Integrating Marine Species Biomass Data by Modelling Functional Knowledge

  • Allan Tucker
  • Daniel Duplisea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7014)

Abstract

Ecosystems and their underlying foodwebs are complex. There are many hypothesised functions that play key roles in the delicate balance of these systems. In this paper, we explore methods for identifying species that exhibit similar functional relationships between them using fish survey data from oceans in three different geographical regions. We also exploit these functionally equivalent species to integrate the datasets into a single functional model and show that the quality of prediction is improved and the identified species make ecological sense. Of course, the approach is not only limited to fish survey data. In fact, it can be applied to any domain where multiple studies are recorded of comparable systems that can exhibit similar functional relationships.

Keywords

Bayesian Network Bayesian Network Model Grey Seal Correct Link Alarm Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Allan Tucker
    • 1
  • Daniel Duplisea
    • 2
  1. 1.School of Information Systems, Computing and MathsBrunel UniversityUxbridgeUK
  2. 2.Fisheries and Oceans CanadaInstitut Maurice LamontagneMont JoliCanada

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