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Institution

University of California, Santa Cruz

EducationSanta Cruz, California, United States
About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.
Topics: Galaxy, Population, Stars, Redshift, Star formation


Papers
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Journal ArticleDOI
17 Jul 2014-Cell
TL;DR: A novel algorithm is used to systematically identify BGCs in the extensive extant microbial sequencing data, indicating for the first time the important roles these compounds play in Gram-negative cell biology.

720 citations

Journal ArticleDOI
TL;DR: In this article, the authors explored the possibility of measuring the density parameter OMEGA-0 and the cosmological constant lambda-0 = LAMBDA/(3H0(2)) using dynamical tests in linear and non-linear theory.
Abstract: The possibility of measuring the density parameter OMEGA-0 and the cosmological constant lambda-0 = LAMBDA/(3H0(2)) using dynamical tests is explored in linear and non-linear theory. In linear theory we find that the rate of growth of the perturbations at the present epoch is approximated by f(z = 0) almost-equal-to-OMEGA-0(0.6) + 1/70 lambda-0(1 + 1/2 OMEGA-0). Therefore, dynamical tests such as infall around clusters and dipoles at the present epoch do not distinguish well between universes with and without a cosmological constant. At higher redshifts, the perturbations also depend mainly on the matter density at a particular epoch, f(z) almost-equal-to OMEGA-0.6(z), which has a strong dependence on lambda-0 at z almost-equal-to 0.5-2.0. Therefore, information on both parameters can be obtained by looking at clustering at different redshifts. In practice, however, the other observables also depend on the cosmology, and in some cases conspire to give a weak dependence on lambda-0. By using the non-linear spherical infall model for a family of Cold Dark Matter (CDM) power-spectra we also find that dynamics at z = 0 does not tell much about lambda-0. At higher redshifts there is unfortunately another conspiracy between conventional observables, which hides information about lambda-0. The final radius of a virialized cluster (relative to the turnaround radius) is approximated by R(f)/R(ta) almost-equal-to (1 - eta/2)/(2 - eta/2), where eta is the ratio of LAMBDA to the density at turn-around. Therefore a repulsive-LAMBDA gives a smaller final radius than a vanishing-LAMBDA.

720 citations

Journal ArticleDOI
TL;DR: In this paper, the authors re-assess exchange rate prediction using a wider set of models that have been proposed in the last decade: interest rate parity, productivity based models, and behavioral equilibrium exchange rate' models.
Abstract: Previous assessments of nominal exchange rate determination have focused upon a narrow set of models typically of the 1970's vintage. The canonical papers in this literature are by Meese and Rogoff (1983, 1988), who examined monetary and portfolio balance models. Succeeding works by Mark (1995) and Chinn and Meese (1995) focused on similar models. In this paper we re-assess exchange rate prediction using a wider set of models that have been proposed in the last decade: interest rate parity, productivity based models, and behavioral equilibrium exchange rate' models. The performance of these models is compared against a benchmark model the Dornbusch-Frankel sticky price monetary model. The models are estimated in error correction and first-difference specifications. Rather than estimating the cointegrating vector over the entire sample and treating it as part of the ex ante information set as is commonly done in the literature, we recursively update the cointegrating vector, thereby generating true ex ante forecasts. We examine model performance at various forecast horizons (1 quarter, 4 quarters, 20 quarters) using differing metrics (mean squared error, direction of change), as well as the consistency' test of Cheung and Chinn (1998). No model consistently outperforms a random walk, by a mean squared error measure; however, along a direction-of-change dimension, certain structural models do outperform a random walk with statistical significance. Moreover, one finds that these forecasts are cointegrated with the actual values of exchange rates, although in a large number of cases, the elasticity of the forecasts with respect to the actual values is different from unity. Overall, model/specification/currency combinations that work well in one period will not necessarily work well in another period.

719 citations

Journal ArticleDOI
Marlee A. Tucker1, Katrin Böhning-Gaese1, William F. Fagan2, John M. Fryxell3, Bram Van Moorter, Susan C. Alberts4, Abdullahi H. Ali, Andrew M. Allen5, Andrew M. Allen6, Nina Attias7, Tal Avgar8, Hattie L. A. Bartlam-Brooks9, Buuveibaatar Bayarbaatar10, Jerrold L. Belant11, Alessandra Bertassoni12, Dean E. Beyer13, Laura R. Bidner14, Floris M. van Beest15, Stephen Blake16, Stephen Blake10, Niels Blaum17, Chloe Bracis1, Danielle D. Brown18, P J Nico de Bruyn19, Francesca Cagnacci20, Francesca Cagnacci21, Justin M. Calabrese2, Justin M. Calabrese22, Constança Camilo-Alves23, Simon Chamaillé-Jammes24, André Chiaradia25, André Chiaradia26, Sarah C. Davidson27, Sarah C. Davidson16, Todd E. Dennis28, Stephen DeStefano29, Duane R. Diefenbach30, Iain Douglas-Hamilton31, Iain Douglas-Hamilton32, Julian Fennessy, Claudia Fichtel33, Wolfgang Fiedler16, Christina Fischer34, Ilya R. Fischhoff35, Christen H. Fleming22, Christen H. Fleming2, Adam T. Ford36, Susanne A. Fritz1, Benedikt Gehr37, Jacob R. Goheen38, Eliezer Gurarie39, Eliezer Gurarie2, Mark Hebblewhite40, Marco Heurich41, Marco Heurich42, A. J. Mark Hewison43, Christian Hof, Edward Hurme2, Lynne A. Isbell14, René Janssen, Florian Jeltsch17, Petra Kaczensky44, Adam Kane45, Peter M. Kappeler33, Matthew J. Kauffman38, Roland Kays46, Roland Kays47, Duncan M. Kimuyu48, Flávia Koch49, Flávia Koch33, Bart Kranstauber37, Scott D. LaPoint50, Scott D. LaPoint16, Peter Leimgruber22, John D. C. Linnell, Pascual López-López51, A. Catherine Markham52, Jenny Mattisson, Emília Patrícia Medici53, Ugo Mellone54, Evelyn H. Merrill8, Guilherme Miranda de Mourão55, Ronaldo Gonçalves Morato, Nicolas Morellet43, Thomas A. Morrison56, Samuel L. Díaz-Muñoz57, Samuel L. Díaz-Muñoz14, Atle Mysterud58, Dejid Nandintsetseg1, Ran Nathan59, Aidin Niamir, John Odden, Robert B. O'Hara60, Luiz Gustavo R. Oliveira-Santos7, Kirk A. Olson10, Bruce D. Patterson61, Rogério Cunha de Paula, Luca Pedrotti, Björn Reineking62, Björn Reineking63, Martin Rimmler, Tracey L. Rogers64, Christer Moe Rolandsen, Christopher S. Rosenberry65, Daniel I. Rubenstein66, Kamran Safi67, Kamran Safi16, Sonia Saïd, Nir Sapir68, Hall Sawyer, Niels Martin Schmidt15, Nuria Selva69, Agnieszka Sergiel69, Enkhtuvshin Shiilegdamba10, João P. Silva70, João P. Silva71, João P. Silva72, Navinder J. Singh5, Erling Johan Solberg, Orr Spiegel14, Olav Strand, Siva R. Sundaresan, Wiebke Ullmann17, Ulrich Voigt44, Jake Wall31, David W. Wattles29, Martin Wikelski16, Martin Wikelski67, Christopher C. Wilmers73, John W. Wilson74, George Wittemyer75, George Wittemyer31, Filip Zięba, Tomasz Zwijacz-Kozica, Thomas Mueller22, Thomas Mueller1 
Goethe University Frankfurt1, University of Maryland, College Park2, University of Guelph3, Duke University4, Swedish University of Agricultural Sciences5, Radboud University Nijmegen6, Federal University of Mato Grosso do Sul7, University of Alberta8, Royal Veterinary College9, Wildlife Conservation Society10, Mississippi State University11, Sao Paulo State University12, Michigan Department of Natural Resources13, University of California, Davis14, Aarhus University15, Max Planck Society16, University of Potsdam17, Middle Tennessee State University18, Mammal Research Institute19, Harvard University20, Edmund Mach Foundation21, Smithsonian Conservation Biology Institute22, University of Évora23, University of Montpellier24, Monash University25, Parks Victoria26, Ohio State University27, Fiji National University28, University of Massachusetts Amherst29, United States Geological Survey30, Save the Elephants31, University of Oxford32, German Primate Center33, Technische Universität München34, Institute of Ecosystem Studies35, University of British Columbia36, University of Zurich37, University of Wyoming38, University of Washington39, University of Montana40, Bavarian Forest National Park41, University of Freiburg42, University of Toulouse43, University of Veterinary Medicine Vienna44, University College Cork45, North Carolina State University46, North Carolina Museum of Natural Sciences47, Karatina University48, University of Lethbridge49, Lamont–Doherty Earth Observatory50, University of Valencia51, Stony Brook University52, International Union for Conservation of Nature and Natural Resources53, University of Alicante54, Empresa Brasileira de Pesquisa Agropecuária55, University of Glasgow56, New York University57, University of Oslo58, Hebrew University of Jerusalem59, Norwegian University of Science and Technology60, Field Museum of Natural History61, University of Grenoble62, University of Bayreuth63, University of New South Wales64, Pennsylvania Game Commission65, Princeton University66, University of Konstanz67, University of Haifa68, Polish Academy of Sciences69, University of Lisbon70, University of Porto71, Instituto Superior de Agronomia72, University of California, Santa Cruz73, University of Pretoria74, Colorado State University75
26 Jan 2018-Science
TL;DR: Using a unique GPS-tracking database of 803 individuals across 57 species, it is found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in area with a low human footprint.
Abstract: Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.

719 citations

Journal ArticleDOI
01 Apr 2022-Science
TL;DR: The T2T-CHM13-T2T Consortium presented a complete 3.055 billion-base pair sequence of a human genome, including gapless assemblies for all chromosomes except Y, corrected errors in the prior references, and introduced nearly 200 million base pairs of sequence containing gene predictions, 99 of which are predicted to be protein coding as discussed by the authors .
Abstract: Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

717 citations


Authors

Showing all 15733 results

NameH-indexPapersCitations
David J. Schlegel193600193972
David R. Williams1782034138789
John R. Yates1771036129029
David Haussler172488224960
Evan E. Eichler170567150409
Anton M. Koekemoer1681127106796
Mark Gerstein168751149578
Alexander S. Szalay166936145745
Charles M. Lieber165521132811
Jorge E. Cortes1632784124154
M. Razzano155515106357
Lars Hernquist14859888554
Aaron Dominguez1471968113224
Taeghwan Hyeon13956375814
Garth D. Illingworth13750561793
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202351
2022328
20212,157
20202,353
20192,209
20182,157