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  • 1
    Keywords: Ecology Mathematical models ; R (Computer program language) ; Computersimulation ; R ; Ökologie ; Modellierung
    Description / Table of Contents: Many texts on ecological models jump to describing either particular relations or computational results, without treating in detail the conceptual and mathematical basis of many steps in modelling: why set up models, what are basic conceptual models, how do conservation laws come in, how are models solved, what are steady states. This book is intended to bridge this gap. It is intended as an introductory text for graduate and post-graduate students, but also as a help for experienced ecologists who want to make more of their data by modelling. It contains many examples, all worked out in the open-source package R, providing the reader the opportunity to practice all methods and get hands-on experience. Audience: This book will be of interest to advanced undergraduate and graduate students in ecology, biology, geology, bio-engineering, and to some extent students from physics and chemistry
    Type of Medium: Book
    Pages: XV, 372 S. , graph. Darst. , 235 mm x 155 mm
    ISBN: 9781402086236
    DDC: 577.015118
    RVK:
    RVK:
    Language: English
    Note: Literaturverz. S. 361 - 365
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  • 2
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    PANGAEA
    In:  Supplement to: Aldridge, John N; Bergman, Magda J N; Bolam, T; Craeymeersch, Johan A; Degraer, Steven; Duineveld, Gerard C A; Eggleton, J D; Goethals, P; Hillewaert, H; Irion, G; Kershaw, P J; Kröncke, Ingrid; Lavaleye, Marc; Mason, Claire; Rachor, Eike; Rees, H L; Reiss, Henning; Rumohr, Heye; Schratzberger, M; Smith, R; Vanden Berghe, E; van Hoey, G; Vincx, Magda; Willems, W (2007): Structure and dynamics of the North Sea benthos. Ices Cooperative Research Report-Rapport des Recherches Collectives, 288, 265 pp, hdl:10013/epic.34479.d001
    Publication Date: 2023-08-05
    Description: In 1986 participants of the Benthos Ecology Working Group of ICES conducted a synoptic mapping of the infauna of the southern and central North Sea. Together with a mapping of the infauna of the northern North Sea by Eleftheriou and Basford (1989, doi:10.1017/S0025315400049158) this provides the database for the description of the benthic infauna of the whole North Sea in this paper. Division of the infauna into assemblages by TWINSPAN analysis separated northern assemblages from southern assemblages along the 70 m depth contour. Assemblages were further separated by the 30, 50 m and 100 m depth contour as well as by the sediment type. In addition to widely distributed species, cold water species do not occur further south than the northern edge of the Dogger Bank, which corresponds to the 50 m depth contour. Warm water species were not found north of the 100 m depth contour. Some species occur on all types of sediment but most are restricted to a special sediment and therefore these species are limited in their distribution. The factors structuring species distributions and assemblages seem to be temperature, the influence of different water masses, e.g. Atlantic water, the type of sediment and the food supply to the benthos.
    Keywords: ICES 100; ICES 110; ICES 118; ICES 125; ICES 126; ICES 127; ICES 128; ICES 129; ICES 130; ICES 131; ICES 137; ICES 138; ICES 139; ICES 140; ICES 141; ICES 147; ICES 148; ICES 149; ICES 150; ICES 151; ICES 152; ICES 158; ICES 159; ICES 160; ICES 161; ICES 162; ICES 163; ICES 168; ICES 169; ICES 170; ICES 171; ICES 172; ICES 173; ICES 55; ICES 63; ICES 72; ICES 81; ICES 90; MarGIS_DANS_Label: ICES8586BSe_8; North Sea; van Veen Grab; VGRAB; VH1486; VH1486_055; VH1486_063; VH1486_072; VH1486_081; VH1486_090; VH1486_100; VH1486_110; VH1486_118; VH1486_125; VH1486_126; VH1486_127; VH1486_128; VH1486_129; VH1486_130; VH1486_131; VH1486_137; VH1486_138; VH1486_139; VH1486_140; VH1486_141; VH1486_147; VH1486_148; VH1486_149; VH1486_150; VH1486_151; VH1486_152; VH1486_158; VH1486_159; VH1486_160; VH1486_161; VH1486_162; VH1486_163; VH1486_168; VH1486_169; VH1486_170; VH1486_171; VH1486_172; VH1486_173; Victor Hensen; xxxVH1486_091; xxxVH1486_101; xxxVH1486_111; xxxVH1486_124; xxxVH1486_165; xxxVH1486_175; xxxVH1486_177; xxxVH1486_179; xxxVH1486_181; xxxVH1486_184; xxxVH1486_186; xxxVH1486_189; xxxVH1486_192; xxxVH1486_194; xxxVH1486_196; xxxVH1486_199; xxxVH1486_201; xxxVH1486_202; xxxVH1486_205; xxxVH1486_208; xxxVH1486_209; xxxVH1486_210; xxxVH1486_212; xxxVH1486_215; xxxVH1486_217; xxxVH1486_220; xxxVH1486_221; xxxVH1486_222; xxxVH1486_223; xxxVH1486_226; xxxVH1486_227; xxxVH1486_230; xxxVH1486_233; xxxVH1486_234; xxxVH1486_235
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 3
    Publication Date: 2023-08-05
    Keywords: Abra alba; Abra nitida; Abra prismatica; Acanthocardia echinata; Acidostoma obesum; Acidostoma sarsi; Acrenhydrosoma perplexum; Acrocnida brachiata; Acteon tornatilis; Ameira brevipes; Ameira parvula; Ameira pusilla; Ameira sp.; Ameiropsis brevicornis; Ameiropsis mixta; Ampelisca brevicornis; Ampelisca diadema; Ampelisca macrocephala; Ampelisca spinipes; Ampelisca tenuicornis; Ampelisca typica; Ampharete; Ampharete baltica; Ampharete falcata; Ampharete finmarchica; Amphicteis gunneri; Amphictene auricoma; Amphitrite cirrata; Amphiura chiajei; Amphiura filiformis; Anaitides; Anaitides groenlandica; Anaitides longipes; Anaitides mucosa; Anaitides rosea; Anobothrus gracilis; Antalis entalis; Anthozoa; Antinoella sarsi; Aonides paucibranchiata; Aoridae; Apherusa ovalipes; Aphrodita aculeata; Arctica islandica; Arenocaris bifida; Arenosetella germanica; Arenosetella sp.; Aricidea catherinae; Aricidea cerrutii; Aricidea simonae; Armina loveni; Ascidiacea; Asellopsis intermedia; Astarte sulcata; Bathyporeia elegans; Bathyporeia tenuipes; Brachyura; Brada villosa; Bradya scotti; Bradya typica; Brissopsis lyrifera; Bulbamphiascus imus; Bulbamphiascus sp.; Byblis gaimardi; Callianassa subterranea; Campylaspis glabra; Campylaspis rubicunda; Canuella perplexa; Capitellidae; Chaetoderma nitidulum; Chaetoparia nilssoni; Chaetopterus variopedatus; Chaetozone setosa; Chamelea gallina; Cheirocratus intermedius; Cirratulus cirratus; Cletodes limicola; Cletodes longicaudatus; Cletodes pusillus; Cletodes sp.; Cletodes tenuipes; Cletodidae sp.; Cnidaria; Cochlodesma praetenue; Colus gracilis; Copepoda; Corbula gibba; Corophium crassicorne; Corystes cassivelaunus; Counting; Curveulima macrophthalmica; Cylichna cylindracea; Dactylopusia tisboides; Danielssenia typica; Date/Time of event; DEPTH, sediment/rock; Diastylis boecki; Diastylis bradyi; Diastylis laevis; Diastylis lucifera; Diastylis rathkei; Diplocirrus glaucus; Ditrupa arietina; Dosinia exoleta; Dyopedos monacanthus; Echinocardium cordatum; Echinocardium flavescens; Echinocyamus pusillus; Echiurus echiurus; Eclysippe vanelli; Ectinosoma melaniceps; Ectinosoma normani; Ectinosoma sp.; Ectinosoma tenuipes; Enhydrosoma buchholtzi; Enhydrosoma sp.; Enipo kinbergi; Enteropneusta; Epitonium trevelyanum; Ericthonius difformis; Eriopisa elongata; Eteone flava; Eteone foliosa; Eteone longa; Euclymene; Euclymene droebachiensis; Eudorella emarginata; Eudorella truncatula; Eudorellopsis deformis; Eulima bilineata; Eumida sanguinea; Eusyllis blomstrandi; Euterpina acutifrons; Evansula pygmaea; Event label; Exogone hebes; Exogone verugera; Fabulina fabula; Facelina bostoniensis; Gammaropsis nitida; Gari fervensis; Gastrotricha; Gattyana cirrosa; Glycera; Glycera alba; Glycera celtica; Glycera lapidum; Glycera rouxi; Glycera tridactyla; Glycinde nordmanni; Goniada maculata; Goniada norvegica; Halectinosoma gothiceps; Halectinosoma herdmani; Halectinosoma propinquum; Halectinosoma sarsi; Halectinosoma sp.; Haloschizopera bulbifera; Haloschizopera pygmaea; Haploops tubicola; Harmothoe; Harmothoe antilopes; Harmothoe castanea; Harmothoe glabra; Harmothoe impar; Harmothoe lunulata; Harmothoe mcintoshi; Harpinia antennaria; Harpinia crenulata; Hastigerella sp.; Hemilamprops rosea; Heteroclymene robusta; Heterolaophonte sp.; Heterolaophonte stroemi; Hippomedon denticulatus; Holothurioidea; Hyala vitrea; Hyalinoecia tubicola; Hyas coarctatus; Hydroides norvegica; Hydrozoa; ICES 100; ICES 109; ICES 110; ICES 118; ICES 119; ICES 120; ICES 125; ICES 126; ICES 127; ICES 128; ICES 129; ICES 130; ICES 131; ICES 137; ICES 138; ICES 139; ICES 140; ICES 141; ICES 142; ICES 143; ICES 147; ICES 148; ICES 149; ICES 150; ICES 151; ICES 152; ICES 153; ICES 158; ICES 159; ICES 160; ICES 161; ICES 162; ICES 163; ICES 168; ICES 169; ICES 170; ICES 171; ICES 172; ICES 173; ICES 55; ICES 63; ICES 72; ICES 81; ICES 90; ICES 99; Idyanthe pusilla; Idyella exigua; Idyella major; Idyella pallidula; Idyellopsis typica; Interleptomesochra eulittoralis; Interleptomesochra tenuicornis; Iphimedia obesa; Isopoda; Kinorhyncha; Lagis koreni; Langerhansia cornuta; Lanice conchilega; Laonice cirrata; Laophonte cornuta; Laophonte inornata; Laophonte longicaudata; Latitude of event; Leptastacus laticaudatus; Leptastacus sp.; Leucothoe lilljeborgi; Levinsenia gracilis; Liocarcinus holsatus; Longipedia coronata; Longipedia helgolandica; Longipedia scotti; Longitude of event; Lucinoma borealis; Lumbrineris; Lumbrineris fragilis; Lumbrineris hibernica; Lumbrineris latreilli; Lumbrineris tetraura; Lunatia montagui; Lunatia poliana; Lysilla loveni; Mactra stultorum; Magelona; Magelona alleni; Maldane sarsi; Maldanidae; MarGIS_DANS_Label: ICES8586BSe_8; Megamphopus cornutus; Microphthalmus; Minuspio cirrifera; Molgula; Montacuta substriata; Mya truncata; Myriochele; Mysella bidentata; Nebalia bipes; Nematoda; Nemertea; Neomenia carinata; Nephtys; Nephtys caeca; Nephtys hombergii; Nephtys incisa; Nephtys longosetosa; Nereimyra punctata; Nereiphylla; Nereis zonata; Nicomache; Nicomache lumbricalis; North Sea; Nothria conchylega; Notomastus latericeus; Nucula nitidosa; Nuculoma tenuis; Nyctiphanes couchi; Ophelia borealis; Ophelina acuminata; Ophiodromus flexuosus; Ophiura affinis; Ophiura albida; Ophiura ophiura; Orbinia sertulata; Ostracoda; Owenia fusiformis; Paphia rhomboides; Paralaophonte congenera; Paraleptastacus espinulatus; Paraleptastacus holsaticus; Paraleptastacus spinicauda; Paramphiascoides vararensis; Paramphiascopsis longirostris; Paramphinome jeffreysii; Paramphitrite tetrabranchia; Paranannopus sp.; Parapleustes bicuspis; Parvicardium minimum; Phaxas pellucidus; Philine quadrata; Philine scabra; Philomedes globosus; Pholoe; Phoronis; Photis longicaudata; Photis reinhardi; Phoxocephalus holbolli; Phtisica marina; Pisione remota; Poecilochaetus serpens; Polychaeta; Polydora caulleryi; Polydora ciliata; Polynoidae; Polyphysia crassa; Pontocrates; Pontocrates longimanus; Praxillella affinis; Praxillura longissima; Priapulida; Prionospio malmgreni; Proameira hiddensoensis; Proameira sp.; Protomedeia fasciata; Psammotopa phyllosetosa; Pseudameira crassicornis; Pseudameira perplexa; Pseudameira sp.; Pseudamphiascopsis herdmani; Pseudobradya pulchella; Pseudobradya sp.; Pseudocuma simile; Pseudolaophonte spinosa; Pseudomesochra longifurcata; Pseudomesochra sp.; Pseudonychocamptus proximus; Pseudopolydora cf. pauchibranchiata; Pseudopolydora pulchra; Pseudosarsameira exilis; Pseudotachidius coronatus; Rhodine gracilior; Sabellidae; Sample code/label; Samytha sexcirrata; Sarsameira parva; Sarsameira sp.; Saxicavella jeffreysi; Scalibregma inflatum; Scolelepis bonnieri; Scolelepis tridentata; Scoloplos armiger; Scopelocheirus hopei; Sicameira leptoderma; Siphonoecetes striatus; Sipunculida indeterminata; Spatangus purpureus; Sphaerodorum flavum; Spiochaetopterus typicus; Spio filicornis; Spio mecznikowianus; Spiophanes bombyx; Spiophanes kroeyeri; Spisula subtruncata; Stenhelia aemula; Stenhelia gibba; Stenhelia sp.; Stenothoe monoculoides; Sthenelais limicola; Streblosoma bairdi; Stylicletodes longicaudatus; Synelmis klatti; Tachidiella minuta; Tachidiella sp.; Tachidiopsis cyclopoides; Tanaidacea; Tardigrada; Tellimya ferruginosa; Terebellides stroemii; Tharyx; Thelepus cincinnatus; Thracia phaseolina; Thyasira; Thyasira ferruginea; Timoclea ovata; Tiron spiniferum; Tisbe sp.; Tmetonyx cicada; Travisia forbesii; Trichobranchus roseus; Tridonta montagui; Tritonia hombergii; Tryphosites longipes; Turbellaria; Turbonilla crenata; Turritella communis; Typhlamphiascus confusus; Typhlamphiascus gracilis; Unciola planipes; Urothoe elegans; van Veen Grab; VGRAB; VH1486; VH1486_055; VH1486_063; VH1486_072; VH1486_081; VH1486_090; VH1486_099; VH1486_100; VH1486_109; VH1486_110; VH1486_118; VH1486_119; VH1486_120; VH1486_125; VH1486_126; VH1486_127; VH1486_128; VH1486_129; VH1486_130; VH1486_131; VH1486_137; VH1486_138; VH1486_139; VH1486_140; VH1486_141; VH1486_142;
    Type: Dataset
    Format: text/tab-separated-values, 27432 data points
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  • 4
    Publication Date: 2024-04-20
    Keywords: Biomass, ash free dry mass per area; Date/Time of event; DEPTH, sediment/rock; Event label; ICES 100; ICES 110; ICES 118; ICES 125; ICES 126; ICES 127; ICES 128; ICES 129; ICES 130; ICES 131; ICES 137; ICES 138; ICES 139; ICES 140; ICES 141; ICES 147; ICES 148; ICES 149; ICES 150; ICES 151; ICES 152; ICES 158; ICES 159; ICES 160; ICES 161; ICES 162; ICES 163; ICES 168; ICES 169; ICES 170; ICES 171; ICES 172; ICES 173; ICES 55; ICES 63; ICES 72; ICES 81; ICES 90; Latitude of event; Longitude of event; MarGIS_DANS_Label: ICES8586BSe_8; North Sea; van Veen Grab; VGRAB; VH1486; VH1486_055; VH1486_063; VH1486_072; VH1486_081; VH1486_090; VH1486_100; VH1486_110; VH1486_118; VH1486_125; VH1486_126; VH1486_127; VH1486_128; VH1486_129; VH1486_130; VH1486_131; VH1486_137; VH1486_138; VH1486_139; VH1486_140; VH1486_141; VH1486_147; VH1486_148; VH1486_149; VH1486_150; VH1486_151; VH1486_152; VH1486_158; VH1486_159; VH1486_160; VH1486_161; VH1486_162; VH1486_163; VH1486_168; VH1486_169; VH1486_170; VH1486_171; VH1486_172; VH1486_173; Victor Hensen
    Type: Dataset
    Format: text/tab-separated-values, 158 data points
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  • 5
    Publication Date: 2019-09-19
    Description: Marine data are needed for many purposes: for acquiring a better scientific understanding of the marine environment, but also, increasingly, as marine knowledge for decision making as well as developing products and services supporting economic growth. Data must be of sufficient quality to meet the specific users' needs. It must also be accessible in a timely manner. And yet, despite being critical, this timely access to known-quality data proves challenging. Europe's marine data have traditionally been collected by a myriad of entities with the result that much of our data are scattered throughout unconnected databases and repositories. Even when data are available, they are often not compatible, making the sharing of the information and data aggregation particularly challenging. In this paper, we present how the European Marine Observation and Data network (EMODnet) has developed over the last decade to tackle these issues. Today, EMODnet is comprised of more than 150 organizations which gather marine data, metadata, and data products and make them more easily accessible for a wider range of users. EMODnet currently consists of seven sub-portals: bathymetry, geology, physics, chemistry, biology, seabed habitats, and human activities. In addition, Sea-basin Checkpoints have been established to assess the observation capacity in the North Sea, Mediterranean, Atlantic, Baltic, Artic, and Black Sea. The Checkpoints identify whether the observation infrastructure in Europe meets the needs of users by undertaking a number of challenges. To complement this, a Data Ingestion Service has been set up to tackle the problem of the wealth of marine data that remain unavailable, by reaching out to data holders, explaining the benefits of sharing their data and offering a support service to assist them in releasing their data and making them available through EMODnet. The EMODnet Central Portal (www.emodnet.eu) provides a single point of access to these services, which are free to access and use. The strategic vision of EMODnet in the next decade is also presented, together with key focal areas toward a more user-oriented service, including EMODnet for business, internationalization for global users, and stakeholder engagement to connect the diverse communities across the marine knowledge value chain.
    Description: Published
    Description: Article 313
    Description: 4A. Oceanografia e clima
    Description: JCR Journal
    Keywords: EMODnet, data portal, open access, checkpoint, data services, marine knowledge, blue economy, data integrator
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Oecologia 77 (1988), S. 457-463 
    ISSN: 1432-1939
    Keywords: Nematodes ; Meiobenthos ; Energy-flow ; Respiration ; Feeding
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Summary An energy budget was constructed for the marine nematode Monhystera disjuncta. Respiration was measured with a modified Cartesian diver technique, in which the nematodes were kept in agar inside the diver ‘head’. The relationship between respiration and body weight was: R =1.53 W0.75. Body growth was exponential during the juvenile phase, with a growth rate equal to 0.61 d-1. After maturation the growth rate fell to 0.17 d-1. Food uptake was measured in experiments with radiolabeled bacteria. In one series of experiments the accumulation of radiolabel in the nematodes was followed. In a second series the decrease in labeling was followed when pre-labeled nematodes fed on unlabeled bacteria. A model for label uptake permitted the calculation of assimilation efficiency and consumption rates. Consumption rates thus measured, correspond well to those calculated from the growth, reproduction and respiration rates. Assimilation efficiency was low, around 25%. Production efficiency (P/(P+R)) was high: 60% for the population at stable age distribution, and up to 75% for reproducing females. This seems to be a general feature in nematodes.
    Type of Medium: Electronic Resource
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  • 7
    ISSN: 1432-1939
    Keywords: Seasonal dynamics ; Tropical seagrass beds Tidal exposure ; Terrigenous influences Canonical correlation analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Seasonal dynamics were studied by monthly monitoring of biological and environmental variables in permanent quadrats in two contrasting intertidal seagrass beds in South Sulawesi, Indonesia, from February 1991 to January 1992. Datasets were analysed with canonical correlation analysis for correlations between environmental and biological variables. Considerable variation in biomass, production and plant tissue nutrient contents in a monospecific seagrass bed of Enhalus acoroides, growing on a coastal terrigenous mudbank (Gusung Tallang), was assumed to be related to riverine influences of the nearby Tallo River. The variation in seagrass variables at this site could, however, not be significantly correlated to seasonal patterns in rainfall, salinity, tides, nutrient availability, water motion or turbidity. A seasonal cycle in biomass, production and nutrient contents in a mixed seagrass bed of Thalassia hemprichii and E. acoroides, growing on carbonate sand on the reef flat of an offshore coral island (Barang Lompo), was found to be largely determined by tidal exposure and water motion. Exposure of the intertidal seagrass bed during hours of low water during spring tides showed a gradual shift from exposure during the night (January-June) to exposure during daylight (July-December). Daylight exposure resulted in a significant loss of above-ground plant biomass through desiccation and ‘burning’ of leaves. The observed seasonal dynamics of the seagrass bed on reef sediment contrast with reports from the Caribbean, where the effect of tidal exposure on comparable shallow-water seagrass communities is relatively insignificant due to a small tidal amplitude.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Hydrobiologia 311 (1995), S. 1-7 
    ISSN: 1573-5117
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract An overview is presented of the major results of the project JEEP-92 (Joint European Estuarine Project). A basic description was made of the ecological structure of the estuaries Elbe, Ems, Westerschelde, Somme, Gironde, Shannon and Tagus. The biological communities in these estuaries have been described and compared. Major macrobiological processes have been quantified: bacterial production, primpary production, zooplankton energy flow, meiofauna and macrofauna dynamics. Hydrodynamic and ecological models have been developed.
    Type of Medium: Electronic Resource
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  • 9
    ISSN: 1573-5117
    Keywords: residence times ; Westerschelde ; estuary
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract The residence time of the water masses in the Westerschelde estuary was determined using a simple compartment-model that simulates the advective-diffusive transport of a conservative dissolved substance (chlorinity). The residence time of a water parcel in the upstream part of the estuary (i.e. the time needed for this water parcel to leave the estuary) varied from about 50 days in winter to about 70 days in summer. The most seaward compartment had residence times of about 10-15 days. Dispersive coefficients that are fixed in time were able to reproduce the observed salinity distributions very well in the Westerschelde. They were obtained by calibration on observed chlorinities. It is argued that the apparent relationship of dispersive coefficients with freshwater flow, which is observed in certain studies, could (partly) reflect the deviation from steady state conditions which are required assumptions to calculate these dispersive coefficients directly from salinity profiles.
    Type of Medium: Electronic Resource
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  • 10
    ISSN: 1573-5117
    Keywords: carbon ; budget ; autotrophy ; heterotrophy ; Westerschelde ; estuary
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract The autotrophic production and heterotrophic consumption of organic matter in the Westerschelde, a highly turbid and eutrophic estuary in the Southwest Netherlands is examined by means of a dynamic simulation model. The model describes the ecologically relevant processes in thirteen spatial compartments and adequately fits most observed data. Three autotrophic processes are included in the model. Net pelagic photosynthetic production is relatively low (average 41 gC m−2 yr−1) and three spatial compartments near the turbidity maximum zone are respiratory sinks of phytoplankton biomass. According to the model, net phytobenthic primary production is more important than pelagic primary production in the upstream half of the Westerschelde. On the scale of the entire estuary, benthic primary production amounts to about 60% of pelagic primary production. Water-column nitrification, which is very important in the nitrogen cycle, is most pronounced near the turbidity zone where it accounts for the major autotrophic fixation of carbon (up to 27 g C m−2 yr−1). Viewed on the scale of the total estuary, however, the process is not very important. Less than 20% of total organic carbon input to the estuary is primary produced, the remainder is imported from waste discharges and from the river. The degree of heterotrophy of the Westerschelde estuary proved to be one of the highest yet reported. On average 380 g carbon per square metre is net lost per year (range 200–1200 gC m−2 yr−1). The yearly community respiration (bacterial mineralization, respiration of higher trophic levels and sedimentation) is 4 to 35 times (estuarine mean of 6) higher than the net production. This degree of heterotrophy is highest near the turbidity maximum and generally decreases from the freshwater to the seaward boundary. About 75% of all carbon losses can be ascribed to pelagic heterotrophic processes; the sediment is only locally important. Mineralisation rates are highest in the turbidity region, but as only a fraction of total carbon resides here, less than 20% of all organic carbon is lost in this part of the estuary. This result is in contradiction with a previous budget of the estuary, based on data of the early seventies, where more than 80% of all carbon was estimated to be lost in the turbidity zone. Part of this discrepancy is probably caused by changes that have occurred in the estuary since that time. Due to the high heterotrophic activity, nearly all imported and in situ produced carbon is lost in the estuary itself and the Westerschelde is an insignificant source of organic matter to the coastal zone. The model estuary acts as a trap for reactive organic matter, both from the land, from the sea or in situ produced. Internal cycling, mainly in the water column, results in the removal of most of the carbon while the more refractory part is exported to the sea.
    Type of Medium: Electronic Resource
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