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Minoarivelo HO, Hui C, Terblanche JS, et al. Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model. Oikos. 2014;123(10):1250-1260doi: 10.1111/oik.00857.
Minoarivelo, H. O., Hui, C., Terblanche, J. S., Pond, S. L., & Scheffler, K. (2014). Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model. Oikos (Copenhagen, Denmark), 123(10), 1250-1260. https://doi.org/10.1111/oik.00857
Minoarivelo, H O, et al. "Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model." Oikos (Copenhagen, Denmark) vol. 123,10 (2014): 1250-1260. doi: https://doi.org/10.1111/oik.00857
Minoarivelo HO, Hui C, Terblanche JS, Pond SL, Scheffler K. Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model. Oikos. 2014 Oct 01;123(10):1250-1260. doi: 10.1111/oik.00857. PMID: 25294947; PMCID: PMC4185186.
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Oikos. 2014 Oct 01;123(10):1250-1260. doi: 10.1111/oik.00857.

Detecting phylogenetic signal in mutualistic interaction networks using a Markov process model.

Oikos (Copenhagen, Denmark)

H O Minoarivelo, C Hui, J S Terblanche, S L Kosakovsky Pond, K Scheffler

Affiliations

  1. H. O. Minoarivelo and K. Scheffler ( [email protected] ), Computer Science Division, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - HOM and C. Hui, Centre for Invasion Biology, Dept of Mathematical Sciences, Stellenbosch Univ., Matieland 7602, South Africa. - KS and S. L. Kosakovsky Pond, Dept of Medicine, Univ. of California, San Diego, USA. - J. S. Terblanche, Centre for Invasion Biology, Dept of Conservation Ecology and Entomology, Stellenbosch Univ., Matieland 7602, South Africa.

PMID: 25294947 PMCID: PMC4185186 DOI: 10.1111/oik.00857

Abstract

Ecological interaction networks, such as those describing the mutualistic interactions between plants and their pollinators or between plants and their frugivores, exhibit non-random structural properties that cannot be explained by simple models of network formation. One factor affecting the formation and eventual structure of such a network is its evolutionary history. We argue that this, in many cases, is closely linked to the evolutionary histories of the species involved in the interactions. Indeed, empirical studies of interaction networks along with the phylogenies of the interacting species have demonstrated significant associations between phylogeny and network structure. To date, however, no generative model explaining the way in which the evolution of individual species affects the evolution of interaction networks has been proposed. We present a model describing the evolution of pairwise interactions as a branching Markov process, drawing on phylogenetic models of molecular evolution. Using knowledge of the phylogenies of the interacting species, our model yielded a significantly better fit to 21% of a set of plant - pollinator and plant - frugivore mutualistic networks. This highlights the importance, in a substantial minority of cases, of inheritance of interaction patterns without excluding the potential role of ecological novelties in forming the current network architecture. We suggest that our model can be used as a null model for controlling evolutionary signals when evaluating the role of other factors in shaping the emergence of ecological networks.

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