Integrating networks and phylogenies

Considering the broad similarities between networks and phylogenies  it is amazing that they have, up until recently,  been very separate approaches. In the world of epidemiology transmission trees have been gaining momentum over the last 5 years (see the excellent review by Hall et al: https://www.ncbi.nlm.nih.gov/pubmed/27217184) as they turn phylogenies into something that more-or-less equates to transmission. Now it appears that ecologists are doing the same thing with this really interesting paper just out in Methods in Ecology and Evolution (see link below). The package attached to Schliep et al looks really cool and I can imagine will be of use to a broad array of disciplines. I’m looking forward to trying it out my self…..

Here is the link: http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12760/full

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FIV in the Seregeti lions :Our paper is our now in JAE.

jane12751-toc-0001Pathogen subtype really does matter – different subtypes of FIV (feline HIV) get around the Serengeti lions is remarkably different ways. This was the general conclusion from our paper just out in the Journal of  Animal Ecology (see link below). After many years work I’m thrilled that this paper is out. This paper hopefully highlights some of the ways in which cool community phylogenetic methods (coupled with phylodynamic approaches) can help understand disease transmission in  a wild population.

Here is a link: http://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12751/full

 

Parasite meta-communities

Studies applying metacommunity concepts to understanding parasite and symbiotic communities are still pretty rare. That’s what make a new paper by Mihalijevic et al in Journal of Animal Ecology that much more exciting. Aside from the impressive data sets assembled, I particularly like how they  use multi-species occupancy models with detection error estimates built in. I agree with the authors that this is particularly useful for parasites. I also like how they estimated how well their models predicted out of sample data – I’ve never seen this in occupancy models before. I did think they interchanged ‘symbiont’ and ‘parasite’ in a confusing way to me at least – but that’s just a minor quibble. Overall it was interesting that host richness and identity were important in explaining parasite composition – this is logical but rarely (if at all?) demonstrated. I think these approaches really are of value for disease ecology and hopefully are used more broadly in the future.

Here is the link: http://onlinelibrary.wiley.com/doi/10.1111/1365-2656.12735/full