MEPS 360:25-36 (2008)  -  DOI: https://doi.org/10.3354/meps07394

Importance of trophic information, simplification and aggregation error in ecosystem models

S. J. Metcalf1,2,3,*, J. M. Dambacher2, A. J. Hobday1,2, J. M. Lyle3

1School of Zoology and QMS, University of Tasmania, Private Bag 5, Hobart, Tasmania, Australia, 7001
2CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania, Australia, 7001
3Marine Research Laboratories, Tasmanian Aquaculture and Fisheries Institute, University of Tasmania, Private Bag 49, Hobart, Tasmania, Australia 7001

ABSTRACT: Ecosystem models are becoming increasingly important as pressure from fisheries intensifies and ecosystem-based fisheries management becomes more widely used. Trophic webs often form the basis of ecosystem models and ecosystem-specific dietary information is crucial for optimal model performance. This is particularly the case if model predictions are used in management decisions. The Tasmanian live fish fishery for banded morwong was used as a case study to investigate the importance of trophic information, model simplification and aggregation error on ecosystem model results. Dietary analysis of 6 commonly captured reef fish was undertaken. Significant trophic overlap was found between blue throat wrasse Notolabrus tetricus and purple wrasse N. fucicola, and banded morwong Cheilodactylus spectabilis and bastard trumpeter Latridopsis forsteri. Marblefish Aplodactylus arctidens and long-snouted boarfish Pentaceropsis recurvirostris had significantly different diets from other species studied. Using this information, a detailed qualitative model was produced and then simplified through the aggregation of variables. Variables were aggregated using 3 methods: Euclidean distance, Bray-Curtis similarity, and regular equivalence for inclusion in 3 simplified models. Variable aggregation is undertaken in many studies and may create aggregation error. Each aggregation method produced a different proportion of incorrect model predictions as a result of aggregation error. The model simplified using regular equivalence produced the least aggregation error and a web structure aligned with the dietary analysis. More widespread use of these methods in fisheries management should be considered.


KEY WORDS: Diet · Qualitative modelling · Model structure · Regular equivalence


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Cite this article as: Metcalf SJ, Dambacher JM, Hobday AJ, Lyle JM (2008) Importance of trophic information, simplification and aggregation error in ecosystem models. Mar Ecol Prog Ser 360:25-36. https://doi.org/10.3354/meps07394

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