A method for under-sampled ecological network data analysis: plant-pollination as case study

• Published in: Journal of pollination ecology Vol. 6
• Main Authors: Sorensen, Peter B., Damgaard, Christian F., Strandberg, Beate, Dupont, Yoko L, Pedersen, Marianne B, Carvalheiro, Luisa G., Biesmeijer, Jacobus C., Olsen, Jens Mogens, Hagen, Melanie, Potts, Simon G
• Format: Journal Article
• Language: English
• Published: Enviroquest Ltd 24.01.2012
• ISSN: 1920-7603; 1920-7603
• DOI: 10.26786/1920-7603(2011)18

In this paper, we develop a method, termed the Interaction Distribution (ID) method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2), qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.