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  • AMER SOC LIMNOLOGY OCEANOGRAPHY  (1)
  • BioOne  (1)
  • Wiley-Blackwell  (1)
  • 2010-2014  (3)
  • 1
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    In situ measurements of pH, Ca2+ and DIC dynamics within the extrapallial fluid of the ocean quahog Arctica islandica (2014)
    BioOne
    In:  Journal of Shellfish Research, 38 (1).
    Details
    Publication Date: 2019-08-06
    Type: Article , PeerReviewed
    DOI: 10.2983/035.038.0107
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 2
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    Measuring the Flow of Energy and Matter in Marine Benthic Animal Populations (2013)
    Wiley-Blackwell
    In:  EPIC3Methods for the study of marine benthos, Methods for the study of marine benthos, West Sussex, Wiley-Blackwell, 78 p., pp. 329-407, ISBN: 978-0-470-67086-6
    Details
    Publication Date: 2014-04-15
    Description: Traditionally, the rationale for energy flow studies was found in the elucidation of energy transfers within ecosystems or within the practical context of the rational management of resources, but it is now widely recognised that its scope embodies almost all biology, including the field of population dynamics and evolutionary studies. Here, we first describe conceptual models of energy and mass budgets at the level of the individual, the population and the community. However, the emphasis is on the next part in which the practicalities of measuring the various components of these budgets in the marine zoobenthic community are described in detail. The measurement of, among other things, ingestion, absorption, defaecation, excretion, growth, reproduction and respiration is discussed. Finally, attention is paid to the estimation of secondary production of benthic populations and to community-level modelling methods.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Inbook , peerRev
    Format: application/pdf
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    PAPER (OA)
  • 3
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    A multi-parameter artificial neural network model to estimate macrobenthic invertebrate productivity and production (2012)
    AMER SOC LIMNOLOGY OCEANOGRAPHY
    In:  EPIC3Limnology and Oceanography-Methods, AMER SOC LIMNOLOGY OCEANOGRAPHY, ISSN: 1541-5856
    Details
    Publication Date: 2019-07-16
    Description: I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e. an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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    PAPER (OA)
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