Week 10: It’s OK to admit not completely reaching an over ambitious goal

May 14, 2021

Hi guys, this is apparently the end of the blog series, for those of you who read all my blogs since the first week, I thank you and it is an honor :). The past week I was keep on coding and doing the research on the effectiveness of simulations on representing real life data. With the previous 2 posts proving its effectiveness in the school and lab settings via researches of others, now I want to focus on what I found on my own internship about this topic.

First of all, I am sorry to tell y’all that I didn’t complete the coding of the intended simulation of population genetics of salt marsh plants–it was more complex than I thought. I started bragging in the 3rd week about using R language to do approximate Bayesian statistics to analyze the resulted genotype grids. Well, that part ain’t happening due to the debugging and transcriptions of python code taking longer than I thought. So I can’t really compare the full simulated result with empirical data as what I originally envisioned, which was disappointing. BUT, I learned to improvise: although the program is not 100% complete, the outputs of functions of the program that are completed could also serve the purpose of demonstrating the effectiveness of simulations in representing biological scenarios in real life. Thus I could still use my own experience as part of the prof of my project. (YAY!?!)

One of these parts is the functions simulating the survival probability at each location of the field grid. In a field habitat of clonal plants, the field is distinct from the surrounding environment, where the plants don’t grow because of various reasons such as unfit soil conditions or presence of predators or competitive species. Therefore, the closer the plant is to the edge of the field, more hinderances it would face when surviving and reproducing, resulting in a lower survival rate comparing to the plant in the center of the field. The left graph shows the probability of survival at each location of the sampled 20×20 field, with the lighter colors in center representing a higher (yellow=0.7) survival rate and the darker colors toward the edges represent a lower (purple=0.3) survival rate. Notice that the transition between survival rate in the center and edges are not abrupt, but in gradual steps, representing the trend in nature that the farther away from the center where population clusters, the more vulnerable individuals are in dying. The right graph shows what happen to the population after one random generation, the purple dots represent alive plants and the yellow dots represent dead plants. At the center of the grid more purple boxes are shown comparing to yellow ones, meaning more plant individuals closer to center survive that generation, this make sense, since the survival probability at the center is 0.7, and the edge is 0.3. However, there are still some purple boxes at the edge since 0.3 is not 0, the individuals there could still survive, just not as likely as those in the center. An example of this phenomenon in nature is your lawn: if you have a neighbor whose lawn is filled with wild grass, the edge of your lawn close to their lawn will also have some wild grass, decreasing the survival probability of your nice grass. Whereas the part of your lawn away from that annoying neighbor would be nice and tidy, showing a higher survival rate of nice grass. These two graphs thus represent the conditions in nature and prove that simulation outputs could effectively make sense in real life.

Okay, so in summary, I did something!!!! I will still try to finish as much as possible of the program until the start of summer.

5 Replies to “Week 10: It’s OK to admit not completely reaching an over ambitious goal”

  1. Leo L. says:

    Hi Jiaming your results are really great! Can’t wait to look at your presentation!

  2. Jiaming Z. says:

    This analyzing of survival grid is one part of the conclusion reached via the simulation made in my internship, for those of you who would be in my presentation group, there is more! 😉

  3. Karan M. says:

    Your persistence throughout this project is admirable. I looked forward to seeing your blog posts every week. Awesome job!

  4. Sean P. says:

    Jiaming, you’ve challenged yourself throughout this entire project. As Karan mentioned, your persistence is truly admirable. Your results look amazing! I can’t wait to see your presentation and all the information behind these images at the Senior Project Showcase!

  5. Peter L. says:

    I enjoyed reading about your research throughout these week a lot Jiaming! Not completing something planned is totally understandable in my opinion, since I went through that too in week 8 and had to change my focus just like you. Looking forward to your presentation!!

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