1,505 research outputs found

    Contrasting life-history responses to climate variability in eastern and western North Pacific sardine populations

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    大洋の東西で異なるマイワシの環境応答 --耳石が示すグローバル生存戦略の鍵--. 京都大学プレスリリース. 2022-10-17.Massive populations of sardines inhabit both the western and eastern boundaries of the world’s subtropical ocean basins, supporting both commercial fisheries and populations of marine predators. Sardine populations in western and eastern boundary current systems have responded oppositely to decadal scale anomalies in ocean temperature, but the mechanism for differing variability has remained unclear. Here, based on otolith microstructure and high-resolution stable isotope analyses, we show that habitat temperature, early life growth rates, energy expenditure, metabolically optimal temperature, and, most importantly, the relationship between growth rate and temperature are remarkably different between the two subpopulations in the western and eastern North Pacific. Varying metabolic responses to environmental changes partly explain the contrasting growth responses. Consistent differences in the life-history traits are observed between subpopulations in the western and eastern boundary current systems around South Africa. These growth and survival characteristics can facilitate the contrasting responses of sardine populations to climate change

    Building confidence in projections of the responses of living marine resources to climate change

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    The Fifth Assessment Report of the Intergovernmental Panel on Climate Change highlights that climate change and ocean acidification are challenging the sustainable management of living marine resources (LMRs). Formal and systematic treatment of uncertainty in existing LMR projections, however, is lacking. We synthesize knowledge of how to address different sources of uncertainty by drawing from climate model intercomparison efforts. We suggest an ensemble of available models and projections, informed by observations, as a starting point to quantify uncertainties. Such an ensemble must be paired with analysis of the dominant uncertainties over different spatial scales, time horizons, and metrics. We use two examples: (i) global and regional projections of Sea Surface Temperature and (ii) projection of changes in potential catch of sablefish (Anoplopoma fimbria) in the 21st century, to illustrate this ensemble model approach to explore different types of uncertainties. Further effort should prioritize understanding dominant, undersampled dimensions of uncertainty, as well as the strategic collection of observations to quantify, and ultimately reduce, uncertainties. Our proposed framework will improve our understanding of future changes in LMR and the resulting risk of impacts to ecosystems and the societies under changing ocean conditions

    Future change of summer hypoxia in coastal California Current

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    The occurrences of summer hypoxia in coastal California Current can significantly affect the benthic and pelagic habitat and lead to complex ecosystem changes. Model-simulated hypoxia in this region is strongly spatially heterogeneous, and its future changes show uncertainties depending on the model used. Here, we used an ensemble of the new generation Earth system models to examine the present-day and future changes of summer hypoxia in this region. We applied model-specific thresholds combined with empirical bias adjustments of the dissolved oxygen variance to identify hypoxia. We found that, although simulated dissolved oxygen in the subsurface varies across the models both in mean state and variability, after necessary bias adjustments, the ensemble shows reasonable hypoxia frequency compared with a hindcast in terms of spatial distribution and average frequency in the coastal region. The models project increases in hypoxia frequency under warming, which is in agreement with deoxygenation projected consistently across the models for the coastal California Current. This work demonstrated a practical approach of using the multi-model ensemble for regional studies while presenting methodology limitations and gaps in observations and models to improve these limitations

    X-ray emission from the Sombrero galaxy: discrete sources

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    We present a study of discrete X-ray sources in and around the bulge-dominated, massive Sa galaxy, Sombrero (M104), based on new and archival Chandra observations with a total exposure of ~200 ks. With a detection limit of L_X = 1E37 erg/s and a field of view covering a galactocentric radius of ~30 kpc (11.5 arcminute), 383 sources are detected. Cross-correlation with Spitler et al.'s catalogue of Sombrero globular clusters (GCs) identified from HST/ACS observations reveals 41 X-rays sources in GCs, presumably low-mass X-ray binaries (LMXBs). We quantify the differential luminosity functions (LFs) for both the detected GC and field LMXBs, whose power-low indices (~1.1 for the GC-LF and ~1.6 for field-LF) are consistent with previous studies for elliptical galaxies. With precise sky positions of the GCs without a detected X-ray source, we further quantify, through a fluctuation analysis, the GC LF at fainter luminosities down to 1E35 erg/s. The derived index rules out a faint-end slope flatter than 1.1 at a 2 sigma significance, contrary to recent findings in several elliptical galaxies and the bulge of M31. On the other hand, the 2-6 keV unresolved emission places a tight constraint on the field LF, implying a flattened index of ~1.0 below 1E37 erg/s. We also detect 101 sources in the halo of Sombrero. The presence of these sources cannot be interpreted as galactic LMXBs whose spatial distribution empirically follows the starlight. Their number is also higher than the expected number of cosmic AGNs (52+/-11 [1 sigma]) whose surface density is constrained by deep X-ray surveys. We suggest that either the cosmic X-ray background is unusually high in the direction of Sombrero, or a distinct population of X-ray sources is present in the halo of Sombrero.Comment: 11 figures, 5 tables, ApJ in pres

    Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jacox, M. G., Alexander, M. A., Siedlecki, S., Chen, K., Kwon, Y., Brodie, S., Ortiz, I., Tommasi, D., Widlansky, M. J., Barrie, D., Capotondi, A., Cheng, W., Di Lorenzo, E., Edwards, C., Fiechter, J., Fratantoni, P., Hazen, E. L., Hermann, A. J., Kumar, A., Miller, A. J., Pirhalla, D., Buil, M. P., Ray, S., Sheridan, S. C., Subramanian, A., Thompson, P., Thorne, L., Annamalai, H., Aydin, K., Bograd, S. J., Griffis, R. B., Kearney, K., Kim, H., Mariotti, A., Merrifield, M., & Rykaczewski, R. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, 183, (2020): 102307, doi:10.1016/j.pocean.2020.102307.Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.This study was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program through grants NA17OAR4310108, NA17OAR4310112, NA17OAR4310111, NA17OAR4310110, NA17OAR4310109, NA17OAR4310104, NA17OAR4310106, and NA17OAR4310113. This paper is a product of the NOAA/MAPP Marine Prediction Task Force

    Global perspectives on observing ocean boundary current systems

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    © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Todd, R. E., Chavez, F. P., Clayton, S., Cravatte, S., Goes, M., Greco, M., Ling, X., Sprintall, J., Zilberman, N., V., Archer, M., Aristegui, J., Balmaseda, M., Bane, J. M., Baringer, M. O., Barth, J. A., Beal, L. M., Brandt, P., Calil, P. H. R., Campos, E., Centurioni, L. R., Chidichimo, M. P., Cirano, M., Cronin, M. F., Curchitser, E. N., Davis, R. E., Dengler, M., deYoung, B., Dong, S., Escribano, R., Fassbender, A. J., Fawcett, S. E., Feng, M., Goni, G. J., Gray, A. R., Gutierrez, D., Hebert, D., Hummels, R., Ito, S., Krug, M., Lacan, F., Laurindo, L., Lazar, A., Lee, C. M., Lengaigne, M., Levine, N. M., Middleton, J., Montes, I., Muglia, M., Nagai, T., Palevsky, H., I., Palter, J. B., Phillips, H. E., Piola, A., Plueddemann, A. J., Qiu, B., Rodrigues, R. R., Roughan, M., Rudnick, D. L., Rykaczewski, R. R., Saraceno, M., Seim, H., Sen Gupta, A., Shannon, L., Sloyan, B. M., Sutton, A. J., Thompson, L., van der Plas, A. K., Volkov, D., Wilkin, J., Zhang, D., & Zhang, L. Global perspectives on observing ocean boundary current systems. Frontiers in Marine Science, 6, (2010); 423, doi: 10.3389/fmars.2019.00423.Ocean boundary current systems are key components of the climate system, are home to highly productive ecosystems, and have numerous societal impacts. Establishment of a global network of boundary current observing systems is a critical part of ongoing development of the Global Ocean Observing System. The characteristics of boundary current systems are reviewed, focusing on scientific and societal motivations for sustained observing. Techniques currently used to observe boundary current systems are reviewed, followed by a census of the current state of boundary current observing systems globally. The next steps in the development of boundary current observing systems are considered, leading to several specific recommendations.RT was supported by The Andrew W. Mellon Foundation Endowed Fund for Innovative Research at WHOI. FC was supported by the David and Lucile Packard Foundation. MGo was funded by NSF and NOAA/AOML. XL was funded by China’s National Key Research and Development Projects (2016YFA0601803), the National Natural Science Foundation of China (41490641, 41521091, and U1606402), and the Qingdao National Laboratory for Marine Science and Technology (2017ASKJ01). JS was supported by NOAA’s Global Ocean Monitoring and Observing Program (Award NA15OAR4320071). DZ was partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063. BS was supported by IMOS and CSIRO’s Decadal Climate Forecasting Project. We gratefully acknowledge the wide range of funding sources from many nations that have enabled the observations and analyses reviewed here

    Observation of long-range, near-side angular correlations in proton-proton collisions at the LHC

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    This is the pre-print version of the Published Article, which can be accessed from the link below - Copyright @ 2010 Springer VerlagResults on two-particle angular correlations for charged particles emitted in proton-proton collisions at center-of-mass energies of 0.9, 2.36, and 7 TeV are presented, using data collected with the CMS detector over a broad range of pseudorapidity (eta) and azimuthal angle (phi). Short-range correlations in Delta(eta), which are studied in minimum bias events, are characterized using a simple "independent cluster" parametrization in order to quantify their strength (cluster size) and their extent in eta (cluster decay width). Long-range azimuthal correlations are studied differentially as a function of charged particle multiplicity and particle transverse momentum using a 980 inverse nb data set at 7 TeV. In high multiplicity events, a pronounced structure emerges in the two-dimensional correlation function for particle pairs with intermediate transverse momentum of 1-3 GeV/c, 2.0< |Delta(eta)| <4.8 and Delta(phi) near 0. This is the first observation of such a long-range, near-side feature in two-particle correlation functions in pp or p p-bar collisions

    Strange Particle Production in pp Collisions at sqrt(s) = 0.9 and 7 TeV

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    Search for pair production of second-generation scalar leptoquarks in pp collisions at √s=7 TeV

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    This is the pre-print version of the Published Article which can be accessed from the link below.A search for pair production of second-generation scalar leptoquarks in the final state with two muons and two jets is performed using proton-proton collision data at √s=7  TeV collected by the CMS detector at the LHC. The data sample used corresponds to an integrated luminosity of 34  pb-1. The number of observed events is in good agreement with the predictions from the standard model processes. An upper limit is set on the second-generation leptoquark cross section times β2 as a function of the leptoquark mass, and leptoquarks with masses below 394 GeV are excluded at a 95% confidence level for β=1, where β is the leptoquark branching fraction into a muon and a quark. These limits are the most stringent to date
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