; species distribution modeling.].
祖先范围估计和生态位模型的过去投影在进化研究中变得很常见,这些研究涉及到生物体的古代分布。然而,这些方法受到互补障碍的阻碍:祖先范围估计中区域的离散特征可能过于粗糙,尤其是在时间尺度较浅的情况下,而生态位模型的投影忽略了进化。系统发育生态位建模通过将进化关系的知识纳入环境耐受度的特征化来解决这两个问题。我们提出了一种新的系统发育生态位建模方法,在 R 中实现。给定过去和现在的气候数据、分类群出现数据和时间校准的系统发育树,我们的方法为每个现存的分类群构建生态位模型,使用祖先特征估计来重建祖先生态位模型,并将这些模型投影到古气候数据中,以提供一个谱系的地理范围的历史估计。可以在系统发育树的节点或分支上估计模型。我们在一小群树蛙上演示了我们的方法,并表明它可以在物种分布范围有限且出现数据较少的情况下进行推断。我们还使用模拟来表明,我们的方法可以在地理和环境空间中可靠地重建已知祖先的生态位。我们的方法将生态位建模、系统发育学和祖先范围估计等领域结合在一个用户友好的包中。