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Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird-plant network.


ABSTRACT: Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird-plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than models considering species abundance. This means that forbidden links, by imposing constraints on species interactions, play a greater role than species abundance in structuring the ecological network. We also show that using the frequency of interaction as a proxy for species abundance and network metrics to describe the detailed network structure might lead to biased conclusions regarding mechanisms generating network structure. Together, our findings suggest that species abundance can be a less important driver of species interactions in communities than previously thought.

SUBMITTER: Vizentin-Bugoni J 

PROVIDER: S-EPMC4027382 | biostudies-other | 2014 Apr

REPOSITORIES: biostudies-other

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Processes entangling interactions in communities: forbidden links are more important than abundance in a hummingbird-plant network.

Vizentin-Bugoni Jeferson J   Maruyama Pietro Kiyoshi PK   Sazima Marlies M  

Proceedings. Biological sciences 20140219 1780


Understanding the relative importance of multiple processes on structuring species interactions within communities is one of the major challenges in ecology. Here, we evaluated the relative importance of species abundance and forbidden links in structuring a hummingbird-plant interaction network from the Atlantic rainforest in Brazil. Our results show that models incorporating phenological overlapping and morphological matches were more accurate in predicting the observed interactions than model  ...[more]

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