Forecasting Futures: Learn data analysis and visualization by exploring the changing habitats of rare species
This Pod will meet once per week for 6 weeks, starting on June 26, 2024 at 7:00pm EDT/4:00pm PDT, with the last session being Wednesday July 31, 2024.
By enrolling you confirm this time works for you.
Date and time
Wednesday, 7:00pm EDT/4:00pm PDT
Group size
3-6 students
Outcome
A research webpage that you can showcase in college applications, AND a 2–3-page research paper submitted to pre-print research archive
Tuition
$495
TAUGHT BY
Yingtong
University of Missouri - Saint Louis PhD in Ecology
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Forecasting Futures: Learn data analysis and visualization by exploring the changing habitats of rare species
The course will guide you to address an important and urgent question – How climate change can affect future distributions of rare species? Climate change, such as global warming and longer drought, can threaten the existence of some of the rarest species on earth. It is important to understand how future suitable habitats will change for these rare species so that we can target our conservation efforts in specific areas. In this project, you will identify a rare species that you like (it can be animals, plants, or fungi!), and gather occurrence data online. Then you will learn how to perform species distribution modeling to map its current and future suitable habitat areas. The changes in the amount or location of future suitable habitats can significantly affect the destiny of a rare species. By doing this Polygence pod, students will not only learn skills in data analyses but also become the best ambassador for this rare species that they love. I hope that students can be vocal about species conservation by presenting findings at society conferences, social media, etc.
ABOUT THE MENTOR
Yingtong
University of Missouri - Saint Louis PhD
I am passionate about mentoring students that are interested in helping solve the biggest environmental issues of today: climate warning, wildfires, droughts, pesticides, heat island effects from cities, light pollution. During my undergrad and graduate school training, I studied species conservation, biodiversity, and global change biology. I will be starting a new research position at Stanford University, working on how wildfires and prescribed burning affect our landscape and ecosystems. My previous Ph.D. projects are related to the species distributions of endemic plant species: I used R programing and species distribution modelling etc. to understand species distributions. I have mentored students that produced results that area complimentary to my research, and produced peer-reviewed publications! But I also would like to guide you through whichever area/field that you are interested in, and I encourage you to produce an independent science project. In my spare time, I like hiking, swimming, gardening, food foraging, and making jewellery out of nature materials :). I also like reading popular science books and National Geographic magazines. I like tree climbing, and I have been applying tree climbing in my own canopy research. I am also motivated to increase diversity and inclusiveness in STEM. I hope that by mentoring women and students of minority backgrounds, I can contribute to increasing diversity and representation in STEM fields.
Forecasting Futures: Learn data analysis and visualization by exploring the changing habitats of rare species
Week by week curriculum
Week 1
Welcome: Student-mentor introductions. This first session will start with an introduction on climate change and its impacts on various ecosystems and organisms. Students will learn what species distribution modeling is and its implications. Students will also learn how to read and find peer-reviewed literature so that they can find relevant research information throughout the course. For homework, students will compile preliminary research on endangered species of their interest, and summarize how climate change might threaten their distributions in future.
Week 2
Diving into Data: In this tutorial workshop, we will learn how to acquire and clean species distribution data using R/Python. We will use a software called Maxent to run species distribution models and produce data visualization. For homework, students will practice cleaning data, conducting data analysis and visualization.
Week 3
Result interpretation: We will do a deep dive into the model assumptions, mechanisms, advantages and drawbacks of Maxent algorithm for predicting species distribution models. We will then guide students to interpret their own findings. For homework, students will start writing down an outline of the methods and results for their research paper.
Week 4
Scientific writing: We will talk about how to do scientific writing, including the structure of a research paper, how to write concisely, and how to cite papers. For homework, students will expand upon the week 3 outline and write the full methods and results section for their research paper.
Week 5
Data visualization 101: We will explore some examples to demonstrate the characteristics of good figures in a scientific paper. Then, we will learn how to build an informative webpage to showcase their research. Part of the session will be dedicated to final project planning. For homework, students will continue writing introduction and discussion sections for their research paper. Students will also start outlining their research webpage.
Week 6
Sharing and Feedback: Students showcase their final projects, ask questions, and share how they plan on using this research experience in the future. By the end of this session, students will be prepared for preprint submission, and have shared their webpage with the group. Homework is for wrapping up any last edits and complete paper submission.