Pokemon Diversity Study, Continued (“Results Section”)

So when we last left off (two weeks ago), we had a guide to setting up a mock diversity study using Pokemon Go.


(Above: The Abra that decided to pop by while my car got new breaks…)

Already, we have a few bumps in the road as Pokemon GO ecologists:

  1. Pokemon GO is, for our purposes, totally random.
  2. Sometimes I don’t have adequate service to play
  3. Accidental transfer of Pokemon happens; luckily I paid attention to the task at hand

So, how did this go over despite the three bumps? Well, I used two very different spots over the span of 2.5 hours: Canton, CT and the National Mall in Washington, DC.  One is a small town that I can walk around a little bit while my car is in the shop: the other is a Pokestop-filled bustling city on a Summer day at peak Tourist time. (My tall and awesome assistant and I even ducked into the Smithsonian Museum of American History for the A/C, Pokestops, and some learning time. No Pokemon were caught within exhibits, however.)

The data? Well, I definitely need more of it to try to do any quantitative analysis, but we can still learn a bit more about using Pokemon GO as a learning tool. (Insert Inception meme here)


Canton:                                                               Washington DC: 

Canton DataDC data


Obviously, I ran into more Pokemon in DC, which in the terms of the game makes sense due to the population density and Pokestops, which is still important when we think about dispersion of real animals. In Canton, there aren’t as many people or Pokestops, so less Pokemon. Unfortunately, this also means less data for me to analyze.

So, for Canton, I only encountered 10 ‘Species’ of Pokemon: My definition of a species being the same evolution tree: so if I get Poliwag candy from a Poliwhirl, that counts as a species. Nidoran are difficult because it’s different candy, so I counted each Nidoran as separate to keep my definition accurate.

In DC, I encountered 19 Pokemon within the time limit and 13 species overall- I did not count the two I hatched (a Tangela and Bellsprout), because I technically did not encounter them. I encountered Sandshrew most frequently, and started a separate column for just Sandshrew. I also kept track of which Pokemon had a qualifier, such as XL/XS, but my sample size wasn’t big enough to analyze either. (Sample size is the amount of good data we can work with mathematically or analytically to support a hypothesis or trend. I can’t say I have a reliable average size of Sandshrew because I only caught 4… that’s a very tiny part of the Sandshrew population!)

Moving on, we’ll discuss what happened here and move onto some more experimental designs that will cover the gaps found in this study. How are your studies doing? Let me know on the facebook or my twitter!



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