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Institution

Oregon State University

EducationCorvallis, Oregon, United States
About: Oregon State University is a education organization based out in Corvallis, Oregon, United States. It is known for research contribution in the topics: Population & Climate change. The organization has 28192 authors who have published 64044 publications receiving 2634108 citations. The organization is also known as: Oregon Agricultural College & OSU.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors present the time independent component of the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), which provides authoritative estimates of the magnitude, location, and time-averaged frequency of potentially damaging earthquakes in California.
Abstract: The 2014 Working Group on California Earthquake Probabilities (WGCEP14) present the time‐independent component of the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), which provides authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes in California. The primary achievements have been to relax fault segmentation and include multifault ruptures, both limitations of UCERF2. The rates of all earthquakes are solved for simultaneously and from a broader range of data, using a system‐level inversion that is both conceptually simple and extensible. The inverse problem is large and underdetermined, so a range of models is sampled using an efficient simulated annealing algorithm. The approach is more derivative than prescriptive (e.g., magnitude–frequency distributions are no longer assumed), so new analysis tools were developed for exploring solutions. Epistemic uncertainties were also accounted for using 1440 alternative logic‐tree branches, necessitating access to supercomputers. The most influential uncertainties include alternative deformation models (fault slip rates), a new smoothed seismicity algorithm, alternative values for the total rate of M w≥5 events, and different scaling relationships, virtually all of which are new. As a notable first, three deformation models are based on kinematically consistent inversions of geodetic and geologic data, also providing slip‐rate constraints on faults previously excluded due to lack of geologic data. The grand inversion constitutes a system‐level framework for testing hypotheses and balancing the influence of different experts. For example, we demonstrate serious challenges with the Gutenberg–Richter hypothesis for individual faults. UCERF3 is still an approximation of the system, however, and the range of models is limited (e.g., constrained to stay close to UCERF2). Nevertheless, UCERF3 removes the apparent UCERF2 overprediction of M 6.5–7 earthquake rates and also includes types of multifault ruptures seen in nature. Although UCERF3 fits the data better than UCERF2 overall, there may be areas that warrant further site‐specific investigation. Supporting products may be of general interest, and we list key assumptions and avenues for future model improvements.

448 citations

Journal ArticleDOI
TL;DR: In this paper, the authors characterize a newly recognized mechanism of dewatering at convergent margins, where freshening of pore waters from hydrate destabilization at depth and free gas drives fluids upward.

448 citations

Journal ArticleDOI
TL;DR: In this article, the authors test the hypothesis that Founding Family Controlled Firms (FFCF) are more averse to control risk than similar non-FFCFs and therefore avoid debt.
Abstract: This paper tests the hypothesis that Founding Family Controlled Firms (FFCFs) are more averse to control risk than similar non-FFCFs and therefore avoid debt. Higher levels of debt increase the lik...

447 citations

Journal ArticleDOI
TL;DR: This study conceptualizes supply network disruption and resilience by examining the structural relationships among entities in the network by comparing four fundamental supply network structures, and shows that node/arc-level disruptions do not necessarily lead to network- level disruptions, and demonstrates the importance of differentiating a nodes/arc disruption vs. a network disruption.

447 citations

Journal ArticleDOI
TL;DR: This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use and documents how metagenomes can be analyzed to quantify community structure and diversity.
Abstract: Environmental DNA sequencing has revealed the expansive biodiversity of microorganisms and clarified the relationship between host-associated microbial communities and host phenotype. Shotgun metagenomic DNA sequencing is a relatively new and powerful environmental sequencing approach that provides insight into community biodiversity and function. But, the analysis of metagenomic sequences is complicated due to the complex structure of the data. Fortunately, new tools and data resources have been developed to circumvent these complexities and allow researchers to determine which microbes are present in the community and what they might be doing. This review describes the analytical strategies and specific tools that can be applied to metagenomic data and the considerations and caveats associated with their use. Specifically, it documents how metagenomes can be analyzed to quantify community structure and diversity, assemble novel genomes, identify new taxa and genes, and determine which metabolic pathways are encoded in the community. It also discusses several methods that can be used compare metagenomes to identify taxa and functions that differentiate communities.

445 citations


Authors

Showing all 28447 results

NameH-indexPapersCitations
Robert Stone1601756167901
Menachem Elimelech15754795285
Thomas J. Smith1401775113919
Harold A. Mooney135450100404
Jerry M. Melillo13438368894
John F. Thompson132142095894
Thomas N. Williams132114595109
Peter M. Vitousek12735296184
Steven W. Running12635576265
Vincenzo Di Marzo12665960240
J. D. Hansen12297576198
Peter Molnar11844653480
Michael R. Hoffmann10950063474
David Pollard10843839550
David J. Hill107136457746
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023105
2022375
20213,156
20203,109
20193,017
20182,987