UZH-Logo

Maintenance Infos

Modeling Food Webs: Exploring Unexplained Structure Using Latent Traits


Rohr, Rudolf Philippe; Scherer, Heike; Kehrli, Patrik; Mazza, Christian; Bersier, Louis-Félix (2010). Modeling Food Webs: Exploring Unexplained Structure Using Latent Traits. The American Naturalist, 176:170-177.

Abstract

Several stochastic models have tried to capture the architecture of food webs. This approach is interesting, but it is limited by the fact that different assumptions can yield similar results. To overcome this limitation, we develop a purely statistical approach. Body size in terms of an optimal ratio between prey and predator is used as explanatory variable. In 12 observed food webs, this model
predicts, on average, 20% of interactions. To analyze the unexplained part, we introduce a latent term: each species is described by two latent traits, foraging and vulnerability, that represent nonmeasured characteristics of species once the optimal body size has been accounted for. The model now correctly predicts an average of 73%
of links. The key features of our approach are that latent traits quantify the structure that is left unexplained by the explanatory variable and that this quantification allows a test of whether independent biological information, such as microhabitat use, camouflage, or phy-
logeny, explains this structure. We illustrate this method with phylogeny and find that it is linked to one or both latent traits in nine of 12 food webs. Our approach opens the door to the formulation of more complex models that can be applied to any kind of biological network.

Several stochastic models have tried to capture the architecture of food webs. This approach is interesting, but it is limited by the fact that different assumptions can yield similar results. To overcome this limitation, we develop a purely statistical approach. Body size in terms of an optimal ratio between prey and predator is used as explanatory variable. In 12 observed food webs, this model
predicts, on average, 20% of interactions. To analyze the unexplained part, we introduce a latent term: each species is described by two latent traits, foraging and vulnerability, that represent nonmeasured characteristics of species once the optimal body size has been accounted for. The model now correctly predicts an average of 73%
of links. The key features of our approach are that latent traits quantify the structure that is left unexplained by the explanatory variable and that this quantification allows a test of whether independent biological information, such as microhabitat use, camouflage, or phy-
logeny, explains this structure. We illustrate this method with phylogeny and find that it is linked to one or both latent traits in nine of 12 food webs. Our approach opens the door to the formulation of more complex models that can be applied to any kind of biological network.

Citations

34 citations in Web of Science®
39 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

42 downloads since deposited on 18 Jul 2013
29 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:Special Collections > SystemsX.ch
Special Collections > SystemsX.ch > Research, Technology and Development Projects > DynamiX
Special Collections > SystemsX.ch > Interdisciplinary Pilot Projects
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:August 2010
Deposited On:18 Jul 2013 09:52
Last Modified:05 Apr 2016 16:50
Publisher:University of Chicago Press
ISSN:0003-0147
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1086/653667
Permanent URL: https://doi.org/10.5167/uzh-78909

Download

[img]
Preview
Filetype: PDF
Size: 2MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations