title: Non-deterministic modelling of food-web dynamics.
abstract: A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as 'null models of food-webs' as originally advocated.
authors.affiliation: Institute of Marine Research, Tromsø, Norway.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Planque
authors.affiliation: Institute of Marine Research, Tromsø, Norway.
authors.forename: Ulf
authors.initials: U
authors.lastname: Lindstrøm
authors.affiliation: Institute of Marine Research, Bergen, Norway.
authors.forename: Sam
authors.initials: S
authors.lastname: Subbey
mesh_terms: D018533:Biomass; D003198:Computer Simulation; D017753:Ecosystem; D020387:Food Chain; D008954:Models, Biological; D011157:Population Dynamics