Wildlife Ecology Modeling (FW680A4)

Course Overview

Schedule (Subject to Change)

Install the most recent versions of R and RStudio Desktop.

Install the software program JAGS.

Notes

  • To download lectures: Go to lecture html. Click ‘e’. This should connect all slides into one page. Right Click Mouse on page. Click ’Print”. Choose printer “Adobe PDF”; might need Adobe Acrobat installed.

Extras

Labs

  • Brian’s Deer lab: html and Zip.

  • Brian’s Prob lab: html and Zip.

  • Brian’s Regression lab: html and Zip.

  • Brian’s GLM lab: html and Zip.

  • Brian’s GLMM lab: html and Zip.

  • Brian’s Bayesian lab: html and Zip.

  • Brian’s CJS lab: html and Zip.

  • Brian’s Occupancy lab: html and Zip.

  • Students will be grouped and assigned a topic (e.g., mark-recapture).

  • Each group should pick an application paper (ideally) or methods paper (if desired) that is published on the assigned topic for the class to read.

  • Please send the paper (pdf) to me via email 2 weeks before the topic is listed on the Schedule; I will then post the paper on the website under the class prior to the discussion date.

  • The group should come prepared to lead the discussion on the paper for (20-25 minutes). Assign questions for us to focus on or come prepared with questions to lead the discussion. Generally focus on things like…

    • what is the statistical model
    • did the authors define it clearly or reference another paper
    • the type of data that is relevant
    • how the sampling was achieved
    • the inference/prediction that was sought
    • how the model was used to answer the fundamental research question
    • nuisances of issues of concern in the modeling or sampling
    • try and connect principles/stastistics in the paper to what we have been doing in the class

Assigned Groups

Species Distribution Model (10/8): Libby Mojica, Travis Rainey
Mark Recapture (10/11): Alex Badeaux, Noel Clark, Elke Tukker
N mixture or Integrated Data Models (10/25): Sarah Gaulke, Sean Ingram
Animal Movement (10/29): Jeremy Alder, Becca Windell
Habitat Selection (11/5): Waverly Davis, Lisa Roerk
Community Modeling (11/12): Cat Adams, Bijoya Paul

Project Type

Decide on whether you will work on a 1) independent research project or 2) develop a short lecture or lab case study on a statistical methodology. Research projects are individual, while a lecture/lab case study can be a team of 2-3 people.

Once decided, individually (for a research project) or as a group (case study), email me a one paragraph synopsis of your plan and topic of choice. Please do this by October 25. I will followup if I have any questions.

Independent Research Project

Conduct a quantitative-focused project, such as a statistical analysis of data, or simulation based investigation. If you are unsure of whether your idea fits, come talk with me. If you want to use data from your graduate research, that would be great, but no need to use all of it or for exactly the purpose of your project. Simplifying the data and analysis is good and appropriate.

Objectives:

  • Write a report; this should be turned in December 6 (last day of classes).

  • Present findings in class as an ignite talk; i.e., a 5 minute long presentation with 20 slides and with the slides advancing automatically every 15 seconds. Presentations will be on December 3 and 6.

Prepare a report via R Markdown that generally follows the sections of 1) idea/hypothesis/setup, 2) data explanation, sampling methodology, and modeling, 3) results, and 4) summary/conclusions.

In Canvas, please submit the compiled HTML, as well as all other files needed to knit this file.

This class is focused on statistical models and model fitting, so make sure to emphasize the specifics of the statistical model that is being used and how it is being fit.

This report does not have to be long, but it should be clear and well presented. Part of the grade will be your focus on communicating the data/model/results visually and via clear statistical language.

Lecture/Lab Case Study

Objective:

  • Create a lecture, R code lab, or hybrid centered around a quantitative approach relevant to wildlife ecology and conservation.

For example, 1) develop a lecture on a specific statistical model, 2) a lab walk through implementing the model and important nuances to consider, or 3) some mixture of these.

Aim for the lecture/lab to be around 25-30 minutes. Presentations will be on December 3 and 6. Please submit the final materials on Canvas by December 6 (last day of classes).

Evaluation will be based on the clarity and organization of the materials presented and the preparedness of the instructors in engaging with the class.