| Autor: |
Alves‐Ferreira, Gabriela, Mota, Flávio Mariano Machado, Custódio Talora, Daniela, Oliveira, Cynthia Valéria, Solé, Mirco, Heming, Neander Marcel |
| Předmět: |
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| Zdroj: |
Ecography; Apr2024, Vol. 2024 Issue 4, p1-9, 9p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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