[This article was first published on Mario's Entangled Bank » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
For this years Halloween I presented the mathematical biology seminar at the Centre for Mathematical Biology. Here is the title and the abstract…
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Cycles in finite populations: a reproducible seminar in three acts Many natural populations exhibit cyclic fluctuations. Explaining the underlying mechanisms of such cycles is a central problem in ecology and has preoccupied population ecologists ever since Elton’s classical work in 1924. Over the years, a wide range of mathematical models have been explored in an attempt to gain understanding of the conditions giving rise to or inhibiting population cycles. Many of these models, however, rely on the assumption that population sizes are infinite, and hence implicitly assume that the effects of demographic stochasticity are negligible. Here I will show how demographic stochasticity can give rise to regular and persistent population cycles, so-called quasi-cycles, in simple finite consumer-resource models that are deterministically stable. The existence of such quasi-cycles expand the scope of population cycles caused by ecological interactions, thereby complicating the conclusive interpretation of such patterns. I will discuss how quasi-cycles dovetail with existing theory and will also illustrate the feasibility of accurately identifying such cycles by systematically applying a series of simple analyses to simulated data and data from natural populations. I will be using this presentation to illustrate how reproducible computational science can be practiced.Regarding the final statement about reproducible computational science… In the name of transparency and executability (if you look at the slides you will understand why this is important) I am making all the information necessary to reproduce this work available here, i.e. slides, source for slides (Sweave code), simulation code (in C), almost all of the data, figures, etc.
To leave a comment for the author, please follow the link and comment on their blog: Mario's Entangled Bank » R.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.