5 out of 10 ecology textbooks on my shelves make this distinction: geometric models are for populations with discrete pulses of births, while exponential models are for populations with continuous births. This zombie idea needs to die. It is both wrong and enourmously confusing to students.
I set up 4 10 gallon aquaria in the teaching lab this semester. The goal was to observe the nitrogen cycle as the tanks settled in. I also needed an excuse to try out the new Hach environmental water testing kit that we ordered. The data are on figshare.
A colleague wrote:
I’m trying to make a really simple (I think) plot in R, but am not sure how to do it. I want to make the attached, where the size of each “bubble” in each grid location depends on a single raw data point (% cover of a type of grass). Can you point me in the right direction?
This is the goal.
Really. I have no concept of what my students' lives are like, and this is something I have to constantly remind myself. I cannot make assumptions about their situations based on my own experience.
I've been teaching students `ggplot2` for graphics exclusively for a year or more now. One issue that seems to throw students is the specification of different data sets for some layers. Part of the confusion seems to arise from reversing the order of arguments between `ggplot()` and `geom_*()`. I'm trying to combat this by always naming my arguments. Is this a good idea?
Should ecologists use sum-to-zero contrasts?