Here is the basic method for organizing your ecological data analysis projects in R. Why do this? Reproducing analyses is critical for good science. There is nothing worse than trying to re-run a script when you finally get comments back from your reviewers only to find that your results are a bit different than before. What?! Speaking from personal experience, it’s taken days of blood, sweat, and tears to figure out what was different in the data, what code I was running in the wrong order, or that I was running the wrong code all together! Start now and get in the habit of sticking to a system for organizing your R projects.
Here is another post based on my response to a question from a current undergrad. They wanted to know what the process for applying to grad schools looks like and any prep they could do along the way to give them an advantage. Here are my thoughts based on my own experience of looking for schools as well as what I've seen other students do to successfully get into grad school in ecology. Quick disclaimer that that my experience is limited to the US system. I know funding and other aspects of the grad school application process are different in other countries.
I recently received a question from Ilesha, a PhD student asking about how to get through entire textbooks when studying for their qualifying exam (also known as candidacy exam and comprehensives). There are a lot of study methods out there, but here is a method that I used (that worked quite well) to get the best return on my investment in time spent studying. Not all topics are equally important and there is never enough time to read the whole book*.
[UPDATE 1]: Now includes some of my own mind-map examples
Luka Negoita, PhD
I received my BA in Human Ecology from College of the Atlantic in 2011 and my PhD in Biology with a focus in theoretical plant ecology in May 2018 with Dr. Jason Fridley at Syracuse University. I love teaching and working with ecology students on everything from mental health to data analysis, research design, and study techniques.