Microbial diversity analyses have revolutionized our knowledge of the microscopic world, from terrestrial and marine to human and urban environments. This growing field rests on the evolutionary relatedness of organisms, and at its frontier is the inference of ecological processes from phylogenetic diversity. However, the rapidly reducing cost of sequencing means that computational analysis of phylogenetic data is becoming increasingly intractable. We develop a new analytical method to address this issue, providing a computationally-efficient way to compare local phylogenetic diversity to a sample from a regional pool of organisms, under a given ecological process. Our approach has both pragmatic and far-reaching applications. Until now investigators have lacked even an analytical method to compare the diversity of unequally-sized communities without throwing data away, while on a deeper level our theory provides a new framework for connecting phylogenetic data to a wide range of ecological processes. As an application of our approach, we use our methods to distinguish between random, clustered and overdispersed sampling for human microbiome habitats. Finally, we identify a new, phylogenetic analogue of the widely used taxonomic measure of diversity, the Species Abundance Distribution, and we find that it has consistent behavior across microbiome habitats.
CITATION STYLE
Agrawal, M., Saxena, B. K., & Rao, K. V. S. (2019). Techno-Economic Analysis of a Grid-Connected Hybrid Solar–Wind Energy System (pp. 81–92). https://doi.org/10.1007/978-981-13-1202-1_7
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