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Optimization of a micronekton model with acoustic data

Citation

Lehodey, P and Conchon, A and Senina, I and Domokos, R and Calmettes, B and Jouanno, J and Hernandez, O and Kloser, R, Optimization of a micronekton model with acoustic data, ICES Journal of Marine Science, 72, (5) pp. 1399-1412. ISSN 1054-3139 (2015) [Refereed Article]

Copyright Statement

Copyright 2014 International Council for the Exploration of the Sea

DOI: doi:10.1093/icesjms/fsu233

Abstract

In the pelagic foodweb, micronekton at the mid-trophic level (MTL) are one of the lesser known components of the ocean ecosystem despite being a major driver of the spatial dynamics of their predators, of which many are exploited species (e.g. tunas). The Spatial Ecosystem and Population Dynamics Model is one modelling approach that includes a representation of the spatial dynamics of several epi- and mesopelagic MTL functional groups. The dynamics of these groups are driven by physical (temperature and currents) and biogeochemical (primary production, euphotic depth) variables. A key issue to address is the parameterization of the energy transfer from the primary production to these functional groups. We present a method using in situ acoustic data to estimate the parameters with a maximum likelihood estimation approach. A series of twin experiments conducted to test the behaviour of the model suggested that in the ideal case, that is, with an environmental forcing perfectly simulated and biomass estimates directly correlated with the acoustic signal, a minimum of 200 observations over several time steps at the resolution of the model is needed to estimate the parameter values with a minimum error. A transect of acoustic backscatter at 38 kHz collected during scientific cruises north of Hawaii allowed a first illustration of the approach with actual data. A discussion followed regarding the various sources of uncertainties associated with the use of acoustic data in micronekton biomass.

Item Details

Item Type:Refereed Article
Keywords:acoustic, maximum likelihood estimation, micronekton, model optimization, modelling, Pacific Ocean, SEAPODYM
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and Estuarine Ecology (incl. Marine Ichthyology)
Objective Division:Environment
Objective Group:Flora, Fauna and Biodiversity
Objective Field:Marine Flora, Fauna and Biodiversity
Author:Kloser, R (Dr Rudy Kloser)
ID Code:118886
Year Published:2015
Web of Science® Times Cited:7
Deposited By:Zoology
Deposited On:2017-07-21
Last Modified:2017-10-18
Downloads:0

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