Neotropical Research in the Time of COVID
The summer after my freshman year, I had the opportunity to travel to Guyana, South America to participate in a bird research program. I was fortunate enough to return in 2019, and was planning an eight week trip to Guyana the summer after my junior year.
Enter 2020. The infamous year of pain and fear and suffering. My plans to travel evaporated, I was furloughed from my job, and I struggled through online classes. But I decided to make the most of my summer and use Excel to analyze some of the bird data that I had helped collect in Guyana.
So last summer, I used Excel to produce preliminary graphs of bird flight feather molting trends. Flight feather molt is a process of losing and replacing wing and tail feathers. This process is energetically expensive and has to be timed carefully along with other life history events like reproduction. Flight feather molt is not well known in tropical bird species, so it was fascinating to look at molt data from the birds captured in Guyana.
But I wanted to do more than make graphs in Excel, a software that I have previous familiarity with. I wanted to learn R Studio, a software program that is becoming more and more common in the wildlife ecology field. I had no experience with R and had to start from scratch. My goal was to create more sophisticated graphs of the molt data for one species: the White-crowned Manakin (Dixiphia pipra), pictured here. This is a small, fruit-eating bird that reproduces through a lekking system and is the most captured species at my Guyana field sites.
But where did I even begin to learn R Studio to create graphs of this wonderful bird?
This brings me to an important lesson: reach out to people for help. Professors, mentors, colleagues, friends: most people are more generous than you think. I was worried about bothering one of the colleagues that I worked with in Guyana who now lives in London, but when I reached out explaining that I was trying to learn R, he was extremely amenable to my questions. He walked me through the basic steps of R, like how best to set up my computer desktop and organize my data folders. He explained the importance of resources like stackoverflow, an online forum with a section for R users. Without his first lessons, I would have been totally lost.
Not only did I reach out to outside professionals, but I also reached out to my friends in other colleges who had already taken R courses. They helped me find a fantastic book to continue my R learning experience: R for Data Science. Once I got through some of the data wrangling lessons of this book (data wrangling is data organization within R), I was able to move onto data visualization: creating graphs.
So after countless hours of coding and Googling, I created 6 graphs of my White-crowned Manakin molt data. The one I am most proud of is the last graph that I created, pictured here. This shows that Manakins are more likely to molt in June and July (wet season), than in November (dry season). The most difficult part about this graph was the labelling: I struggled for a long time to get the x-axis to show the month names as opposed to the month numbers. Plus, I was overjoyed when I was able to show the sample size, n, through color coding the bars in different shades of blue.
This experience shows you what you can do as a student in the College of Natural Resources: take something that you are passionate about and dive deep into it, even doing things that you thought you would never do before. I honestly never dreamed that I would code, but now here I am, teaching myself R Studio!