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© 2015 Macmillan Publishers Limited. Ruminant livestock are important sources of human food and global greenhouse gas emissions. Feed degradation and methane formation by ruminants rely on metabolic interactions between rumen microbes and affect ruminant productivity. Rumen and camelid foregut microbial community composition was determined in 742 samples from 32 animal species and 35 countries, to estimate if this was influenced by diet, host species, or geography. Similar bacteria and archaea dominated in nearly all samples, while protozoal communities were more variable. The dominant bacteria are poorly characterised, but the methanogenic archaea are better known and highly conserved across the world. This universality and limited diversity could make it possible to mitigate methane emissions by developing strategies that target the few dominant methanogens. Differences in microbial community compositions were predominantly attributable to diet, with the host being less influential. There were few strong co-occurrence patterns between microbes, suggesting that major metabolic interactions are non-selective rather than specific. ; We thank Ron Ronimus, Paul Newton, and Christina Moon for reading and commenting on the manuscript. We thank all who provided assistance that allowed Global Rumen Census collaborators to supply samples and metadata (Supplemental Text 1). AgResearch was funded by the New Zealand Government as part of its support for the Global Research Alliance on Agricultural Greenhouse Gases. The following funding sources allowed Global Rumen Census collaborators to supply samples and metadata, listed with the primary contact(s) for each funding source: Agencia Nacional de Investigación e Innovación, Martín Fraga; Alberta Livestock and Meat Agency, Canada, Tim A. McAllister; Area de Ciencia y Técnica, Universidad Juan A Maza (Resolución Proy. N° 508/2012), Diego Javier Grilli; Canada British Columbia Ranching Task Force Funding Initiative, John Church; CNPq, Hilário Cuquetto Mantovani, Luiz Gustavo Ribeiro Pereira; FAPEMIG, Hilário Cuquetto Mantovani; FAPEMIG, PECUS RumenGases, Luiz Gustavo Ribeiro Pereira; Cooperative Research Program for Agriculture Science & Technology Development (project number PJ010906), Rural Development Administration, Republic of Korea, Sang-Suk Lee; Dutch Dairy Board & Product Board Animal Feed, André Bannink, Kasper Dieho, Jan Dijkstra; Ferdowsi University of Mashhad, Vahideh Heidarian Miri; Finnish Ministry of Agriculture and Forestry, Ilma Tapio; Instituto Nacional de Tecnología Agropecuaria, Argentina (Project PNBIO1431044), Silvio Cravero, María Cerón Cucchi; Irish Department of Agriculture, Fisheries and Food, Alexandre B. De Menezes; Meat & Livestock Australia; and Department of Agriculture, Fisheries & Forestry (Australian Government), Chris McSweeney; Ministerio de Agricultura y desarrollo sostenible (Colombia), Olga Lucía Mayorga; Montana Agricultural Experiment Station project (MONB00113), Carl Yeoman; Multistate project W-3177 Enhancing the competitiveness of US beef (MONB00195), Carl Yeoman; NSW Stud Merino Breeders' Association, Alexandre Vieira Chaves; Queensland Enteric Methane Hub, Diane Ouwerkerk; RuminOmics, Jan Kopecny, Ilma Tapio; Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government and the Technology Strategy Board, UK, R. John Wallace; Science Foundation Ireland (09/RFP/GEN2447), Sinead Waters; Secretaría de Agricultura, Ganadería, Desarrollo Rural, Pesca y Alimentación, Mario A. Cobos-Peralta; Slovenian Research Agency (project number J1-6732 and P4-0097), Blaz Stres; Strategic Priority Research Program, Climate Change: Carbon Budget and Relevant Issues (Grant No.XDA05020700), ZhiLiang Tan; The European Research Commission Starting Grant Fellowship (336355—MicroDE), Phil B. Pope; The Independent Danish Research Council (project number 4002-00036), Torsten Nygaard Kristensen; and The Independent Danish Research Council (Technology and Production, project number 11-105913), Jan Lassen. These funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer Reviewed

The Event Horizon Telescope Collaboration ; Recent developments in compact object astrophysics, especially the discovery of merging neutron stars by LIGO, the imaging of the black hole in M87 by the Event Horizon Telescope, and high- precision astrometry of the Galactic Center at close to the event horizon scale by the GRAVITY experiment motivate the development of numerical source models that solve the equations of general relativistic magnetohydrodynamics (GRMHD). Here we compare GRMHD solutions for the evolution of a magnetized accretion flow where turbulence is promoted by the magnetorotational instability from a set of nine GRMHD codes: Athena++, BHAC, Cosmos++, ECHO, H-AMR, iharm3D, HARM-Noble, IllinoisGRMHD, and KORAL. Agreement among the codes improves as resolution increases, as measured by a consistently applied, specially developed set of code performance metrics. We conclude that the community of GRMHD codes is mature, capable, and consistent on these test problems. © 2019. The American Astronomical Society. All rights reserved. ; R.N. thanks the National Science Foundation (NSF; grants OISE-1743747, AST-1816420) and acknowledges computational support from the NSF via XSEDE resources (grant TG-AST080026N). L.D.Z. acknowledges support from the PRIN-MIUR project Multi-scale Simulations of High-Energy Astrophysical Plasmas (Prot. 2015L5EE2Y) and from the INFN-TEONGRAV initiative. C.J.W. made use of thComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, ChileComision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chilee Extreme Science and Engineering Discovery Environment (XSEDE) Comet at the San Diego Supercomputer Center through allocation AST170012. The H-AMR high-resolution simulation was made possible by NSF PRAC award Nos. 1615281 and OAC-1811605 at the Blue Waters sustained-petascale computing project and supported in part under grant No. NSF PHY-1125915 (PI A. Tchekhovskoy). K.C. and S.M. are supported by the Netherlands Organization for Scientific Research (NWO) VICI grant (No. 639.043.513); M.L. is supported by the NWO Spinoza Prize (PI M.B.M. van der Klis). The HARM-Noble simulations were made possible by NSF PRAC award No. NSF OAC-1515969, OAC-1811228 at the Blue Waters sustained-petascale computing project, and supported in part under grant No. NSF PHY-1125915. The BHAC CKS-GRMHD simulations were performed on the Dutch National Supercomputing cluster Cartesius and are funded by the NWO computing grant 16431. S.C.N. was supported by an appointment to the NASA Postdoctoral Program at the Goddard Space Flight Center administered by USRA through a contract with NASA. Y.M., H.O., O.P., and L.R. acknowledge support from the ERC synergy grant >BlackHoleCam: Imaging the Event Horizon of Black Holes> (grant No. 610058). M.B. acknowledges support from the European Research Council (grant No. 715368-MagBURST) and from the Gauss Centre for Supercomputing e.V. (www.Gauss-centre.eu) for funding this project by providing computing time on the GCS Supercomputer SuperMUC at Leibniz Supercomputing Centre (www.lrz.de).P.C.F.was supported by NSF grant AST-1616185 and used resources from the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by NSF grant No. ACI-1548562. Work by P.A. was performed in part under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. The authors of the present paper further thank the following organizations and programs: the Academy of Finland (projects 274477, 284495, 312496); the Advanced European Network of E-infrastructures for Astronomy with the SKA (AENEAS) project, supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement 731016; the Alexander von Humboldt Stiftung; the Black Hole Initiative at Harvard University, through a grant (60477) from the John Templeton Foundation; the China Scholarship Council; Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile, via PIA ACT172033, Fondecyt 1171506, BASAL AFB-170002, ALMA-conicyt 31140007); Consejo Nacional de Ciencia y Tecnologia (CONACYT, Mexico, projects 104497, 275201, 279006, 281692); the Delaney Family via the Delaney Family John A. Wheeler Chair at Perimeter Institute; Direccion General de Asuntos del Personal Academico-Universidad Nacional Autonoma de Mexico (DGAPA-UNAM, project IN112417); the European Research Council Synergy Grant >BlackHoleCam: Imaging the Event Horizon of Black Holes> (grant 610058); the Generalitat Valenciana postdoctoral grant APOSTD/2018/177; the Gordon and Betty Moore Foundation (grants GBMF-3561, GBMF-5278); the Istituto Nazionale di Fisica Nucleare (INFN) sezione di Napoli, iniziative specifiche TEONGRAV; the International Max Planck Research School for Astronomy and Astrophysics at the Universities of Bonn and Cologne; the Jansky Fellowship program of the National Radio Astronomy Observatory (NRAO); the Japanese Government (Monbukagakusho: MEXT) Scholarship; the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for JSPS Research Fellowship (JP17J08829); the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS, grants QYZDJ-SSW-SLH057, QYZDJ-SSW-SYS008); the Leverhulme Trust Early Career Research Fellowship; the Max-Planck-Gesellschaft (MPG); the Max Planck Partner Group of the MPG and the CAS; the MEXT/JSPS KAKENHI (grants 18KK0090, JP18K13594, JP18K03656, JP18H03721, 18K03709, 18H01245, 25120007); the MIT International Science and Technology Initiatives (MISTI) Funds; the Ministry of Science and Technology (MOST) of Taiwan (105-2112-M-001-025-MY3, 106-2112-M-001-011, 106-2119-M-001-027, 107-2119-M-001-017, 107-2119-M-001-020, and 107-2119-M-110-005); the National Aeronautics and Space Administration (NASA, Fermi Guest Investigator grant 80NSSC17K0649); the National Institute of Natural Sciences (NINS) of Japan; the National Key Research and Development Program of China (grant 2016YFA0400704, 2016YFA0400702); the National Science Foundation (NSF, grants AST-0096454, AST-0352953, AST-0521233, AST-0705062, AST-0905844, AST-0922984, AST-1126433, AST-1140030, DGE-1144085, AST-1207704, AST-1207730, AST-1207752, MRI-1228509, OPP-1248097, AST-1310896, AST-1312651, AST-1337663, AST-1440254, AST-1555365, AST-1715061, AST-1615796, AST-1716327, OISE-1743747, AST-1816420); the Natural Science Foundation of China (grants 11573051, 11633006, 11650110427, 10625314, 11721303, 11725312); the Natural Sciences and Engineering Research Council of Canada (NSERC, including a Discovery Grant and the NSERC Alexander Graham Bell Canada Graduate Scholarships Doctoral Program); the National Youth Thousand Talents Program of China; the National Research Foundation of Korea (the Global PhD Fellowship Grant: grants NRF-2015H1A2A1033752, 2015-R1D1A1A01056807, the Korea Research Fellowship Program: NRF-2015H1D3A1066561); the Netherlands Organization for Scientific Research (NWO) VICI award (grant 639.043. 513) and Spinoza Prize SPI 78-409; the New Scientific Frontiers with Precision Radio Interferometry Fellowship awarded by the South African Radio Astronomy Observatory (SARAO), which is a facility of the National Research Foundation (NRF), an agency of the Department of Science and Technology (DST) of South Africa; the Onsala Space Observatory (OSO) national infrastructure, for the provisioning of its facilities/observational support (OSO receives funding through the Swedish Research Council under grant 2017-00648); the Perimeter Institute for Theoretical Physics (research at Perimeter Institute is supported by the Government of Canada through the Department of Innovation, Science and Economic Development, and by the Province of Ontario through the Ministry of Research, Innovation and Science); the Russian Science Foundation (grant 17-12-01029); the Spanish Ministerio de Economia y Competitividad (grants AYA2015-63939-C2-1-P, AYA2016-80889-P); the State Agency for Research of the Spanish MCIU through the >Center of Excellence Severo Ochoa> award for the Instituto de Astrofisica de Andalucia (SEV-2017-0709); the Toray Science Foundation; the US Department of Energy (USDOE) through the Los Alamos National Laboratory (operated by Triad National Security, LLC, for the National Nuclear Security Administration of the USDOE (Contract 89233218CNA000001)); the Italian Ministero dell'Istruzione Universita e Ricerca through the grant Progetti Premiali 2012-iALMA (CUP C52I13000140001); the European Union's Horizon 2020 research and innovation programme under grant agreement No. 730562 RadioNet; ALMA North America Development Fund; the Academia Sinica; and Chandra TM6-17006X. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant ACI-1548562, and CyVerse, supported by NSF grants DBI-0735191, DBI-1265383, and DBI-1743442. XSEDE Stampede2 resource at TACC was allocated through TG-AST170024 and TG-AST080026N. XSEDE JetStream resource at PTI and TACC was allocated through AST170028. The simulations were performed in part on the SuperMUC cluster at the LRZ in Garching, on the LOEWE cluster in CSC in Frankfurt, and on the HazelHen cluster at the HLRS in Stuttgart. This research was enabled in part by support provided by Compute Ontario (http://computeontario.ca), Calcul Quebec (http://www.calculquebec.ca), and Compute Canada (http://www.computecanada.ca).