Plant communities affect arbuscular mycorrhizal fungal diversity and community composition in grassland microcosms

The diversity of arbuscular mycorrhizal (AM) fungi was investigated in an unfertilized limestone grassland soil supporting different synthesized vascular plant assemblages that had developed for 3 yr. The experimental treatments comprised: bare soil; monocultures of the nonmycotrophic sedge Carex flacca; monocultures of the mycotrophic grass Festuca ovina; and a species-rich mixture of four forbs, four grasses and four sedges. The diversity of AM fungi was analysed in roots of Plantago lanceolata bioassay seedlings using terminal-restriction fragment length polymorphism (T-RFLP). The extent of AM colonization, shoot biomass and nitrogen and phosphorus concentrations were also measured. The AM diversity was affected significantly by the floristic composition of the microcosms and shoot phosphorus concentration was positively correlated with AM diversity. The diversity of AM fungi in P. lanceolata decreased in the order: bare soil > C. flacca > 12 species > F. ovina. The unexpectedly high diversity in the bare soil and sedge monoculture likely reflects differences in the modes of colonization and sources of inoculum in these treatments compared with the assemblages containing established AM-compatible plants

The Akaike Information Criterion Will Not Choose the No Common Mechanism Model

This is an electronic version of an article published in Systematic Biology [Holder, Mark T., Paul O. Lewis, and David L. Swofford. The Akaike information criterion will not choose the no common mechanism model. Systematic Biology, 59(4):477{485, 2010. ] Systematic Biology is available online at informaworld http://dx.doi.org/10.1093/sysbio/syq028

BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software

Hastings Ratio of the LOCAL Proposal Used in Bayesian Phylogenetics

This is an electronic version of an article published in Systematic Biology ["Holder, Mark T., Paul O. Lewis, David L. Swofford, and Bret Larget. Hastings ratio of the local proposal used in Bayesian phylogenetics. Systematic Biology, 54:961{965, 2005.] Systematic Biology is available online at informaworld http://dx.doi.org/10.1080/1063515050035467

BEAGLE 3:Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics

© 2019 The Author(s). BEAGLE is a high-performance likelihood-calculation library for phylogenetic inference. The BEAGLE library defines a simple, but flexible, application programming interface (API), and includes a collection of efficient implementations for calculation under a variety of evolutionary models on different hardware devices. The library has been integrated into recent versions of popular phylogenetics software packages including BEAST and MrBayes and has been widely used across a diverse range of evolutionary studies. Here, we present BEAGLE 3 with new parallel implementations, increased performance for challenging data sets, improved scalability, and better usability. We have added new OpenCL and central processing unit-threaded implementations to the library, allowing the effective utilization of a wider range of modern hardware. Further, we have extended the API and library to support concurrent computation of independent partial likelihood arrays, for increased performance of nucleotide-model analyses with greater flexibility of data partitioning. For better scalability and usability, we have improved how phylogenetic software packages use BEAGLE in multi-GPU (graphics processing unit) and cluster environments, and introduced an automated method to select the fastest device given the data set, evolutionary model, and hardware. For application developers who wish to integrate the library, we also have developed an online tutorial. To evaluate the effect of the improvements, we ran a variety of benchmarks on state-of-the-art hardware. For a partitioned exemplar analysis, we observe run-time performance improvements as high as 5.9-fold over our previous GPU implementation. BEAGLE 3 is free, open-source software licensed under the Lesser GPL and available at https://beagle-dev.github.io

BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

Phylogenetic inference is fundamental to our understanding of most aspects of the origin and evolution of life, and in recent years, there has been a concentration of interest in statistical approaches such as Bayesian inference and maximum likelihood estimation. Yet, for large data sets and realistic or interesting models of evolution, these approaches remain computationally demanding. High-throughput sequencing can yield data for thousands of taxa, but scaling to such problems using serial computing often necessitates the use of nonstatistical or approximate approaches. The recent emergence of graphics processing units (GPUs) provides an opportunity to leverage their excellent floating-point computational performance to accelerate statistical phylogenetic inference. A specialized library for phylogenetic calculation would allow existing software packages to make more effective use of available computer hardware, including GPUs. Adoption of a common library would also make it easier for other emerging computing architectures, such as field programmable gate arrays, to be used in the future. We present BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference. The API provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms. The library includes a set of efficient implementations and can currently exploit hardware including GPUs using NVIDIA CUDA, central processing units (CPUs) with Streaming SIMD Extensions and related processor supplementary instruction sets, and multicore CPUs via OpenMP. To demonstrate the advantages of a common API, we have incorporated the library into several popular phylogenetic software packages. The BEAGLE library is free open source software licensed under the Lesser GPL and available from http://beagle-lib.googlecode.com. An example client program is available as public domain software.This work was supported by the National Science Foundation [grant numbers DBI-0755048, DEB-0732920, DEB-1036448, DMS-0931642, EF-0331495, EF-0905606, EF-0949453]; the National Institutes of Health [grant numbers R01-HG006139, R01-GM037841, R01-GM078985, R01-GM086887, R01-NS063897]; the Biotechnology and Biological Sciences Research Council [grant number BB/H011285/1]; the Wellcome Trust [grant number WT092807MA]; and Google Summer of Code

Epiparasitic plants specialized on arbuscular mycorrhizal fungi

Over 400 non-photosynthetic species from 10 families of vascular plants obtain their carbon from fungi and are thus defined as myco-heterotrophs. Many of these plants are epiparasitic on green plants from which they obtain carbon by 'cheating' shared mycorrhizal fungi. Epiparasitic plants examined to date depend on ectomycorrhizal fungi for carbon transfer and exhibit exceptional specificity for these fungi, but for most myco-heterotrophs neither the identity of the fungi nor the sources of their carbon are known. Because many myco-heterotrophs grow in forests dominated by plants associated with arbuscular mycorrhizal fungi (AMF; phylum Glomeromycota), we proposed that epiparasitism would occur also between plants linked by AMF. On a global scale AMF form the most widespread mycorrhizae, thus the ability of plants to cheat this symbiosis would be highly significant. We analysed mycorrhizae from three populations of Arachnitis uniflora (Corsiaceae, Monocotyledonae), five Voyria species and one Voyriella species (Gentianaceae, Dicotyledonae), and neighbouring green plants. Here we show that non-photosynthetic plants associate with AMF and can display the characteristic specificity of epiparasites. This suggests that AMF mediate significant inter-plant carbon transfer in nature

Changing the computer-patient-physician relationship : a qualitative evaluation of 30-inch computer screens in family medicine exam rooms

The electronic health record (EHR) and use of computers in today's exam rooms is a dramatic change in medicine from decades past. There are concerns about how the computer and EHR might adversely affect patient-provider interaction and that it may be detrimental to PCC. Patient-centered care (PCC) promotes active involvement of the patient in their medical care. Several positive outcomes have been associated with PCC, including: better emotional health, improved symptom burden, improved recovery, and fewer diagnostic tests and referrals both at the time of the visit and in the subsequent 2 months. PCC can therefore help to decrease medical expenditures while improving patient outcomes and satisfaction. It has been proposed that certain exam room and computer configurations combined with uses of the EHR may enhance PCC. If we can better determine how different types of computers affect this interaction, it would help suggest improvements for increasing PCC, thus gaining the aforementioned benefits of decreased cost and improved health outcomes