Potential update on the definition of taxonomic/functional/energetic group in MESOPP models in relation to new acoustic technology information

Roland Proud, Rudy J Kloser

Research output: Book/ReportCommissioned report

Abstract

Ecosystem models typically output predictions of biomass and/or abundance split into taxonomical/functional/energetic groups. Assessment of predicted mid-trophic-level biomass could be carried out using active-acoustic observations, e.g. scientific echosounder observations, but this process requires that the predicted biomass of each model group is converted into echo intensity, summed over all of the groups, and then compared with spatially-averaged echosounder observations. Presently, the conversion step generates large uncertainty because the model groups are comprised of a mixture of acoustic scattering groups (e.g. gas-bladdered, fluid-filled, tissue-based etc.) that can not be resolved independently. To reduce this uncertainty, echosounder observations need to be split into groups that correspond to ecosystem model groups e.g. generic fish and zooplankton groups. To do this, more information is required relating to the length-frequency and presence/absence of species by depth and by functional group e.g. obtained using multi-frequency echosounder observations coupled with optics, environmental DNA (eDNA) and trawl data. However, each instrument and observation technique, including observations made using echosounders, is selective, and typically does not observe the full size range of different species equally and is therefore biased.
Original languageEnglish
PublisherZenodo
Commissioning bodyEuropean Commission
Number of pages20
DOIs
Publication statusPublished - 28 Feb 2019

Keywords

  • ecosystem models
  • active-acoustics
  • mid-trophic-level
  • marine observation model

Fingerprint

Dive into the research topics of 'Potential update on the definition of taxonomic/functional/energetic group in MESOPP models in relation to new acoustic technology information'. Together they form a unique fingerprint.

Cite this