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Complexity in quantitative food webs
Author(s) -
Banašek-Richter Carolin,
Bersier Louis-Félix,
Cattin Marie-France,
Baltensperger Richard,
Gabriel Jean-Pierre,
Merz Yves,
Ulanowicz Robert E.,
Tavares Annette F.,
Williams D. Dudley,
Ruiter Peter Cde,
Winemiller Kirk O.,
Naisbit Russell E.
Publication year - 2009
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/08-2207.1
Subject(s) - food web , trophic level , ecology , stability (learning theory) , diversity (politics) , biology , computer science , machine learning , sociology , anthropology
Food webs depict who eats whom in communities. Ecologists have examined statistical metrics and other properties of food webs, but mainly due to the uneven quality of the data, the results have proved controversial. The qualitative data on which those efforts rested treat trophic interactions as present or absent and disregard potentially huge variation in their magnitude, an approach similar to analyzing traffic without differentiating between highways and side roads. More appropriate data are now available and were used here to analyze the relationship between trophic complexity and diversity in 59 quantitative food webs from seven studies (14–202 species) based on recently developed quantitative descriptors. Our results shed new light on food‐web structure. First, webs are much simpler when considered quantitatively, and link density exhibits scale invariance or weak dependence on food‐web size. Second, the “constant connectance” hypothesis is not supported: connectance decreases with web size in both qualitative and quantitative data. Complexity has occupied a central role in the discussion of food‐web stability, and we explore the implications for this debate. Our findings indicate that larger webs are more richly endowed with the weak trophic interactions that recent theories show to be responsible for food‐web stability.