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.
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Tucker, A., Duplisea, D. (2011). Integrating Marine Species Biomass Data by Modelling Functional Knowledge. In: Gama, J., Bradley, E., Hollmén, J. (eds) Advances in Intelligent Data Analysis X. IDA 2011. Lecture Notes in Computer Science, vol 7014. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24800-9_33
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DOI: https://doi.org/10.1007/978-3-642-24800-9_33
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