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  • 1
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    Phytoplankton pigment concentrations and phytoplankton groups measured on water samples collected from various expeditions in the Atlantic Ocean from 71°S to 84°N (2023)
    PANGAEA
    Details
    Publication Date: 2024-02-14
    Description: This data set composes a large amount of quality controlled in situ measurements of major pigments based on HPLC collected from various expeditions across the Atlantic Ocean spanning from 71°S to 84°N, including 11 expeditions with RV Polarstern from the North Atlantic to the Arctic Fram Strait: PS74, PSS76, PS78, PS80, PS85, PS93.2 (https://doi.org/10.1594/PANGAEA.894872), PS99.1 (https://doi.org/10.1594/PANGAEA.905502), PS99.2 ( https://doi.org/10.1594/PANGAEA.894874), PS106 (https://doi.org/10.1594/PANGAEA.899284), PS107 (https://doi.org/10.1594/PANGAEA.894860), PS121 (https://doi.org/10.1594/PANGAEA.941011), four expeditions (two with RV Polarstern and two Atlantic Meridional Transect expeditions with RRS James Clark Ross and RRS Discovery) in the trans-Atlantic Ocean: PS113 ( https://doi.org/10.1594/PANGAEA.911061), PS120, AMT28 and AMT29, and one expedition with RV Polarstern in the Southern Ocean: PS103 (https://doi.org/10.1594/PANGAEA.898941). Chlorophyll a concentration (Chl-a) of six phytoplankton functions groups (PFTs) derived from these pigments have been also included. This published data set has contributed to validate satellite PFT products available on the EU funded Copernicus Marine Service (CMEMS, https://marine.copernicus.eu/), which are derived from multi-sensor ocean colour reflectance data and sea surface temperature using an empirical orthogonal function based approach (Xi et al. 2020; 2021). Description on in situ PFT Chl-a determination from pigment data: PFT Chl-a in this data set were derived using an updated diagnostic pigment analysis (DPA) method (Soppa et al., 2014; Losa et al., 2017) with retuned coefficients by Alvarado et al (2021), that was originally developed by Vidussi et al. (2001), adapted in Uitz et al. (2006) and further refined by Hirata et al. (2011) and Brewin et al. (2015). The values of retuned DPA weighting coefficients for PFT Chl-a determination are: 1.56 for fucoxanthin, 1.53 for peridinin, 0.89 for 19'-hexanoyloxyfucoxanthin, 0.44 for 19'-butanoyloxyfucoxanthin, 1.94 for alloxanthin, 2.63 for total chlorophyll b, and 0.99 for zeaxanthin. The coefficient retuning was based on an updated global HPLC pigment data base for the open ocean (water depth 〉200 m), which was compiled based on the previously published data sets spanning from 1988 to 2012 described in Losa et al. (2017), with updates in Xi et al. (2021) and Álvarez et al. (2022), by adding other newly available HPLC pigment data collected between 2012 and 2018 mainly from SeaBASS (https://seabass.gsfc.nasa.gov/), PANGAEA, British Oceanographic Data Centre (BODC, https://www.bodc.ac.uk/), and Australian Open Access to Ocean Data (AODN, https://portal.aodn.org.au/) (as of February 2020, see Table 1 attached in the 'Additional metadata' for more details on the data sources).
    Keywords: 19-Butanoyloxyfucoxanthin; 19-Hexanoyloxyfucoxanthin; AC3; Alloxanthin; AMT28; AMT28_10-33; AMT28_1-1; AMT28_11-36; AMT28_12-41; AMT28_13-44; AMT28_14-48; AMT28_15-50; AMT28_16-57; AMT28_17-58; AMT28_18-64; AMT28_19-66; AMT28_20-71; AMT28_21-73; AMT28_22-78; AMT28_23-80; AMT28_2-4; AMT28_24-85; AMT28_25-87; AMT28_27-93; AMT28_28-95; AMT28_29-100; AMT28_30-101; AMT28_31-105; AMT28_32-111; AMT28_33-112; AMT28_34-117; AMT28_35-120; AMT28_36-124; AMT28_37-126; AMT28_3-8; AMT28_38-133; AMT28_40-137; AMT28_4-11; AMT28_41-142; AMT28_43-147; AMT28_44-150; AMT28_45-155; AMT28_46-158; AMT28_47-164; AMT28_48-166; AMT28_49-174; AMT28_50-176; AMT28_51-181; AMT28_5-13; AMT28_52-183; AMT28_53-188; AMT28_54-190; AMT28_55-198; AMT28_56-199; AMT28_57-204; AMT28_58-206; AMT28_59-210; AMT28_59-212; AMT28_61-218; AMT28_6-17; AMT28_62-220; AMT28_63-226; AMT28_64-227; AMT28_65-232; AMT28_66-234; AMT28_7-21; AMT28_8-24; AMT28_9-28; AMT29; AMT29_AA; AMT29_AB; AMT29_AC; AMT29_AD; AMT29_AE; AMT29_AF; AMT29_AG; AMT29_AH; AMT29_AI; AMT29_AJ; AMT29_AK; AMT29_AL; AMT29_AM; AMT29_AN; AMT29_AO; AMT29_AP; AMT29_AQ; AMT29_AR; AMT29_AS; AMT29_AV; AMT29_AX; AMT29_BC; AMT29_BD; AMT29_BE; AMT29_BF; AMT29_BG; AMT29_BH; AMT29_BI; AMT29_BJ; AMT29_BK; AMT29_BL; AMT29_BM; AMT29_BN; AMT29_BO; AMT29_BP; AMT29_BQ; AMT29_BR; AMT29_BS; AMT29_BT; AMT29_BU; AMT29_BV; AMT29_BW; AMT29_BX; AMT29_BY; AMT29_BZ; AMT29_CA; AMT29_CB; AMT29_CC; AMT29_CD; AMT29_CE; AMT29_CF; AMT29_CG; AMT29_CH; AMT29_CJ; AMT29_CK; AMT29_CL; AMT29_CM; AMT29_CN; AMT29_CO; AMT29_CP; AMT29_CQ; AMT29_CR; AMT29_CS; AMT29_CT; AMT29_CTD_001; AMT29_CTD_002; AMT29_CTD_003; AMT29_CTD_004; AMT29_CTD_005; AMT29_CTD_006; AMT29_CTD_007; AMT29_CTD_008; AMT29_CTD_009; AMT29_CTD_010; AMT29_CTD_011; AMT29_CTD_013; AMT29_CTD_015; AMT29_CTD_016; AMT29_CTD_017; AMT29_CTD_018; AMT29_CTD_019; AMT29_CTD_020; AMT29_CTD_021; AMT29_CTD_022; AMT29_CTD_024; AMT29_CTD_025; AMT29_CTD_026; AMT29_CTD_027; AMT29_CTD_028; AMT29_CTD_029; AMT29_CTD_030; AMT29_CTD_031; AMT29_CTD_032; AMT29_CTD_034; AMT29_CTD_035; AMT29_CTD_036; AMT29_CTD_037; AMT29_CTD_038; AMT29_CTD_039; AMT29_CTD_041; AMT29_CTD_042; AMT29_CTD_043; AMT29_CTD_044; AMT29_CTD_045; AMT29_CTD_046; AMT29_CTD_047; AMT29_CTD_048; AMT29_CTD_049; AMT29_CTD_050; AMT29_CTD_051; AMT29_CTD_052; AMT29_CTD_053; AMT29_CTD_054; AMT29_CTD_055; AMT29_CU; AMT29_CV; AMT29_CW; AMT29_CX; AMT29_CY; AMT29_CZ; AMT29_DA; AMT29_DB; AMT29_DC; AMT29_DD; AMT29_DE; AMT29_DF; AMT29_DG; AMT29_DH; AMT29_DI; AMT29_DJ; AMT29_DK; AMT29_DL; AMT29_DM; AMT29_DN; AMT29_DO; AMT29_DP; AMT29_DQ; AMT29_DR; AMT29_DS; AMT29_DT; AMT29_DU; AMT29_DV; AMT29_DZ; AMT29_EB; AMT29_EC; AMT29_EE; AMT29_EF; AMT29_EG; AMT29_EI; AMT29_EK; AMT29_EL; AMT29_EM; AMT29_EO; AMT29_EQ; AMT29_ER; AMT29_ES; AMT29_ET; AMT29_EV; ANT-XXXII/2; ANT-XXXIII/4; Arctic Amplification; Arctic Ocean; ARK-XXIV/1; ARK-XXIV/2; ARK-XXIX/2.2; ARK-XXV/1; ARK-XXV/2; ARK-XXVI/1; ARK-XXVII/1; ARK-XXVII/2; ARK-XXVIII/2; ARK-XXX/1.1; ARK-XXX/1.2; ARK-XXXI/1.1,PASCAL; ARK-XXXI/1.2; ARK-XXXI/2; AWI_BioOce; Barents Sea; Biological Oceanography @ AWI; Campaign; Canarias Sea; chlorophyll; Chlorophyll a; Chlorophyll a, Diatoms; Chlorophyll a, Dinoflagellata; Chlorophyll a, Green algae; Chlorophyll a, Haptophyta; Chlorophyll a, Prochlorococcus; Chlorophyll a, Prokaryotes; Chlorophyll a + Divinyl chlorophyll a + Chlorophyllide a; Chlorophyll b + Divinyl chlorophyll b + Chlorophyllide b; Chlorophyllide a; CT; CTD, towed system; CTD/Rosette; CTD/Rosette with Underwater Vision Profiler; CTD001; CTD002; CTD003; CTD004; CTD005; CTD006; CTD007; CTD008; CTD009; CTD010; CTD011; CTD012; CTD013; CTD014; CTD015; CTD016; CTD017; CTD018; CTD019; CTD020; CTD021; CTD022; CTD023; CTD024; CTD025; CTD026; CTD027; CTD028; CTD029; CTD030; CTD031; CTD032; CTD033; CTD034; CTD035; CTD036; CTD037; CTD038; CTD039; CTD040; CTD041; CTD042; CTD043; CTD044; CTD045; CTD046; CTD047; CTD048; CTD049; CTD050; CTD051; CTD052; CTD053; CTD054; CTD055; CTD056; CTD057; CTD058; CTD059; CTD060; CTD061; CTD062; CTD063; CTD-Acoustic Doppler Current Profiler; CTD-ADCP; CTD-RO; CTD-RO_UVP; CTD-twoyo; DATE/TIME; DEPTH, water; Diagnostic Pigment Analysis (DPA); Discovery (2013); Divinyl chlorophyll a; DPA; DY110; EG_I; EG_II; EG_III; EG_IV; Event label; Exploitation of Sentinel-5-P for Ocean Colour Products; FRAM; FRontiers in Arctic marine Monitoring; Fucoxanthin; Global Long-term Observations of Phytoplankton Functional Types from Space; GLOPHYTS; Hand net; HG_I; HG_II; HG_III; HG_IV; HG_IX; HG_V; HG_VI; HG_VIII; HGIV; High Performance Liquid Chromatography (HPLC); HN; HPLC; ICE; Ice station; James Clark Ross; JR18001; Kb0; LATITUDE; Lazarev Sea; LONGITUDE; N3; N4; N5; North Greenland Sea; North Sea; Norwegian Sea; ORDINAL NUMBER; Peridinin; phytoplankton functional types; pigments; Polarstern; PORTWIMS; Project Portugal Twinning for Innovation and Excellence in Marine Science and Earth Observation; PS103; PS103_0_Underway-3; PS103_1-1; PS103_11-1; PS103_15-1; PS103_22-5; PS103_23-5; PS103_2-4; PS103_27-2; PS103_29-3; PS103_3-1; PS103_31-2; PS103_34-6; PS103_39-3; PS103_40-3; PS103_4-1; PS103_43-4; PS103_45-3; PS103_48-1; PS103_5-2; PS103_59-2; PS103_6-6; PS103_67-1; PS103_8-3; PS103_9-1; PS106_18-2; PS106_21-2; PS106_27-6; PS106_28-2; PS106_31-2; PS106_32-2; PS106_45-1; PS106_50-1; PS106_ZODIAK_170527; PS106_ZODIAK_170529; PS106_ZODIAK_170531; PS106_ZODIAK_170601; PS106_ZODIAK_170607; PS106_ZODIAK_170608; PS106_ZODIAK_170617; PS106_ZODIAK_170618; PS106_ZODIAK_170619; PS106_ZODIAK_170624; PS106_ZODIAK_170625; PS106_ZODIAK_170626; PS106_ZODIAK_170627; PS106_ZODIAK_170629; PS106_ZODIAK_170630; PS106_ZODIAK_170701; PS106_ZODIAK_170702; PS106_ZODIAK_170703; PS106_ZODIAK_170705; PS106_ZODIAK_170706; PS106_ZODIAK_170708; PS106_ZODIAK_170709; PS106_ZODIAK_170710; PS106_ZODIAK_170711; PS106_ZODIAK_170713; PS106_ZODIAK_170714; PS106_ZODIAK_170715; PS106/1; PS106/2; PS107; PS107_0_underway-9; PS107_10-4; PS107_12-3; PS107_14-1; PS107_16-3; PS107_18-3; PS107_19-1; PS107_20-8; PS107_21-1; PS107_22-6; PS107_24-1; PS107_28-1; PS107_29-1; PS107_33-6; PS107_34-5; PS107_36-1; PS107_37-1; PS107_40-2; PS107_40-3; PS107_40-4; PS107_40-5; PS107_40-6; PS107_48-1; PS107_6-8; PS107_7-1; PS107_8-1; PS113; PS113_0_underway-5; PS113_11-2; PS113_1-2; PS113_13-2; PS113_14-2; PS113_15-1; PS113_17-2; PS113_18-2; PS113_20-1; PS113_21-1; PS113_22-2; PS113_23-2; PS113_25-1; PS113_26-2; PS113_27-1; PS113_28-1; PS113_29-2; PS113_30-2; PS113_31-1; PS113_3-2; PS113_33-1; PS113_5-2; PS113_6-2; PS113_7-2; PS113_9-2; PS120; PS120_0_underway-10; PS120_11-3; PS120_15-3; PS120_19-3; PS120_20-1; PS120_21-3; PS120_24-3; PS120_3-1; PS120_5-3; PS120_8-3; PS121; PS121_0_Underway-65; PS121_1-2; PS121_12-2; PS121_15-1; PS121_16-5; PS121_24-2; PS121_25-2; PS121_27-2; PS121_28-4; PS121_29-1; PS121_32-2; PS121_33-2; PS121_34-1; PS121_35-3; PS121_36-1; PS121_38-1; PS121_39-1; PS121_40-3; PS121_43-7; PS121_44-3; PS121_45-1; PS121_52-2; PS121_52-6; PS121_5-3; PS121_7-3; PS74; PS74/104-1; PS74/107-1; PS74/108-1; PS74/112-1; PS74/119-1; PS74/120-1; PS74/127-1; PS74/128-1; PS74/132-1; PS74/133-1; PS74/134-1; PS74/1-track; PS74/2-track; PS76; PS76/001-1; PS76/002-1; PS76/005-1; PS76/007-2; PS76/009-1; PS76/017-1; PS76/020-1; PS76/025-1; PS76/026-1; PS76/030-1; PS76/034-3; PS76/039-1; PS76/041-1; PS76/044-1; PS76/049-1; PS76/051-1; PS76/057-1; PS76/058-1; PS76/062-1; PS76/064-1; PS76/068-1; PS76/072-1; PS76/080-1; PS76/082-1; PS76/094-1; PS76/098-1; PS76/102-1; PS76/109-3; PS76/110-1; PS76/111-1; PS76/120-2; PS76/121-1; PS76/122-1; PS76/124-3; PS76/129-1; PS76/132-1; PS76/134-1; PS76/135-1; PS76/136-1; PS76/138-1; PS76/139-1; PS76/157-1; PS76/159-2; PS76/166-1; PS76/167-1; PS76/170-2; PS76/173-1; PS76/174-1; PS76/175-1; PS76/176-1; PS76/178-1; PS76/179-3; PS76/181-1; PS76/182-1; PS76/184-1; PS76/185-1; PS76/194-1; PS76/200-1; PS76/201-1; PS76/203-1; PS76/204-1; PS76/208-5; PS76/210-2; PS76/211-1; PS76/216-1; PS76/220-1; PS76/223-1; PS76/224-1; PS76/227-3; PS76/229-1; PS76/231-1; PS76/233-1; PS76/235-
    Type: Dataset
    Format: text/tab-separated-values, 37522 data points
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    DATA PANGAEA
  • 2
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    The potential of Sentinel-5P’s high spectral resolution for ocean applications (2021)
    In:  EPIC3EGU General Assembly 2021, online, 2021-04-19-2021-04-30
    Details
    Publication Date: 2021-12-21
    Description: Hyperspectral satellite data are a source of the top of the atmosphere radiance signal which can be used for novel algorithms aimed for observations of marine ecosystems and the light-lit ocean. Atmospheric sensors such as SCIAMACHY, GOME-2 and OMI have proven in the past to yield valuable information on phytoplankton diversity, sun-induced marine fluorescence, and the underwater light field, however at low coverage and spatial resolution. Within the ESA Sentinel-5p+ Innovation themes, we explore TROPOMI's potential for deriving the diffuse attenuation coefficient and the quantification of different phytoplankton groups. As commonly used for the retrieval of atmospheric trace gases, we apply the differential optical absorption spectroscopy combined with radiative transfer modeling (RTM) to infer these oceanic parameters. We present results on a measure describing the diminishing of incoming radiation in the ocean with depth, the diffuse attenuation coefficient KD. KD is derived by the retrieval of the vibrational Raman scattering signal in backscattered radiances measured by TROPOMI in the UV and spectral range which then is further converted to the associated KD using RTM. The final TROMPOMI KD data sets resolved for three spectral regions (UV-B+short wave UV-A, UV-A and short blue) agree well with in situ data sampled during an expedition with RV Polarstern in 2018 in the Atlantic Ocean. Further, KD-blue compared to wavelength-converted KD(490nm) products (OLCI-A and the merged OC-CCI) from common, multispectral, ocean color sensors, show that differences between the three data sets are within uncertainties given for the OC-CCI product. Our study shows for the first time KD products for the UV spectral range retrieved from space based data. TROPOMI KD-blue results have higher quality and much higher spatial coverage and resolution than previous ones from SCIAMACHY, GOME-2 and OMI. Additionally, first results on TROPOMI’s potential for retrieving three phytoplankton groups will be shown and compared to similar multispectral phytoplankton group data for the same time period and ocean region as shown for TROPOMI KD.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 3
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    Diffuse Attenuation Of Underwater UV And Short Blue Light Obtained From TROPOMI’s High Spectral Resolution (2022)
    In:  EPIC312th EARSeL Workshop on Imaging Spectroscopy, Potsdam, Germany, 2022-06-22-2022-06-24
    Details
    Publication Date: 2022-10-04
    Description: In this study, we exploited high spectrally reoslved Sentinel-5 Precursor’s (S5P) sensor TROPOMI’s potential to retrieve the diffuse attenuation for three bands reaching from the UV-B to the short blue wavelengths range. As a baseline, previously developed algorithms applied to similar atmospheric satellite sensors such as SCIAMACHY, GOME-2 and OMI were adapted and extended. Opposed to these precursor sensors, TROPOMI enable data acquisition due to a large swath with spatial and temporal resolution nearly as good as obtained from common open ocean color sensors, until today only multispectral. The later sensors do not enable retrievals in the UV spectral region, but are used for intercomparison to the short blue diffuse attenuation retrieved from TROPOMI. In this presentation, we provide detailed insights into the retrieval method, its uncertainty and the application to obtain data in the global ocean in open ocean and coastal regions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 4
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    Phytoplankton functional types from multi-sensor satellite observations – towards a long-term monitoring (2002-2020) (2022)
    In:  EPIC3Ocean Science Meeting 2022, 2022-02-24-2022-03-04
    Details
    Publication Date: 2023-06-21
    Description: Phytoplankton in the sunlit layer of the ocean act as the base of the marine food web fueling fisheries, and also regulate key biogeochemical processes such as exporting carbon to the deep ocean. Phytoplankton composition structure varies in ocean biomes and different phytoplankton groups drive differently the marine ecosystem. As one of the algorithms deriving phytoplankton composition from space borne data, within the framework of the EU Copernicus Marine Service (CMEMS), OLCI-PFT algorithm was developed using multi-spectral satellite data collocated to an extensive in-situ PFT data set based on HPLC pigments and sea surface temperature data (Xi et al. 2020, 2021). It provides global PFT retrievals including chlorophyll a estimations of diatoms, haptophytes, dinoflagellates, chlorophytes and prokaryotic phytoplankton spanning the period from 2002 until today, by using multi-sensor merged products and OLCI data. These PFT products with per-pixel uncertainty are publicly available on the CMEMS. Due to different lifespans and radiometric characteristics of the ocean color sensors, it is crucial to evaluate the CMEMS PFT products to provide quality-assured data for a consistent long-term monitoring of the phytoplankton community structure. In this study, using in-situ phytoplankton data (HPLC pigment data further evaluated with microscopic, flow cytometry, molecular and hyperspectral optical data) collected from expeditions since 2009 in the tropical, temperate and polar (mainly Fram Strait within the PEBCAO network) regions, we aim to 1) validate the CMEMS PFT products and investigate the continuity of the PFTs data derived from different satellites, and 2) deliver two-decade consistent PFT products for times series analysis. For the latter we determine inter-annual trends and variation of the surface phytoplankton community structure targeting some key sub-regions (e.g.,east Fram Strait) that have been observed being influenced by the changing marine environment.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev , info:eu-repo/semantics/conferenceObject
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  • 5
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    Toward the Synergistic Use of Ocean Colour products to Improve the Description of Phytoplankton Productivity within the Global Ocean (2022)
    In:  EPIC3Ocean Carbon from Space Workshop. 2nd Workshop in the CLEO (Colourand Light in the ocean from Earth Observation, ESA virtual online event, 2022-02-14-2022-02-18ESA
    Details
    Publication Date: 2023-06-21
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 6
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    Novel ocean color information from Sentinel-5P’s high spectral resolution (2022)
    In:  EPIC3Living Planet Symposium 2022, Bonn, Germany, 2022-05-23-2022-05-27ESA
    Details
    Publication Date: 2023-06-21
    Description: High spectrally resolved satellite data are a source of the top of the atmosphere radiance signal which can be used for novel algorithms aimed for observations of phytoplankton groups biomass and the spectral composition of the light-lit ocean. Atmospheric sensors such as SCIAMACHY, GOME-2 and OMI have proven in the past to yield valuable information on phytoplankton diversity, sun-induced marine fluorescence, and the underwater light field. However, the use of these data sets was limited by their temporal and spatial resolution mostly not meeting requirements for time series studies. Within the ESA Sentinel-5p+ Innovation project S5POC, we explore Sentinel-5P instrument TROPOMI's potential for deriving the diffuse attenuation coefficient and the quantification of different phytoplankton groups. As commonly used for the retrieval of atmospheric trace gases, we apply the differential optical absorption spectroscopy combined with radiative transfer modeling (RTM) to infer these oceanic parameters. We present results on a measure describing the diminishing of incoming radiation in the ocean with depth, the diffuse attenuation coefficient Kd. Kd is derived by the retrieval of the vibrational Raman scattering signal in backscattered radiances measured by TROPOMI in the UV and blue spectral range which then is further converted to the associated Kd using RTM. The final TROMPOMI KD data sets resolved for three spectral regions (UV-B+short wave UV-A, UV-A and short blue) agree well with in situ data sampled during an expedition with RV Polarstern in 2018 in the tropical, temperate and polar Atlantic Ocean. Further, Kd-blue compared to wavelength-converted Kd(490 nm) products (OLCI-A and the merged OC-CCI) from common, multispectral, ocean color sensors, show that differences between the three data sets are within uncertainties given for the OC-CCI product. TROPOMI’s potential for retrieving phytoplankton groups is also explored for the Atlantic open ocean and, additionally, for the Portuguese coast and coast and British Columbia, Canada coast. Comparison to independent phytoplankton groups biomass data derived from in-situ pigment data and similar satellite products (CMEMS global PFT product based on Xi et al. 2021 and OCPFT algorithm following Losa et al. 2017 applied to OLCI-Chla and OC-CCI data sets) show reasonable agreement for most groups. Having established these new TROPOMI products, the next steps are to investigate global products over the full operating period of TROPOMI to assess the temporal and spatial stability of the products. Perspectively, these data products delivering information on the spectral underwater light and phytoplankton composition can be used as auxiliary information for modeling marine ecosystem/biogeochemical functioning or photochemical reaction rates of climatically important compounds and inhibition of primary productivity.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 7
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    20-year satellite observations of phytoplankton functional types (PFTs) in the Atlantic Ocean (2022)
    In:  EPIC3ESA Living Planet Symposium 2022, Bonn, Germany, 2022-05-23-2022-05-27
    Details
    Publication Date: 2023-06-21
    Description: Phytoplankton composition structure varies in ocean biomes. Different phytoplankton groups drive differently the marine ecosystem and biogeochemical processes. Therefore, variations in phytoplankton composition influence the entire ocean environment, specifically the ocean energy transfer, the deep ocean carbon export, water quality etc. As one of the algorithms deriving phytoplankton composition from space borne data, the EOF-PFT algorithm was developed using multi-spectral satellite data collocated to an extensive global in-situ PFT data set based on HPLC pigments and sea surface temperature data (Xi et al. 2020, 2021). By using multi-sensor merged products and Sentinel-3 OLCI data, the algorithm provides global chlorophyll a (Chla) data with per-pixel uncertainty for diatoms, haptophytes, dinoflagellates, chlorophytes and prokaryotic phytoplankton spanning the period from 2002 until today, with products available on the EU Copernicus Marine Service (CMEMS). The objectives of this study are to 1) evaluate CMEMS PFT products and improve their continuity along the products derived from different satellite sensors, and 2) 20-year satellite PFT products for time series analysis of climatology, trends, anomaly and phenology of multiple PFTs in the whole Atlantic and its different biogeochemical provinces (Longhurst, 2006).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev , info:eu-repo/semantics/conferenceObject
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    Satellite monitoring of surface phytoplankton functional types in the Atlantic Ocean over 20 years (2002–2021) (2023)
    Copernicus Publications
    In:  EPIC3State of the Planet, Copernicus Publications, 1-osr7, pp. 1-1, ISSN: 2752-0706
    Details
    Publication Date: 2024-01-31
    Description: An analysis of multi-satellite-derived products of four major phytoplankton functional types (PFTs – diatoms, haptophytes, prokaryotes and dinoflagellates) was carried out to investigate the PFT time series in the Atlantic Ocean between 2002 and 2021. The investigation includes the 2-decade trends, climatology, phenology and anomaly of PFTs for the whole Atlantic Ocean and its different biogeochemical provinces in the surface layer that optical satellite signals can reach. The PFT time series over the whole Atlantic region showed mostly no clear trend over the last 2 decades, except for a small decline in prokaryotes and an abrupt increase in diatoms during 2018–2019, which is mainly observed in the northern Longhurst provinces. The phenology of diatoms, haptophytes and dinoflagellates is very similar: at higher latitudes bloom maxima are reached in spring (April in the Northern Hemisphere and October in the Southern Hemisphere), in the oligotrophic regions in winter time and in the tropical regions during May to September. In general, prokaryotes show opposite annual cycles to the other three PFTs and present more spatial complexity. The PFT anomaly (in percent) of 2021 compared to the 20-year mean reveals mostly a slight decrease in diatoms and a prominent increase in haptophytes in most areas of the high latitudes. Both diatoms and prokaryotes show a mild decrease along coastlines and an increase in the gyres, while prokaryotes show a clear decrease at mid-latitudes to low latitudes and an increase on the western African coast (Canary Current Coastal Province, CNRY and Guinea Current Coastal Province, GUIN) and southwestern corner of North Atlantic Tropical Gyral Province (NATR). Dinoflagellates, as a minor contributor to the total biomass, are relatively stable in the whole Atlantic region. This study illustrated the past and current PFT state in the Atlantic Ocean and acted as the first step to promote long-term consistent PFT observations that enable time series analyses of PFT trends and interannual variability to reveal potential climate-induced changes in phytoplankton composition on multiple temporal and spatial scales.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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    Endocrine-disrupting effects of methylparaben on the adult gerbil prostate (2017)
    Wiley
    Details
    Publication Date: 2017-02-10
    Description: Parabens are xenoestrogens widely employed in cosmetics, foodstuffs, and pharmaceutical products. These chemicals are known to disrupt hormone-dependent organs, due to their binding affinity for hormonal receptors. Although recent studies have evaluated the endocrine-disrupting potential of parabens in several reproductive organs, few have investigated the effects of these chemicals in the prostate. The aim of this work was to evaluate the effects of oral exposure to methylparaben (500 mg/kg/day) for 3, 7, and 21 days on male and female adult gerbil prostate. For this purpose, we employed biometrical, morphological, and immunohistochemical analyses. The results showed that methylparaben caused morphological changes in gerbil prostates in all experimental groups. These animals displayed similar alterations such as prostate epithelial hyperplasia, increased cell proliferation, and a higher frequency of AR-positive cells. However, the prostate of the female gerbil showed additional changes such as stromal inflammatory infiltration, intraepithelial neoplasia foci, and an increase in AR-positive frequency. Altogether, these data show that methylparaben was responsible for disrupting estrogenic and androgenic receptors, suggesting that parabens may have estrogenic and antiandrogenic effects in the prostate.
    Print ISSN: 1520-4081
    Electronic ISSN: 1522-7278
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Wiley
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    O clássico e o novo - tendências, objetos e abordagens em ciências sociais e saúde (2021)
    SciELO Books - Editora FIOCRUZ
    Details
    Publication Date: 2023-12-21
    Description: Tratando de temas, como a cultura e a subjetividade, as questões éticas da atualidade, a qualidade de vida no mundo contemporâneo etc., O Clássico e o Novo é o fruto de trabalhos apresentados no 2o Congresso Brasileiro de Ciências Sociais em Saúde, e reúne uma gama dos mais qualificados profissionais que tratam de diferentes temas, intencionando uma perspectiva multidisciplinar. Partindo do pressuposto de que dentro da própria área das Ciências Sociais há um processo de fragmentação que vem exigindo cada vez mais novas interlocuções interdisciplinares, procura-se aqui estabelecer um diálogo profícuo entre este campo do saber e a área da saúde. Dessa forma, ao abordar questões relacionadas à área da saúde, este livro se constitui como leitura obrigatória para os profissionais de saúde coletiva, introduzindo diferentes e instigantes propostas de reflexão para a saúde na atualidade.
    Keywords: R5-920 ; Qualidade de vida ; Política de saúde ; Iniquidade na saúde ; Política social ; bic Book Industry Communication::M Medicine
    Language: Portuguese
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