Phylogeographic Estimation and Simulation of Global Diffusive Dispersal

2020 ◽  
Author(s):  
Stilianos Louca
Keyword(s):  
Brownian Motion ◽  
Geographic Location ◽  
R Package ◽  
Estimation Methods ◽  
Influenza B ◽  
Independent Contrasts ◽  
Time Resolved ◽  
Location Data ◽  
Brownian Motion Model ◽  
Random Walk Simulation

Abstract The analysis of time-resolved phylogenies (timetrees) and geographic location data allows estimation of dispersal rates, for example, for invasive species and infectious diseases. Many estimation methods are based on the Brownian Motion model for diffusive dispersal on a 2D plane; however, the accuracy of these methods deteriorates substantially when dispersal occurs at global scales because spherical Brownian motion (SBM) differs from planar Brownian motion. No statistical method exists for estimating SBM diffusion coefficients from a given timetree and tip coordinates, and no method exists for simulating SBM along a given timetree. Here, I present new methods for simulating SBM along a given timetree, and for estimating SBM diffusivity from a given timetree and tip coordinates using a modification of Felsenstein’s independent contrasts and maximum likelihood. My simulation and fitting methods can accommodate arbitrary time-dependent diffusivities and scale efficiently to trees with millions of tips, thus enabling new analyses even in cases where planar BM would be a sufficient approximation. I demonstrate these methods using a timetree of marine and terrestrial Cyanobacterial genomes, as well as timetrees of two globally circulating Influenza B clades. My methods are implemented in the R package “castor.” [Independent contrasts; phylogenetic; random walk; simulation; spherical Brownian motion.]

scholarly journals Metacoder: An R Package for Visualization and Manipulation of Community Taxonomic Diversity Data

2016 ◽  
Author(s):  
Zachary S. L. Foster ◽  
Thomas J. Sharpton ◽  
Niklaus J. Grünwald
Keyword(s):  
Geographic Location ◽  
Community Analysis ◽  
Taxonomic Diversity ◽  
R Package ◽  
Digital Pcr ◽  
Location Data ◽  
Level Data ◽  
The Hierarchical Structure ◽  
Hierarchical Nature ◽  
Tree Visualization

AbstractCommunity-level data, the type generated by an increasing number of metabarcoding studies, is often graphed as stacked bar charts or pie graphs that use color to represent taxa. These graph types do not convey the hierarchical structure of taxonomic classifications and are limited by the use of color for categories. As an alternative, we developed metacoder, an R package for easily parsing, manipulating, and graphing publication-ready plots of hierarchical data. Metacoder includes a dynamic and flexible function that can parse most text-based formats that contain taxonomic classifications, taxon names, taxon identifiers, or sequence identifiers. Metacoder can then subset, sample, and order this parsed data using a set of intuitive functions that take into account the hierarchical nature of the data. Finally, an extremely flexible plotting function enables quantitative representation of up to 4 arbitrary statistics simultaneously in a tree format by mapping statistics to the color and size of tree nodes and edges. Metacoder also allows exploration of barcode primer bias by integrating functions to run digital PCR. Although it has been designed for data from metabarcoding research, metacoder can easily be applied to any data that has a hierarchical component such as gene ontology or geographic location data. Our package complements currently available tools for community analysis and is provided open source with an extensive online user manual.Note: This article was previously submitted as a pre-print: Zachary S. L. Foster, Thomas J. Sharpton, Niklaus J. Grünwald. 2016. Metacoder: An R package for manipulation and heat tree visualization of community taxonomic data from metabar-coding. BioRxiv 071019; doi: http://dx.doi.org/10.1101/071019.

scholarly journals Trait Evolution on Phylogenetic Networks

2015 ◽  
Author(s):  
Dwueng-Chwuan Jhwueng ◽  
Brian O'Meara
Keyword(s):  
Brownian Motion ◽  
Measurement Error ◽  
Drought Tolerance ◽  
R Package ◽  
Phylogenetic Networks ◽  
Ancestral State ◽  
Trait Evolution ◽  
New Methods ◽  
Hybridization Event ◽  
Brownian Motion Model

Species may evolve on a reticulate network due to hybridization or other gene flow rather than on a strictly bifurcating tree, but comparative methods to deal with trait evolution on a network are lacking. We create such a method, which uses a Brownian motion model. Our method seeks to separately or jointly detect a bias in trait value coming from hybridization (β) and a burst of variation at the time of hybridization (v_H) associated with the hybridization event, as well as traditional Brownian motion parameters of ancestral state (μ) and rate of evolution (σ^2) of Brownian motion, as well as measurement error of the tips (SE). We test the method with extensive simulations. We also apply the model to two empirical examples, cichlid body size and Nicotiana drought tolerance, and find substantial measurement error and a hint that hybrids have greater drought tolerance in the latter case. The new methods are available in CRAN R package BMhyd.

Self-avoiding random walk: A Brownian motion model with local time drift

1987 ◽  
Vol 74 (2) ◽  
pp. 271-287 ◽  
Author(s):  
J. R. Norris ◽  
L. C. G. Rogers ◽  
David Williams
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Local Time ◽  
Motion Model ◽  
Time Drift ◽  
Brownian Motion Model

scholarly journals Blue Straggler Bimodality: A Brownian Motion Model

2018 ◽  
Vol 867 (2) ◽  
pp. 163 ◽  
Author(s):  
Mario Pasquato ◽  
Paolo Miocchi ◽  
Suk-Jin Yoon
Keyword(s):  
Brownian Motion ◽  
Motion Model ◽  
Blue Straggler ◽  
Brownian Motion Model

THE KRAMERS TURNOVER PROBLEM: RECROSSING EFFECTS AND THE ENERGY DIFFUSION DESCRIPTION OF THERMAL ACTIVATION

1989 ◽  
Vol 03 (14) ◽  
pp. 1093-1099 ◽  
Author(s):  
H. DEKKER
Keyword(s):  
Spectral Analysis ◽  
Brownian Motion ◽  
Thermal Activation ◽  
Phase Space Density ◽  
Potential Well ◽  
Motion Model ◽  
Action Variable ◽  
Energy Diffusion ◽  
Metastable Potential ◽  
Brownian Motion Model

Kramers' Brownian motion model for escape from a metastable potential well is reconsidered in terms of the particle's energy and the action variable near the peak of the barrier. The pertinent phase space density ρ(ε, s) is uniquely determined (i) by means of a spectral analysis and (ii) upon specifying the energy distribution of (re-)entering particles. The ensuing decay rate Γ goes to zero in the low as well as in the high friction limit according to Kramers' original formulae. The nature of the intermediate turnover regime is critically discussed — and a comparison with related recent work by Büttiker, Harris and Landauer, Mel'nikov and Meshkov, and Grabert is made — while a problem with the underlying density is pointed out.

scholarly journals Evaluation of an iron ore price forecast using a geometric Brownian motion model

2019 ◽  
Vol 72 (1 suppl 1) ◽  
pp. 9-15 ◽  
Author(s):  
André Lubene Ramos ◽  
Douglas Batista Mazzinghy ◽  
Viviane da Silva Borges Barbosa ◽  
Michel Melo Oliveira ◽  
Gilberto Rodrigues da Silva
Keyword(s):  
Brownian Motion ◽  
Iron Ore ◽  
Geometric Brownian Motion ◽  
Motion Model ◽  
Price Forecast ◽  
Brownian Motion Model

scholarly journals Analysis of the geomagnetic activity of the <i>D<sub>st</sub></i> index and self-affine fractals using wavelet transforms

2004 ◽  
Vol 11 (3) ◽  
pp. 303-312 ◽  
Author(s):  
H. L. Wei ◽  
S. A. Billings ◽  
M. Balikhin
Keyword(s):  
Brownian Motion ◽  
Geomagnetic Activity ◽  
Power Law ◽  
Wavelet Transforms ◽  
Effective Measure ◽  
Dst Index ◽  
Power Spectral ◽  
Power Law Exponent ◽  
Brownian Motion Model

Abstract. The geomagnetic activity of the Dst index is analyzed using wavelet transforms and it is shown that the Dst index possesses properties associated with self-affine fractals. For example, the power spectral density obeys a power-law dependence on frequency, and therefore the Dst index can be viewed as a self-affine fractal dynamic process. In fact, the behaviour of the Dst index, with a Hurst exponent H≈0.5 (power-law exponent β≈2) at high frequency, is similar to that of Brownian motion. Therefore, the dynamical invariants of the Dst index may be described by a potential Brownian motion model. Characterization of the geomagnetic activity has been studied by analysing the geomagnetic field using a wavelet covariance technique. The wavelet covariance exponent provides a direct effective measure of the strength of persistence of the Dst index. One of the advantages of wavelet analysis is that many inherent problems encountered in Fourier transform methods, such as windowing and detrending, are not necessary.

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