Constraints on Patterns of Abundance and Aggregation in Biological Systems

Understanding the mechanisms that structure biological systems is a primary goal of biology. My research shows that the biological structure is constrained in important ways by general variables such as the number of base pairs in a genome and the number of individuals and species in a community. I used a combination of macroecology, bioinformatics, statistics, mathematics, and advanced computing to pursue my research and published several peer-reviewed scientific manuscripts and open-source software as a result.I was funded through a combination of fellowships and scholarships awarded by the Utah State University School of Graduate Studies, College of Science, and Department of Biology, as well as teaching assistantships awarded through the Department of Biology at Utah State University, and research assistantships funded through a CAREER grant from the U.S. National Science Foundation (DEB-0953694) awarded to my advisor, Dr. Ethan White. With the help of my advisor, I also obtained a computing grant from Amazon Web Services in the amount of $7,500. Altogether, funding for my research and education totaled approximately$123,500. Using over 9000 communities of plants, animals, fungi, and microorganisms, I demonstrated that the forms of empirical species abundance distributions (SADs) are constrained by total abundance and species richness. Using over 300 microbial genomes, I demonstrate that nucleotide aggregation is constrained by genome length and differs between regions of coding and noncoding DNA. General state variables of genomes and ecological communities (i.e. genome length, total abundance and species richness) constrain simple structural properties of each system

Simple Structural Differences between Coding and Noncoding DNA

Background The study of large-scale genome structure has revealed patterns suggesting the influence of evolutionary constraints on genome evolution. However, the results of these studies can be difficult to interpret due to the conceptual complexity of the analyses. This makes it difficult to understand how observed statistical patterns relate to the physical distribution of genomic elements. We use a simpler and more intuitive approach to evaluate patterns of genome structure. Methodology/Principal Findings We used randomization tests based on Morisita\u27s Index of aggregation to examine average differences in the distribution of purines and pyrimidines among coding and noncoding regions of 261 chromosomes from 223 microbial genomes representing 21 phylum level groups. Purines and pyrimidines were aggregated in the noncoding DNA of 86% of genomes, but were only aggregated in the coding regions of 52% of genomes. Coding and noncoding DNA differed in aggregation in 94% of genomes. Noncoding regions were more aggregated than coding regions in 91% of these genomes. Genome length appears to limit aggregation, but chromosome length does not. Chromosomes from the same species are similarly aggregated despite substantial differences in length. Aggregation differed among taxonomic groups, revealing support for a previously reported pattern relating genome structure to environmental conditions. Conclusions/Significance Our approach revealed several patterns of genome structure among different types of DNA, different chromosomes of the same genome, and among different taxonomic groups. Similarity in aggregation among chromosomes of varying length from the same genome suggests that individual chromosome structure has not evolved independently of the general constraints on genome structure as a whole. These patterns were detected using simple and readily interpretable methods commonly used in other areas of biology

A Communal Catalogue Reveals Earth\u27s Multiscale Microbial Diversity

Our growing awareness of the microbial world\u27s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth\u27s microbial diversity

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

Data from: A residence time theory for biodiversity

From microorganisms to the largest macroorganisms, much of Earth’s biodiversity is subject to forces of physical turnover. Residence time is the ratio of an ecosystem’s size to its rate of flow and provides a means for understanding the influence of physical turnover on biological systems. Despite its use across scientific disciplines, residence time has not been integrated into the broader understanding of biodiversity, life history, and the assembly of ecological communities. Here, we propose a residence time theory for the growth, activity, abundance, and diversity of traits and taxa in complex ecological systems. Using thousands of stochastic individual-based models to simulate energetically constrained life history processes, we show that our predictions are conceptually sound, mutually compatible, and support ecological relationships that underpin much of biodiversity theory. We discuss the importance of residence time across the ecological hierarchy and propose how residence time can be integrated into theories ranging from population genetics to macroecology

Simulation data from residence time modeling

This compressed file is a directory that contains four files, each containing data from 10,000 individual-based models (IBMs). The file active.RAD-Data.csv contains simulated species rank-abundance data from the active portions of communities. The file RAD-Data.csv contains simulated species rank-abundance data from entire communities (active + dormant). Finally, the SimData.csv file contains all other simulated data resulting from residence time IBMs and needed to reproduce all figures for the associated manuscript

A residence time theory for biodiversity

ABSTRACT 6 From microorganisms to the largest macroorganisms, much of Earth's biodiversity is subject to forces of physical turnover. Residence time is the ratio of an ecosystem's size to its 8 rate of flow and provides a means for understanding the influence of physical turnover on biological systems. Despite its use across scientific disciplines, residence time has not been 10 integrated into the broader understanding of biodiversity, life history, and the assembly of ecological communities. Here, we propose a residence time theory for the growth, activity, 12 abundance, and diversity of traits and taxa in complex ecological systems. Using thousands of stochastic individual-based models to simulate energetically constrained life history processes, 14 we show that our predictions are conceptually sound, mutually compatible, and support ecological relationships that underpin much of biodiversity theory. We discuss the importance of 16 residence time across the ecological hierarchy and propose how residence time can be integrated into theories ranging from population genetics to macroecology. 18 PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2727v3 | CC BY 4.0 Open Access