Literature DB >> 21560672

Rareness and specialization in plant-pollinator networks.

Jimena Dorado1, Diego P Vázquez, Erica L Stevani, Natacha P Chacoff.   

Abstract

Most rare species appear to be specialists in plant-pollinator networks. This observation could result either from real ecological processes or from sampling artifacts. Several methods have been proposed to overcome these artifacts, but they have the limitation of being based on visitation data, causing interactions involving rare visitor species to remain undersampled. We propose the analysis of food composition in bee trap nests to assess the reliability of network specialization estimates. We compared data from a plant-pollinator network in the Monte Desert of Villavicencio Nature Reserve, Argentina, sampled by visit observation, and data from trap nests sampled at the same time and location. Our study shows that trap nest sampling was good for estimating rare species degree. The rare species in the networks appear to be more specialized than they really are, and the bias in the estimation of the species degree increases with the rareness. The low species degree of these rare species in the visitation networks results from insufficient sampling of the rare interactions, which could have important consequences for network structure.

Entities:  

Mesh:

Year:  2011        PMID: 21560672     DOI: 10.1890/10-0794.1

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  11 in total

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8.  Phylogenetic structure of specialization: A new approach that integrates partner availability and phylogenetic diversity to quantify biotic specialization in ecological networks.

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9.  Understanding linkage rules in plant-pollinator networks by using hierarchical models that incorporate pollinator detectability and plant traits.

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Journal:  PLoS One       Date:  2013-07-01       Impact factor: 3.240

10.  Flower diversity and bee reproduction in an arid ecosystem.

Authors:  Jimena Dorado; Diego P Vázquez
Journal:  PeerJ       Date:  2016-07-26       Impact factor: 2.984

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