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  • 1
    Publication Date: 1930-05-16
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 2
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    PANGAEA
    In:  Supplement to: Fay, Amanda R; McKinley, Galen A (2014): Global open-ocean biomes: mean and temporal variability. Earth System Science Data, 6(2), 273-284, https://doi.org/10.5194/essd-6-273-2014
    Publication Date: 2023-01-13
    Description: Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid. By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.
    Type: Dataset
    Format: application/x-netcdf, 7.4 MBytes
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  • 3
    Publication Date: 2023-01-13
    Keywords: DATE/TIME; Identification; LATITUDE; LONGITUDE; Sea surface temperature, annual mean
    Type: Dataset
    Format: text/tab-separated-values, 581178 data points
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  • 4
    Publication Date: 2023-01-13
    Keywords: Chlorophyll total; DATE/TIME; Depth of the euphotic zone; Diffuse attenuation coefficient at 490 nm; Identification; LATITUDE; LONGITUDE; Net primary production of carbon; Radiation, photosynthetically active
    Type: Dataset
    Format: text/tab-separated-values, 1556094 data points
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  • 5
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    PANGAEA
    In:  Supplement to: Mouw, Colleen B; Barnett, Audrey; McKinley, Galen A; Gloege, Lucas; Pilcher, Darren (2016): Global ocean particulate organic carbon flux merged with satellite parameters. Earth System Science Data, 8(2), 531-541, https://doi.org/10.5194/essd-8-531-2016
    Publication Date: 2023-05-12
    Description: The efficiency of the biological pump of carbon to the deep ocean depends largely on the biologically mediated export of carbon from the surface ocean and its remineralization with depth. Global satellite studies have primarily focused on chlorophyll concentration and net primary production (NPP) to understand the role of phytoplankton in these processes. Recent satellite retrievals of phytoplankton composition now allow for the size of phytoplankton cells to be considered. Here, we improve understanding of phytoplankton size structure impacts on particle export, remineralization and transfer. Particulate organic carbon (POC) flux observations from sediment traps and 234Th are compiled across the global ocean. Annual climatologies of NPP, percent microplankton, and POC flux at four time series locations and within biogeochemical provinces are constructed, and sinking velocities are calculated to align surface variables with POC flux at depth. Parameters that characterize POC flux vs. depth (export flux ratio, labile fraction, remineralization length scale) are then fit to the aligned dataset. Times of the year dominated by different size compositions are identified and fit separately in regions of the ocean where phytoplankton cell size showed enough dynamic range over the annual cycle. Considering all data together, our findings support the paradigm of high export flux but low transfer efficiency in more productive regions and vice versa for oligotrophic regions. However, when parsing by dominant size class, we find periods dominated by small cells to have both greater export flux and lower transfer efficiency than periods when large cells comprise a greater proportion of the phytoplankton community.
    Type: Dataset
    Format: application/zip, 6 datasets
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  • 6
    Publication Date: 2023-05-12
    Keywords: Identification; LATITUDE; LONGITUDE; Mixed layer depth, upper; Month
    Type: Dataset
    Format: text/tab-separated-values, 23202 data points
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  • 7
    Publication Date: 2023-05-12
    Keywords: Chlorophyll total; DATE/TIME; Depth of the euphotic zone; Diffuse attenuation coefficient at 490 nm; Identification; LATITUDE; LONGITUDE; Net primary production of carbon; Radiation, photosynthetically active
    Type: Dataset
    Format: text/tab-separated-values, 1522642 data points
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  • 8
    Publication Date: 2023-05-12
    Keywords: DATE/TIME; Identification; LATITUDE; LONGITUDE; Microplankton fraction
    Type: Dataset
    Format: text/tab-separated-values, 122954 data points
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  • 9
    Publication Date: 2024-02-17
    Keywords: Aluminium, particulate, flux per day; Aluminium, particulate, flux per day, standard deviation; Area; Barium, flux; Calcium carbonate, flux; Calcium carbonate, flux, standard deviation; Carbon, inorganic, particulate, flux per day; Carbon, inorganic, particulate, flux per day, standard deviation; Carbon, organic, particulate, flux; Carbon, organic, particulate, flux, standard deviation; Carbon, total, flux; Carbon, total, flux, standard deviation; Chlorophyll, flux; DATE/TIME; Date/time end; Depth, bathymetric; DEPTH, water; Detrital, flux per day; Duration, number of days; ELEVATION; Flux, standard deviation; Flux of total mass; Identification; Iron, flux; LATITUDE; LONGITUDE; Manganese, flux; Nitrogen, organic, particulate, flux per day; Nitrogen, organic, particulate, flux per day, standard deviation; Phaeopigments, flux; Phosphorus, organic, particulate, flux per day; Phosphorus, organic, particulate, flux per day, standard deviation; Reference/source; Silica, particulate, flux per day; Silicate, particulate, flux per day; Silicon, particulate, flux; Silicon, particulate, flux, standard deviation; Titanium, flux; Type
    Type: Dataset
    Format: text/tab-separated-values, 198789 data points
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  • 10
    Publication Date: 2024-03-29
    Description: Destroying Democracy, volume six of the Democratic Marxism series, focuses on how decades of neoliberal capitalism have eroded the global democratic project and how, in the process, rising authoritarianism is expressing itself in divisive and exclusionary politics, populist political parties and movements, increased distrust in fact-based information and news, and the withering accountability of state institutions. Over the last four decades, democracy has radically shifted to a market democracy in which all aspects of human, non-human and planetary life are commodified and corporations have become more powerful than states and their citizens. This is how neoliberal capitalism functions at a systemic level and if left unchecked is the greatest threat to democracy and a sustainable planet. The authors home in on four country cases – India, Brazil, South Africa and the United States of America to interrogate issues of politics, ecology, state security, media, access to information and political parties, and affirm the need to reclaim and re-build an expansive and inclusive democracy. The book is an invaluable resource for all who are interested in understanding the threats to democracy and the rising tide of authoritarianism in the global south and the global north.
    Keywords: neoliberal capitalism; democratic capitalism; neoliberalism; authoritarianism; eco-fascism; democracy; populism; fascism; nationalism; far-right; fossil fuels; climate change; media freedoms and surveillance; USA; India; Brazil; South Africa ; bic Book Industry Communication::J Society & social sciences::JP Politics & government ; bic Book Industry Communication::K Economics, finance, business & management::KC Economics ; thema EDItEUR::J Society and Social Sciences::JP Politics and government ; thema EDItEUR::K Economics, Finance, Business and Management::KC Economics
    Language: English
    Format: image/jpeg
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