outbreakR — reconstructing insect outbreaks from tree-ring data in R

This R-based project aims to make insect outbreak histories producible using tree-ring data. While still in its early stages (v. 0.2), it currently allows for fast outbreak history reconstructions using outputs from the popular dplR package. All that’s needed is tree-level host data and a nonhost chronology. Sample data are available through Dropbox

If you have any feedback on this version or you’re a researcher who wants to try these methods, please check my contact information at the end!

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Science, Stories

depression, school, and life : exploratory data analysis with personal data


I started this as a simple data-exploration exercise, and as a giddy excuse to explore a dataset relevant to my life — not about trees, climate, insects or fire: but a personal story. In doing so, I felt it necessary to provide an introduction, which got a bit out of hand:

I graduated with a BSc. in Physical Geography from Texas State University in 2012. It took me 5 ½ years to get that degree — partly a mix of generational malaise, partly depression, partly uncertainty about my future.

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Book Reviews, Non-fiction, Science

Winston Chang’s R Graphics Cookbook (2013)

If you’re ever fumbling around with data in R, you’re probably familiar with the built-in, unattractive graphics. ggplot2’s been increasingly recognized as a necessity for getting the most out of your imagery. It offers nearly complete control over your graphics output, building them layer by layer.

I spent a solid year learning and exploring R as a graduate student before I cracked open Winston Chang’s R Graphics Cookbook and started learning ggplot2’s little oddities. ggplot2 is itself almost like another language within R, but it’s thankfully a very simple language — far more simple and far more flexible, I feel, than the built-in graphics options.

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