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  • 1
    Electronic Resource
    Electronic Resource
    Characterization of bacterial communities in four freshwater lakes differing in nutrient load and food web structure (2005)
    Oxford, UK : Blackwell Publishing Ltd
    FEMS microbiology ecology 53 (2005), S. 0 
    Details
    ISSN: 1574-6941
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: The phylogenetic composition of bacterioplankton communities in the water column of four shallow eutrophic lakes was analyzed by partially sequencing cloned 16S rRNA genes and by PCR-DGGE analysis. The four lakes differed in nutrient load and food web structure: two were in a clearwater state and had dense stands of submerged macrophytes, while two others were in a turbid state characterized by the occurrence of phytoplankton blooms. One turbid and one clearwater lake had very high nutrient levels (total phosphorus 〉 100 μg/l), while the other lakes were less nutrient rich (total phosphorus 〈 100μg/l). Cluster analysis, multidimensional scaling and ANOSIM (analysis of similarity) were used to investigate differences among the bacterial community composition in the four lakes.Our results show that each lake has its own distinct bacterioplankton community. The samples of lake Blankaart differed substantially from those of the other lakes; this pattern was consistent throughout the year of study. The bacterioplankton community composition in lake Blankaart seems to be less diverse and less stable than in the other three lakes. Clone library results reveal that Actinobacteria strongly dominated the bacterial community in lake Blankaart. The relative abundance of Betaproteobacteria was low, whereas this group was dominant in the other three lakes. Turbid lakes had a higher representation of Cyanobacteria, while clearwater lakes were characterized by more representatives of the Bacteroidetes. Correlating our DGGE data with environmental parameters, using the BIOENV procedure, suggests that differences are partly related to the equilibrium state of the lake.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1016/j.femsec.2004.12.006
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  • 2
    Electronic Resource
    Electronic Resource
    Salinity, depth and the structure and composition of microbial mats in continental Antarctic lakes (2004)
    Oxford, UK : Blackwell Science Ltd
    Freshwater biology 49 (2004), S. 0 
    Details
    ISSN: 1365-2427
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: 1. Lakes and ponds in the Larsemann Hills and Bølingen Islands (East-Antarctica) were characterised by cyanobacteria-dominated, benthic microbial mats. A 56-lake dataset representing the limnological diversity among the more than 150 lakes and ponds in the region was developed to identify and quantify the abiotic conditions associated with cyanobacterial and diatom communities.2. Limnological diversity in the lakes of the Larsemann Hills and Bølingen Islands was associated primarily with conductivity and conductivity-related variables (concentrations of major ions and alkalinity), and variation in lake morphometry (depth, catchment and lake area). Low concentrations of pigments, phosphate, nitrogen, DOC and TOC in the water column of most lakes suggest extremely low water column productivity and hence high water clarity, and may thus contribute to the ecological success of benthic microbial mats in this region.3. Benthic communities consisted of prostrate and sometimes finely laminated mats, flake mats, epilithic and interstitial microbial mats. Mat physiognomy and carotenoid/chlorophyll ratios were strongly related to lake depth, but not to conductivity.4. Morphological-taxonomic analyses revealed the presence of 26 diatom morphospecies and 33 cyanobacterial morphotypes. Mats of shallow lakes (interstitial and flake mats) and those of deeper lakes (prostrate mats) were characterised by different dominant cyanobacterial morphotypes. No relationship was found between the distribution of these morphotypes and conductivity. In contrast, variation in diatom species composition was strongly related to both lake depth and conductivity. Shallow ponds were mainly characterised by aerial diatoms (e.g. Diadesmis cf. perpusilla and Hantzschia spp.). In deep lakes, communities were dominated by Psammothidium abundans and Stauroforma inermis. Lakes with conductivities higher than ±1.5 mS cm−1 became susceptible to freezing out of salts and hence pronounced conductivity fluctuations. In these lakes P. abundans and S. inermis were replaced by Amphora veneta. Stomatocysts were important only in shallow freshwater lakes.5. Ice cover influenced microbial mat structure and composition both directly by physical disturbance in shallow lakes and by influencing light availability in deeper lakes, as well as indirectly by generating conductivity increases and promoting the development of seasonal anoxia.6. The relationships between diatom species composition and conductivity, and diatom species composition and depth, were statistically significant. Transfer functions based on these data can therefore be used in paleolimnological reconstruction to infer changes in the precipitation–evaporation balance in continental Antarctic lakes.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1111/j.1365-2427.2004.01186.x
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  • 3
    Electronic Resource
    Electronic Resource
    Structural characteristics of phytoplankton assemblages in tidal and non-tidal freshwater systems: a case study from the Schelde basin, Belgium (1997)
    Oxford, UK : Blackwell Science Ltd
    Freshwater biology 38 (1997), S. 0 
    Details
    ISSN: 1365-2427
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology
    Notes: 1. The Schelde estuary, its side basins and their tributaries were sampled in August 1995 and April 1996 for phytoplankton abundance, biomass, diversity and species composition. In order to clarify the underlying causes of differences in phytoplankton communities, the results were related to some important abiotic variables.2. Although species richness and diversity did not differ significantly between the riverine and the freshwater tidal stations, multivariate ordination techniques based on species abundances differentiate between these two ecosystems. While in the rivers phytoplankton standing stocks were as high in summer as in spring, standing stocks in the freshwater tidal estuary were significantly higher in the August samples.3. It is postulated that due to the resuspension of suspended solids by estuarine currents, light is limiting phytoplankton development in the freshwater tidal reaches in spring. At that stage, phytoplankton populations have already developed in the rivers. In summer, zooplankton prevent any further increase of riverine phytoplankton populations. In the freshwater tidal estuary, however, increased light levels, a higher residence time compared to rivers and the absence of zooplankton due to low oxygen concentrations permit phytoplankton populations to bloom.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1046/j.1365-2427.1997.00211.x
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  • 4
    Electronic Resource
    Electronic Resource
    Diatom-temperature transfer functions based on the altitudinal zonation of diatom assemblages in Papua New Guinea: a possible tool in the reconstruction of regional palaeoclimatic changes (1995)
    Springer
    Journal of paleolimnology 13 (1995), S. 65-77 
    Details
    ISSN: 1573-0417
    Keywords: diatom assemblages ; altitudinal gradient ; Papua New Guinea ; calibration ; palaeotemperature
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Geosciences
    Notes: Abstract Indirect and direct gradient ordination techniques were used to study the relationship between present-day benthic and periphytic diatom assemblages and environmental factors along an altitudinal gradient in Papua New Guinea. Both within the screened initial data-set and a narrowly-defined subset of soft-water lakes, shifts in diatom assemblages are clearly related to altitudinal differences. This relation is used to construct transfer functions for inferring altitude (and hence average water temperature) from the diatom records. Calibration by canonical correspondence analysis (CCA) and simple weighted averaging calibration proved to be superior to models using WA with tolerance downweighting and to a simple WA model based on a selection of 52 indicator taxa. From the calibration models and the linear relationship between altitude and epilimnetic water temperature, the average lake water temperature can be predicted with an accuracy of 3.2°C. After further refinement, a transfer function for palaeotemperature based on diatoms would be of potential value for climatic reconstructions in tropical regions.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00678111
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  • 5
    Electronic Resource
    Electronic Resource
    Dynamics and trophic roles of heterotrophic protists in the plankton of a freshwater tidal estuary (2000)
    Springer
    Hydrobiologia 432 (2000), S. 25-36 
    Details
    ISSN: 1573-5117
    Keywords: heterotrophic nanoflagellates ; ciliates ; rotifers ; bacteria ; microbial food web ; tidal river ; estuary ; Schelde
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Freshwater tidal estuaries comprise the most upstream reaches of estuaries and are often characterised by the presence of dense bacterial and algal populations which provide a large food source for bacterivorous and algivorous protists. In 1996, the protistan community in the freshwater tidal reaches of the Schelde estuary was monitored to evaluate whether these high food levels are reflected in a similarly high heterotrophic protistan biomass. Protistan distribution patterns were compared to those of metazoan zooplankton to evaluate the possible role of top-down regulation of protists by metazoans. Apart from the algivorous sarcodine Asterocaelum, which reached high densities in summer, heterotrophic protistan biomass was dominated by ciliates and, second in importance, heterotrophic nanoflagellates (HNAN). HNAN abundance was low (annual average 2490 cells ml−1) and did not display large seasonal variation. It is hypothesised that HNAN were top-down controlled by oligotrich ciliates throughout the year and by rotifers in summer. Ciliate abundance was generally relatively high (annual average 65 cells ml−1) and peaked in winter (maximum 450 cells ml−1). The decline of ciliate populations in summer was ascribed to grazing by rotifers, which developed dense populations in that season. In winter, ciliate populations were probably regulated `internally' by carnivorous ciliates (haptorids and Suctoria). Our observations suggest that, in this type of productive ecosystems, the microbial food web is mainly top-down controlled rather than regulated by food availability.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1004017018702
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  • 6
    Electronic Resource
    Electronic Resource
    Short-term fluctuations in benthic diatom numbers on an intertidal sandflat in the Westerschelde estuary (Zeeland, The Netherlands) (1993)
    Springer
    Hydrobiologia 269-270 (1993), S. 275-284 
    Details
    ISSN: 1573-5117
    Keywords: benthic diatoms ; seasonality ; Westerschelde
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract During the period March–May 1991, sediment samples were taken every two or three days at one intertidal station in the brackish part of the Westerschelde estuary. Quantitative cell counts were made in order to investigate the short-term temporal changes in diatom numbers and assemblage structure. Throughout the whole sampling period, the diatom assemblage was dominated by epipsammic diatoms. Three species, Achnanthes delicatula, Opephora cf. perminuta and Catenula adhaerens on average accounted for almost 67% of all valves counted. The epipsammic diatom fraction showed no significant changes in absolute numbers; its species composition appeared relatively stable. In contrast, epipelic diatom densities significantly increased towards the end of the study period. Species composition within this fraction was less stable. Multivariate analysis (Principal Components Analysis), in combination with multiple regression, indicated that total sky irradiance (on the second and third day preceding sampling) and percentage organic matter were related to the short-term fluctuations of the epipelic diatom fraction.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF00028026
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  • 7
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    The HYPERMAQ dataset (2022)
    PANGAEA
    Details
    Publication Date: 2023-06-24
    Description: The HYPERMAQ dataset contributes to a better description of marine optics in optically complex water bodies by providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging between 1 to 700 FNU and between 0.9 to 180 mg m-3 respectively. The HYPERMAQ dataset is composed of biogeochemical parameters (i.e. turbidity, suspended particulate matter, chlorophyll-a and other phytoplankton pigments concentrations), apparent optical properties (i.e. water reflectance from above water measurements) and inherent optical properties (i.e. absorption and attenuation coefficients) from six different study areas. These study areas include large estuaries (i.e. the Rio de la Plata in Argentina, the Yangtze Estuary in China and the Gironde Estuary in France), inland waters (i.e. the Spuikom in Belgium and Chascomus Lake in Argentina) and coastal waters (Belgium). All data were collected between April and September 2018.
    Keywords: chlorophyll-a concentration; HYPERMAQ; Hyperspectral and multi-mission high resolution optical remote sensing of aquatic environments; inherent optical properties; LifeWatch_BE; LifeWatch BE; optically complex waters; radiometry; Suspended particulate matter; turbidity; water reflectance
    Type: Dataset
    Format: application/zip, 11 datasets
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  • 8
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    Water reflectance standard deviation from six different study areas (in Argentina, China, France and Belgium) measured with TRiOS (2022)
    PANGAEA
    Details
    Publication Date: 2023-08-07
    Keywords: BELGIUM_WATERS_APRIL2018; BELGIUM_WATERS_APRIL2018_ST130; BELGIUM_WATERS_APRIL2018_ST215; BELGIUM_WATERS_APRIL2018_ST230; BELGIUM_WATERS_APRIL2018_ST330; BELGIUM_WATERS_APRIL2018_ST700; BELGIUM_WATERS_APRIL2018_ST710; BELGIUM_WATERS_APRIL2018_ST780; BELGIUM_WATERS_APRIL2018_W07BIS; BELGIUM_WATERS_JULY2018; BELGIUM_WATERS_JULY2018_LW_120; BELGIUM_WATERS_JULY2018_LW_130; BELGIUM_WATERS_JULY2018_LW_215; BELGIUM_WATERS_JULY2018_LW_230; BELGIUM_WATERS_JULY2018_LW_330; BELGIUM_WATERS_JULY2018_LW_700; BELGIUM_WATERS_JULY2018_LW_710; BELGIUM_WATERS_JULY2018_LW_780; BELGIUM_WATERS_JULY2018_LW_Harbour; BELGIUM_WATERS_JULY2018_LW_ZG02; Campaign; CHASCOMUS; CHASCOMUS_C01; CHASCOMUS_C02; CHASCOMUS_C03; CHASCOMUS_C04; CHASCOMUS_C05; chlorophyll-a concentration; DATE/TIME; DEPTH, water; Event label; HYP_0001; HYP_0002; HYP_0003; HYP_0004; HYP_0005; HYP_0006; HYP_0007; HYP_0008; HYP_0010; HYP_0011; HYP_0012; HYP_0013; HYP_0014; HYP_0015; HYP_0016; HYP_0017; HYP_0018; HYP_0019; HYP_0020; HYP_0021; HYP_0022; HYP_0023; HYP_0024; HYP_0081; HYP_0082; HYP_0083; HYP_0084; HYP_0085; HYP_0086; HYP_0087; HYP_0088; HYP_0089; HYP_0090; HYP_0091; HYP_0094; HYP_0095; HYP_0096; HYP_0097; HYP_0098; HYP_0099; HYP_0100; HYP_0101; HYP_0102; HYP_0103; HYP_0104; HYP_0105; HYP_0106; HYP_0107; HYP_0108; HYP_0109; HYP_0110; HYP_0111; HYP_0112; HYP_0113; HYP_0114; HYP_0115; HYP_0117; HYP_0118; HYP_0119; HYP_0120; HYP_0121; HYP_0122; HYP_0123; HYP_0124; HYP_0125; HYP_0126; HYP_0127; HYP_0128; HYP_0129; HYP_0130; HYP_0131; HYP_0132; HYP_0133; HYP_0134; HYP_0135; HYP_0136; HYP_0137; HYP_0138; HYP_0139; HYP_0140; HYP_0141; HYP_0142; HYP_0143; HYP_0144; HYP_0145; HYP_0146; HYP_0153; HYP_0155; HYP_0157; HYP_0158; HYP_0159; HYP_0160; HYP_0161; HYP_0162; HYP_0163; HYP_0164; HYP_0165; HYP_0166; HYP_0167; HYP_0168; HYP_0169; HYP_0170; HYP_0171; HYP_0172; HYP_0173; HYP_0174; HYP_0175; HYP_0176; HYP_0177; HYP_0178; HYP_0179; HYPERMAQ; Hyperspectral and multi-mission high resolution optical remote sensing of aquatic environments; Identification; inherent optical properties; LATITUDE; LE_VERDON; LE_VERDON_GG14; LE_VERDON_GG15; LE_VERDON_GG16; LE_VERDON_GG17; LE_VERDON_GG18; LE_VERDON_GG19; LE_VERDON_GG20; LE_VERDON_GG21; LE_VERDON_GG22; LE_VERDON_GG23; LE_VERDON_GG24; LE_VERDON_GG41; LE_VERDON_GG42; LE_VERDON_GG43; LE_VERDON_GG44; LE_VERDON_GG45; LE_VERDON_GG46; LE_VERDON_GG47; LE_VERDON_GG48; LE_VERDON_GG49; LE_VERDON_GG50; LE_VERDON_GG51; LifeWatch_BE; LifeWatch BE; LONGITUDE; MULT; Multiple investigations; optically complex waters; PAUILLAC; PAUILLAC_GG01; PAUILLAC_GG02; PAUILLAC_GG03; PAUILLAC_GG04; PAUILLAC_GG05; PAUILLAC_GG06; PAUILLAC_GG07; PAUILLAC_GG08; PAUILLAC_GG09; PAUILLAC_GG10; PAUILLAC_GG11; PAUILLAC_GG25; PAUILLAC_GG26; PAUILLAC_GG27; PAUILLAC_GG28; PAUILLAC_GG29; PAUILLAC_GG30; PAUILLAC_GG31; PAUILLAC_GG32; PAUILLAC_GG33; PAUILLAC_GG34; PAUILLAC_GG35; PAUILLAC_GG36; PAUILLAC_GG37; PAUILLAC_GG38; Radiometer, TriOS; radiometry; RIO_DE_LA_PLATA; RIO_DE_LA_PLATA_P01; RIO_DE_LA_PLATA_P02; RIO_DE_LA_PLATA_P03; RIO_DE_LA_PLATA_P04; RIO_DE_LA_PLATA_P05; RIO_DE_LA_PLATA_P06; RIO_DE_LA_PLATA_P07; RIO_DE_LA_PLATA_P08; RIO_DE_LA_PLATA_P09; RIO_DE_LA_PLATA_P10; RIO_DE_LA_PLATA_P11; RIO_DE_LA_PLATA_P12; RIO_DE_LA_PLATA_P13; RIO_DE_LA_PLATA_P14; RIO_DE_LA_PLATA_P15; RIO_DE_LA_PLATA_P16; Rubber boat; Sampling on land; Simon Stevin; SPUIKOM_APRIL2018; SPUIKOM_APRIL2018_SP38; SPUIKOM_APRIL2018_SP39b; SPUIKOM_APRIL2018_SP40b; SPUIKOM_APRIL2018_SP41; SPUIKOM_APRIL2018_SP42; SPUIKOM_APRIL2018_SP43; SPUIKOM_APRIL2018_SP44; SPUIKOM_JULY2018; SPUIKOM_JULY2018_SP50; SPUIKOM_JULY2018_SP51; SPUIKOM_JULY2018_SP52; SPUIKOM_JULY2018_SP53; SPUIKOM_JULY2018_SP54; SPUIKOM_JULY2018_SP55; SPUIKOM_JULY2018_SP56; SPUIKOM_JULY2018_SP57; SPUIKOM_JULY2018_SP58; SPUIKOM_JULY2018_SP59; SPUIKOM_JULY2018_SP60; SPUIKOM_JULY2018_SP62; SPUIKOM_JULY2018_SP63; SPUIKOM_JULY2018_SP64; SPUIKOM_JULY2018_SP65; SPUIKOM_JULY2018_SP66; SPUIKOM_JULY2018_SP67; SPUIKOM_JULY2018_SP68; Station label; Suspended particulate matter; turbidity; water reflectance; Water reflectance at 350 nm, standard deviation; Water reflectance at 352.5 nm, standard deviation; Water reflectance at 355 nm, standard deviation; Water reflectance at 357.5 nm, standard deviation; Water reflectance at 360 nm, standard deviation; Water reflectance at 362.5 nm, standard deviation; Water reflectance at 365 nm, standard deviation; Water reflectance at 367.5 nm, standard deviation; Water reflectance at 370 nm, standard deviation; Water reflectance at 372.5 nm, standard deviation; Water reflectance at 375 nm, standard deviation; Water reflectance at 377.5 nm, standard deviation; Water reflectance at 380 nm, standard deviation; Water reflectance at 382.5 nm, standard deviation; Water reflectance at 385 nm, standard deviation; Water reflectance at 387.5 nm, standard deviation; Water reflectance at 390 nm, standard deviation; Water reflectance at 392.5 nm, standard deviation; Water reflectance at 395 nm, standard deviation; Water reflectance at 397.5 nm, standard deviation; Water reflectance at 400 nm, standard deviation; Water reflectance at 402.5 nm, standard deviation; Water reflectance at 405 nm, standard deviation; Water reflectance at 407.5 nm, standard deviation; Water reflectance at 410 nm, standard deviation; Water reflectance at 412.5 nm, standard deviation; Water reflectance at 415 nm, standard deviation; Water reflectance at 417.5 nm, standard deviation; Water reflectance at 420 nm, standard deviation; Water reflectance at 422.5 nm, standard deviation; Water reflectance at 425 nm, standard deviation; Water reflectance at 427.5 nm, standard deviation; Water reflectance at 430 nm, standard deviation; Water reflectance at 432.5 nm, standard deviation; Water reflectance at 435 nm, standard deviation; Water reflectance at 437.5 nm, standard deviation; Water reflectance at 440 nm, standard deviation; Water reflectance at 442.5 nm, standard deviation; Water reflectance at 445 nm, standard deviation; Water reflectance at 447.5 nm, standard deviation; Water reflectance at 450 nm, standard deviation; Water reflectance at 452.5 nm, standard deviation; Water reflectance at 455 nm, standard deviation; Water reflectance at 457.5 nm, standard deviation; Water reflectance at 460 nm, standard deviation; Water reflectance at 462.5 nm, standard deviation; Water reflectance at 465 nm, standard deviation; Water reflectance at 467.5 nm, standard deviation; Water reflectance at 470 nm, standard deviation; Water reflectance at 472.5 nm, standard deviation; Water reflectance at 475 nm, standard deviation; Water reflectance at 477.5 nm, standard deviation; Water reflectance at 480 nm, standard deviation; Water reflectance at 482.5 nm, standard deviation; Water reflectance at 485 nm, standard deviation; Water reflectance at 487.5 nm, standard deviation; Water reflectance at 490 nm, standard deviation; Water reflectance at 492.5 nm, standard deviation; Water reflectance at 495 nm, standard deviation; Water reflectance at 497.5 nm, standard deviation; Water reflectance at 500 nm, standard deviation; Water reflectance at 502.5 nm, standard deviation; Water reflectance at 505 nm, standard deviation; Water reflectance at 507.5 nm, standard deviation; Water reflectance at 510 nm, standard deviation; Water reflectance at 512.5 nm, standard deviation; Water reflectance at 515 nm, standard deviation; Water reflectance at 517.5 nm, standard deviation; Water reflectance at 520 nm, standard deviation; Water reflectance at 522.5 nm, standard deviation; Water reflectance at 525 nm, standard deviation; Water reflectance at 527.5 nm, standard deviation; Water reflectance at 530 nm, standard deviation; Water reflectance at 532.5 nm, standard deviation; Water reflectance at 535 nm, standard deviation; Water reflectance at 537.5 nm, standard deviation; Water reflectance at 540 nm, standard deviation; Water reflectance at 542.5 nm, standard deviation; Water reflectance at 545 nm, standard deviation; Water
    Type: Dataset
    Format: text/tab-separated-values, 20223 data points
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    DATA PANGAEA
  • 9
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    Spectral downwelling irradiance from six different study areas (in Argentina, China, France and Belgium) measured with TRiOS (2022)
    PANGAEA
    Details
    Publication Date: 2023-08-07
    Keywords: BELGIUM_WATERS_APRIL2018; BELGIUM_WATERS_APRIL2018_ST130; BELGIUM_WATERS_APRIL2018_ST215; BELGIUM_WATERS_APRIL2018_ST230; BELGIUM_WATERS_APRIL2018_ST330; BELGIUM_WATERS_APRIL2018_ST700; BELGIUM_WATERS_APRIL2018_ST710; BELGIUM_WATERS_APRIL2018_ST780; BELGIUM_WATERS_APRIL2018_W07BIS; BELGIUM_WATERS_JULY2018; BELGIUM_WATERS_JULY2018_LW_120; BELGIUM_WATERS_JULY2018_LW_130; BELGIUM_WATERS_JULY2018_LW_215; BELGIUM_WATERS_JULY2018_LW_230; BELGIUM_WATERS_JULY2018_LW_330; BELGIUM_WATERS_JULY2018_LW_700; BELGIUM_WATERS_JULY2018_LW_710; BELGIUM_WATERS_JULY2018_LW_780; BELGIUM_WATERS_JULY2018_LW_Harbour; BELGIUM_WATERS_JULY2018_LW_ZG02; Campaign; CHASCOMUS; CHASCOMUS_C01; CHASCOMUS_C02; CHASCOMUS_C03; CHASCOMUS_C04; CHASCOMUS_C05; chlorophyll-a concentration; DATE/TIME; Event label; HYP_0001; HYP_0002; HYP_0003; HYP_0004; HYP_0005; HYP_0006; HYP_0007; HYP_0008; HYP_0010; HYP_0011; HYP_0012; HYP_0013; HYP_0014; HYP_0015; HYP_0016; HYP_0017; HYP_0018; HYP_0019; HYP_0020; HYP_0021; HYP_0022; HYP_0023; HYP_0024; HYP_0081; HYP_0082; HYP_0083; HYP_0084; HYP_0085; HYP_0086; HYP_0087; HYP_0088; HYP_0089; HYP_0090; HYP_0091; HYP_0094; HYP_0095; HYP_0096; HYP_0097; HYP_0098; HYP_0099; HYP_0100; HYP_0101; HYP_0102; HYP_0103; HYP_0104; HYP_0105; HYP_0106; HYP_0107; HYP_0108; HYP_0109; HYP_0110; HYP_0111; HYP_0112; HYP_0113; HYP_0114; HYP_0115; HYP_0117; HYP_0118; HYP_0119; HYP_0120; HYP_0121; HYP_0122; HYP_0123; HYP_0124; HYP_0125; HYP_0126; HYP_0127; HYP_0128; HYP_0129; HYP_0130; HYP_0131; HYP_0132; HYP_0133; HYP_0134; HYP_0135; HYP_0136; HYP_0137; HYP_0138; HYP_0139; HYP_0140; HYP_0141; HYP_0142; HYP_0143; HYP_0144; HYP_0145; HYP_0146; HYP_0153; HYP_0155; HYP_0157; HYP_0158; HYP_0159; HYP_0160; HYP_0161; HYP_0162; HYP_0163; HYP_0164; HYP_0165; HYP_0166; HYP_0167; HYP_0168; HYP_0169; HYP_0170; HYP_0171; HYP_0172; HYP_0173; HYP_0174; HYP_0175; HYP_0176; HYP_0177; HYP_0178; HYP_0179; HYPERMAQ; Hyperspectral and multi-mission high resolution optical remote sensing of aquatic environments; Identification; inherent optical properties; LATITUDE; LE_VERDON; LE_VERDON_GG14; LE_VERDON_GG15; LE_VERDON_GG16; LE_VERDON_GG17; LE_VERDON_GG18; LE_VERDON_GG19; LE_VERDON_GG20; LE_VERDON_GG21; LE_VERDON_GG22; LE_VERDON_GG23; LE_VERDON_GG24; LE_VERDON_GG41; LE_VERDON_GG42; LE_VERDON_GG43; LE_VERDON_GG44; LE_VERDON_GG45; LE_VERDON_GG46; LE_VERDON_GG47; LE_VERDON_GG48; LE_VERDON_GG49; LE_VERDON_GG50; LE_VERDON_GG51; LifeWatch_BE; LifeWatch BE; LONGITUDE; MULT; Multiple investigations; optically complex waters; PAUILLAC; PAUILLAC_GG01; PAUILLAC_GG02; PAUILLAC_GG03; PAUILLAC_GG04; PAUILLAC_GG05; PAUILLAC_GG06; PAUILLAC_GG07; PAUILLAC_GG08; PAUILLAC_GG09; PAUILLAC_GG10; PAUILLAC_GG11; PAUILLAC_GG25; PAUILLAC_GG26; PAUILLAC_GG27; PAUILLAC_GG28; PAUILLAC_GG29; PAUILLAC_GG30; PAUILLAC_GG31; PAUILLAC_GG32; PAUILLAC_GG33; PAUILLAC_GG34; PAUILLAC_GG35; PAUILLAC_GG36; PAUILLAC_GG37; PAUILLAC_GG38; Radiometer, TriOS; radiometry; RIO_DE_LA_PLATA; RIO_DE_LA_PLATA_P01; RIO_DE_LA_PLATA_P02; RIO_DE_LA_PLATA_P03; RIO_DE_LA_PLATA_P04; RIO_DE_LA_PLATA_P05; RIO_DE_LA_PLATA_P06; RIO_DE_LA_PLATA_P07; RIO_DE_LA_PLATA_P08; RIO_DE_LA_PLATA_P09; RIO_DE_LA_PLATA_P10; RIO_DE_LA_PLATA_P11; RIO_DE_LA_PLATA_P12; RIO_DE_LA_PLATA_P13; RIO_DE_LA_PLATA_P14; RIO_DE_LA_PLATA_P15; RIO_DE_LA_PLATA_P16; Rubber boat; Sampling on land; Simon Stevin; Spectral irradiance, downward at 350 nm; Spectral irradiance, downward at 352.5 nm; Spectral irradiance, downward at 355 nm; Spectral irradiance, downward at 357.5 nm; Spectral irradiance, downward at 360 nm; Spectral irradiance, downward at 362.5 nm; Spectral irradiance, downward at 365 nm; Spectral irradiance, downward at 367.5 nm; Spectral irradiance, downward at 370 nm; Spectral irradiance, downward at 372.5 nm; Spectral irradiance, downward at 375 nm; Spectral irradiance, downward at 377.5 nm; Spectral irradiance, downward at 380 nm; Spectral irradiance, downward at 382.5 nm; Spectral irradiance, downward at 385 nm; Spectral irradiance, downward at 387.5 nm; Spectral irradiance, downward at 390 nm; Spectral irradiance, downward at 392.5 nm; Spectral irradiance, downward at 395 nm; Spectral irradiance, downward at 397.5 nm; Spectral irradiance, downward at 400 nm; Spectral irradiance, downward at 402.5 nm; Spectral irradiance, downward at 405 nm; Spectral irradiance, downward at 407.5 nm; Spectral irradiance, downward at 410 nm; Spectral irradiance, downward at 412.5 nm; Spectral irradiance, downward at 415 nm; Spectral irradiance, downward at 417.5 nm; Spectral irradiance, downward at 420 nm; Spectral irradiance, downward at 422.5 nm; Spectral irradiance, downward at 425 nm; Spectral irradiance, downward at 427.5 nm; Spectral irradiance, downward at 430 nm; Spectral irradiance, downward at 432.5 nm; Spectral irradiance, downward at 435 nm; Spectral irradiance, downward at 437.5 nm; Spectral irradiance, downward at 440 nm; Spectral irradiance, downward at 442.5 nm; Spectral irradiance, downward at 445 nm; Spectral irradiance, downward at 447.5 nm; Spectral irradiance, downward at 450 nm; Spectral irradiance, downward at 452.5 nm; Spectral irradiance, downward at 455 nm; Spectral irradiance, downward at 457.5 nm; Spectral irradiance, downward at 460 nm; Spectral irradiance, downward at 462.5 nm; Spectral irradiance, downward at 465 nm; Spectral irradiance, downward at 467.5 nm; Spectral irradiance, downward at 470 nm; Spectral irradiance, downward at 472.5 nm; Spectral irradiance, downward at 475 nm; Spectral irradiance, downward at 477.5 nm; Spectral irradiance, downward at 480 nm; Spectral irradiance, downward at 482.5 nm; Spectral irradiance, downward at 485 nm; Spectral irradiance, downward at 487.5 nm; Spectral irradiance, downward at 490 nm; Spectral irradiance, downward at 492.5 nm; Spectral irradiance, downward at 495 nm; Spectral irradiance, downward at 497.5 nm; Spectral irradiance, downward at 500 nm; Spectral irradiance, downward at 502.5 nm; Spectral irradiance, downward at 505 nm; Spectral irradiance, downward at 507.5 nm; Spectral irradiance, downward at 510 nm; Spectral irradiance, downward at 512.5 nm; Spectral irradiance, downward at 515 nm; Spectral irradiance, downward at 517.5 nm; Spectral irradiance, downward at 520 nm; Spectral irradiance, downward at 522.5 nm; Spectral irradiance, downward at 525 nm; Spectral irradiance, downward at 527.5 nm; Spectral irradiance, downward at 530 nm; Spectral irradiance, downward at 532.5 nm; Spectral irradiance, downward at 535 nm; Spectral irradiance, downward at 537.5 nm; Spectral irradiance, downward at 540 nm; Spectral irradiance, downward at 542.5 nm; Spectral irradiance, downward at 545 nm; Spectral irradiance, downward at 547.5 nm; Spectral irradiance, downward at 550 nm; Spectral irradiance, downward at 552.5 nm; Spectral irradiance, downward at 555 nm; Spectral irradiance, downward at 557.5 nm; Spectral irradiance, downward at 560 nm; Spectral irradiance, downward at 562.5 nm; Spectral irradiance, downward at 565 nm; Spectral irradiance, downward at 567.5 nm; Spectral irradiance, downward at 570 nm; Spectral irradiance, downward at 572.5 nm; Spectral irradiance, downward at 575 nm; Spectral irradiance, downward at 577.5 nm; Spectral irradiance, downward at 580 nm; Spectral irradiance, downward at 582.5 nm; Spectral irradiance, downward at 585 nm; Spectral irradiance, downward at 587.5 nm; Spectral irradiance, downward at 590 nm; Spectral irradiance, downward at 592.5 nm; Spectral irradiance, downward at 595 nm; Spectral irradiance, downward at 597.5 nm; Spectral irradiance, downward at 600 nm; Spectral irradiance, downward at 602.5 nm; Spectral irradiance, downward at 605 nm; Spectral irradiance, downward at 607.5 nm; Spectral irradiance, downward at 610 nm; Spectral irradiance, downward at 612.5 nm; Spectral irradiance, downward at 615 nm; Spectral irradiance, downward at 617.5 nm; Spectral irradiance, downward at 620 nm; Spectral irradiance, downward at 622.5 nm; Spectral irradiance, downward at 625 nm; Spectral
    Type: Dataset
    Format: text/tab-separated-values, 24864 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 10
    facet.materialart.
    Unknown
    Measurements of turbidity, chlorophyll-a, suspended particulate matter and suspended particulate inorganic matter in six different study areas (in Argentina, China, France and Belgium) (2022)
    PANGAEA
    Details
    Publication Date: 2023-08-07
    Keywords: BAOZHEN; BAOZHEN_0604S1; BAOZHEN_0604S2; BAOZHEN_0604S3; BAOZHEN_0604S4; BAOZHEN_0604S5; BAOZHEN_0605S1; BAOZHEN_0605S2; BAOZHEN_0605S3; BAOZHEN_0605S4; BAOZHEN_0605S5; BAOZHEN_0605S6; BAOZHEN_0605S7; BAOZHEN_0605S8; BAOZHEN_0606S1; BAOZHEN_0606S2; BAOZHEN_0606S3; BAOZHEN_0606S4; BAOZHEN_0606S5; BAOZHEN_0606S6; BAOZHEN_0606S7; BAOZHEN_0606S8; BAOZHEN_0607S1; BAOZHEN_0607S2; BAOZHEN_0607S3; BAOZHEN_0607S4; BAOZHEN_0607S5; BAOZHEN_0607S6; BAOZHEN_0607S7; BAOZHEN_0607S8; BAOZHEN_0608S1; BAOZHEN_0608S2; BAOZHEN_0608S3; BAOZHEN_0608S4; BAOZHEN_0608S5; BAOZHEN_0608S6; BAOZHEN_0608S7; BAOZHEN_0608S8; BELGIUM_WATERS_APRIL2018; BELGIUM_WATERS_APRIL2018_ST130; BELGIUM_WATERS_APRIL2018_ST215; BELGIUM_WATERS_APRIL2018_ST230; BELGIUM_WATERS_APRIL2018_ST330; BELGIUM_WATERS_APRIL2018_ST700; BELGIUM_WATERS_APRIL2018_ST710; BELGIUM_WATERS_APRIL2018_ST780; BELGIUM_WATERS_APRIL2018_W07BIS; BELGIUM_WATERS_APRIL2018_ZG02; BELGIUM_WATERS_JULY2018; BELGIUM_WATERS_JULY2018_LW_120; BELGIUM_WATERS_JULY2018_LW_130; BELGIUM_WATERS_JULY2018_LW_215; BELGIUM_WATERS_JULY2018_LW_230; BELGIUM_WATERS_JULY2018_LW_330; BELGIUM_WATERS_JULY2018_LW_700; BELGIUM_WATERS_JULY2018_LW_710; BELGIUM_WATERS_JULY2018_LW_780; BELGIUM_WATERS_JULY2018_LW_Harbour; BELGIUM_WATERS_JULY2018_LW_ZG02; Campaign; CHASCOMUS; CHASCOMUS_C01; CHASCOMUS_C02; CHASCOMUS_C03; CHASCOMUS_C04; CHASCOMUS_C05; Chlorophyll a; chlorophyll-a concentration; CHONGXI; CHONGXI_0531S1; CHONGXI_0531S2; CHONGXI_0601S1; CHONGXI_0601S2; CHONGXI_0601S3; CHONGXI_0601S4; CHONGXI_0601S5; CHONGXI_0601S6; CHONGXI_0601S7; CHONGXI_0601S8; CHONGXI_0603S1; CHONGXI_0603S2; CHONGXI_0603S3; CHONGXI_0603S4; CHONGXI_0603S5; CHONGXI_0603S6; CHONGXI_0603S7; CHONGXI_0603S8; DATE/TIME; DEPTH, water; Event label; HYP_0001; HYP_0002; HYP_0003; HYP_0004; HYP_0005; HYP_0006; HYP_0007; HYP_0008; HYP_0009; HYP_0010; HYP_0011; HYP_0012; HYP_0013; HYP_0014; HYP_0015; HYP_0016; HYP_0017; HYP_0018; HYP_0019; HYP_0020; HYP_0021; HYP_0022; HYP_0023; HYP_0024; HYP_0025; HYP_0026; HYP_0027; HYP_0028; HYP_0029; HYP_0030; HYP_0031; HYP_0032; HYP_0033; HYP_0034; HYP_0035; HYP_0036; HYP_0037; HYP_0038; HYP_0039; HYP_0040; HYP_0041; HYP_0042; HYP_0043; HYP_0044; HYP_0045; HYP_0046; HYP_0047; HYP_0048; HYP_0049; HYP_0050; HYP_0051; HYP_0052; HYP_0053; HYP_0054; HYP_0055; HYP_0056; HYP_0057; HYP_0058; HYP_0059; HYP_0060; HYP_0061; HYP_0062; HYP_0063; HYP_0064; HYP_0065; HYP_0066; HYP_0067; HYP_0068; HYP_0069; HYP_0070; HYP_0071; HYP_0072; HYP_0073; HYP_0074; HYP_0075; HYP_0076; HYP_0077; HYP_0078; HYP_0079; HYP_0080; HYP_0081; HYP_0082; HYP_0083; HYP_0084; HYP_0085; HYP_0086; HYP_0087; HYP_0088; HYP_0089; HYP_0090; HYP_0091; HYP_0092; HYP_0093; HYP_0094; HYP_0095; HYP_0096; HYP_0097; HYP_0098; HYP_0099; HYP_0100; HYP_0101; HYP_0102; HYP_0103; HYP_0104; HYP_0105; HYP_0106; HYP_0107; HYP_0108; HYP_0109; HYP_0110; HYP_0111; HYP_0112; HYP_0113; HYP_0114; HYP_0115; HYP_0116; HYP_0117; HYP_0118; HYP_0119; HYP_0120; HYP_0121; HYP_0122; HYP_0123; HYP_0124; HYP_0125; HYP_0126; HYP_0127; HYP_0128; HYP_0129; HYP_0130; HYP_0131; HYP_0132; HYP_0133; HYP_0134; HYP_0135; HYP_0136; HYP_0137; HYP_0138; HYP_0139; HYP_0140; HYP_0141; HYP_0142; HYP_0143; HYP_0144; HYP_0145; HYP_0146; HYP_0147; HYP_0148; HYP_0149; HYP_0150; HYP_0151; HYP_0152; HYP_0153; HYP_0154; HYP_0155; HYP_0156; HYP_0157; HYP_0158; HYP_0159; HYP_0160; HYP_0161; HYP_0162; HYP_0163; HYP_0164; HYP_0165; HYP_0166; HYP_0167; HYP_0168; HYP_0169; HYP_0170; HYP_0171; HYP_0172; HYP_0173; HYP_0174; HYP_0175; HYP_0176; HYP_0177; HYP_0178; HYP_0179; HYPERMAQ; Hyperspectral and multi-mission high resolution optical remote sensing of aquatic environments; Identification; inherent optical properties; LATITUDE; LE_VERDON; LE_VERDON_GG13; LE_VERDON_GG14; LE_VERDON_GG15; LE_VERDON_GG16; LE_VERDON_GG17; LE_VERDON_GG18; LE_VERDON_GG19; LE_VERDON_GG20; LE_VERDON_GG21; LE_VERDON_GG22; LE_VERDON_GG23; LE_VERDON_GG24; LE_VERDON_GG39; LE_VERDON_GG40; LE_VERDON_GG41; LE_VERDON_GG42; LE_VERDON_GG43; LE_VERDON_GG44; LE_VERDON_GG45; LE_VERDON_GG46; LE_VERDON_GG47; LE_VERDON_GG48; LE_VERDON_GG49; LE_VERDON_GG50; LE_VERDON_GG51; LifeWatch_BE; LifeWatch BE; LONGITUDE; MULT; Multiple investigations; optically complex waters; PAUILLAC; PAUILLAC_GG01; PAUILLAC_GG02; PAUILLAC_GG03; PAUILLAC_GG04; PAUILLAC_GG05; PAUILLAC_GG06; PAUILLAC_GG07; PAUILLAC_GG08; PAUILLAC_GG09; PAUILLAC_GG10; PAUILLAC_GG11; PAUILLAC_GG12; PAUILLAC_GG25; PAUILLAC_GG26; PAUILLAC_GG27; PAUILLAC_GG28; PAUILLAC_GG29; PAUILLAC_GG30; PAUILLAC_GG31; PAUILLAC_GG32; PAUILLAC_GG33; PAUILLAC_GG34; PAUILLAC_GG35; PAUILLAC_GG36; PAUILLAC_GG37; PAUILLAC_GG38; radiometry; RIO_DE_LA_PLATA; RIO_DE_LA_PLATA_P01; RIO_DE_LA_PLATA_P02; RIO_DE_LA_PLATA_P03; RIO_DE_LA_PLATA_P04; RIO_DE_LA_PLATA_P05; RIO_DE_LA_PLATA_P06; RIO_DE_LA_PLATA_P07; RIO_DE_LA_PLATA_P08; RIO_DE_LA_PLATA_P09; RIO_DE_LA_PLATA_P10; RIO_DE_LA_PLATA_P11; RIO_DE_LA_PLATA_P12; RIO_DE_LA_PLATA_P13; RIO_DE_LA_PLATA_P14; RIO_DE_LA_PLATA_P15; RIO_DE_LA_PLATA_P16; RIO_DE_LA_PLATA_P17; RIO_DE_LA_PLATA_P18; RIO_DE_LA_PLATA_P19; RIO_DE_LA_PLATA_P20; RIO_DE_LA_PLATA_P21; RIO_DE_LA_PLATA_P22; Rubber boat; Sampling on land; Simon Stevin; SPUIKOM_APRIL2018; SPUIKOM_APRIL2018_SP38; SPUIKOM_APRIL2018_SP39a; SPUIKOM_APRIL2018_SP39b; SPUIKOM_APRIL2018_SP40a; SPUIKOM_APRIL2018_SP40b; SPUIKOM_APRIL2018_SP41; SPUIKOM_APRIL2018_SP42; SPUIKOM_APRIL2018_SP43; SPUIKOM_APRIL2018_SP44; SPUIKOM_JULY2018; SPUIKOM_JULY2018_SP50; SPUIKOM_JULY2018_SP51; SPUIKOM_JULY2018_SP52; SPUIKOM_JULY2018_SP53; SPUIKOM_JULY2018_SP54; SPUIKOM_JULY2018_SP55; SPUIKOM_JULY2018_SP56; SPUIKOM_JULY2018_SP57; SPUIKOM_JULY2018_SP58; SPUIKOM_JULY2018_SP59; SPUIKOM_JULY2018_SP60; SPUIKOM_JULY2018_SP62; SPUIKOM_JULY2018_SP63; SPUIKOM_JULY2018_SP64; SPUIKOM_JULY2018_SP65; SPUIKOM_JULY2018_SP66; SPUIKOM_JULY2018_SP67; SPUIKOM_JULY2018_SP68; Station label; Suspended particulate inorganic matter; Suspended particulate inorganic matter, standard deviation; Suspended particulate matter; Suspended particulate matter, standard deviation; turbidity; Turbidity, standard deviation; Turbidity (Formazin Backscatter Unit); Turbidity (Formazin nephelometric unit); Turbidity meter, HACH, portable; Turbidity meter, OBS501; water reflectance
    Type: Dataset
    Format: text/tab-separated-values, 1765 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
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