-
Course: Analytical Palaeobiology (PB-E2)
-
Instructors: Wolfgang Kiessling, Rachel Warnock, Nussaibah Raja
-
Access Notebook: Click here to launch the interactive Jupyter notebook. Login details should have already been provided to you.
Skip to Course Outline
This module presents modern methods of quantitative analyses of the fossil record. Computer exercises are introduced by short lectures on theoretical foundations. Students use R (www.r-project.org) and modify existing scripts to apply them to palaeobiological problems using data from the Paleobiology Database (www.paleobiodb.org) and other sources. Topics covered are reconstructions of biodiversity and their dynamics, measuring evolutionary rates, quality of the fossil record, and sampling standardization.
The students are able to
-
Understand and apply modern quantitative methods of analyzing the fossil record at large
-
Use R and tailor existing scripts for palaeobiological problems
-
Apply statistics to separate biologically meaningful signals from random noise
All homework are listed within the Course Outline. As part of the course assignment, you will need to come up with your own project. More information on the course assignment can be found here
- Accept the invitation for the assignment provided to you by email.
- Make an RStudio project by choosing the option Version Control to link to your homework repository. More info available here
- Make sure all of your code is committed.
- Push/sync up to GitHub.
- You can continue to push fixes and improvements until the deadline (if provided) or until you're happy with your code.
- Quantitative methods and hypothesis testing in Paleobiology
- Hypothesis Testing
- Fundamental Statistics
- Tutorial: Covid-19
- Evaluate data quality and selecting the best variables
- Model time series data for prediction
- Homework: How sensitive are predictions to the number of known data points. We now have a history of 90 days to inform our model. How does forecast change when limiting the time of previous observations? Solution
- Limit data start to when Covi-19 became a global pandemic (March 1)
- Limit data end to some arbitrary date in the first two weeks of April
- Time Series Analyses
- Attributes of time Series
- Autocorrelation
- Cross-Autocorrelation
- Homework
- Based on the data provided (
div_earthsystem.csv), is there an influence of changes in earth system parameters on changes in biodiversity and origination rates through geological time? - Plot the raw data first:
- Diversity vs time + isotopic data and sea level
- Origination vs time + isotopic data and sea level
- Remove autocorrelation in the data and calculate cross correlations. What conclusions can you derive? Solution
- Based on the data provided (
- The pitfalls and strengths data which are ordered in time
- Analyzing Evolutionary Trends
- Diversity in Space and Time – Paleobiological Databases
- Sampling Standardization and Diversity Dynamics (Alpha, Beta, Gamma) with the 9. Paleobiology Database
- Methods in phylogenies
- Project work and presentation
- You need to present our own project at the end (20 minutes) showing that
- You are able to ask an interesting scientific question
- Transform the question into a testable hypothesis
- Apply the methods learned in this course to test the hypothesis (or hypotheses)
- Discuss the results and provide clear conclusions
- Start early to design your project
- Get inspired by the macroevolution lecture and examples provided in this course
- Get feedback from lecturers about the feasibility of your intended project and adjust
- Do your project work in the course (2nd half of semester) for constant advice
- Evaluation criteria
- Scientific question and hypothesis
- Methodological toolkit applied
- Scientific understanding
- Originality of approach
- Presentation quality
-
Foote, M. & Miller, A.I. (2007): Principles of Paleontology (W.H. Freeman and Company, New York) Third Ed p 354.
-
Knell, R.J. (2013). Introductory R: A Beginner's Guide to Data Visualisation and Analysis using R.