Modul: Combining Ecological Models and Data (3201-590)

Personen:

• Prof. Dr. Frank Schurr (verantwortlich)
• Dr. Jörn Pagel (verantwortlich)

Studiengang:

• Landscape Ecology (Master, PO vom 01.10.2014)
  2. Semester, Wahlpflicht
• Environmental Science - Soil, Water, and Biodiversity (PO 2014) (Master, PO vom 01.10.2014)
  2. Semester, Wahlpflicht
• Environmental Science - Soil, Water, and Biodiversity (PO 2019) (Master, PO vom 01.04.2019)
  2. Semester, Pflicht

Bezug zu anderen Modulen:

This module prepares for modelling-based projects in the module Project in Landscape Ecology (3201-610).

Teilnahme­vorraussetzungen:

Participants need a basic understanding of population dynamics and experience with the programming language R as acquired in the module Landscape Ecology (3201-560) or equivalent courses.

Sprache:

englisch

ECTS:

7,5 credits

Angebotshäufigkeit:

jedes SS

Dauer des Moduls:

4 Wochen (Block 1)

Arbeitsaufwand:

70 h Präsenz + 130 h Eigenanteil + Prüfung = 200 h Workload

Fachkompetenzen:

The module provides an overview of modelling approaches in the environmental and ecological sciences and introduces modern statistical methods that can be used to parameterize and evaluate such models with empirical data. A range of examples deepens the understanding of theoretical concepts in landscape and population ecology. Hands-on exercises familiarize the participants with the practical basics of scientific programming.

Schlüsselkompetenzen:

Participants gain insights into the iterative process of formulating quantitative models and confronting them with empirical data as an integral part of the scientific method. They learn that the awareness and communication of uncertainties, which are attached to any study results and derived predictions, are crucial in both scientific and professional projects. Course projects improve their skills in work organization, data management and (in particular graphical) presentation of own findings.

Anmerkungen:

Participants are required to register for this module on ILIAS before 30th March 2020.

eLearning:

Veranstaltung im ILIAS

Lehrveranstaltungen