Course manual 2024/2025

Course content

Global environments have been extensively transformed over the last decades, and are projected to change at an accelerated rate over the coming centuries. Human-induced and natural forcing mechanisms, such as land-cover change, climate change, and population growth are the primary drivers of current environmental change. However, to understand if the observed, and projected, environmental changes are outside the normal variation of the Earths system functioning, in terms of magnitude and speed, we require a longer-term context. Landscape, societies and climates evolve over timescales of decades to millennia, and on spatial scales of tens to thousands of kilometers. To obtain insight into how environments have changed beyond the documentary record, we must turn to the fossil record for information. Indicators of past environmental change allow us to reconstruct many aspects of past environments, such as climates, vegetation, and human history, but to make these directly comparable with observed and projected changes a clear understanding of timescales is required. In this course we will consider how information on time can be obtained from the fossil record (dating methods), apply the different methods for reconstructing chronologies, and explore patterns of environmental change through time.

In the course we focus on the importance of timescales for environmental change using a systems science approach to think about function and interactions.

Study materials

Literature

  • Background to the subject: Lowe, J.J. & Walker, M.J.C. (2015) Reconstructing Quaternary Environments Routledge, London

Software

Other

Objectives

  • Explain the importance of spatial and temporal scale in understanding environmental change.
  • Summarize how extraterrestrial, Earth system, and human factors drive environmental change.
  • Locate relevant data sets to explore past environmental change.
  • Analyze past environmental change data sets in multiple ways to identify uncertainty.
  • Evaluate data analysis outputs, and defend their scientific evaluation.

Teaching methods

  • Lecture
  • Laptop seminar
  • Presentation/symposium
  • Self-study
  • Working independently on e.g. a project or thesis
  • Supervision/feedback meeting

Lectures will provide a basic grounding to key principles and themes in past environmental change research.
Tutorials will provide an opportunity to discuss literature on past environmental change and give a greater insight into specific areas.
Laptop seminars will provide training in data handeling, specifically age vs. depth modelling, time-series analysis and climate modelling.
Presentations will provide an opportunity for students to present their own investigations to the class, and to learn from other students work.

Learning activities

Lectures: 16 hours
Tutorials: 6 hours
Laptop seminar: 14 hours
Student presentations: 8 hours

Attendance

Requirements of the programme concerning attendance (OER-B):

  1. Attendance during practical components exercises is mandatory.

Additional requirements for this course:

There is no mandatory attendance; however, students are strongly advised to attend all components of the course.

Assessment

Item and weight Details

Final grade

0.1 (10%)

Computational exercise

Must be ≥ 5

0.4 (40%)

Model-data comparison project

Must be ≥ 5

0.5 (50%)

Tentamen

Must be ≥ 5

You must complete all assessed aspects of the course and acquire the minimum grade in each:

  1. Computational exercise: Age-depth modelling and data exploration (10% final grade)
  2. Model-data comparison project (40% final grade)
  3. Written examination (50% final grade)

To pass the course for each individual part of the assessment you must obtain at least the equivalent of 5 out of 10, and together your combined grade must be higher than the equivalent of 5.5 out of 10. A resit is available for the exam. Reports and Exams will be checked for plagiarism.

Assignments

Computational excercise

  • Age-depth modelling and data exploration (10% final grade)

Model-data comparison project

  • Past climate and empirical data comparison (40% final grade)

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Deadlines for assessed components

  • Computational exercise: Monday 4 November
  • Model-data comparison project: Monday 18 November
  • Exam: Thursday 21 November

Contact information

Coordinator

  • prof. dr. W.D. Gosling

Staff