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  • 2015-2019  (21)
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  • 11
    Publication Date: 2021-05-19
    Description: The distribution and cycling of biogenic organic matter in the Canary Current Large Marine Ecosystem is strongly affected by the intense mesoscale activity of the area, mainly in the form of meanders, filaments and eddies, and their interaction. Filaments contribute significantly to the offshore export of coastal upwelling primary production in the form of dissolved and suspended organic matter. Cyclonic and anticyclonic eddies (mostly generated by flow perturbation by Madeira and the Canary Islands) may enhance the production of fresh organic matter during their early stages of formation, favouring the vertical sinking of particles. Additionally, they may accumulate and transport suspended particles and dissolved organic matter through a permanent westward corridor of eddies. Organic matter deposited in coastal sediments is also transported laterally to the adjacent ocean in the form of intermediate and bottom nepheloid layers resulting from the erosion of the shelf and slope sediments by the intense and variable coastal currents. All these mechanisms contribute exporting the biogenic materials produced in the coast hundreds of kilometres into the open ocean.
    Description: Published
    Keywords: Filaments ; Island eddies ; Nepheloid layers ; CCLME ; ASFA15::D::Dissolved organic matter ; ASFA15::P::Particulate organic matter
    Repository Name: AquaDocs
    Type: Report Section , Refereed
    Format: pp. 151-159
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  • 12
    Publication Date: 2022-10-26
    Description: © 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.
    Description: 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.
    Description: 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.
    Keywords: Western boundary current systems ; Eastern boundary current systems ; Ocean observing systems ; Time series ; Autonomous underwater gliders ; Drifters ; Remote sensing ; Moorings
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 13
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 7 (2017): 10129, doi:10.1038/s41598-017-10974-y.
    Description: Transports of suspended particulate (POCsusp) and dissolved (DOC) organic carbon are inferred from a box-model covering the eastern boundary of the North Atlantic subtropical gyre. Corresponding net respiration rates (R) are obtained from a net organic carbon budget that is based on the transport estimates, and includes both vertical and lateral fluxes. The overall R in the mesopelagic layer (100–1500 m) is 1.6 ± 0.4 mmol C m−2 d−1. DOC accounts for up to 53% of R as a result of drawdown of organic carbon within Eastern North Atlantic Central Water (ENACW) that is entrained into sinking Mediterranean Overflow Water (MOW) that leads to formation of Mediterranean water (MW) at intermediate depths (~900 m). DOC represents 90% of the respired non-sinking organic carbon. When converted into oxygen units, the computed net respiration rate represents less than half the oxygen utilization rates (OUR) reported for the mesopelagic waters of the subtropical North Atlantic. Mesoscale processes in the area, not quantified with our approach, could account in part for the OUR differences observed between our carbon budget and other published studies from the North Atlantic, although seasonal or interannual variability could also be responsible for the difference in the estimates.
    Description: This research was supported by projects ORCA (CTM2005-04701-CO2-01), Malaspina (CSD2008-00077), HOTMIX (CTM2011-30010-C02) and FLUXES (CTM2015-69392-C3), financed by the Spanish “Plan Nacional de I + D”. YSF was supported by a Spanish fellowship from the Agencia Canaria de Investigación, Innovación y Sociedad de la Información (ACIISI). EM has been partially supported by the Copernicus Marine Environment Monitoring Service (CMEMS) MedSUB project, and a post-doctoral grant from the Conselleria d’Educació, Cultura i Universitats del Govern de les Illes Balears (Mallorca, Spain) and the European Social Fund.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 14
    Publication Date: 2022-11-07
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
    Format: application/pdf
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  • 15
    Publication Date: 2022-05-26
    Description: © The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part I: Oceanographic Research Papers 115 (2016): 63–73, doi:10.1016/j.dsr.2016.05.010.
    Description: Remineralization of organic matter in the mesopelagic zone (ca. 150–700 m) is a key controlling factor of carbon export to the deep ocean. By using a tracer conservation model applied to climatological data of oxygen, dissolved inorganic carbon (DIC) and nitrate, we computed mesopelagic respiration at the ESTOC (European Station for Time- Series in the Ocean, Canary Islands) site, located in the Eastern boundary region of the North Atlantic subtropical gyre. The tracer conservation model included vertical Ekman advection, geostrophic horizontal transport and vertical diffusion, and the biological remineralization terms were diagnosed by assuming steady state. Three different approaches were used to compute reference velocities used for the calculation of geostrophic velocities and flux divergences: a no-motion level at 3000 m, surface geostrophic velocities computed from the averaged absolute dynamic topography field, and surface velocities optimized from the temperature model. Mesopelagic respiration rates computed from the model were 2.8–8.9molO2 m2 y=1, 2.0–3.1mol Cm2 y=1 and 0.6–1.0molNm2 y=1, consistent with remineralization processes occurring close to Redfield stoichiometry. Model estimates were in close agreement with respiratory activity, derived from electron transport system (ETS) measurements collected in the same region at the end of the winter bloom period (3.61 ± 0.48molO2 m=2 y=1). According to ETS estimates, 50% of the respiration in the upper 1000 m took place below 150 m. Model results showed that oxygen, DIC and nitrate budgets were dominated by lateral advection, pointing to horizontal transport as the main source of organic carbon fuelling the heterotrophic respiration activity in this region.
    Description: Funding for this study was provided by the Xunta de Galicia under the research project VARITROP (09MDS001312PR, PI B. Mouriño-Carballido) and by the Ministerio de Educación y Cultura under the research project MESOPELAGIC (MAR97-1036, PI S. Hernández-León). B. Fernández-Castro acknowledges the receipt of FPU grant from the Spanish government (AP2010-5594).
    Description: 2017-05-26
    Keywords: Mesopelagic respiration ; Tracer conservation model ; Horizontal advection ; North Atlantic subtropical gyre ; ESTOC
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 16
    Publication Date: 2024-03-06
    Keywords: Ammonium; BIOACID; Biogenic silica; Biological Impacts of Ocean Acidification; Chlorophyll a; Day of experiment; Event label; KOSMOS_2016; KOSMOS_2016_Mesocosm-M2; KOSMOS_2016_Mesocosm-M3; KOSMOS_2016_Mesocosm-M4; KOSMOS_2016_Mesocosm-M5; KOSMOS_2016_Mesocosm-M6; KOSMOS_2016_Mesocosm-M7; KOSMOS_2016_Mesocosm-M8; KOSMOS Gran Canaria; MESO; Mesocosm experiment; Mesocosm label; Nitrogen oxide; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); Phase; Phosphate; Shannon Diversity Index; Silicate
    Type: Dataset
    Format: text/tab-separated-values, 1608 data points
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  • 17
    Publication Date: 2024-03-06
    Keywords: BIOACID; Biological Impacts of Ocean Acidification; Biomass as carbon per volume; Day of experiment; Event label; Genus; KOSMOS_2016; KOSMOS_2016_Mesocosm-M2; KOSMOS_2016_Mesocosm-M3; KOSMOS_2016_Mesocosm-M4; KOSMOS_2016_Mesocosm-M5; KOSMOS_2016_Mesocosm-M6; KOSMOS_2016_Mesocosm-M7; KOSMOS_2016_Mesocosm-M8; KOSMOS Gran Canaria; MESO; Mesocosm experiment; Mesocosm label; Phase
    Type: Dataset
    Format: text/tab-separated-values, 7300 data points
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  • 18
    Publication Date: 2024-03-06
    Keywords: Abundance; BIOACID; Biological Impacts of Ocean Acidification; Day of experiment; Event label; Genus; KOSMOS_2016; KOSMOS_2016_Mesocosm-M2; KOSMOS_2016_Mesocosm-M3; KOSMOS_2016_Mesocosm-M4; KOSMOS_2016_Mesocosm-M5; KOSMOS_2016_Mesocosm-M6; KOSMOS_2016_Mesocosm-M7; KOSMOS_2016_Mesocosm-M8; KOSMOS Gran Canaria; MESO; Mesocosm experiment; Mesocosm label; Phase
    Type: Dataset
    Format: text/tab-separated-values, 2455 data points
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  • 19
    Publication Date: 2024-03-06
    Keywords: BIOACID; Biological Impacts of Ocean Acidification; Biomass, total; Carbon quota, average; Day of experiment; Event label; KOSMOS_2016; KOSMOS_2016_Mesocosm-M2; KOSMOS_2016_Mesocosm-M3; KOSMOS_2016_Mesocosm-M4; KOSMOS_2016_Mesocosm-M5; KOSMOS_2016_Mesocosm-M6; KOSMOS_2016_Mesocosm-M7; KOSMOS_2016_Mesocosm-M8; KOSMOS Gran Canaria; MESO; Mesocosm experiment; Mesocosm label; Phase
    Type: Dataset
    Format: text/tab-separated-values, 734 data points
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  • 20
    Publication Date: 2024-03-06
    Keywords: Abundance per volume; BIOACID; Biological Impacts of Ocean Acidification; Day of experiment; Event label; Genus; KOSMOS_2016; KOSMOS_2016_Mesocosm-M2; KOSMOS_2016_Mesocosm-M3; KOSMOS_2016_Mesocosm-M4; KOSMOS_2016_Mesocosm-M5; KOSMOS_2016_Mesocosm-M6; KOSMOS_2016_Mesocosm-M7; KOSMOS_2016_Mesocosm-M8; KOSMOS Gran Canaria; MESO; Mesocosm experiment; Mesocosm label; Phase
    Type: Dataset
    Format: text/tab-separated-values, 7308 data points
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