The spatial exploration of richness, endemism, and evolutionary diversity patterns has become an important part of biogeographic research and conservation planning. As the volume and complexity of biogeographical and phylogenetic data increase, the need for efficient tools to manipulate and analyze these datasets becomes essential. The 'phyloraster' package addresses this need by facilitating the analysis of evolutionary diversity and endemism for rasters. Our package offers a set of functions to support the linkage of species distribution models (SDMs) with phylogenies, providing then an understanding of the spatial distribution of biodiversity. It covers three main stages: pre-processing, processing, and post-processing of macroecological and phylogenetic data. During the pre-processing step, basic functions are provided to prepare the data. The processing step combines functions to calculate indices including species richness, Faith's phylogenetic diversity, phylogenetic endemism, weighted endemism, and evolutionary distinctiveness. Additionally, this step includes functions to compute the standardized effect size for each metric using spatial and phylogenetic randomization methods, ensuring proper control for richness effects. The post-processing stage includes functions to calculate the change of metrics between different times (e.g. present and future). In relation to processing in our functions, we show that 'phyloraster' takes up considerably less RAM than the other packages when computing the same metrics (weighted endemism). Lower RAM usage minimizes the hardware requirements to work with high-resolution datasets from local to global scales. This broadens user accessibility of the spatialized measures of endemism and evolutionary diversity.

中文翻译：

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'phyloraster'：一个 R 包，用于计算栅格的特有现象和进化多样性的度量

对丰富性、特有性和进化多样性模式的空间探索已成为生物地理学研究和保护规划的重要组成部分。随着生物地理和系统发育数据的数量和复杂性的增加，对有效工具来操作和分析这些数据集的需求变得至关重要。 “phyloraster”包通过促进栅格的进化多样性和特有性分析来满足这一需求。我们的软件包提供了一组函数来支持物种分布模型（SDM）与系统发育的联系，从而提供对生物多样性空间分布的理解。它涵盖三个主要阶段：宏观生态和系统发育数据的预处理、处理和后处理。在预处理步骤中，提供了准备数据的基本功能。处理步骤结合函数来计算指数，包括物种丰富度、Faith 的系统发育多样性、系统发育特有性、加权特有性和进化独特性。此外，此步骤包括使用空间和系统发育随机化方法计算每个指标的标准化效应大小的函数，确保对丰富度效应的适当控制。后处理阶段包括计算不同时间（例如现在和未来）之间指标变化的函数。关于我们的函数中的处理，我们表明，在计算相同的指标（加权特有现象）时，“phyloraster”比其他包占用的 RAM 少得多。较低的 RAM 使用量可最大限度地降低处理从本地到全球规模的高分辨率数据集的硬件要求。这拓宽了用户对特有现象和进化多样性的空间化测量的可及性。