The Grind

On Tuesday, we all met one last time to work in R and to write our paper. These last weeks have zipped by. Learning R and doing data analysis is hard enough to do in two weeks, and having to formulate our paper makes it even tougher! From my experience (this might not be shared among everyone), I really enjoyed exploring the data in R. I thought coding in R itself was fun (and challenging), but it was super cool when a graph came out right to shed some light on a biological interaction. We all put SO MUCH WORK into this experiment over these two quarters. And now, it’s finally coming together.

At this point, most of us were well versed enough in R that we were beginning to finalize our scripts. One big problem I had was forcing myself to stop doing data analysis and to finally start writing the paper! We have multiple, huge data sets. There are so many questions to ask and so many data to explore. After each model, I wanted to do more. I could always think of another graph or another model. This happened to a point where I was getting lost in the R world. I know this happened to a bunch of people, and one of the major things we did on Tuesday was to pull ourselves out into the real world. The most important part of doing data analysis is ultimately to ask important and interesting biological questions. Our data revealed a lot. Invertebrates are definitely attracted to light. Predators are also attracted to light, and possibly more so than non-predators, as we saw greater proportions of predators in lit treatments. We also see greater rates in night time predation at lit treatments. Without going more into this, the point is that it’s vital to take this information and to explain it biologically. Why are invertebrates attracted to light? Why are predators so attracted to light? What does it mean that we’ve created more predator rich, dense communities of invertebrates? What novel species interactions can arise from this?

These questions are what we tried to tackle on Tuesday, and will continue to tackle in on Thursday and our papers. For Thursday, we’ve decided to have informal presentations of our R Markdowns. What did we find? What was most interesting? Our data set is huge, and there’s no way any one person can analyze it all. Together, we hope to tell a coherent story of how artificial light at night influences invertebrate communities and drives trophic cascades.

Thursday Schedule:

  • 1:40 – 4:30: individual presentations. About 10 minutes per student, relaxed if discussion is good.

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