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  • PANGAEA  (6,849)
  • Cambridge University Press
  • 2010-2014  (7,633)
  • 1935-1939  (40)
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  • 1
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    PANGAEA
    In:  Supplement to: Daniau, Anne-Laure; Bartlein, Patrick J; Harrison, S P; Prentice, Iain Colin; Brewer, Simon; Friedlingstein, Pierre; Harrison-Prentice, T I; Inoue, J; Izumi, K; Marlon, Jennifer R; Mooney, Scott D; Power, Mitchell J; Stevenson, J; Tinner, Willy; Andric, M; Atanassova, J; Behling, Hermann; Black, M; Blarquez, O; Brown, K J; Carcaillet, C; Colhoun, Eric A; Colombaroli, Daniele; Davis, Basil A S; D'Costa, D; Dodson, John; Dupont, Lydie M; Eshetu, Z; Gavin, D G; Genries, A; Haberle, Simon G; Hallett, D J; Hope, Geoffrey; Horn, S P; Kassa, T G; Katamura, F; Kennedy, L M; Kershaw, A Peter; Krivonogov, S; Long, C; Magri, Donatella; Marinova, E; McKenzie, G Merna; Moreno, P I; Moss, Patrick T; Neumann, F H; Norstrom, E; Paitre, C; Rius, D; Roberts, Neil; Robinson, G S; Sasaki, N; Scott, Louis; Takahara, H; Terwilliger, V; Thevenon, Florian; Turner, R; Valsecchi, V G; Vannière, Boris; Walsh, M; Williams, N; Zhang, Yancheng (2012): Predictability of biomass burning in response to climate changes. Global Biogeochemical Cycles, 26(4), https://doi.org/10.1029/2011GB004249
    Publication Date: 2024-01-13
    Description: We analyze sedimentary charcoal records to show that the changes in fire regime over the past 21,000 yrs are predictable from changes in regional climates. Analyses of paleo- fire data show that fire increases monotonically with changes in temperature and peaks at intermediate moisture levels, and that temperature is quantitatively the most important driver of changes in biomass burning over the past 21,000 yrs. Given that a similar relationship between climate drivers and fire emerges from analyses of the interannual variability in biomass burning shown by remote-sensing observations of month-by-month burnt area between 1996 and 2008, our results signal a serious cause for concern in the face of continuing global warming.
    Keywords: Center for Marine Environmental Sciences; MARUM
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 2
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    Cambridge University Press
    In:  EPIC3Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, United Kingdom and New York, NY, USA, Cambridge University Press, pp. 1-32, ISBN: 9781107641655
    Publication Date: 2015-03-08
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , peerRev
    Format: application/pdf
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  • 3
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    Cambridge University Press
    In:  EPIC3Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge, United Kingdom and New York, NY, USA, Cambridge University Press, pp. 35-94, ISBN: 9781107641655
    Publication Date: 2015-03-08
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , peerRev
    Format: application/pdf
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  • 4
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    PANGAEA
    In:  Supplement to: Byrne, James M; Coker, V S; Moise, S; Wincott, P L; Vaughan, D J; Tuna, F; Arenholz, E; van der Laan, G; Pattrick, R A D P; Lloyd, J R; Telling, N D (2013): Controlled cobalt doping in biogenic magnetite nanoparticles. Journal of The Royal Society Interface, 10(83), 20130134-20130134, https://doi.org/10.1098/rsif.2013.0134
    Publication Date: 2023-01-13
    Description: Cobalt doped magnetite (CoxFe3-xO4) nanoparticles have been produced through the microbial reduction of cobalt-iron oxyhydroxide by the bacterium Geobacter sulfurreducens. The materials produced, as measured by SQUID, x-ray magnetic circular dichroism, Mössbauer spectroscopy, etc., show dramatic increases in coercivity with increasing cobalt content without a major decrease in overall saturation magnetization. Structural and magnetization analyses reveal a reduction in particle size to 〈4 nm at the highest Co content, combined with an increase in the effective anisotropy of the magnetic nanoparticles. The potential use of these biogenic nanoparticles in aqueous suspensions for magnetic hyperthermia applications is demonstrated. Further analysis of the distribution of cations within the ferrite spinel indicates that the cobalt is predominantly incorporated in octahedral coordination, achieved by the substitution of Fe2+ site with Co2+, with up to 17 per cent Co substituted into tetrahedral sites.
    Type: Dataset
    Format: application/zip, 695.2 kBytes
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  • 5
    Publication Date: 2011-02-15
    Description: SUMMARYA reliable evaluation of crop nutritional status is crucial for supporting fertilization aiming at maximizing qualitative and quantitative aspects of production and reducing the environmental impact of cropping systems. Most of the available simulation models evaluate crop nutritional status according to the nitrogen (N) dilution law, which derives critical N concentration as a function of above-ground biomass. An alternative approach, developed during a project carried out with students of the Cropping Systems Masters course at the University of Milan, was tested and compared with existing models (N dilution law and approaches implemented in EPIC and DAISY models). The new model (MAZINGA) reproduces the effect of leaf self-shading in lowering plant N concentration (PNC) through an inverse of the fraction of radiation intercepted by the canopy. The models were tested using data collected in four rice (Oryza sativaL.) experiments carried out in Northern Italy under potential and N-limited conditions. MAZINGA was the most accurate in identifying the critical N concentration, and therefore in discriminating PNC of plants growing under N-limited and non-limited conditions, respectively. In addition, the present work proved the effectiveness of crop models when used as tools for supporting education.
    Print ISSN: 0021-8596
    Electronic ISSN: 1469-5146
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
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  • 6
    Publication Date: 2022-03-21
    Type: info:eu-repo/semantics/bookPart
    Format: application/pdf
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  • 7
    Publication Date: 2023-03-14
    Keywords: -; Alkalinity, total; Ammonium; Arsenic; Arsenic, error, relative; Bahamas; Barium; Barium, error, relative; Cadmium, error, relative; Caesium; Caesium, error, relative; Calcium; Calcium, error, relative; Calculated; Carbon, inorganic, dissolved; Carbonate ion; Chromium; Chromium, error, relative; Cobalt; Cobalt, error, relative; Copper; Copper, error, relative; DEPTH, sediment/rock; Description; Exuma; Hydrogen sulfide; ICP-Q-MS; Inductively coupled plasma-quadrupole-mass spectrometry; Iron; Iron, error, relative; Lead; Lead, error, relative; Magnesium; Magnesium, error, relative; Manganese; Manganese, error, relative; Nickel; Nickel, error, relative; Oxygen saturation; pH; Phosphate; Rhenium; Rhenium, error, relative; Rubidium; Rubidium, error, relative; Salinity; Strontium; Strontium, error, relative; Uranium; Uranium, error, relative; Vanadium; Vanadium, error, relative; Wet chemistry; δ13C, dissolved inorganic carbon
    Type: Dataset
    Format: text/tab-separated-values, 2589 data points
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  • 8
    Publication Date: 2023-03-27
    Description: The smallest marine phytoplankton, collectively termed picophytoplankton, have been routinely enumerated by flow cytometry since the late 1980s, during cruises throughout most of the world ocean. We compiled a database of 40,946 data points, with separate abundance entries for Prochlorococcus, Synechococcus and picoeukaryotes. We use average conversion factors for each of the three groups to convert the abundance data to carbon biomass. After gridding with 1° spacing, the database covers 2.4% of the ocean surface area, with the best data coverage in the North Atlantic, the South Pacific and North Indian basins. The average picophytoplankton biomass is 12 ± 22 µg C L-1 or 1.9 g C m-2. We estimate a total global picophytoplankton biomass, excluding N2-fixers, of 0.53 - 0.74 Pg C (17 - 39 % Prochlorococcus, 12 - 15 % Synechococcus and 49 - 69 % picoeukaryotes). Future efforts in this area of research should focus on reporting calibrated cell size, and collecting data in undersampled regions.
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 6.6 MBytes
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  • 9
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    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Publication Date: 2023-03-27
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths.
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 1.7 MBytes
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  • 10
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    PANGAEA
    In:  Supplement to: Butler, Paul G; Wanamaker, Alan D; Scourse, James D; Richardson, Christopher A; Reynolds, David J (2013): Variability of marine climate on the North Icelandic Shelf in a 1357-year proxy archive based on growth increments in the bivalve Arctica islandica. Palaeogeography, Palaeoclimatology, Palaeoecology, 373, 141-151, https://doi.org/10.1016/j.palaeo.2012.01.016
    Publication Date: 2023-01-13
    Description: A multicentennial and absolutely-dated shell-based chronology for the marine environment of the North Icelandic Shelf has been constructed using annual growth increments in the shell of the long-lived bivalve clam Arctica islandica. The region from which the shells were collected is close to the North Atlantic Polar Front and is highly sensitive to the varying influences of Atlantic and Arctic water masses. A strong common environmental signal is apparent in the increment widths, and although the correlations between the growth increment indices and regional sea surface temperatures are significant at the 95% confidence level, they are low (r ~ 0.2), indicating that a more complex combination of environmental forcings is driving growth. Remarkable longevities of individual animals are apparent in the increment-width series used in the chronology, with several animals having lifetimes in excess of 300 years and one, at 507 years, being the longest-lived non-colonial animal so far reported whose age at death can be accurately determined. The sample depth is at least three shells after AD 1175, and the time series has been extended back to AD 649 with a sample depth of one or two by the addition of two further series, thus providing a 1357-year archive of dated shell material. The statistical and spectral characteristics of the chronology are investigated by using two different methods of removing the age-related trend in shell growth. Comparison with other proxy archives from the same region reveals several similarities in variability on multidecadal timescales, particularly during the period surrounding the transition from the Medieval Climate Anomaly to the Little Ice Age.
    Keywords: B05AD03; Bottom trawl; BT; North Icelandic Shelf
    Type: Dataset
    Format: application/zip, 7 datasets
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