Description: This module trains students to use systems ecological thinking as a means to improving ecological forecasts. Using the Soil
Plant-Atmosphere Continuum (SPAC) as a case study, students conduct hands-on experiments measuring plant water use and the soil water balance with weighing lysimeters. Students develop a SPAC model, thereby gaining experience in scientific programming of ordinary differential equations. This model is then calibrated using the lysimeter experiment data with a state-space modelling approach. Students thereby gain experience with using Monte Carlo Markov chain methods for near term forecasting with uncertainty assessments.
Learning outcomes:
Explain the principles of systems ecology and their relevance to ecological forecasting.
Design and conduct experiments quantifying interactions within the Soil–Plant–Atmosphere Continuum.
Develop and implement mechanistic models using differential equations to simulate ecological processes.
Apply state-space and MCMC methods to calibrate models and quantify uncertainty in forecasts.
Integrate experimental, theoretical, and computational approaches to improve predictive understanding of ecosystem dynamics.
Module group: Themes Module
Credits: 5 ECTS
Lecturers: Prof. Dr. Efstathios Diamantopoulos