The May edition from the Journal of Animal Ecology is pretty much essential reading for anyone interested in disease ecology (particularly those using network approaches). Springer et al’s paper about dynamic networks and Cryptosporidium spread is particularly interesting – I really like the fact that they incorporated different transmission modes into their dynamic network model – this reflects the reality in lots of host-parasite systems. I also like that they used both empirically derived networks and simulated models. The comparison between static and dynamic models wasn’t particularly exciting – it seemed obvious that dynamic models were always going to lead to bigger outbreaks. Nonetheless really interesting work.
The study by Patterson et al on tuberculosis and meerkats was also really cool – combining both social and environmental predictors to understand tb risk in the Kalahari was interesting and is something I’m trying to with the Serengeti lions. They should have used machine learning though!
Furthermore the community ecology section is full of interesting papers as well – hopefully I’ll get around to reading them soon.