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doi: 10.1890/02-0638
handle: 10261/41705
Both dynamic and topologic approaches in food webs have shown how structure alters conditions for stability. However, while most studies concerning the structure of food webs have shown a nonrandom pattern, it still remains unclear how this structure is related to compartmentalization and to responses to perturbations. Here we build a bridge between connectance, food web structure, and compartmentalization by studying how links are distributed within and between subwebs. A ‘‘k subweb’’ is defined as a subset of species that are connected to at least k species from the same subset. We study the k subweb frequency distribution (i.e., the number of k subwebs in each food web). This distribution is highly skewed, decaying in all cases as a power law. The most dense subweb has the most interactions, despite containing a small number of species, and shows connectivity values independent of species richness. The removal of the most dense subweb implies multiple fragmentation. Our results show a cohesive organization, that is, a high number of small subwebs highly connected among themselves through the most dense subweb. We discuss the implications of this organization in relation to different types of disturbances
Peer reviewed
Compartmentalization, null model, Cohesion, Connectance, food web structure, Null models, subweb
Compartmentalization, null model, Cohesion, Connectance, food web structure, Null models, subweb
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 87 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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