2008
DOI: 10.1007/s10236-008-0165-2
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Local dynamical equivalence of certain food webs

Abstract: An important challenge in theoretical ecology is to find good coarse-grained representations of complex food webs. Here, we use the approach of generalized modeling to show that it may be possible to formulate a coarse-graining algorithm that conserves the local dynamics of the model exactly. We show examples of food webs with a different number of species that have exactly identical local bifurcation diagrams. Based on these observations, we formulate a conjecture governing which populations of complex food w… Show more

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Cited by 7 publications
(21 citation statements)
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“…Extension of the results in [33] to directed and weighted networks allows application of them to study the food web dynamics. This reveals the topological mechanism of the reduction rule identified heuristically in [30] and provides more general rules for food web aggregation. We note that the previously observed identity is of limited use for the analysis of food web data.…”
mentioning
confidence: 72%
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“…Extension of the results in [33] to directed and weighted networks allows application of them to study the food web dynamics. This reveals the topological mechanism of the reduction rule identified heuristically in [30] and provides more general rules for food web aggregation. We note that the previously observed identity is of limited use for the analysis of food web data.…”
mentioning
confidence: 72%
“…A GM for ecological food webs [31] was used in [30] to study critical points in parameter space in which the dynamics around steady states changes in bifurcations. The authors noted…”
Section: Dynamical Equivalence Of Food Websmentioning
confidence: 99%
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“…This method allows to investigate the occurrence of different dynamical regions without the need to specify the precise form of interaction terms and equilibrium concentrations. This method has already been successfully applied to ecological food webs [11,20,21], socio-economic models [11] and metabolic networks [22,23].…”
Section: Modelmentioning
confidence: 99%