Introduction to Ecological Modelling: From Microbial to Ecosystem Dynamics
Course content
This course provides an overview of and an introduction to ecological modelling. The course emphasizes on computational simulations of two contrasting biological levels: the ecosystem and the microbial community. We model their responses to environmental and climate changes. We teach basic concepts in modelling, the structures of two widely used ecological models (i.e., LPJ-GUESS and DEMENT), and how models, together with observational data, can be used to understand ecological systems better. We apply and test ecological models to understand process interactions and system responses. The teachers have extensive experience with these models, and you will work closely with the teachers during the practical sessions.
Topics include:
- Ecosystem biogeochemical cycles
- Vegetation dynamics
- Microbial processes: traits and community structure
- Model-data integration
- Model sensitivity testing, evaluation and prediction
- Modelling plant-plant and microbial community competition
BSc Programme in Biology
After completion of the course, you will have acquired the following:
Knowledge:
- Explain how different ecosystem processes and ecological interactions are represented in models.
- Describe the basic concepts of model structure, inputs and outputs, model sensitivity and uncertainty testing.
- Identify diverse methods for integrating observational data with models to investigate ecological processes.
Skills:
- Compile model codes and run simulations using varied inputs
- Conduct sensitivity and uncertainty testing to assess the relative importance of different inputs and parameters
- Assess model performance by comparing simulations with observational data
- Apply AI tools to enhance efficiency and accuracy in modelling-related tasks.
Competences:
- Independently execute model simulations to quantify process and organismal interactions and evaluate the relative importance of different processes/parameters
- Reflect on complex ecological questions by applying model simulation experiments
- Critically evaluate and interpret model outputs, draw conclusions about studied ecological processes, and assess their implications.
Lectures, computer practicals, group discussions, peer feedback and student presentations of model outputs
- Luo, Y., & Smith, B. (Eds.). (2022). Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, & Ecological Forecasting (1st ed.). CRC Press. https://doi.org/10.1201/9780429155659 (Chp2, Chp33)
- Smith B. LPJ-GUESS – an ecosystem modelling framework.
- Sitch S, Smith B, Prentice IC, et al. (2003) Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology 9: 161-185.
- Wang, B., & Steven D. Allison. (2022) Climate-driven legacies in simulated microbial communities alter litter decomposition rates. Frontiers in Ecology and Evolution 10,841824
- van den Berg, Naomi Iris, et al. "Ecological modelling approaches for predicting emergent properties in microbial communities." Nature Ecology & Evolution
- Nugent, Andie, and Steven D. Allison. "A framework for soil microbial ecology in urban ecosystems." Ecosphere 13.3 (2022): e3968
It is recommended that students have taken courses equivalent to
Almen Økologi (General Ecology) or Almen mikrobiologi (General
Microbiology) to attend this course.
For Biology students who have passed all first-year courses and
half of the second-year courses by the start of the course
(corresponding to a total of 90 ECTS points) of their curriculum
should be well prepared to master the course
material.
We expect students to have passed basic bachelor-level courses in mathematics, equivalent to NMAA04011U Matematik/Statistik (MatStat) (Mathematics/Statistics). No previous experience with modelling software is expected.
Students must bring their own laptops
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral exam on basis of previous submission, 20 minutes
- Type of assessment details
- Written group report during the practical session of the
course, followed by an individual oral examination, 20 minutes.
The written report is prepared in groups during the course and presents modelling steps and results. The written report must be handed in in groups before the exam week.
After handing in the report, there will be one week to prepare for the oral exam. At the oral exam, the student will present the handed-in group report individually. It will focus on explaining the model steps, outputs, sensitivity testing, and model uncertainties. - Examination prerequisites
-
Students must actively participate in at least 3 out of 4 oral presentations during practical sessions and submit their written report.
- Aid
- Only certain aids allowed (see description below)
Reports: All aids are allowed.
Large Language Models (LLM)/large multimodal models (LMM), e.g., ChatGPT and GPT-4, are allowed to assist in making figures, interpreting model code, and writing codes.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal examiner
- Re-exam
-
Same as the ordinary exam.
If the report has not been approved, a new report must be handed in no later than three weeks before the re-exam, all aids are allowed.
If the student hasn't attented in all the required oral presentations, the student must make a new oral presentation, no later than three weeks before the re-exam, the detalis are agreed with the course coordinator.
Criteria for exam assessment
In order to obtain the grade 12, the student should convincingly demonstrate their understanding of two models and show knowledge, skills and competencies described under Learning Outcome.
- Category
- Hours
- Lectures
- 20
- Class Instruction
- 20
- Preparation
- 40
- E-Learning
- 16
- Project work
- 90
- Exam Preparation
- 15
- Exam
- 5
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NBIB25002U
- ECTS
- 7,5 ECTS
- Programme level
- Bachelor
- Duration
-
1 block
- Placement
- Block 4
- Schedulegroup
-
C
- Capacity
- 30
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student. - Studyboard
- Study Board for the Biological Area
Contracting department
- Department of Biology
Contracting faculty
- Faculty of Science
Course Coordinator
- Jing Tang (9-6f6e736c337966736c45676e7433707a336970)
Teacher
Jing Tang
Jonas Fernbach
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