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Ecological Modelling
Article . 2006 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Effective trophic positions in ecological acyclic networks

Authors: Scotti, M.; Allesina, S.; Bondavalli, C.; Bodini, A.; Abarca-Arenas, L. G.;

Effective trophic positions in ecological acyclic networks

Abstract

In the tropho-dynamic analysis of ecosystems the heuristic, discrete concept of trophic level has been replaced by the more realistic, continuous definition of trophic position. In ecological network analysis (ENA) the suite of matrix manipulations called canonical trophic aggregation (CTA) apportions each species’ feeding activity to a series of discrete trophic levels sensu Lindeman. The effective trophic position is computed as the sum of the fractions of trophic activity that each species performs at different trophic levels. In this paper we present an extension of the CTA that combines matrix manipulation and sensitivity analysis. Applying this “extended” CTA to an hypothetical network and to real ecosystems we show how trophic position can be computed taking into account the contribution of external inflows, making it scale-insensitive. Moreover “extended” CTA solves ambiguities related to trophic position in the presence of multiple non-living nodes, considering them as imports.

Country
Italy
Keywords

ecological network analysi, canonical trophic aggregation, imports, trophic level, 540, trophic position

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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).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Average
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